Podcasts about crds

Cette semaine: deux propositions sans lendemain. La première, celle de l'U2P, le syndicat patronal des artisans et des commerçants, qui souhaite supprimer en 5 ans l'intégralité de la CSG et de la CRDS prélevées sur les actifs. L'idée est de faire payer plus le capital, les retraités ou encore les consommateurs. La seconde, celle d'un référendum sur les choix budgétaires, portée par François Bayrou... Sauf que la compétence budgétaire appartient exclusivement au Parlement. C'est votre Doze bonus de la semaine.

Ce mercredi 7 mai, la proposition choc de l'U2P, qui veut la suppression de la CSG sur les revenus pour augmenter le salaire net, ainsi que la stratégie fixée par Élisabeth Borne pour renforcer la place des femmes dans les métiers scientifiques, ont été abordées par Céline Antonin, économiste à l'OFCE, Sylvain Orebi, président d'Orientis, et Gaël Sliman, président d'Odoxa, dans l'émission Les Experts, présentée par Nicolas Doze sur BFM Business. Retrouvez l'émission du lundi au vendredi et réécoutez la en podcast.

Dans cette édition :Le conclave des cardinaux est en cours dans la chapelle Sixtine pour élire le successeur du pape François, dans une atmosphère solennelle et religieuse.Le président français Emmanuel Macron reçoit le président syrien par intérim Ahmad Al-Charaa, ancien chef djihadiste, pour discuter de la stabilisation de la région et de la lutte contre le terrorisme.Deux mandats d'arrêt algériens visent l'écrivain franco-algérien Kamel Daoud, lauréat du Goncourt 2024, pour son roman sur les années noires du GIA en Algérie.L'organisation patronale U2P propose un "big bang" pour augmenter les revenus nets du travail, en supprimant la CSG et la CRDS sur les salaires.Le PSG affronte Arsenal ce soir au Parc des Princes dans un match décisif pour la qualification en finale de la Ligue des Champions.Notre équipe a utilisé un outil d'Intelligence artificielle via les technologies d'Audiomeans© pour accompagner la création de ce contenu écrit.Distribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Ce mercredi 7 mai, la proposition de loi choc de l'U2P (Union des entreprises de proximité) visant à supprimer totalement la CSG (Contribution sociale généralisée) sur les revenus d'activité pour augmenter le salaire net a été abordée par Nicolas Doze dans sa chronique Doze d'économie dans l'émission Tout pour investir présentée par Lorraine Goumot sur BFM Business. Retrouvez l'émission du lundi au vendredi et réécoutez la en podcast.

Dans cette édition :Le conclave des cardinaux est en cours dans la chapelle Sixtine pour élire le successeur du pape François, dans une atmosphère solennelle et religieuse.Le président français Emmanuel Macron reçoit le président syrien par intérim Ahmad Al-Charaa, ancien chef djihadiste, pour discuter de la stabilisation de la région et de la lutte contre le terrorisme.Deux mandats d'arrêt algériens visent l'écrivain franco-algérien Kamel Daoud, lauréat du Goncourt 2024, pour son roman sur les années noires du GIA en Algérie.L'organisation patronale U2P propose un "big bang" pour augmenter les revenus nets du travail, en supprimant la CSG et la CRDS sur les salaires.Le PSG affronte Arsenal ce soir au Parc des Princes dans un match décisif pour la qualification en finale de la Ligue des Champions.Notre équipe a utilisé un outil d'Intelligence artificielle via les technologies d'Audiomeans© pour accompagner la création de ce contenu écrit.Distribué par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Ce mercredi 7 mai, la proposition de loi choc de l'U2P (Union des entreprises de proximité) visant à supprimer totalement la CSG (Contribution sociale généralisée) sur les revenus d'activité pour augmenter le salaire net a été abordée par Nicolas Doze dans sa chronique Doze d'économie dans l'émission Tout pour investir présentée par Lorraine Goumot sur BFM Business. Retrouvez l'émission du lundi au vendredi et réécoutez la en podcast.

An airhacks.fm conversation with Alvaro Hernandez (@ahachete) about: discussion about stackgres as a complete database cloud solution for PostgreSQL, kubernetes as an abstraction layer over infrastructure providing a programmable API, Stackgres offering high availability with primary and replica nodes using patroni, integrated connection pooling with PgBouncer, kubernetes operators and Custom Resource Definitions (CRDs) as a powerful way to extend Kubernetes, day two operations automated through CRDs including benchmarks and version upgrades, Stackgres supporting sharding with Citus for horizontal scaling similar to DynamoDB, Change Data Capture capabilities using embedded debezium, failover mechanisms taking typically 30 seconds with DNS updates, synchronous vs asynchronous replication options affecting data loss during failover, Stackgres being implemented in Java using quarkus, ContainerD as a programmable container runtime that can be used without Kubernetes, Stackgres offering multiple interfaces including CRDs, REST API, and a web console, considerations for running databases on Kubernetes vs cloud-managed services, the advantages of containerization for infrastructure, the challenges of multi-leader setups in PostgreSQL requiring conflict resolution, the value of Kubernetes for on-premises deployments vs cloud environments Alvaro Hernandez on twitter: @ahachete

Editor's Summary by Anne Rentoumis Cappola, MD, ScM, Associate Editor of JAMA, the Journal of the American Medical Association, for the July 16, 2024, issue.

In this episode, hosts Lois Houston and Nikita Abraham speak with senior OCI instructor Mahendra Mehra about the capabilities of self-managed nodes in Kubernetes, including how they offer complete control over worker nodes in your OCI Container Engine for Kubernetes environment.   They also explore the various options that are available to effectively manage your Kubernetes deployments.   OCI Container Engine for Kubernetes Specialist: https://mylearn.oracle.com/ou/course/oci-container-engine-for-kubernetes-specialist/134971/210836   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X (formerly Twitter): https://twitter.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Radhika Banka, and the OU Studio Team for helping us create this episode.   --------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Nikita: Hello and welcome to the Oracle University Podcast! I'm Nikita Abraham, Principal Technical Editor with Oracle University, and with me is Lois Houston, Director of Innovation Programs. Lois: Hi everyone! Last week, we discussed how OKE virtual nodes can offer you a complete serverless Kubernetes experience. Nikita: Yeah, and in today's episode, we'll focus on self-managed nodes, where you get complete control over the worker nodes within your OKE environment. We'll also talk about how you can manage your Kubernetes deployments. 00:57 Lois: To tell us more about this, we have Mahendra Mehra, a senior OCI instructor with Oracle University. Hi Mahendra! Welcome back! Let's get started with self-managed nodes. Can you tell us what they are? Mahendra: In Container Engine for Kubernetes, a self-managed node is essentially a worker node that you personally create and host on a compute instance or instance pool within the compute service. Unlike managed nodes or virtual nodes, self-managed nodes are not grouped into node pools by default. They are often referred to as Bring Your Own Nodes, also abbreviated as BYON. If you wish to streamline administration and manage multiple self-managed nodes collectively, you can utilize the compute service to create a compute instance pool for hosting these nodes. This allows for greater flexibility and customization in your Kubernetes environment. 01:58 Nikita: Mahendra, what are some practical usage scenarios for OKE self-managed nodes? Mahendra: These nodes offer a range of advantages for specific use cases. Firstly, for specialized workloads, leveraging the compute service allows you to configure compute instances with shapes and image combination that may not be available for managed nodes or virtual nodes. This includes options like GPU shapes for hardware accelerated workloads or high frequency processor cores for demanding high-performance computing tasks. Secondly, if you require complete control over your compute instance configuration, self-managed nodes are the ideal choice. This gives you the flexibility to tailor each node to your specific requirements. Additionally, self-managed nodes are particularly well suited for Oracle Cloud Infrastructure cluster networks. These nodes provide high bandwidth, low latency RDMA connectivity, making them a preferred option for certain networking setups. Lastly, the use of compute instance pools with self-managed nodes enables the creation of infrastructure for handling complex distributed computing tasks. This can greatly enhance the efficiency of your Kubernetes environment. Consider these points carefully to determine the optimal use of OKE self-managed nodes in your deployments. 03:30 Lois: What do we need to consider before creating a self-managed node and integrating it into a cluster? Mahendra: There are two crucial aspects to address. Firstly, you need to confirm that the cluster to which you plan to add a self-managed node is configured appropriately.  Secondly, it's essential to choose the right image for the compute instance hosting the self-managed node.  03:53 Nikita: Can you dive a little deeper into these prerequisites? Mahendra: To successfully integrate a self-managed node into your cluster, you must ensure that the cluster is an enhanced cluster. This is a crucial prerequisite for the addition of self-managed nodes. The flannel CNI plugin for pod networking should be utilized, not the VCN-native pod networking CNI plugin. This ensures optimal pod networking for your self-managed nodes. The control plane nodes of the cluster must be running Kubernetes version 1.25 or later. This is essential for compatibility and optimal performance. Lastly, maintain compatibility between the Kubernetes version on control plane nodes and worker nodes with a maximum allowable difference of two minor versions. This ensures a smooth and stable operation of your Kubernetes environment. Keep these cluster requirements in mind as you prepare to add self-managed nodes to your OKE cluster. 04:55 Lois: What about the image requirements when creating self-managed nodes? Mahendra: Choose either Oracle Linux 7 or Oracle Linux 8 image, for your self-managed nodes. Ensure that the selected image has a release date of March 28, 2023 or later. Obtain the image OCID, also known as Oracle Cloud Identifier, from the respective sources. When specifying an image, be mindful of the Kubernetes version it contains. It's your responsibility to select an image with a Kubernetes version that aligns with the Kubernetes version skew support policy. Keep in mind that the Container Engine for Kubernetes does not automatically check the compatibility. So it's up to you to ensure harmony between the Kubernetes version on the self-managed node and the cluster's control plane nodes. These considerations will help you make informed choices when configuring images for your self-managed nodes. 05:57 Nikita: I really like the flexibility and customization OKE self-managed nodes offer. Now I want to switch gears a little and ask you about OCI Service Operator for Kubernetes. Can you tell us a bit about it? Mahendra: OCI Service Operator for Kubernetes is an open-source Kubernetes add-on that transforms the way we manage and connect OCI resources within our Kubernetes clusters. This powerful operator enables you to effortlessly create, configure, and interact with OCI resources directly from your Kubernetes environment, eliminating the need for constant navigation between the Oracle Cloud Infrastructure Console, CLI, or other tools. With the OCI Service Operator, you can seamlessly leverage kubectl to call the operator framework APIs, providing a streamlined and efficient workflow. 06:53 Lois: On what framework is the OCI Service Operator built? Mahendra: OCI Service Operator for Kubernetes is built using the open-source Operator Framework toolkit. The Operator Framework manages Kubernetes-native applications called operators in an effective, automated, and scalable way. The Operator Framework comprises essential components like Operator SDK. This leverages the Kubernetes controller-runtime library, providing high-level APIs and abstractions for writing operational logic. Additionally, it offers tools for scaffolding and code generation. 07:35 Do you want to stay ahead of the curve in the ever-evolving AI landscape? Look no further than our brand-new OCI Generative AI Professional course and certification. For a limited time only, we're offering both the course and certification for free! So, don't miss out on this exclusive opportunity to get certified on Generative AI at no cost. Act fast because this offer is valid only until July 31, 2024. Visit https://education.oracle.com/genai to get started. That's https://education.oracle.com/genai. 08:14 Nikita: Welcome back! Mahendra, are there any other components within OCI Service Operator to manage Kubernetes deployments? Mahendra: The other essential component is Operator Lifecycle Manager, also abbreviated as OLM. OLM extends Kubernetes by introducing a declarative approach to install, manage, and upgrade operators within a cluster. The OCI Service Operator for Kubernetes is intelligently packaged as an Operator Lifecycle Manager bundle, simplifying the installation process on Kubernetes clusters. This comprehensive bundle encapsulates all necessary objects and definitions, including CRDs, RBACs, ConfigMaps, and deployments, making it effortlessly deployable on a cluster. 09:02 Lois: So much that users can take advantage of! What about OCI Service Operator's integration with other OCI services?  Mahendra: One of its standout features is its seamless integration with a range of OCI services. The first one is Autonomous Database, specifically tailored for transaction processing, mixed workloads, analytics, and data warehousing. Enjoy automated patching, upgrades, and tuning, allowing routine maintenance tasks to be performed without human intervention. The next on the list is MySQL HeatWave, a fully-managed Database Service designed for developing and deploying secure cloud-native applications using widely adopted MySQL open-source database. Third on the list is OCI Streaming service. Experience a fully managed, scalable, and durable solution for ingesting and consuming high-volume data streams in real time. Next is Service Mesh. This service offers a set of capabilities to facilitate communication among microservices within a cloud-native application. The communication is centrally managed and secured, ensuring a smooth and secure interaction. The OCI Service Operator for Kubernetes serves as a versatile bridge, seamlessly connecting your Kubernetes clusters with these powerful Oracle Cloud Infrastructure services. 10:31 Nikita: That's awesome! I've also heard about Ingress Controllers. Can you tell us what they are? Mahendra: A Kubernetes Ingress Controller serves as the enforcer of rules defined in a Kubernetes Ingress. Its primary role is to manage, load balance, and route incoming traffic to specific service pods residing on worker nodes within the cluster. At the heart of this process is the Kubernetes Ingress Resource. Think of it as a blueprint, a rich configuration holding routing rules and options, specifically crafted for handling HTTP and HTTPS traffic. It serves as a powerful orchestrator for managing external communication with services inside the cluster. 11:15 Lois: Mahendra, how do Ingress Controllers bring about efficiency? Mahendra: Efficiency comes with consolidation. With a single ingress resource, you can neatly gather routing rules for multiple services. This eliminates the need to create a Kubernetes service of type LoadBalancer for each service seeking external or private network traffic. The OCI native ingress controller is a powerhouse. It crafts an OCI Flexible Load Balancer, your gateway to efficient request handling. The OCI native ingress controller seamlessly adapts to changes in routing rules with real-time updates. 11:53 Nikita: And what about integration with an OKE cluster? Mahendra: Absolutely. It harmonizes with the cluster for streamlined traffic management. Operating as a single pod on a randomly selected worker node, it ensures a balanced workload distribution. 12:08 Lois: Moving on, let's talk about running applications on ARM-based nodes and GPU nodes. We'll start with ARM-based nodes.  Mahendra: Typically, developers use ARM-based worker nodes in Kubernetes cluster to develop and test applications. Selecting the right infrastructure is crucial for optimal performance.  12:28 Nikita: What kind of options do developers have when running applications on ARM-based nodes? Mahendra: When it comes to running applications on ARM-based nodes, you have a range of options at your fingertips. First up, consider the choice between ARM-based bare metal shapes and flexible VM shapes. Each comes with its own unique advantages. Now, let's talk about the heart of it all, the Ampere A1 Compute instances. These instances are driven by the cutting edge Ampere Altra processor, ensuring high performance and efficiency for your workloads. You must specify the ARM-based node pool shapes during cluster or node pool creation, whether you choose to navigate through the user-friendly console, leverage the flexibility of the API, or command with precision through the CLI, the process remains seamless. 13:23 Lois: Can you define pods to run exclusively on ARM-based nodes within a heterogeneous cluster setup? Mahendra: In scenarios where a cluster comprises node pools with ARM-based shapes alongside other shapes, such as AMD64, you can employ a powerful tool called node selector in the pod specification. This allows you to precisely dictate that an application should exclusively run on ARM-based worker nodes, ensuring your workloads aligns with the desired architecture. 13:55 Nikita: And before we end this episode, can you explain why developers must run applications on GPU nodes? Mahendra: Originally designed for graphics manipulations, GPUs prove highly efficient in parallel data processing. This makes them a top choice for deploying data-intensive applications. Our GPU nodes utilize cutting edge NVIDIA graphics cards ensuring efficient and powerful data processing. Seamless access to this computing prowess is made possible through CUDA libraries. To ensure smooth integration, be sure to select a GPU shape and opt for an Oracle Linux GPU image preloaded with the essential CUDA libraries. CUDA here is Compute Unified Device Architecture, which is a parallel computing platform and application-programming interface model created by NVIDIA. It allows developers to use NVIDIA graphics-processing units for general-purpose processing, rather than just rendering graphics. 14:57 Nikita: Thank you, Mahendra, for another insightful session. We appreciate you joining us today. Lois: For more information on everything we discussed, go to mylearn.oracle.com and search for the OCI Container Engine for Kubernetes Specialist course. You'll find plenty of demos and skill checks to supplement your learning. Join us next week when we'll discuss vital security practices for your OKE clusters on OCI. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 15:28 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Can a new ECG finding identify individuals at risk for dying suddenly? Jason D. Roberts, MD, of McMaster University joins JAMA Associate Editor Gregory M. Marcus, MD, MAS, to discuss A Clinical Diagnostic Test for Calcium Release Deficiency Syndrome (CRDS). CRDS is a recently described cause of sudden arrhythmic death. Until now, no clinical test has existed to identify those with the disease. Related Content: A Clinical Diagnostic Test for Calcium Release Deficiency Syndrome The First Clinical Test for Calcium Release Deficiency Syndrome?

Interview with Lauren Megaw, Investor Relations of Reyna Silver Corp.Our previous interview: https://www.cruxinvestor.com/posts/reyna-silver-tsxvrslv-advancing-high-potential-crd-silver-projects-in-nevada-mexico-5134Recording date: 14th May 2024Reyna Silver Corp (TSXV:RSLV) is an emerging precious metals exploration company with a portfolio of high-grade, district-scale projects in the world-class mining jurisdictions of Nevada and Mexico. The company's flagship asset is the Gryphon project in Nevada, where drilling is set to commence this summer to test multiple gold, silver, copper, and zinc targets.Reyna Silver's management team has a proven track record of success in exploring for carbonate replacement deposits (CRDs), which are known for their potential to host large, high-grade ore bodies. The company's CEO, Jorge Ramiro Monroy, was a key member of the MAG Silver team that discovered the Juanicipio CRD deposit in Mexico while Peter Megaw, Reyna Silver's Chief Exploration Officer, is a world-renowned expert on CRDs and has been involved in multiple major discoveries over his career.In addition to the Gryphon project, Reyna Silver has three other wholly-owned projects that offer significant exploration upside: Medicine Springs, Nevada: A carbonate replacement deposit target with strong potential for high-grade silver, lead, and zinc mineralization; Guigui, Mexico: A large, district-scale CRD play in the heart of the Santa Eulalia mining district, the world's largest known CRD system; and Batopilas, Mexico: A historically productive, high-grade native silver district with excellent potential for additional discoveries.Reyna Silver is well-funded to aggressively advance its projects, having recently raised C$4.6 million through a private placement. The company has a tight share structure and management owns approximately 20% of the shares, ensuring strong alignment with shareholders.The macro backdrop for precious metals is highly favorable, with negative real interest rates, unprecedented monetary and fiscal stimulus, and rising geopolitical tensions all supportive of higher gold and silver prices. Silver, in particular, stands to benefit from its dual role as both a monetary and industrial metal. Silver's use in solar panels, electric vehicles, and 5G technology could drive strong demand growth in the coming years.Reyna Silver offers investors a compelling opportunity to gain exposure to the bull market in precious metals through a company with high-quality assets, a proven management team, and multiple near-term catalysts. With drilling set to commence at the flagship Gryphon project this summer, the company is well-positioned to deliver exploration success and create significant shareholder value.The key risks to consider include the inherent exploration risk in the mining sector, as well as the potential for permitting delays or challenges in the company's operating jurisdictions. However, Reyna Silver's experienced team and diversified asset base help mitigate these risks.In summary, Reyna Silver offers a unique investment opportunity in the precious metals space. The company's focus on high-grade, district-scale CRD deposits, coupled with its strong management team and robust financial position, make it well-suited to capitalize on the bull market in gold and silver. With drill rigs set to turn at the Gryphon project in the coming months, investors would be wise to keep Reyna Silver on their radar.View Reyna Silver's company profile: https://www.cruxinvestor.com/companies/reyna-silverSign up for Crux Investor: https://cruxinvestor.com

On this episode of Infrastructure Matters, host Camberley Bates is joined by NetApp's Eric Han and Shiva Subramanyam, for an insightful conversation on the new architecture and integration of NetApp's Astra and its implications in the world of Kubernetes for advanced data management. Our discussion covers: The origins and development of Astra by NetApp How Astra is being used to advance data management with Kubernetes The architecture of Astra, and its design for Kubernetes-native, including CRDs, least privilege access, and self-contained backups Real-world customer use cases in the Kubernetes space, demonstrating the demand for advanced data management capabilities  

Interview with Jorge Ramiro Monroy, CEO of Reyna Silver (TSX-V:RSLV)Our previous interview: https://www.cruxinvestor.com/posts/reyna-silver-tsxvrslv-prudent-management-and-exploration-in-progress-3902Recording date: 2nd March 2024Reyna Silver Corp (TSXV:RSLV) is a silver-focused exploration company advancing a portfolio of high-potential projects in the prolific mining jurisdictions of Nevada, USA and Mexico. The company is led by a highly experienced management team with a track record of major discoveries, including Dr. Peter Megaw, a world-renowned expert in carbonate replacement deposits (CRDs) who serves as Reyna's Chief Technical Advisor.Reyna Silver recently closed a $4.6 million CAD financing to fund aggressive exploration across its project portfolio, with a near-term focus on drilling the advanced-stage Griffin CRD project in Nevada. Griffin, which was acquired in November 2022, hosts an extensive historical database of 12,000 meters of drilling, 4,000 surface samples, and multiple geophysical surveys. However, this data was generated by previous operators primarily focused on exploring for Carlin-type gold mineralization. Reyna's technical team recognized the potential for a significant CRD system and will be the first to systematically explore the project from this perspective.CEO Jorge Ramiro Monroy explained in a recent interview, "The core that we're going to look at has pretty much never been looked at with the eyes of CRDs. And you know, it has very specific characteristics." The company plans to relog the historic drill core and integrate the extensive data to refine high-priority drill targets in areas of known mineralization. This work will culminate in a substantial drill program later this year, with the goal of rapidly advancing Griffin towards a maiden resource estimate.In addition to Griffin, Reyna Silver has a portfolio of earlier-stage but highly prospective silver projects in Mexico. These projects, including Guigui and Batopilas, were acquired from MAG Silver as part of a 2019 deal that saw Dr. Peter Megaw join Reyna's technical team. Mexico is a world-class jurisdiction for silver exploration and production, and Reyna's projects are located in historic mining districts with significant upside potential.However, recent uncertainty surrounding proposed changes to Mexico's mining law has impacted foreign investment and led some companies to focus their exploration efforts elsewhere in the near-term. Reyna Silver is taking a pragmatic approach in response to this uncertainty. The company is maintaining its Mexican property portfolio and continuing low-cost exploration activities but has elected to defer drilling until after the upcoming presidential election in July and the swearing-in of the new government in December.Despite the challenging market conditions for silver over the past two years, the fundamentals for the metal remain compelling. The appetite for silver among investors remains strong, but a lack of high-quality exploration and development projects in the pipeline has created the potential for a significant supply shortage in the coming years. As CEO Jorge Ramiro Monroy noted, "If you look at the last four or five years, the big silver companies - Pan American Silver, First Majestic - they didn't go and buy silver projects. They used their silver premium, looked around and said, 'There's no silver projects.' So there is certainly a need to make new silver discoveries."With a strong treasury, experienced management team, and portfolio of drill-ready exploration projects in world-class mining jurisdictions, Reyna Silver Corp represents a compelling opportunity for investors looking for exposure to silver discovery potential. The company's near-term focus on drilling the advanced-stage Griffin CRD project in Nevada provides the potential for a major new discovery in a politically stable jurisdiction, while the earlier-stage Mexican portfolio offers investors additional upside optionality. With a tight share structure, strong institutional support, and an attractive valuation compared to its peer group, Reyna Silver is well-positioned for success in the coming year.—Learn more: https://cruxinvestor.com/companies/reyna-silverSign up for Crux Investor: https://cruxinvestor.com

Interview with Chad Peters, CEO of Ridgeline Minerals (TSX-V: RDG)Recording date: 12th September 2023Ridgeline Minerals is a Nevada-focused precious and base metals explorer aiming to make new discoveries in proven districts. The company went public in 2020 but adapted its business model due to market conditions, forging strategic partnerships to advance projects while still retaining upside.Ridgeline's flagship project is the 100% owned Selena project, which has potential to be a globally significant carbonate replacement deposit (CRD) discovery. CRDs are genetically related to porphyry copper systems and can contain substantial amounts of silver, lead, zinc and copper.Selena shares similarities with successful projects like the Taylor deposit in Arizona. Ridgeline has already drilled intercepts up to 6 meters of 1,200 g/t silver equivalent at Selena and believes the project could deliver transformational value.To advance other projects while minimizing dilution, Ridgeline executed deals with Nevada Gold Mines on its Swift and Carlin East gold projects, worth $40 million in spending for 70% ownership. Importantly, Ridgeline retains 25% fully carried interest through to first gold production on any new discoveries.This innovative structure provides upside exposure without excessive spending requirements if the projects are advanced. The deals allow Ridgeline to focus its technical team and capital on progressing Selena.Located in Eureka County, Nevada, Selena covers 39 square km of highly prospective ground. Ridgeline plans to systematically de-risk Selena and achieve initial resource estimates to attract interest from mid-tier and major base metals producers.Ridgeline's experienced management team leverages extensive local relationships to source overlooked projects with major discovery potential, like the newly acquired Big Blue copper-silver project.With a lean team, capital from supportive institutions and strategic investors, and district-scale targets in top mining jurisdictions, Ridgeline offers substantial discovery potential and leveraged exposure to new high-value deposits.

Hey there, 5G Guys Podcast listeners! Today, we're diving into the world of emergency response and the revolutionary technology that's making it all possible: FirstNet. FirstNet is the first-ever nationwide, interoperable broadband network that's exclusively dedicated to first responders. It all started with the tragedy of 9/11, which led to the complete collapse of the New York cellular networks. In response, the US government formed the FirstNet authority, which was tasked with creating a nationwide network that would give first responders a dedicated channel for emergency communications, prioritized over commercial users. We had the opportunity to speak with Jeff Bratcher, CTO of FirstNet, who provided us with a detailed history of the network and how it operates. With the help of AT&T, FirstNet dedicates 20 MHz of spectrum and billions of dollars to ensure that first responders have the resources they need to communicate during emergencies. The network operates on cutting-edge technology, which allows for lightning-fast communication between first responders and their teams. It prioritizes emergency communications, so first responders can communicate seamlessly without any lag or interference. This means that in times of crisis, first responders can focus on saving lives without having to worry about connectivity issues. Overall, FirstNet is a game-changer for emergency response. It's making our communities safer by providing first responders with the resources they need to do their job more effectively. We hope you enjoy listening to our conversation with Jeff Bratcher and learn more about the incredible technology behind FirstNet. Thanks for tuning in to the 5G Guys Podcast with Dan and Wayne! As always, reach out to us via the links below and share your thoughts or episode ideas.   More Of What's Inside:   FirstNet Authority website:  FirstNet Authority | First Responder Network Authority FirstNet portable connectivity:  Portable connectivity: CRDs meet public safety needs in the field, on the road, along the fire line Example of FirstNet in action:  FirstNet - Preemption FirstNet service website:  Nationwide Broadband For First Responders & Public Safety at FirstNet Connect With Us:  Sponsor Links:  Website: www.vertex-us.com Website: Website: https://5gguys.com Social: Facebook: https://www.facebook.com/5Gguys LinkedIn: https://www.linkedin.com/groups/12515882 Twitter: https://twitter.com/5gGuys Submit Your Ideas or Feedback: https://5gguys.com/contact-2 Episode Minute By Minute: 0:00 Sneak Peak and a word about our sponsor 1:25 Welcome to the show! Get to know Jeff Bratcher and FirstNet 10:39 The size of FirstNet across the country can be measured in terms of the number of agencies and users per megahertz of spectrum 18:55 How they actually make FIrstNet work 20:54 The interoperable carrier that is available across all agencies 23:44 Technical advancements born out of the partnership with ATT 30:35 From 4G LTE to 5G  

Fonte única para gerenciar ambientes e aplicações?No episódio #119 do Kubicast, conversamos com Yros Aguiar, para explorar o potencial da metodologia GitOps, quando combinada com a ferramenta de gerenciamento Crossplane. Nosso convidado explica como automatizar a implantação e gerenciar uma infraestrutura de nuvem com eficiência, agilidade e confiança.Recomendações do programa:Pizzaria em Floripa: Berre BirraDar um rolê na lagoa de FlorianópolisO pálido olho azul, disponível na NetflixThe last of us, disponível na HBOLinks do programa:Crossplane site: https://www.crossplane.io/Twitter Crossplane: https://twitter.com/crossplane_ioCrossplane Concepts: https://docs.crossplane.io/v1.9/concepts/Documentacao do CRDs e providers: https://doc.crds.dev/Examples AWS : https://github.com/crossplane-contrib/provider-aws/tree/master/examplesUpbound: https://github.com/upbound/universal-crossplaneContato com o Yros:Github: https://github.com/yrosaguiarLinkedin: https://www.linkedin.com/in/yros-aguiar-6a893b32/Email: yrosaguiar@gmail.comO Kubicast é uma produção da Getup, empresa especialista em Kubernetes e outras tecnologias cloud native que trazem performance, automação e resiliência para infraestrutura de TI. Os episódios do podcast estão em getup.io, nas principais plataformas de áudio digital e no YouTube.com/@getupcloud.

Pour marquer votre intérêt pour le week-end immo: Merci de laisser vos coordonnées sur le site du club1vest:www.club1vest.frTous les liens pour m'écrire, rejoindre le Club1vest, le groupe Telegram, les programmes, les formations sont sur mon site ! www.grosbillets.comLe prélancement de la formation et bénéficiez d'un tarif de -50% jusqu'au 28.02.2023. https://www.grosbillets.com/podcast Dans cet épisode, j'ai la joie d'accueillir Sonine, expert-comptable et investisseuse immobilier qui va nous expliquer dans un premier temps comment elle a mis en place une vraie stratégie business pour ses locations courtes durées pour pouvoir quitter son emploi en un an.Dans un second temps, on va faire le tour de la fiscalité et surtout des cotisations sociales qui s'appliquent à un entrepreneur ou un investisseur ayant dit byebyepatron. Combien paye-t-on en LMNP, LMP, faut-il privilégier la SAS ou la SARL pour se lancer? De combien sont les cotisations et les impôts afférents à chacun des statuts ?Nous ferons également un tour des différentes possibilités légales qui existent pour dire byebyepatron (démission, rupture conventionnelle et plus encore).   Accrochez-vous Sonine nous explique tout !! 

Klaus and I go through what happened at the Kubecon North America event in Detroit. Specifically, lessons learned in watching how the community reacts to new technologies like CRDs, declarative programming, and cluster APIs. We also discuss the health of the community and the operators and vendors who were involved. We give our impressions and insight - this conversation deep dives into practical use and futures in Kubernetes. Transcript: https://otter.ai/u/8sNj_ZMTbKuJxAhOZhlvLAckWhc Image: https://www.pexels.com/photo/elderly-man-and-woman-looking-outside-window-7551662/

https://go.dok.community/slack https://dok.community We are going to speak about CRDs, and discuss considering them as higher level entities that we normally consider them. CRDs normally are kind of a byproduct of an operator. But in reality, they can be considered as the user-facing API of the operator surface. And as such, we would like to introduce conversations about even standardizing some of them, or creating "specifications" out of some CRDs. Take this for example: there are some CRDs that could be, potentially, common across multiple operators. Think of a CRD to represent an S3 (or any other storage object) bucket. For operators that store data in object stores, each and every one of them are creating their own versions. But shouldn't we have some "standardized" `ObjectStorage` CRD, without a controller, that all could use? We'll be joined by John Sanda of DataStax who works on the K8ssandra project, Alvaro Hernandez who is the CEO of Ongres and Postgres superhero, and Eyar Zilberman Co-Founder and Chief Product Officer at Datree.

It’s release day! We discuss today’s Kubernetes 1.25 with release team lead Cici Huang, Software Engineer at Google Cloud. What’s in, what’s out, and what is it like to lead a release you are also promoting a feature in? Do you have something cool to share? Some questions? Let us know: web: kubernetespodcast.com mail: kubernetespodcast@google.com twitter: @kubernetespod Chatter of the week Nelson underwater England underwater A picture of a sheep Follow Craig on Twitter for more like that News of the week Kubernetes 1.25 release Introducing Acorn Acorn Labs: Rancher Co-Founders’ New Kubernetes Startup by Christine Hall Episode 57, with Darren Shepherd GKE updates: New observability metrics GKE Autopilot now default 256 pods per node KubeCon schedule published Cloud Native Rejekts Scaling Kubernetes to thousands of CRDs by Nic Cope Links from the interview IBM Watson Kubernetes Community Awards SIG API Machinery Chair & Cici’s hiring manager: Fede Bongiovanni Kubernetes 1.25 release team Release blog Highlights: PodSecurityPolicy is removed; Pod Security Admission is stable cgroups v2 KMS v2alpha1 CRD valdation experession language Registry change Kubernetes 1.24 delay Theme and logo Envelopes: 1.24 lead: Episode 178, with James Laverack 1.26 lead: Leonard Pahlke Cici Huang on GitHub

https://go.dok.community/slack https://dok.community ABSTRACT OF THE TALK When providing data analysis as a service, one must tackle several problems. Data privacy and protection by design are crucial when working on sensitive data. Performance and scalability are fundamental for compute-intensive workloads, e.g. training Deep Neural Networks. User-friendly interfaces and fast prototyping tools are essential to allow domain experts to experiment with new techniques. Portability and reproducibility are necessary to assess the actual value of results. Kubernetes is the best platform to provide reliable, elastic, and maintainable services. However, Kubernetes alone is not enough to achieve large-scale multi-tenant reproducible data analysis. OOTB support for multi-tenancy is too rough, with only two levels of segregation (i.e. the single namespace or the entire cluster). Offloading computation to off-cluster resources is non-trivial and requires the user's manual configuration. Also, Jupyter Notebooks per se cannot provide much scalability (they execute locally and sequentially) and reproducibility (users can run cells in any order and any number of times). The Dossier platform allows system administrators to manage multi-tenant distributed Jupyter Notebooks at the cluster level in the Kubernetes way, i.e. through CRDs. Namespaces are aggregated in Tenants, and all security and accountability aspects are managed at that level. Each Notebook spawns into a user-dedicated namespace, subject to all Tenant-level constraints. Users can rely on provisioned resources, either in-cluster worker nodes or external resources like HPC facilities. Plus, they can plug their computing nodes in a BYOD fashion. Notebooks are interpreted as distributed workflows, where each cell is a task that one can offload to a different location in charge of its execution. BIO Iacopo Colonnelli is a Computer Science research fellow. He received his Ph.D. with honours in Modeling and Data Science at Università di Torino with a thesis on novel workflow models for heterogeneous distributed systems, and his master's degree in Computer Engineering from Politecnico di Torino with a thesis on a high-performance parallel tracking algorithm for the ALICE experiment at CERN. His research focuses on both statistical and computational aspects of data analysis at large scale and on workflow modeling and management in heterogeneous distributed architectures. Dario is an SWE that turned DevOps, and he's regretting this choice day by day. Besides making memes on Twitter that gain more reactions than technical discussions, leading the development of Open Source projects at CLASTIX, an Open Source-based start-up focusing on Multi-Tenancy in Kubernetes. KEY TAKE-AWAYS FROM THE TALK From this talk, people will learn: - The different requirements of Data analysis as a service - How to configure for multi-tenancy at the cluster level with Capsule - How to write distributed workflows as Notebooks with Jupyter Workflows - How to combine all these aspects into a single platform: Dossier All the software presented in the talk is OpenSource, so attendees can directly play with them and include them in their experiments with no additional restrictions.

Kubernetes won the container wars and continues to grow in use across many industries. But how did something that was about Cloud-native Applications gain traction without a developer experience?SHOW: 595CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:Teleport is the easiest, most secure way to access all your infrastructure Get started with Teleport CloudZero - Cloud Cost Intelligence for Engineering TeamsDatadog Kubernetes Solution: Maximum Visibility into Container EnvironmentsStart monitoring the health and performance of your container environment with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.SHOW NOTES:Kubernetes - The Documentary - Part 1Kubernetes - The Documentary - Part 2Software Defined Talk - Eps.344 - Kubernetes Documentary HOW DID KUBERNETES WIN WHEN IT STARTED FROM BEHIND?Listening to this week's SDT show, and remembering listening to SDT years ago, @cote comments about why Kubernetes "won" were always interesting. In essence it was late to market, was lacking in features vs. competitors (Mesos, Swarm, CF), and had a terrible user-experience...so how did it "win"? It all seems ass-backwards. HOW HAS KUBERNETES CONTINUED TO WIN, WITHOUT A DEVELOPER EXPERIENCE?Mesos, CF and Swarm were all single-vendor dominated projects, and many companies had concerns about another generation of vendor lock-in. This point is reasonably valid, but the companies that were using Mesos, CF and Swarm did all seem to love that technology.Mesos was primarily focused on big data workloads. For each new application-type, you needed to write (or use) another application-specific framework. So it was good at its niche, but couldn't easily be used for other types of apps. [Kubernetes eventually copied this model with CRDs].Swarm was the easiest to use, but it wasn't very good technology and didn't scale. So it got pigeon-holed for smaller projects.CF focused on Java/SpringBoot, which is a big Enterprise opportunity. but CF was super complicated to set up. And CF never really embraced containers, so companies were weary of if they were missing this big trend (Docker).Kubernetes comes along and  becomes the good-enough platform. It's not dominated by a single vendor. It natively supports Docker, it has some built-in usage patterns so it's easier than Mesos to add apps, it scales better than Swarm, and it can support Java/Spring or even legacy Java (lift-and-shift). And as Joe Beda says, you could use it natively or you could build some PaaS-y like features on top of it.FEEDBACK?Email: show at the cloudcast dot netTwitter: @thecloudcastnet

This is Gerhard's first set of interviews from KubeCon North America 2021. William Morgan shares with us some of the finer Linkerd details, such as the underlying security theme, why native Kubernetes objects are preferable to more CRDs, and the joy of meeting team members in person. Frederic Branczyk speaks about Parca, a new continuous system profiling tool that uses eBPF to help you understand what is happening on your hosts. Andrew Rynhard gives us a great Talos OS and Kubespan perspective, and shares some really good follow-up videos on these topics. The last conversation is with David Flanagan - you know him as Rawkode - about new beginnings. It's only been less than two months since we've had him in episode 18, and he kept really busy. Caleb, his 3 weeks old baby boy, was the youngest attendee at this conference, and some talks made him sleepy, so good job everyone.

This is Gerhard's first set of interviews from KubeCon North America 2021. William Morgan shares with us some of the finer Linkerd details, such as the underlying security theme, why native Kubernetes objects are preferable to more CRDs, and the joy of meeting team members in person. Frederic Branczyk speaks about Parca, a new continuous system profiling tool that uses eBPF to help you understand what is happening on your hosts. Andrew Rynhard gives us a great Talos OS and Kubespan perspective, and shares some really good follow-up videos on these topics. The last conversation is with David Flanagan - you know him as Rawkode - about new beginnings. It's only been less than two months since we've had him in episode 18, and he kept really busy. Caleb, his 3 weeks old baby boy, was the youngest attendee at this conference, and some talks made him sleepy, so good job everyone.

Les brocantes et vide-greniers sont plus populaires que jamais. Au point qu'un Français sur deux a déclaré avoir participé, en 2019, aux quelque 50.000 ventes au déballage organisées chaque année. Mais devez-vous déclarer aux services fiscaux les revenus que vous en tirez ?Des revenus en principe non imposésSi vous êtes un particulier, les revenus tirés de la vente d'objets dans le cadre d'une brocante ne sont pas imposés. Il n'est donc pas nécessaire de les déclarer.À condition, toutefois, que vous respectiez certaines conditions. En premier lieu, vous ne pouvez vendre que des objets usagés, dont vous êtes le propriétaire. Par ailleurs, vous ne pouvez participer à plus de deux vide-greniers par an.C'est pour vérifier que cette règle est respectée que vous devez vous inscrire sur un registre spécifique. On peut aussi vous demander d'attester sur l'honneur que vous n'avez pas déjà pris part à deux ventes au déballage.L'objectif est de faire la distinction entre un simple particulier et un professionnel. Ce dernier, en effet, acquiert ou fabrique des objets neufs dans le but de les revendre. Ses revenus sont alors soumis à l'impôt sur le revenu.Des exceptions cependantDans certains circonstances, vous êtes pourtant tenu, même si vous respectez ces conditions, de déclarer les revenus provenant d'une participation à une vente au déballage.C'est d'abord le cas de l'argent obtenu en vendant des métaux précieux. En principe, ils sont taxés à 11 %, à quoi il faut ajouter 0,5 % pour pour la CRDS (contribution au remboursement de la dette sociale).Vous devrez également déclarer vos revenus si la vente vous rapporte plus de 5.000 euros. Dans ce cas, vous serez soumis au régime d'imposition des plus-values, si du moins vous en réalisez une. L'écart entre le prix d'achat et le prix de vente sera taxé au taux de 36,2 %.Ceci étant, tous les biens vendus pour plus de 5.000 euros ne sont pas forcément déclarés. C'est notamment le cas de l'électroménager, des meubles ou encore des voitures, sauf si ce sont des véhicules de collection. See acast.com/privacy for privacy and opt-out information.

About RichRich Burroughs is a Senior Developer Advocate at Loft Labs where he's focused on improving workflows for developers and platform engineers using Kubernetes. He's the creator and host of the Kube Cuddle podcast where he interviews members of the Kubernetes community. He is one of the founding organizers of DevOpsDays Portland, and he's helped organize other community events. Rich has a strong interest in how working in tech impacts mental health. He has ADHD and has documented his journey on Twitter since being diagnosed.Links: Loft Labs: https://loft.sh Kube Cuddle Podcast: https://kubecuddle.transistor.fm LinkedIn: https://www.linkedin.com/in/richburroughs/ Twitter: https://twitter.com/richburroughs Polywork: https://www.polywork.com/richburroughs TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is sponsored in part my Cribl Logstream. Cirbl Logstream is an observability pipeline that lets you collect, reduce, transform, and route machine data from anywhere, to anywhere. Simple right? As a nice bonus it not only helps you improve visibility into what the hell is going on, but also helps you save money almost by accident. Kind of like not putting a whole bunch of vowels and other letters that would be easier to spell in a company name. To learn more visit: cribl.ioCorey: This episode is sponsored in part by Thinkst. This is going to take a minute to explain, so bear with me. I linked against an early version of their tool, canarytokens.org in the very early days of my newsletter, and what it does is relatively simple and straightforward. It winds up embedding credentials, files, that sort of thing in various parts of your environment, wherever you want to; it gives you fake AWS API credentials, for example. And the only thing that these things do is alert you whenever someone attempts to use those things. It's an awesome approach. I've used something similar for years. Check them out. But wait, there's more. They also have an enterprise option that you should be very much aware of canary.tools. You can take a look at this, but what it does is it provides an enterprise approach to drive these things throughout your entire environment. You can get a physical device that hangs out on your network and impersonates whatever you want to. When it gets Nmap scanned, or someone attempts to log into it, or access files on it, you get instant alerts. It's awesome. If you don't do something like this, you're likely to find out that you've gotten breached, the hard way. Take a look at this. It's one of those few things that I look at and say, “Wow, that is an amazing idea. I love it.” That's canarytokens.org and canary.tools. The first one is free. The second one is enterprise-y. Take a look. I'm a big fan of this. More from them in the coming weeks.scaCorey: Welcome to Screaming in the Cloud. I'm Corey Quinn. Periodically, I like to have, well, let's call it fun, at the expense of developer advocates; the developer relations folks; DevRelopers as I insist on pronouncing it. But it's been a while since I've had one of those come on the show and talk about things that are happening in that universe. So, today we're going back to change that a bit. My guest today is Rich Burroughs, who's a Senior Developer Advocate—read as Senior DevReloper—at Loft Labs. Rich, thanks for joining me.Rich: Hey, Corey. Thanks for having me on.Corey: So, you've done a lot of interesting things in the space. I think we first met back when you were at Sensu, you did a stint over at Gremlin, and now you're over at Loft. Sensu was monitoring things, Gremlin was about chaos engineering and breaking things on purpose, and when you're monitoring things that are breaking that, of course, leads us to Kubernetes, which is what Loft does. I'm assuming. That's probably not your marketing copy, though, so what is it you folks do?Rich: I was waiting for your Kubernetes trash talk. I knew that was coming.Corey: Yeah. Oh, good. I was hoping I could sort of sneak it around in there.Rich: [laugh].Corey: But yeah, you know me too well.Rich: By the way, I'm not dogmatic about tools, right? I think Kubernetes is great for some things and for some use cases, but it's not the best tool for everything. But what we do is we really focus a lot on the experience of developers who are writing applications that run in Kubernetes cluster, and also on the platform teams that are having to maintain the clusters. So, we really are trying to address the speed bumps, the things that people bang their shins on when they're trying to get their app running in Kubernetes.Corey: Part of the problem I've always found is that the thing that people bang their shins on is Kubernetes. And it's one of those, “Well, it's sort of in the title, so you can't really avoid it. The only way out is through.” You could also say, “It's better never begin; once begun, better finish.” The same thing seems to apply to technology in a whole bunch of different ways.And that's always been a strange thing for me where I would have bet against Kubernetes. In fact, I did, and—because it was incredibly complicated, and it came out of Google, not that someone needed to tell me. It was very clearly a Google-esque product. And we saw it sort of take the world by storm, and we are all senior YAML engineers now. And here we are.And now you're doing developer advocacy, which means you're at least avoiding the problem of actually working with Kubernetes day-in-day out yourself, presumably. But instead, you're storytelling about it.Rich: You know, I spent a good part of my day a couple days ago fighting with my Kubernetes cluster at Docker Desktop. So, I still feel the pain some, but it's a different kind of pain. I've not maintaining it in production. I actually had the total opposite experience to you. So, my introduction to Kubernetes was seeing Kelsey Hightower talk about it in, like, 2015.And I was just hooked. And the reason that I was hooked is because of what Kubernetes did, and I think especially the service primitive, is that it encoded a lot of these operational patterns that had developed into the actual platform. So, things like how you check if an app is healthy, if it's ready to start accepting requests. These are things that I was doing in the shops that I was working at already, but we had to roll it ourselves; we had to invent a way to do that. But when Kelsey started talking about Kubernetes, it became apparent to me that the people who designed this thing had a lot of experience running applications in distributed systems, and they understood what you needed to be able to do that competently.Corey: There's something to be said for packaging and shipping expertise, and it does feel like we're on a bit of a cusp, where the complexity has risen and risen and risen, and it's always a sawtooth graph where things get so complicated that you then are paying people a quarter-million dollars a year to run the thing. And then it collapses in on itself. And the complexity is still there, but it's submerged to a point where you don't need to worry about it anymore. And it feels like we're a couple years away from Kubernetes hitting that, but I do view that as inevitable. Is that, basically, completely out to sea? Is that something that you think is directionally correct, or something else?Rich: I mean, I think that the thing that's been there for a long time is, how do we take this platform and make it actually usable for people? And that's a lot more about the whole CNCF ecosystem than Kubernetes itself. How do we make it so that we can easily monitor this thing, that we can have observability, that we can deploy applications to it? And I think what we've seen over the last few years is that, even more than Kubernetes itself, the tools that allow you to do those other things that you need to do to be able to run applications have exploded and gotten a lot better, I think.Corey: The problem, of course, is the explosion part of it because we look at the other side, at the CNCF landscape diagram, and it is a hilariously overwrought picture of all of the different offerings and products and tools in the space. There are something like 400 blocks on it, the last time I checked. It looks like someone's idea of a joke. I mean, I come up with various shitposts that I'm sort of embarrassed I didn't come up with one anywhere near that funny.Rich: I left SRE a few years ago, and this actually is one of the reasons. So, the explosion in tools gave me a huge amount of imposter syndrome. And I imagine I'm not the only one because you're on Twitter, you're hanging around, you're seeing people talk about all these cool tools that are out there, and you don't necessarily have a chance to play with them, let alone use them in production. And so what I would find myself doing is I would compare myself to these people who were experts on these tools. Somebody who actually invented the thing, like Joe Beda or something like that, and it's obviously unfair to do because I'm not that person. But my brain just wants to do that. You see people out there that know more than you and a lot of times I would feel bad about it. And it's an issue, I really think it is.Corey: So, one of the problems that I ran into when I left SRE was that I was solving the same problem again and again, in rapid succession. I was generally one of the first early SRE-type hires, and, “Oh, everything's on fire, and I know how to fix those things. We're going to migrate out of EC2 Classic into VPCs; we're going to set up infrastructure as code so we're not hand-building these things from scratch every time.” And in time, we wind up getting to a point where it's, okay, there are backups, and it's easy to provision stuff, and things mostly work. And then it becomes tedium, where the day starts to look too much alike.And I start looking for other problems elsewhere in the organization, and it turns out that when you don't have strategic visibility into what other orgs are doing but tell them what they're doing wrong, you're not a popular person; and you're often wrong. And that was a source of some angst in my case. The reason I started what I do now is because I was looking to do something different where no two days look alike, and I sort of found that. Do you find that with respect to developer advocacy, or does it fall into some repetitive pattern? Not there's anything wrong with that; I wish I had the capability to do that, personally.Rich: So, it's interesting that you mentioned this because I've talked pretty publicly about the fact that I've been diagnosed with ADHD a few months ago. You talked about the fact that you have it as well. I loved your Twitter thread about it, by the way; I still recommend it to people. But I think the real issue for me was that as I got more advanced in my career, people assumed that because you have ‘senior' in your title, that you're a good project manager. It's just assumed that as you grow technically and move into more senior roles, that you're going to own projects. And I was just never good at that. I was always very good at reactive things, I think I was good at being on call, I think I was good at responding to incidents.Corey: Firefighting is great for someone with our particular predilections. It's, “Oh, great. There's a puzzle to solve. It's extremely critical that we solve it.” And it gets the adrenaline moving. It's great, “Cool, now fill out a bunch of Jira tickets.” And those things will sit there unfulfilled until the day I die.Rich: Absolutely. And it's still not a problem that I've solved. I'll preface this with the kids don't try this at home advice because everybody's situation is different. I'm a white guy in the industry with a lot of privilege; I've developed a really good network over the years; I don't spend a lot of time worried about what happens if I lose my job, right, or how am I going to get another one. But when I got this latest job that I'm at now, I was pretty open with the CEO who interviewed me—it's a very small company, I'm like employee number four.And so when we talked to him ahead of time, I was very clear with him about the fact that bored Rich is bad. If Rich gets bored with what he's doing, if he's not engaged, it's not going to be good for anyone involved. And so—Corey: He's going to go find problems to solve, and they very well may not align with the problems that you need solved.Rich: Yeah, I think my problem is more that I disengage. Like, I lose my passion for what it is that I'm doing. And so I've been pretty intentional about trying to kind of change it up, make different kinds of content. I happen to be at this place that has four open-source projects, right, along with our commercial project. And so, so far at least, there's been plenty for me to talk about. I haven't had to worry about being bored so far.Corey: Small companies are great for that because you're everyone does everything to some extent; you start spreading out. And the larger a company gets, the smaller your remit is. The argument I always made against working at Google, for example was, let's say that I went in with evil in mind on day one. I would not be able—regardless of how long I was there, how high in the hierarchy I climbed—to take down google.com for one hour—the search engine piece.If I can't have that much impact intentionally, then the question really becomes how much impact can I have in a positive direction with everyone supposedly working in concert with me? And the answer I always came up with was not that much, not in the context of a company like that. It's hard for me to feel relevant to a large company. For better or worse, that is the thing that keeps me engaged is, “You know, if I get this wrong enough, we don't have a company anymore,” is sort of the right spot for me.Rich: [laugh]. Yeah, I mean, it's interesting because I had been at a number of startups last few years that were fairly early stage, and when I was looking for work this last time, my impulse was to go the opposite direction, was to go to a big company, you know, something that was going to be a little more stable, maybe. But I just was so interested in what these folks were building. And I really clicked with Lukas, the CEO, when we talked, and I ended up deciding to go this route. But there's a flip side to that.There's a lot of responsibility that comes with that, too. Part of me wanting to avoid being in that spotlight, in a way; part of me wanted to back off and be one of the million people building things. But I'm happy that I made this choice, and like I said, it's been working out really well, so far.Corey: It seems to be. You seem happy, which is always a nice thing to be able to pick up from someone in how they go about these things. Talk to me a little bit about what Loft does. You're working on some virtual cluster nonsense that mostly sails past me. Can you explain it using small words?Rich: [laugh]. Yeah, sure. So, if you talk to people who use Kubernetes, a lot, you are—Corey: They seem sad all the time. But please continue.Rich: One of the reasons that they're sad is because of multi-tenancy in Kubernetes; it just wasn't designed with that sort of model in mind. And so what you end up with is a couple of different things that happen. Either people build these shared clusters and feel a whole lot of pain trying to share them because people commonly use namespaces to isolate things, and that model doesn't completely work. Because there are objects like CRDs and things that are global, that don't live in the namespace, and so that can cause pain. Or the other option that people go with is that they just spin up a whole bunch of clusters.So, every team or every developer gets their own cluster, and then you've got all this cluster sprawl, and you've got costs, and it's not great for the environment. And so what we are really focused a lot on with the virtual cluster stuff is it provides people what looks like a full-blown Kubernetes cluster, but it just lives inside the namespace on your host cluster. So, it actually uses K3s, from the Rancher folks, the SUSE folks. And literally, this K3s API server sits in the namespace. And as a user, it looks to you like a full-blown Kubernetes cluster.Corey: Got it. So, basically a lightweight [unintelligible 00:13:31] that winds up stripping out some of the overwrought complexity. Do you find that it winds up then becoming a less high-fidelity copy of production?Rich: Sure. It's not one-to-one, but nothing ever is, right?Corey: Right. It's a question of whether people admit it or not, and where they're willing to make those trade-offs.Rich: Right. And it's a lot closer to production than using Docker Compose or something like that. So yeah, like you said, it's all about trade-offs, and I think that everything that we do as technical people is about trade-offs. You can give everybody their own Kubernetes cluster, you know, would run it in GK or AWS, and there's going to be a cost associated with that, not just financially, but in terms of the headaches for the people administering things.Corey: The hard part from where I've always been sitting has just been—because again, I deal with large-scale build-outs; I come in in the aftermath of these things—and people look at the large Kubernetes environments that they've built and it's expensive, and you look at it from the cloud provider perspective, and it's just a bunch of one big noisy application that doesn't make much sense from the outside because it's obviously not a single application. And it's chatty across availability zone boundaries, so it costs two cents per gigabyte. It has no [affinity 00:14:42] for what's nearby, so instead of talking to the service that is three racks away, it talks the thing over an expensive link. And that has historically been a problem. And there are some projects being made in that direction, but it's mostly been a collective hand-waving around it.And then you start digging into it in other directions from an economics perspective, and they're at large scale in the extreme corner cases, it always becomes this, “Oh, it's more trouble than it's worth.” But that is probably unfair for an awful lot of the real-world use cases that don't rise to my level of attention.Rich: Yeah. And I mean, like I said earlier, I think that it's not the best use case for everything. I'm a big fan of the HashiCorp tools. I think Nomad is awesome. A lot of people use it, they use it for other things.I think that one of the big use cases for Nomad is, like, running batch jobs that need to be scheduled. And there are people who use Nomad and Kubernetes both. Or you might use something like Cloud Run or AppRun, whatever works for you. But like I said, from someone who spent literally decades figuring out how to operate software and operating it, I feel like the great thing about this platform is the fact that it does sort of encode those practices.I actually have a podcast of my own. It's called Kube Cuddle. I talk to people in the Kubernetes community. I had Kelsey Hightower on recently, and the thing that Kelsey will tell you, and I agree with him completely, is that, you know, we talk about the complexity in Kubernetes, but all of that complexity, or a lot of it, was there already.We just dealt with it in other ways. So, in the old days, I was the Kubernetes scheduler. I was the guy who knew which app ran on which host, and deployed them and did all that stuff. And that's just not scalable. It just doesn't work.Corey: This episode is sponsored by our friends at Oracle Cloud. 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Visit https://snark.cloud/oci-free that's https://snark.cloud/oci-free.Corey: The hardest part has always been the people aspect of things, and I think folks have tried to fix this through a lens of, “The technology will solve the problem, and that's what we're going to throw at it, and see what happens by just adding a little bit more code.” But increasingly, it doesn't work. It works for certain problems, but not for others. I mean, take a look at the Amazon approach, where every team communicates via APIs—there's no shared data stores or anything like that—and their entire problem is a lack of internal communication. That's why the launch services that do basically the same thing as each other because no one bothers to communicate with one another. And half my job now is introducing Amazonians to one another. It empowers some amazing things, but it has some serious trade-offs. And this goes back to our ADHD aspect of the conversation.Rich: Yeah.Corey: The thing that makes you amazing is also the thing that makes you suck. And I think that manifests in a bunch of different ways. I mean, the fact that I can switch between a whole bunch of different topics and keep them all in state in my head is helpful, but it also makes me terrible, as far as an awful lot of different jobs, where don't come back to finish things like completing the Jira ticket to hit on Jira a second time in the same recording.Rich: Yeah, I'm the same way, and I think that you're spot on. I think that we always have to keep the people in mind. You know, when I made this decision to come to Loft Labs, I was looking at the tools and the tools were cool, but it wasn't just that. It's that they were addressing problems that people I know have. You hear these stories all the time about people struggling with the multi-tenancy stuff and I could see very quickly that the people building the tools were thinking about the people using them, and I think that's super important.Corey: As I check your LinkedIn profile, turns out, no, we met back in your Puppet days, the same era that I was a traveling trainer, teaching people how to Puppet and hoping not to get myself ejected from the premises for using sarcastic jokes about the company that I was conducting the training for. And that was fun. And then I worked at a bunch of places, you worked in a bunch of places, and you mentioned a few minutes ago that we share this privilege where if one of us loses our job, the next one is going to be a difficult thing for us to find, given the skill set that we have, the immense privilege that we enjoy, and the way that this entire industry works. Now, I will say that has changed somewhat since starting my own company. It's no longer the fear of, “Well, I'm going to land on my feet.” Rich: Right.Corey: Yeah, but I've got a bunch of people who are counting on me not to completely pooch this up. So, that's the thing that keeps me awake at night, now. But I'm curious, do you feel like that's given you the flexibility to explore a bunch of different company types and a bunch of different roles and stretch yourself a little with the understanding that, yeah, okay. If you've never last five years at the same company, that's not an inherent problem.Rich: Yeah, it's interesting. I've had conversations with people about this. If you do look up my LinkedIn, you're going to see that a lot of the recent jobs have been less than two years: year, year and a half, things like that. And I think that I do have some of that freedom, now. Those exits haven't always been by choice, right?And that's part of what happens in the industry, too. I think I've been laid off, like, four or five times now in my career. The worst one by far was when the bubble burst back in 2000. I was working at WebMD, and they ended up closing our office here.Corey: You were Doctor Google.Rich: I kind of was. So, I was actually the guy who would deploy the webmd.com site back then. And it was three big Sun servers. And I would manually go in and run shell scripts and take one out of the load balancer and roll the new code on it, and then move on to the next one. And those are early days; I started in the industry in about '95. Those early days, I just felt bulletproof because everybody needed somebody with my skills. And after that layoff in 2000, it was a lot different. The market just dried up, I went 10 months unemployed. I ended up taking a job where I took a really big pay cut in a role that wasn't really good for me, career-wise. And I guess it's been a little bit of a comfort to me, looking back. If I get laid off now, I know it's not going to be as bad as that was. But I think that's important, and one of the things that's helped me a lot and I'm assuming it's helped you, too, is building up a network, meeting people, making friends. I sort of hate the word networking because it has really negative connotations to it to me. The salespeople slapping each other on the back at the bar and exchanging business cards is the image that comes to my mind when I think of networking. But I don't think it has to be like that. I think that you can make genuine friendships with people in the industry that share the interests and passions that you have.Corey: That's part of it. People, I think, also have the wrong idea about passion and how that interplays with career. “Do a thing that you love, and the money will follow,” is terrific advice in the United States to make about $30,000 a year. I assure you, when I started this place, I was not deeply passionate about AWS billing. I developed a passion for it as I rapidly had to become an expert in this thing.I knew there was an expensive business problem there that leveraged the skill set that I already had and I could apply it to something that was valuable to more than just engineers because let's face it, engineers are generally terrible customers for a variety of reasons. And by doing that and becoming the expert in that space, I developed a passion for it. I think it was Scott Galloway who in one of his talks said he had a friend who was a tax attorney. And do you think that he started off passionate about tax law? Of course not.He was interested in making a giant pile of money. Like, his preferred seat when he flies is ‘private.' So, he's obviously very passionate about it now, but he found something that he could enjoy that would pay a bunch of money because it was an in-demand, expensive skill. I often wonder if instead of messing around and computers, my passion had been oil painting, for example. Would I have had anything approaching to the standard of living I have now?The answer is, “Of course not.” It would have been a very different story. And that says many deeply troubling things about our society across the board. I don't know how to fix any of them. I'm one of those people that rather than sitting here talking how the world should be; I deal with the world as I encounter it.And at times, that doesn't feel great, but it is the way that I've learned to cope, I guess, with the existential angst. I'm envious in some ways of the folks who sit here saying, “No, we demand a better world.” I wish I shared their optimism or ability to envision it being different than it is, but I just don't have it.Rich: Yeah, I mean, there are oil painters who make a whole lot of money, but it's not many of them, right?Corey: Yeah, but you shouldn't have to be dead first.Rich: [laugh]. I used to… know a painter who Jim Carrey bought one of his big canvases for quite a lot of money. So, they're not all dead. But again, your point is very valid. We are in this bubble in the tech industry where people do make on average, I think, a lot more money than people do in many other kinds of jobs.And I recently started thinking about possibly going into ADHD coaching. So, I have an ADHD coach myself; she has made a very big difference in my life so far. And I actually have started taking classes to prepare for possibly getting certified in that. And I'm not sure that I'm going to do it. I may stay in tech.I may do some of both. It doesn't have to be either-or. But it's been really liberating to just have this vision of myself working outside of tech. That's something that I didn't consider was even possible for quite a long time.Corey: I have to confess I've never had an ADHD coach. I was diagnosed when I was five years old and back then—my mother had it as well, and the way that it was dealt with in the '50s and '60s when she was growing up was, she had a teacher once physically tie her to a chair. Which—Rich: Oh, my gosh.Corey: —is generally frowned upon these days. And coaching was never a thing. They decided, “Oh, we're going to medicate you to the gills,” in my case. And that was great. I was basically a zombie for a lot of my childhood.When I was 17, I took myself off of it and figured I'd white-knuckle it for the next 10 years or so. Again, everyone's experience is different, but for me, didn't work, and it led to some really interesting tumultuous times in my '20s. I've never explored coaching just because it feels like so much of what I do is the weirdest aspects of different areas of ADHD. I also have constraints upon me that most folks with ADHD wouldn't have. And conversely, I have a tremendous latitude in other areas.For example, I keep dropping things periodically from time to time; I have an assistant. Turns out that most people, they bring in an assistant to help them with stuff will find themselves fired because you're not supposed to share inside company data with someone who is not an employee of that company. But when you own the company, as I do, it's well, okay, I'm not supposed to share confidential client data or give access to it to someone who's not an employee here. “Da da da da da. Welcome aboard. Your first day is Monday.”And now I've solved that problem in a way that is not open to most people. That is a tremendous benefit and I'm constantly aware of how much privilege is just baked into that. It's a hard thing for me to reconcile, so I've never explored the coaching angle. I also, on some level—and this is an area that I understand is controversial and I in no way, shape or form, mean any—want anyone to take anything negative away from this. There are a number of people I know where ADHD is a cornerstone of their identity, where that is the thing that they are.That is the adjective that gets hung on them the most—by choice, in many cases—and I'm always leery about going down that path because I'm super strange ever on a whole bunch of different angles, and even, “Oh, well he has ADHD. Does that explain it?” No, not really. I'm still really, really strange. But I never wanted to go down that path of it being, “Oh, Corey. The guy with ADHD.”And again, part of this is growing up with that diagnosis. I was always the odd kid, but I didn't want to be quote-unquote, “The freak” that always had to go to the nurse's office to wind up getting the second pill later in the day. I swear people must have thought I had irritable bowel syndrome or something. It was never, “Time to go to the nurse, Corey.” It was one of those [unintelligible 00:27:12]. “Wow, 11:30. Wow, he is so regular. He must have all the fiber in his diet.” Yeah, pretty much.Rich: I think that from reading that Twitter thread of yours, it sounds like you've done a great job at mitigating some of the downsides of ADHD. And I think it's really important when we talk about this that we acknowledge that everybody's experience is different. So, your experience with ADHD is likely different than mine. But there are some things that a lot of us have in common, and you mentioned some of them, that the idea of creating that Jira ticket and never following through, you put yourself in a situation where you have people around you and structures, external structures, that compensate for the things that you might have trouble with. And that's kind of how I'm looking at it right now.My question is, what can I do to be the most successful Rich Burroughs that I can be? And for me right now, having that coach really helps a lot because being diagnosed as an adult, there's a lot of self-image problems that can come from ADHD. You know that you failed at a lot of things over time; people have often pointed that out to you. I was the kid in high school who the counselors or my teachers were always telling me I needed to apply myself.Corey: “If you just tried harder and suck a little less, then you'll be much better off.” Yeah, “Just to apply yourself. You have so much potential, Rich.” Does any of that ring a bell?Rich: Yeah, for sure. And, you know, something my coach said to me not too long ago, I was talking about something and I said to her, I can't do X. Like, I'm just not—it's not possible. And her response was, “Well, what if you could?” And I think that's been one of the big benefits to me is she helps me think outside of my preconceptions of what I can do.And then the other part of it, that I'm personally finding really valuable, is having the goal setting and some level of accountability. She helps with those things as well. So, I'm finding it really useful. I'm sure it's not for everybody. And like we said, everybody's experience with ADHD isn't the same, but one of the things that I've had happened since I started talking about getting diagnosed, and what I've learned since then, is I've had a bunch of people come to me.And it's usually on Twitter; it's usually in DMs; you know, they don't want to talk about it publicly themselves, but they'll tell me that they saw my tweets and they went out and got diagnosed or their kid got diagnosed. And when I think about the difference that could make in someone's life, if you're a kid and you actually get diagnosed and hopefully get better treatment than it sounds like you did, it could make a really big positive impact in someone's life and that's the reason that I'm considering putting doing it myself is because I found that so rewarding. Some of these messages I get I'm almost in tears when I read them.Corey: Yeah. The reason I started talking about it more is that I was hoping that I could serve as something of, if not a beacon of inspiration, at least a cautionary tale of what not to do. But you never know if you ever get there or not. People come up and say that things you've said or posted have changed the trajectory of how they view their careers and you've had a positive impact on their life. And, I mean, you want to talk about weird Gremlins in our own minds?I always view that as just the nice things people say because they feel like they should. And that is ridiculous, but that's the voice in my head that's like, “You aren't shit, Corey, you aren't shit,” that's constantly whispering in my ear. And it's, I don't know if you can ever outrun those demons.Rich: I don't think I can outrun them. I don't think that the self-image issues I have are ever going to just go away. But one thing I would say is that since I've been diagnosed, I feel like I'm able to be at least somewhat kinder to myself than I was before because I understand how my brain works a little bit better. I already knew about the things that I wasn't good at. Like, I knew I wasn't a good project manager; I knew that already.What I didn't understand is some of the reasons why. I'm not saying that it's all because of ADHD, but it's definitely a factor. And just knowing that there's some reason for why I suck, sometimes is helpful. It lets me let myself off the hook, I guess, a little bit.Corey: Yeah, I don't have any answers here. I really don't. I hope that it becomes more clear in the fullness of time. I want to thank you for taking so much time to speak with me about all these things. If people want to learn more, where can they find you?Rich: I'm @richburroughs on Twitter, and also on Polywork, which I've been playing around with and enjoying quite a bit.Corey: I need to look into that more. I have an account but I haven't done anything with it, yet.Rich: It's a lot of fun and I think that, speaking of ADHD, one of the things that occurred to me is that I'm very bad at remembering the things that I accomplish.Corey: Oh, my stars, yes. People ask me what I do for a living and I just stammer like a fool.Rich: Yeah. And it's literally this map of, like, all the content I've been making. And so I'm able to look at that and, I think, appreciate what I've done and maybe pat myself on the back a little bit.Corey: Which is important. Thank you so much again, for your time, Rich. I really appreciate it.Rich: Thanks for having me on, Corey. This was really fun.Corey: Rich Burroughs, Senior Developer Advocate at Loft Labs. I'm Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice along with a comment telling me what the demon on your shoulder whispers into your ear and that you can drive them off by using their true name, which is Kubernetes.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

Cloud Posse holds public "Office Hours" every Wednesday at 11:30am PST to answer questions on all things related to DevOps, Terraform, Kubernetes, CICD. Basically, it's like an interactive "Lunch & Learn" session where we get together for about an hour and talk shop. These are totally free and just an opportunity to ask us (or our community of experts) any questions you may have. You can register here: https://cloudposse.com/office-hoursJoin the conversation: https://slack.cloudposse.com/Find out how we can help your company:https://cloudposse.com/quizhttps://cloudposse.com/accelerate/Learn more about Cloud Posse:https://cloudposse.comhttps://github.com/cloudpossehttps://sweetops.com/https://newsletter.cloudposse.comhttps://podcast.cloudposse.com/[00:00:00​] Intro[00:01:17​] July 21st: Waypoint Demo presented by Taylor Dolezal  [00:01:45​] AWS Controllers for Kubernetes - manage AWS resources from K8shttps://aws.amazon.com/blogs/containers/aws-controllers-for-kubernetes-ack/[00:05:54] Free AWS Certified Solutions Architect Associate Training by AWShttps://www.techrepublic.com/article/aspiring-aws-cloud-architects-have-a-new-free-learning-option-on-twitch/[00:06:45​] Behind the scenes of AWS Lambdahttps://www.bschaatsbergen.com/behind-the-scenes-lambda[00:07:45​] Amazon EKS managed node groups now supports parallel node upgradeshttps://aws.amazon.com/about-aws/whats-new/2021/07/amazon-eks-managed-node-groups-now-supports-parallel-node-upgrades/[00:09:00​] Why are CRDs with Helm such a pain? Helm explains.https://github.com/helm/community/blob/main/hips/hip-0011.md[00:00:00​] Anyone know if AWS SSO supports the SourceIdentity attribute?https://aws.amazon.com/blogs/security/how-to-relate-iam-role-activity-to-corporate-identity/[00:13:42​] How to manage Terraform dev/stage/prod releases when you're utilizing terraform workspaces over the directory structure approach?[00:33:01​] Best reverse proxy options to replace Apache httpd with docker-compose [00:39:07​] @AquaSecTeam has acquired @tfsec_devhttps://www.aquasec.com/news/aqua-security-acquires-tfsec/[00:39:49] What does the test workflow looks like in the Cloud Posse Terraform repositories[00:50:50​] Distinguishing between (Datadog) metrics from our internal services (EKS) and the infrastructure services, like DD agent, k8-cni, etc. [00:53:03​] When will Kubernetes fix the issue with Jobs and InitContainers? [00:55:56] Terraform Enterprise vs S3 bucket for state management[01:02:06​] Outro#officehours,#cloudposse,#sweetops,#devops,#sre,#terraform,#kubernetes,#awsSupport the show (https://cloudposse.com/office-hours/)

Jim and Chris answer listener questions about Social Security, Delayed Retirement Credits, IRD, CRDs, and Commission-Free Annuities. (4:45) A Nevadan wants to know if severance payments affect their Social Security earnings record. (13:38) A listener asks two questions about Social Security survivor benefits and delayed retirement credits. (24:57) George from California wanted clarification on a […] The post Social Security, Delayed Retirement Credits, IRD, CRDs, and Commission-Free Annuities: Q&A #2112 appeared first on The Retirement and IRA Show.

https://go.dok.community/slack Abstract of the talk… Is deploying Postgres in Kubernetes just repackaging it into a container? Can't Postgres leverage the wide range of Cloud-Native software and integrate well with K8s? Join this journey that will cover and demonstrate, with demos running on StackGres: How to structure Postgres into an init-less container, plus several sidecar containers for connection pooling, backups, agents, etc. Defining high level CRDs as the single API to interact with the Postgres operator. Using K8s RBAC for user authentication of a web UI management interface. Using Prometheus for monitoring; bundling a node, Postgres and PgBouncer exporters together. Proxying Postgres traffic through Envoy. Terminate Postgres SSL with an Envoy plugin, that also exports wire protocol metrics to Prometheus. Using Fluentbit to capture Postgres logs and forward them to Fluentd, which stores them on a centralized Postgres database. Key take-aways from the talk… Understand how and why to "de-construct" Postgres into a cloud native application. Learn how to leverage K8s CRDs to interact with Postgres in Kubernetes, without being a Postgres expert. Understand the benefits of proxying Postgres traffic with the Envoy proxy and its Postgres filter. How to use FluentBit and Fluentd to capture and collect logs from Postgres pods and consolidate into a central location. Learn about the open source StackGres platform, a Postgres Distribution for Kubernetes. The goal of this talk is to share with the Community all the knowledge and best practices learned while integrating Postgres with the Kubernetes ecosystem. They stem from the development of the open source StackGres (https://stackgres.io) Postgres platform. StackGres followed instead a novel approach: re-analyze all Postgres architecture and find what components and subsystems could be externalized to K8s ecosystem tools, and construct sidecars for all the agents and related software, avoiding the use of init systems. Bio… Álvaro is a passionate database and software developer. He founded and works as the Founder & CEO of OnGres (https://ongres.com). He has been dedicated to PostgreSQL and R&D in databases for two decades. An open source advocate and developer at heart, Álvaro is a well-known member of the PostgreSQL Community, to which he has contributed founding the non-profit Fundación PostgreSQL (https://postgresql.fund) and the Spanish PostgreSQL User Group. You can find him frequently speaking at PostgreSQL, database, cloud, and Java conferences. Every year, Álvaro travels approximately three-four times around the globe—in 2020 (or now more likely 2021 due to COVID-19), he will hit the milestone of having delivered 100 tech talks. AWS Data Hero (2019).

Jim and Chris begin to clarify the details on coronavirus related distributions (CRDs) and the tax implications surrounding them in this first part of the CRD focused EDU show. The post Coronavirus Related Distributions (CRDs) Part 1: EDU #2046 appeared first on The Retirement and IRA Show.

Les fonctionnaires internationaux et retraités européens d'une organisation internationale en Suisse (CERN, ONU, OMS, OMPI...) ont gagné une guerre judiciaire  contre l'Etat français sur le terrain des assurances sociales. Ils ne paieront désormais plus de CSG CRDS en France sur les revenus du patrimoine. La décision du Conseil d'État est par ailleurs rétroactive sur 3 ans. Cette bataille a été engagée par un avocat fiscaliste, Maître Michel Brocard, très actif pour les frontaliers et fonctionnaires internationaux, et que j'ai le plaisir d'interviewer aujourd'hui.  Retrouvez plus d'informations sur notre article dédié au sujet et sur le site de Maître Michel Brocard.

Why was Flyte built at Lyft? What sorts of requirements does a ML infrastructure team have at lyft? What problems does it solve / use cases? Where does it fit in in the ML and Data ecosystem? What is the vision? Who should consider using it? Learnings as the engineering team tried to bootstrap an open-source community. Ketan Umare is a senior staff software engineer at Lyft responsible for technical direction of the Machine Learning Platform and is a founder of the Flyte project. Before Flyte he worked on ETA, routing and mapping infrastructure at Lyft. He is also the founder of Flink Kubernetes operator and contributor to Spark on kubernetes. Prior to Lyft he was a founding member of Oracle Baremetal Cloud and lead teams building Elastic Block Storage. Prior to that, he started and lead multiple teams in Mapping and Transportation optimization infrastructure at Amazon. He received his Masters in Computer Science from Georgia Tech specializing in High-performance computing and his Bachelors in Engineering in Computer Science from VJTI Mumbai. Besides work, he enjoys spending time with his daughter and wife. He loves the Pacific Northwest outdoors and will try anything new. Lyft Pricing, Locations, Estimated Time of Arrivals (ETA), Mapping, Self-Driving (L5), etc. What sort of scale, storage, network bandwidth are we looking at? Tens of thousands of workflows, hundreds of thousands of executions, millions of tasks, and tens of millions of containers! Flyte: more than 900k workflow executed a month and more than 30+ million container executions per month Typical flow of information? What are the user stories you’re typically dealing with at lyft? How do you set it up? On-prem, cloud, etc. Helm installable? Why Golang? What problems does it solve? Complex data dependencies? Why Orchestrated compute on demand Reuse and sharing Key features Multi-tenant, hosted, serverless Parametrized, data lineage, caching Additionally, if the run invokes a task that has already been computed before, regardless of who executed it, Flyte will smartly use the cached output, saving you both time and money. Versioning, sharing Modular, loosely coupled Seems like you guys recognize that the best task for the job might be hosted elsewhere, so it was important to integrate other solutions into flyte. Flyte extensions Backend plugins - is it true you can create and manage k8s resources like CRDs for things like spark, sagemaker, bigquery? Drop a Star https://flyte.org Flyte community ----------- Connect With Us ✌️------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Ketan on LinkedIn: https://www.linkedin.com/in/ketanumare/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with David on LinkedIn: https://www.linkedin.com/in/aponteanalytics/

Yesterday I talked about K3s a little bit. Let's take a look at what is out there for K8s on the edge. Why use K8s at the edge? - Consistent platform for development - Test on the cloud, deploy to the edge - The power of CRDs and operators - Doesn't fix the hardware and true edge device issues - Do we really need something on top of Linux and is K8s it? What's out there? - #KubeEdge - resource optimized, open-source, ARM or x86, cloud-edge model - #K3s - sub 40mb executable, ARM or x86, no cloud needed, Server and Agent model - #MicroK8s - canonical, pure upstream K8s, ARM or x86, single-node or cluster model

What impact do ex-spouses, income, and early retirement have on collecting your Social Security benefits? Plus, indexed universal life insurance, estate planning with a step-up in basis on private placement real estate, and more on CRDs, RMDs, and stimulus checks. Joe and Big Al also submit their forecasts for whether Congress might tax Roth IRA growth in the future. Send in money questions and access the episode transcript and free financial resources in the podcast show notes: https://bit.ly/YMYW-281

Jusqu'où pourrait culminer la dette publique française ? Eléments de réponses avec la Cour des Comptes qui publie ses projections dans son rapport sur les perspectives des finances publiques. L'analyse de Raphaël Legendre, journaliste à l'Opinion. Ecorama du 1er juillet 2020, présenté par David Jacquot sur Boursorama.com

In this episode of the Business Cloud Native, host Emily Omier talks with Jon Tirsen, who is engineering lead for storage at Cash App. This conversation focuses on Cash App's cloud native journey, and how they are working to build an application that is more scalable, flexible, and easier to manage.The conversation covers: How the need for hybrid cloud services and uniform program models led Cash App to Kubernetes.  Some of the major scaling issues that Cash App was facing. For example, the company needed to increase user capacity, and add new product lines.  The process of trying to scale Cash App's MySQL database, and the decision to split up their dataset into smaller parts that could run on different databases. Cash App's monolithic application, which contains hundreds of thousands of lines of code — and why it's becoming increasingly difficult to manage and grow.  How Jon's team is trying to balance product/ business and technical needs, and deliver value while rearchitecting their system to scale their operations. Why Cash App is working to build small, product-oriented teams, and a system where products can be executed and deployed at their own pace through the cloud. Jon also discusses some of the challenges that are preventing this from happening. How Cash App was able to help during the pandemic, by facilitating easy stimulus transfers through their service — and why it wouldn't have been possible without a cloud native architecture.  Links: Cash App: https://cash.app/ Square: https://squareup.com/us/en Jon on Twitter: https://twitter.com/tirsen?lang=en Connect with Jon on LinkedIn: https://www.linkedin.com/in/tirsen/?originalSubdomain=au The Business of Cloud Native: http://thebusinessofcloudnative.com  TranscriptAnnouncer: Welcome to The Business of Cloud Native podcast where we explore how end users talk and think about the transition to Kubernetes and cloud-native architectures.Emily: Welcome to The Business of Cloud Native. My name is Emily Omier, I'm here chatting with Jon Tirsen.Jon: Happy to be here. My name is, as you said, Jon Tirsen, and I work as the engineering lead of storage here at Cash App. I've been at Cash for maybe four or five years now. So, I've been with it from the very early days. And before Cash, I was doing a startup, that failed, for five years. So, it's a travel guide in the mobile phone startup. And before that, I was at Google working on another failed product called the Google Wave, which you might remember, and before that, it was a company called ThoughtWorks, which some of you probably know about as well.Emily: And in case people don't know, the Cash App is part of Square, right?Jon: Yes. Cash App is where we're separating all the different products quite a lot these days. So, it used to be called just Square Cash, but now it has its own branding and its own identity, and its own leadership, and everything. So, we're trying to call it an ecosystem of startups. So, each product line can run its business the way it wants to, to a large degree.Emily: And so, what do you actually spend your day doing?Jon: Most of my days, I'm still code, and doing various operational tasks, and setting up systems, and testing, and that sort of thing. I also, maybe about half my day, I spend on more management tasks, which is reviewing documents, writing documents, and talking to people trying to figure out our strategy and so on. So, maybe about half my time, I do real technical things, and then the other half I do more management stuff.Emily: Where would you say the cloud-native journey started for you?Jon: Well, so a lot of Square used to run on-premises. So, we had our own data centers and things. But especially for Cash App, since we've grown so quickly, it started getting slightly out of control. We were basically outgrowing—we could not physically put more machines into our data centers. So, we've started moving a lot of our services over to Amazon in this case, and we want to have a shared way of building services that would work both in the Cloud and also in our data centers. So, something like Kubernetes and all the tools around that would give us a more uniform programming model that we could use to deploy apps in both of these environments. We started that, two, three years ago. We started looking at moving our workload out of our data centers.Emily: What were the issues that you were encountering? Give me a little bit more details about the scaling issues that we were talking about.Jon: There two dimensions that we needed to scale out the Cash App, sort of, system slash [unintelligible] architecture. So, one thing was that we just grew so quickly that we needed to be able to increase capacity. So, that was across the board. So, from databases to application servers, and bandwidth, everywhere. We need to just be able to increase our capacity of handling more users, but also we were trying to grow our product as well. So, at the same time, we also want to build and be able to add new features at an increased pace. So, we want to be able to add new product lines in the Cash App. So, for example, we built the Cash Card, which is a way you can keep your money in the Cash App bank accounts, and then you can spend that money using a separate card, and then we add a new functionality around that card, and so on. So, we also needed to be able to scale out the team to be able to have more people working on the team to build new products for our users, for our customers. Those are the two dimensions: we needed to scale out the system, but we also needed to have more people be able to work productively. So, that's why we started trying to chop up—we have this big monolith as most companies probably do, which that's I don't know how many hundreds of thousands of lines of code in there. But we also wanted to move things out of that, to be able to have more people contribute productively.Emily: And where are you in that process?Jon: Well, [laughs], we're probably adding still adding code at an exponential rate to the monolith. We're also adding code at an exponential rate outside of the monolith, but it just feels so much easier to just build some code in the monolith than it is outside of it, unfortunately, which something we're trying to fix, but it's very hard. And it is getting a little bit out of hand, this monolith now. So, we have, sort of, a moratorium on adding new code to the monolith now, and I'm not sure how much of an effect that has made. But the monolith is still growing, as well as our non-monolith services as well, of course. Emily: When you were faced with this scaling issue, what were the conversations happening between the technical side and the business owners? And how is this decision made about the best way to solve this problem is x, is the Cloud, is cloud-native architecture?Jon: I think the business side—the product owners, product managers—they trust us to make the right decision. So, it was largely a decision made on the technical side. They do still want us to build functionality, and to add new features, and fix bugs, and so on. So, they want us to do that, but they don't really have strong influence on the technical choices we've made. I think that's something we have to balance out. So, how can we keep on giving the product side and the business side what they need? So, to keep on delivering value to them while we try to rearchitect our system so that we can scale out our operations on our side. So, it's a very tricky balance to find there. And I think so far, maybe we've erred on the side of keep on delivering functionality, and maybe we need to do more on the rearchitecting things. But yeah, that's always a constant rebalancing act we're always dealing with. Emily: Do you think that you have gotten the increased scalability? How far along are you on reaching the goals that you originally had?Jon: I think we have a pretty scalable system now, in terms of the amount of customers we can service. So, we can add capacity. If we can keep on adding hardware to it, we can grow very far. We've actually noticed that the last few weeks, we've had an almost unprecedented growth, especially with the Coronavirus crisis. Every single day, it's almost a record. I mean, there's still issues, of course, and we're constantly trying to stay on top of that growth, but we have a reasonably good architecture there. What I think is probably our larger problem is the other side, so the human side. As I said, we are still adding code to this monolith, which is getting completely out of hand to work with. And we're not growing our smaller services fast enough. It's probably time to spend more effort on rearchitecting that side of things as well.Emily: What are some of the organizational, or people challenges that you've run into?Jon: Yeah. So, we want to build smaller teams oriented around products. We see ourselves more of a platform on products these days: we're not just a single product. And we want to build smaller teams. That is, maybe we have one team that is around our card, and one team around our [unintelligible] trading and so on. And we want to have the smaller teams, and we want them to be able to execute independently. So, we want to be able to put together a cross-functional team of some engineers, and some UX people, and some product people, and some business people, and then they should be able to execute independently and have their own services running in our cloud infrastructure, and not have to coordinate too much with all of the other teams that are also trying to execute independently. So, each product can do its own thing, and own their own services, and deploy at their own pace, and so on. That's what we're trying to achieve, but as long as they still have to do a lot of work inside of our big monolith, then they can't really execute independently. So, one team might build something that actually causes issues with another team's products, and so on, and that becomes very complicated to deal with. So, we tried to move away from that, and move towards a model where a team has a couple of services that they own, and they can do most of their work inside of those services.Emily: What do you think is preventing you from being farther along than you are? Farther along towards this idea of teams being totally self-sufficient?Jon: Yeah, I think it's the million-dollar question, really. Why are we still seeing exponential growth in code size in our monolith, and not in our services? And I think it's a combination of many, many things. One thing I think, we don't have all of the infrastructure available to us in our cloud, in our smaller services. So, say you want to build a little feature, you want to add a little button that does something, and if you want to do that inside our monolith, that might take you two, three days. Whereas if you want to pull up a completely new service—I think we've solved it at an infrastructural layer, it's very quick and easy to just pull up a new service, and have it run, and be able to take traffic, and so on—but it's more of the domain-specific infrastructures of being able to access all the different data sets that you need to be able to access, and be able to shift information back to the mobile device. And all these things, it's very easy to do inside a monolith, but it's much harder to do outside of the monolith. So, we have to replicate a big set of what we call product platforms. So, instead of infrastructural platform is more product specific platform features like customer information, and be able to send information back to the client, and so on. And all those things have to be rebuilt for cloud services. We haven't really gotten all the way there yet.Emily: If I understood correctly from the case study with the CNCF, you sort of started the cloud-native journey with your databases.Jon: Yes, that was the thing that was on fire. Cash App was initially built as a hack week project, and it was never really designed to scale. So, it was just running on a single MySQL database for a really long time. And we actually literally put a piece of hardware on fire with that database. We managed to roll it, roll it off, of course, didn't take down our service, but it was actually smoking in our [laughs] data centers. It melted the service around it in its chassis. So, that was a big problem, and we needed to solve that very quickly. So, that's where we started.Emily: Could you actually go into that just a little bit more? I read the case study, but probably most listeners haven't. Why was the database such a big problem? And how did you solve it?Jon: Yeah, as I said, so we only had a single MySQL database. And as most people know, it's very hard to keep on scaling that, so we bought more and more expensive hardware. And since we were a mobile app, we don't get all the benefits from caching and replica reads, so most of the time, the user is actually accessing data that is already on the device, so they don't actually make any calls out to our back end to read the data. Usually, you scale out a database by adding replicas, and caching, and that sort of stuff, but that wasn't our bottleneck. Our bottleneck was that we simply could not write to the database, we couldn't update the database fast enough, or with enough capacity. So, we needed to shard it, and split up the data set into smaller parts that we could run on separate databases. And we used the thing called Vitess for that, which is a Cloud Native Foundation member, a product and [unintelligible] CNCF. And with Vitess, we were able to split up the database into smaller parts. It was quite a large project, and especially back then, Vitess was—it was quite early days. So, the Vitess was used to scale out YouTube and then it was open-sourced. And then, we started using it. I think, not long after that, it was also used by Slack. So now, currently Slack uses it for most of its data. And we started using it very early, so it was still kind of early days, and we had to build a lot of new functionality in there, and we had to port [00:15:20 unintelligible] make sure all of our queries worked with the Vitess. But then we were able to do shard splitting. So, without having to restart or have downtime in our app, we could split up the database into smaller parts, and then the Vitess would handle the routing of queries, and so on.Emily: If at all, how did that serve as the gateway to then starting to think about changing more of the application, or moving more into services as opposed to a monolith?Jon: Yeah, I think that was kind of orthogonal in some ways. So, while we scaled out the database layer, we also realized that we needed to scale out the human side of it. So, we have multiple teams being able to work independently. And that is something we haven't I think we haven't really gotten to completely, yet. So, while we've scaled out the database layer, we're not quite there from the human side of things.Emily: Why is it important to scale any of this out? I understand the database, but why is it important to get the scaling for the teams?Jon: Yeah, I mean, it's a very competitive space, what we're trying to do. We have a very formidable competitors, both from other apps and also from the big banks, and for us to be able to keep on delivering new features for our customers at a high pace, and be able to change those features to react to changing customer demands or, like during this crisis we are in now, and being able to respond to what our competitors are doing. I mean, that just makes us a more effective business. And we don't always know when we start a new product line where it's exactly going to lead us, we sort of look at what our customers are using it and where that takes us, and being able to respond to that quickly, that's something that is very hard if you have a big monolith that has a million lines of code and takes you several hours to compile, then it's going to be very hard for you to deliver functionality and make changes to functionality in a good time.Emily: Can you think of any examples where you're able to respond really quickly to something like this current crisis in a way that wouldn't have been possible with the old models?Jon: I don't actually know the details here. I live currently in Australia, so I don't know. But the US government is handing out these checks, right? So, you get some kind of a subsidy. And apparently, they were going to mail those out to a lot of people, but we actually stepped up and said, look, you can just Cash App them out to people. So, people sign up for a Cash App account, and then they can receive their subsidies directly into the Cash App accounts, or into their bank accounts via our payment rails. And we were able to execute on that very quickly, and I think we are now an official way to get that subsidy from the US government. So, that's something that we probably wouldn't have been able to do unless we've invested more to be able to respond to that so quickly, within just weeks, I think.Emily: And as Cash App has moved to increasingly service-oriented architectures and increasingly cloud-native, what has been surprisingly easy?Jon: Surprisingly easy. I don't think I've been surprised by anything being easy, to my recollection. I think most things have been surprisingly hard. [laughs]. I think we are still somewhat in the early days of this infrastructure, and there are so many issues; there's so many bugs; there's so many unknowns. And when you start digging into things, it just surprises you how hard. So, I work in the infrastructure team, and we try to provide a curated experience for our product teams, the product engineering teams, so we deal with that pain directly where we have to figure out how all these products work together, and how to build functionality on top of them. I think we deal with that pain for our product engineers. But of course, they are also running into things all the time. So, no, it is surprisingly hard sometimes, but it's all right.Emily: What do you think has been surprisingly challenging, unexpectedly challenging?Jon: Maybe I shouldn't be, but I am somewhat surprised how immature things still are. Just as an example, how hard it is, if you run a pod, in a EKS—Amazon Kubernetes cluster, and you just want to authenticate to be able to use other Amazon products like Dynamo, or S3, or something, this is still something that is incredibly hard to do. So, you would think that just having two products from the same vendor inside of the same ecosystem, you would think that that would be a no-brainer: that they would just work together, but no. I think we'll figure it out eventually, but currently, it's still a lot of work to get things to play well together.Emily: If you had a top-three wish list of things for the community to address, what do you think they would be?Jon: Yeah, I guess the out-of-the-box experience with all of these tools, so that they just work together really well, without having to manually set up a lot of different things, that'd be nice. I think I also, maybe this all exists, we haven't integrated all these tools, but something that struck me the other day, I was debugging some production issue—it wasn't a major issue, but it was an issue that had been an ongoing thing for two weeks—and I just wanted to see what change happened those two weeks ago. What was the delta? What made that change happen? And being able to get that information out of Kubernetes and Amazon—and maybe there's some audit logging tools and all this stuff, but it's not entirely clear how to use them, or how to turn them on, and so on. So, that's a really nice, user friendly, and easy to use kind of auditing, and audit trail tools would be really nice. So, that's one wish, I guess, in general: having a curated experience. So, if you start from scratch, and you want to get all of the best practice tools, and you want to get all the functionality out of a cloud infrastructure, there's still a lot of choices to make, and there's a lot of different tools that you need to set up to make them work together, Prometheus, and Grafana, and Kubernetes, and so on. And having a curated out-of-the-box experience that just makes everything work, and you don't have to think about everything, that would be quite nice. So, Kubernetes operators are great, and these CRDs, this metadata you can store and work with inside of Kubernetes is great, but unfortunately they don't play well with the rest of the cloud infrastructure at Amazon, at AWS. Amazon was working on this Amazon operator, which you would be able to configure other AWS resources from inside of the Kubernetes cluster. So, you could have a CRD for an S3 bucket, so you wouldn't need a Terraform. So right now, you can have Helm Charts and similar to manage the Kubernetes side of things, but then you also need Terraform stuff to manage the AWS side of things, but just something thing that unifies this, so you can have a single place for all your infrastructural metadata. That would be nice. And Amazon is working on this, and they open-sourced something like an AWS operator, but I think they actually withdrew it and they are doing something closed-source. I don't know where that project is going. But that would be really nice.Emily: Go back again to this idea of the business of cloud-native. To what extent do you have to talk about this with business stakeholders? What are those conversations look like?Jon: A Cash App, we usually do not pull in product and business people in these conversations, I think, except when it comes to cost [laughs] and budgeting. But they think more in terms of features and being able to deliver and have teams be able to execute independently, and so on. And our hope is that we can construct an infrastructure that provides these capabilities to our business side. So, it's almost like a black box. They don't know what's inside. We are responsible for figuring out how to give it to them, but they don't always know exactly what's inside of the box.Emily: Excellent. The last question is if there's an engineering tool you can't live without?Jon: I would say all of the JetBrains IDEs for development. I've been using those for maybe 20 years, and they keep on delivering new tools, and I just love them all.Emily: Well, thank you so much for joining.Jon: Thanks for inviting me to speak on the podcast.Announcer: Thank you for listening to The Business of Cloud Native podcast. Keep up with the latest on the podcast at thebusinessofcloudnative.com and subscribe on iTunes, Spotify, Google Podcasts, or wherever fine podcasts are distributed. We'll see you next time.This has been HumblePod production. Stay humble.

Last week’s job numbers have had a big impact on this week’s main topic of discussion: reopening. Communities around the country are starting to establish guidelines that will, hopefully, allow more folks to get back to work while also keeping the spread of COVID-19 in check. In the meantime, folks who are hurting are starting to get some relief via extended unemployment benefits and federal tax rebate checks. Others are weighing new options created by the CARES Act, including coronavirus-related distributions (CRDs). If you’re thinking about using your retirement assets to navigate the pandemic, you’re definitely going to want to listen to our discussion on how CRDs may help.

This week's radio show and video guest is Kaaren Hall alongside Bruce and Aaron Norris. Kaaren is the CEO of uDirect IRA Services, and she's also a board member at the Retirement Industry Trust Association. She's here today to fill us in on what you can and can't do with your retirement accounts at these interesting times.  Kaaren will be answering some of Bruce and Aaron's questions regarding the CARES Act and how it impacts retirement accounts.  Bruce and Aaron will also be answering their subscribers' questions and giving us an update on COVID-19, including the latest numbers, the Pandemic Unemployment Assistance, foreclosure evictions, property taxes, CRDs and more.   The Norris Group originates and services loans in California and Florida under California DRE License 01219911, Florida Mortgage Lender License 1577, and NMLS License 1623669.  For more information on hard money lending, go www.thenorrisgroup.com and click the Hard Money tab.Video LinkRadio Show http://www.thenorrisgroup.com/

Running Kubernetes on conventional operating systems is time-consuming and labor-intensive. Today’s guests Andrew Rynhard and Timothy Gerla have engineered a product that attempts to provide a solution to this problem. They call it Talos, and it is a modern OS designed specifically to host Kubernetes clusters, managed by a flexible and powerful API. Talos is completely stripped down to the bare components required to run Kubernetes and get information from the system. It stays updated by keeping time with Kubernetes, but also provides the user with a large degree of control in the event that they might need to update a flag. In this episode, Andrew and Timothy get into some of the mechanics and thought processes behind Talos, telling us why they went with a read-only API, how they handle security concerns on the OS, and how a system like theirs might get adopted by the Kubernetes community and layperson more broadly. They get into the advantages provided by a stripped-down solution for systematizing the use of Kubernetes across communities and running new components through clusters rather than on the OS itself. In a space where most participants are largely operating in the dark, it is a pleasure to see innovations like this display such lasting power so make sure you check out this episode. Follow us: https://twitter.com/thepodlets Website: https://thepodlets.io Feeback: info@thepodlets.io https://github.com/vmware-tanzu/thepodlets/issues Guests: Andrew Rynhard https://twitter.com/andrewrynhard Tim Gerla https://twitter.com/tybstar Hosts: Carlisia Campos Bryan Liles Olive Power Key Points From This Episode: What a Kubernetes OS is: a stripped-down OS that integrates with Kubernetes. The difficulties of managing and getting Kubernetes installed on regular OSs. Why a Kubernetes OS? Less attack surface and OS compatibility issues. What Talos does: quickly makes nodes part of a Kubernetes cluster by being stripped down. How replacing SSH with an API alleviates some users’ security concerns. A command-line interface called OSCTL that allows users to explore the API. What does ‘stripped-down’ mean? Talos runs kubelets and gets information from the OS. The ability to run new components through clusters rather than from the OS. How the Kubernetes OS evolves with Kubernetes but gets separately controlled too. Better integrating into Kubernetes by abstracting OS features into Kubernetes as operators. Security precautions: kernel hardening, SSH and Bash removal, and a read-only OS. Usability of Talos for the average Joe, and its consistency across base platforms. Possibilities for interacting with deeper levels of an OS through an API managed OS. How Talos might become appealing to laypeople: decreasing costs for porting to it. Value gained from switching to a purpose-built OS as something which could outweigh costs. Tendencies to hang onto tried and trusted tech even if its predecessors are superior. Quotes: “To me, it’s just about abstracting away the operating system and not even having to worry about it anymore, and looking at Kubernetes and the entire cluster as an operating system.” — Andrew Rynhard [0:05:00] “As rapid as the technology is changing, you need an operating system that is going to evolve with it or at least the operations intelligence to evolve with Kubernetes right alongside it.” — Andrew Rynhard [0:13:08] “The challenge I think for us and for anybody changing the way that operating systems work is is it better enough than what I have today or what I had before?” — @tybstar [0:26:50] “There’s a lot of companies out there who got us at this point in tech that don’t exist anymore, but if they didn’t do what they did, we would not be here right now.” — @bryanl [0:33:41] Links Mentioned in Today’s Episode: Talos — https://www.talos-systems.com/ Timothy Gerla — http://www.gerla.net/ Timothy Gerla on Twitter — https://twitter.com/tybstar Andrew Ryndhard on LinkedIn —https://www.linkedin.com/in/andrewrynhard/ Andrew Ryndhard on GitHub — https://github.com/andrewrynhard Jed Salazar on LinkedIn — https://www.linkedin.com/in/jedsalazar/ Bryan Liles on LinkedIn — https://www.linkedin.com/in/bryanliles/ Carlisia Campos on LinkedIn — https://www.linkedin.com/in/carlisia/ Red Hat — https://www.redhat.com/en/technologies/linux-platforms/enterprise-linux Arch — https://www.archlinux.org/Debian — https://www.debian.org/ Linux — https://www.linux.org/ Bell Labs — http://www.bell-labs.com/ AT&T — https://www.att.com/ Transcript: EPISODE 20 [INTRODUCTION] [0:00:08.7] ANNOUNCER: Welcome to The Podlets Podcast, a weekly show that explores Cloud Native one buzzword at a time. Each week, experts in the field will discuss and contrast distributed systems concepts, practices, tradeoffs and lessons learned to help you on your Cloud Native journey. This space moves fast and we shouldn’t reinvent the wheel. If you’re an engineer, operator or technically minded decision maker, this podcast is for you. [INTERVIEW] [00:00:41] CC: Hi, everybody. Welcome back to the Podlets. Today we have a special episode, and on the show, we have a special guest, Andrew Ryndhard. Say hi, Andrew. [00:00:53] AR: Hello, how are you? [00:00:55] CC: We also have Timothy Gerla. Say hi, Tim. [00:00:58] TG: Hi. Thanks for having me. [00:01:00] CC: Yeah. Andrew and Timothy are from Talos. Andrew dropped an issue on our GitHub repo and here we are. It was a great suggestion. What we’re going to talk about today is what they are working on, which is a Kubernetes operating system. We have tons of questions for them for sure. We also have a special participant on the episode today as a co-host, Jed Salazar. Hi, Jed. [00:01:28] JS: Hey, everyone. Jed Salazar here from the CRE team here at VMware. [00:01:31] CC: And Bryan Liles. [00:01:32] BL: Hi. [00:01:33] CC: Hi. And me, Carlisia Campos. Who’d like to get the party started and kick this off? [00:01:41] BL: Oh, I’m here. Let’s throw the gauntlet down. We’re talking about Kubernetes operating systems today. I have an operating system, a Mac, or I have Linux. I can run Kubernetes. What is a Kubernetes operating system and why should I even be thinking about this? [00:01:58] AR: Sure. I’d like to think about Kubernetes operating system as an operating system that has stripped down the absolute bare minimum to run Kubernetes. Everything that is required to run the kubelet, and essentially that’s it, at least in my opinion. It should be super minimal to start with. Second of all, I also think that it should integrate with Kubernetes as well. The combination of just being able to strip down Linux as we know as small as possible and then actually integrating with Kubernetes itself using APIs to figure out things about itself, whatever. I think that that, in my opinion, is what I would call a Kubernetes OS. [00:02:42] BL: Interesting. Okay. Now that we know a little bit about Kubernetes operating systems, and like I said, I’m starting in early today as the devil’s advocate. Now, like I said before, I have a Mac and I have Linux and I have Windows on my desktop. There’re been lots of efforts from lots of people trying to get Kubernetes running up on Ubuntu or Fedora, and it’s cool that you’re trying to slim this down, but really why would I look at a Kubernetes operating system over my Linux that I’m familiar with? I like Ubuntu with Debian. [00:03:17] AR: Sure. That’s a great question. It’s one we get a lot. I like to think that you actually just get less operational overhead when you actually have a Kubernetes-specific operating system. I think that Kubernetes itself is a job, managing it, getting it installed, unfortunately. It’s getting better, but it’s still a job at the end of the day. Having to manage Kubernetes and the operating system, everything that you need to pass compliance on the operating system, get all the packages installed, these are all things that we kind of know that Kubernetes needs already and yet we’re still having to go in and app install whatever we might need to get Kubernetes up and running. The idea with a Kubernetes operating system in my mind is that we should stop worrying about the individual node, the underlying operating system and start looking at Kubernetes as a whole as a giant machine and we just add machines, nodes to this giant machine that give us extra resources. The less that we have to care about the machine or the underlying operating system, the better, in my mind. We get to focus on Kubernetes. Not only that, but because it’s minimal, you get a smaller attack surface. There’re just not things there that you would otherwise have to worry about. I’ve done Kubernetes for three years now and having to go in and worry about updating packages that are just completely unrelated, it’s something that I think we shouldn’t have to do anymore. If you’re dedicated to running your apps and your stack in Kubernetes, then why are we going in and managing the nodes on an individual basis. For that matter, managing things that don’t really have any relevance for running Kubernetes. To me, it’s just about abstracting away the operating system and not even having to worry about it anymore and looking at Kubernetes and the entire whole cluster as an operating system. We can’t really get there if we’re having to worry about the two jobs of managing both at the same time. [00:05:17] JS: Andrew, can I ask a follow up question? [00:05:18] AR: Sure. [00:05:20] JS: I fully agree with all of those statements. I think a general purpose operating system might not be the best job for a specific role, like being a Kubernetes node. As you mentioned, you have to deal with kind of all the various packages that might be beneficial to you if you’re running it for some general purpose. It’s really supposed to be running a workload as a Kubernetes node so you can kind of scope that down. I’m just wondering when you kind of make this pitch or kind of let these folks know, how do you get folks to kind of relinquish their desire to have full control over their operating system from being able to install their own security management processes on it or being a little bit shy about not being able to SSH or kind of use their common patterns of operating system management? [00:06:09] AR: Oh, that’s a great question. I think the biggest thing that I always answer back is – I can take this in two parts. Let me first of all talk about what – People, they do want to run things on the host. My answer always back is can you run it in Kubernetes? Kubernetes is sort of your package manager, if you will. They sit back usually and they’re like, “Hmm. Yeah, I probably could.” If you need to run something on every host, Kubernetes has something for that. It’s a daemon set. Run it on Kubernetes and call it a day. This isn’t something that’s going to work for absolutely everything I imagine. Nothing in the world is like that. But I think for the majority of the use cases out there and for the things that people want to run on the host, you could actually just run it in Kubernetes itself. As far as SSH and for those that don’t really know what we’ve done in Talos, in Talos we’ve actually stripped down just the kernel and a small Go lang binary that’s our – That, basically, its whole goal is to create a Kubernetes cluster or make a node part of a Kubernetes cluster as fast as possible, and that’s really it. We’ve gone so far as ripping out Bash and SSH and we’ve actually replaced that with an API. My answer always back to the SSH question is what is it that you really trying to get out of SSH? 9 times out of 10, it’s, “I want to get information about what’s wrong. I want to do troubleshooting.” If our answer back to them is, “Oh! We have an API for that,” you still at the end of the day – it’s really the information that you’re after. It’s not necessarily that you need SSH to do that. You need a way to get this information and not necessarily have to sit there and wait for a Prometheus metric, see it pulled it every minute. You want something right on the spot. You want to ask a question and you want to get an immediate answer. I feel like we can answer that with an API. That tends to satisfy the desire for wanting SSH most of the time. I mean, as you said, people are still going to want to hold on to it, but I think over time we’re going to have to educate people that this is a better way. It’s a read-only API that gives operations engineers a way to get that information that they would otherwise get by SSH-ing and asking via Unix utilities what you want to know. [00:08:27] CC: When you say an API, are you also giving them a command line tool or like in the case of Talos, or only an actual API? [00:08:37] TG: Yeah, we do provide a command line interface to the API. It’s called OSCTL and it basically wraps our API, and our intention is that that will be used for exploration of the system, automation through scripting languages, etc. Then as you get more sophisticated with your environment, you might begin to build your own tools that interact directly with that API. [00:08:56] CC: Cool. Yeah, this is a really cool subject. I wasn’t even aware that Kubernetes operating system was a thing until really recently, and I don’t remember how I came across it. One question I have is, Andrew, you were saying, “Well, we strip down Kubernetes to the bare minimum.” How opinionated is it in your case in specific? When you say you – it’s a stripped down version to the bare minimum, this statement of bare minimum, would there be a consensus in the community that, yes, this set of functionality is the bare minimum? Is it your opinion of what the bare minimum should be? [00:09:38] AR: Sure. I think at the absolute bare minimum, we need to run the kubelet. In my mind, that’s really all we need, but you still have this practical issue of, like you said, you need to get information off that machine. You need to be able to kind of manage Kubernetes without having to need Kubernetes as a chicken and egg’s problem. That’s where the API was actually born. When I started Talos, I actually just built a very minimal strip down route-fs that all that did was run the kubelet. But figuring out why the kubelet wasn’t running successfully obviously was not very easy. I figured, “You know what? Let’s put an API in front of this. I want to keep this as minimal as possible. I want to keep this read-only.” I threw an API in front of it. I think you need two things, really. You need to have what’s required by the kubelet. You need a CNI. You need all the utilities that the kubelet will run and you also need a way to query the system. If that is – If in the case of other operating systems that are minimal operating systems, they have decided to do SSH and all the classic utilities that we all know and love, we went another route with an API. But I don’t think the operating system, the route-fs should have any more than what’s required by the kubelet. That would be the pie in the sky dream right there. [00:11:01] CC: The two questions that come to my mind are if I wanted to add Kubernetes components to that, would it be possible? If I wanted to add anything to the operating system, would it possible? I think the second question you already answered, which is, well, if you need to run – Correct me if I’m wrong. If you need to run something on the operating system that’s not there, you can run it in the actual cluster. [00:11:27] AR: Yeah, that’s the idea, is that Kubernetes gives us the APIs to do – We could schedule to specific nodes. We can schedule to a class of nodes. We can schedule to every single node. I think that you can actually handle a lot of the use cases out there for any kind of application with Kubernetes itself. I think that that’s really strong because you get one single consistent API in managing your infrastructure. I want to deploy applications for this team or this team. At the end of the day, everything is just declarative and Kubernetes will make it happen. You don’t have to worry about the scheduling and all of these different things. The only thing that the operating system is concerned about is making that machine available to the Kubernetes cluster. [00:12:10] BL: This idea of slimmed down operating systems, it’s not a new one. CoreOS was doing this years ago. One issue that CoreOS ran into was like, “Well, what’s current?” Well, it depends on what stream you’re on. How do you manage keeping everything up-to-date? [00:12:28] AR: Our goal is to keep pace with Kubernetes essentially. I know that, traditionally, there’s long-term support and there’s all these different ways of releasing different versions of an operating system, but Kubernetes isn’t really there yet. There is no notion that I know of of LTS in Kubernetes yet. There’s just, I believe, it’s N-2 or something like that where they actually offer official support. I think that the operating system is bound to that. I think that it needs to follow Kubernetes as close as possible. There’re constantly different feature gates being opened up. There’re things being graduated to GA. I think especially at this time right now, as rapid as the technology is changing, you need an operating system that is going to evolve with it or at least the operations intelligence to evolve with Kubernetes right alongside it. [00:13:20] BL: So that brings up an interesting point. I mean, there are two things here. There’s the operating system itself and there’s Kubernetes. Do they upgrade in lockstep or are they upgraded separately? [00:13:29] AR: I could only speak for ourselves. There are people that I think they actually have upgrades kind of be one and the same, where the operating system and a Kubernetes upgrade both happen. We’ve decided started to go the other route where we actually want to evolve our APIs sort of independently, but then give you a way to still manage Kubernetes on its own. We’ve actually done self-hosted Kubernetes. In Talos, we’ll actually bootstrap a lightweight control plane, small control plane and then we’ll spin up another control plane using the Kubernetes API. Then now, Kubernetes upgrades simply look like a kubectl edit. I’m going to update my daemon step for my API server. Then from there, you will have to basically update the kub. We use hyperkub for the kubelet. You have to tell Talos, “Use this kubelet image next time you boot.” We’ve separated the two I think for good reason. I think that the two should be able to evolve independently to give a little bit more power back to the user. If you combine them, if you couple them really closely, it becomes really, really opinionated. I think we should at least support what Kubernetes supports, and that’s the N-2 and leave it up to the user to kind of configure Kubernetes, but we still have same best practices out of the box. [00:14:54] BL: Yeah, that makes sense, because yesterday, what did we get? We got a Kubernetes 1.15.10, and I don’t know 16, but we got 1.17.3 yesterday too. You might not want to move, because you might not – 1.17 introduced a whole bunch of deprecations and for custom resource definition. You’re not ready to move yet. We’re on beta 1 for a while for CRDs. I totally see why you had moved that direction. [00:15:20] AR: Yeah, that’s exactly it. We can’t impose too much opinion, but I think that we should drive – The opinion at least up until like, “Hey, don’t worry about what’s on this machine. I’m going to make it a Kubernetes node for you. Just tell me which version you want.” I think that’s where we should draw the boundary and then we should still give the controls back to the user as far as what flags do I want to specify. What kind of feature gates? All these various things that you don’t get out of a lot of the different managed products out there. Hopefully we’ll be tittering right on the line of having that convenience of managed but still giving you that power and flexibility to update a flag if you need to. [00:16:04] CC: This episode is so in the style of an interrogation. It’s hilarious. [00:16:08] BL: That’s me. I’m digging in. [00:16:09] CC: I feel like – No. We are all digging in. It’s just because – At least speaking from myself. I’m super curious. I wanted to ask you, Andrew, at the beginning you were saying that a Kubernetes operating system needs to integrate with Kubernetes and I was sitting here thinking, “Operate? It’s supposed to be Kubernetes.” What did you have in mind when you said that? Did you mean to be able to interface with another Kubernetes cluster? Was that what you meant? [00:16:36] AR: Not quite. What I meant by that is there’s this really powerful thing that Kubernetes gives us in CRDs and this idea of operators or controllers. If you can actually have a way to use an operator controller, say, for upgrading your operating system, which we have in Talos, it’s just an upgrade operator lives in Kubernetes and knows how to talk to Kubernetes and it knows how to talk to our API and sort of orchestrate upgrades across the board. Part of that is, for example, when you receive the upgrade API on a Talos node, it actually is aware, “Hey, I’m running Kubernetes. I’m going to cordon myself, because I know I’ve gotten this and I know that I’m not going to be able to schedule workload on me.” I think that that’s just one example, but we could probably take that a lot farther one day. But I would like to see everything that we know and love about our operating systems today essentially be abstracted and pushed up into Kubernetes as operators. There’s a lot of power in that where you can actually orchestrate things, like I said, like upgrades. I think that that’s one example of how we can integrate better with Kubernetes as how an operating system should, at least. [00:17:45] CC: Got you. [00:17:46] JS: I was wondering if we can kind of maybe just pivot a little bit, like maybe to satisfy my own curiosities, but I was kind of hoping we could talk a little bit about like some of the selling features. Imagine if I’m a hardened sys admin or security team and basically someone comes up and says, “Hey, I want to run this Kubernetes operating system.” Knowing what I know about the state of security today and operating systems, there’s a lot of efforts to basically kind of contain things. No pun intended, but we have user space operates out of some type of sandbox. We have seccomp to limit sys calls. How does Talos approach security maybe like philosophically or maybe even down to the implementation details? What is security in Talos look like? [00:18:33] AR: Yeah. Again, our goal is to basically – We want people to forget about the operating system. But to forget about the operating system, you have to know it’s secure. You have to go to great lengths to secure that because you can’t forget about it for that reason. We actually go down to the kernel, we actually apply what’s called the kernel self-protection project. We basically try to harden the kernel, and at boot time, we do a bunch of checks to make sure that your kernel is running at least most of those configurations. I think we have a little bit of work to do as far as enforcing all of them. But we do some checks to ensure that your kernel is compatible with KSPP, for example. That alone has a ton of benefits to it. It’s a statically compiled kernel so you it can’t do any kernel module loading and stuff like that. That’s completely prohibited. That alone just kind of cuts off a lot of security issues in itself. Then going up the stack further, we’ve actually stripped out SSH. We stripped out Bash. So you have nothing that you can really log on to anymore. Again, that’s just flat out removes a lot of – A whole category of potential attacks potentially. Going even further than that, we’ve actually have Talos running completely out of RAM and it’s a squash-fs. So it’s a read-only file system. The only thing that actually uses a disk is the kubelet. The idea is that we want to make the operating system, again, just have it go away. Having it read-only I think is a really strong thing, and squash-fs in particular, because you can’t remount it, rewrite if you’re a user or something like that. Then up in Kubernetes we actually – Out of the box, we try to deploy it with all of the security best practices, the CIS benchmarks and all of that. We go to all the way from the kernel, to our user LAN and even to Kubernetes itself. We try to bring out security best practices out of the box. I think that’s something I’d love to see for Kubernetes itself upstream, but for now that’s what we’re doing. [00:20:33] BL: Can we go back to the interrogation? No. Let’s not go back to an interrogation. Thinking of – If we take the concept of a Kubernetes operating system, that can be updated in a different cadence, then the Kubernetes running on it – Who is Talos for? Who does it make – Could Joe as a neophyte or someone who doesn’t really know the space, will this make their life any easier or is there a special set of expertise that we would need to be fruitful with this? [00:21:06] TG: I think from our perspective, we hope that everybody who uses Kubernetes would find something useful in Talos, or a system like Talos. Number one, I think Talos would be a great way to get started on your laptop or workstation. I got some basic features to standup a small Kubernetes cluster there. That’s one place to start. As you move further into production, I think that a Kubernetes OS-based platform would be particularly useful in an environment where you might have multiple clusters spread across different geographical locations, spread across different teams. Maybe spread across different hosting environments. We’ve talked to a number of folks who have been running Kubernetess in production for a couple of years now, and these clusters kind of come up organically within a larger organization in different areas, doing different things for the business, managed by different teams. Now that a little bit of time has passed, these organizations are realizing that, “Hey, we’ve got kind of a Kubernetes sprawl problem. We have this team over here on Amazon managing and running Kubernetes one way. We have a separate team managing and running Kubernetes a different way over here on a different kind of platform.” I think anything that – anywhere where we can drive some consistency across the tooling, consistency across the base platforms would be useful. We also think that the minimal aspect of our system and some of the design decisions we’ve made around security and make it particularly useful in maybe a regulated environment. I think that that claim would hold true for any sort of special purpose operating system or minimal operating system designed for a specific task. [00:22:35] BL: Interesting. Just thinking about a concept of a Kubernetes operating system, what’s next? I’m not asking what’s next from Talos, but given all the opportunity all the time and all the knowledge. What should we be doing that we’re not doing right now? [00:22:49] AR: Specifically around operating systems or Kubernetes? [00:22:52] BL: Well, you know what? You can start with operating systems. I mean, you can go to Kubernetes and then we’ll see if our lists match. [00:22:57] AR: That’s a good question. Right off the bat, I’m going to say I don’t really know. I think this is new space. I think that we have a big task in front of us already in getting people to use these kinds of operating systems, hopefully not too big of a task. I’m hoping to see – Because you find these big companies, “Oh! We can’t do this. We can’t do that,” because getting a new OS is hard. I think we first of all need to win people over on just these even more minimal operating systems beyond what CoreOS has done. Personally, I don’t know if I could answer that question honestly without just owing something. [00:23:33] TG: I’ve got a thought here. One of the things that I’m really interested in beyond just Kubernetes and beyond just the operating system – what is computing going to look like in 5, 10, 15 years? I don’t know if Kubernetes is going to be around. I’m kind of a tech-cynic, right? I’ve seen a lot of fads in my career and things that pop up and are very popular for a couple of years and then sort of disappear. I don’t think Kubernetes is one of those. I think Kubernetes and the concepts and the layers of abstraction that Kubernetes has provided, all of that will remain useful and powerful in distant future whether or not it’s called Kubernetes or if it’s called something else, some new paradigm. But what I’m really interested in is seeing what can we do with this idea of an API-managed OS? If you look at the general purpose operating systems out there, some aspects of the system might expose an API. But for the most part, you’re still interacting and interfacing with this system like you were 30 years ago, 35, 40 years ago even. That’s fine. What works works, but everything else today has an API. Kubernetes has a powerful and extensible API and I think that your operating system should have something similar, something comparable, something that you can interact with using the same tools and the same processes and the same ideas that you can at the top of the stack and move some of those concepts down to the host OS level where we’re talking about today. [00:24:51] CC: This brings up a point that I’m so curious about, not only the idea of having a Kubernetes operating system, but any idea that is new that you were just talking about, Tim, is – So what works works. For example, every year or every couple of years, I am evaluating a new code editor or I am evaluating a new note taking app, or do-to-list app, those three things. I’m continuously finding something to reevaluate because what I have has never worked for me just the way I think. Actually, recently I found a couple of things that are really good. In any case, the thing is they just never worked for years. They’re very limited. They don’t match my thinking. But operating system, I would never – Well, I’m not an administrator also, but just like from having my own laptops forever, I’m not going to go out there. That’s not true either, but I was going to say I’m not going to go out there and try a new operating system to see if it’s offering that I already have, then it might be better for me. But that’s not true, because I have done that many times too. So never mind. But I think the idea of my question is stance, is how are you communicating to people out there that, “Hey, there is this new thing that maybe it’s working for you – Maybe you think it’s working for you, but you just don’t know that there is a new different way of doing.” When you do try to do that, how are people responding? I mean, of course, there are those cases where people just know they get it and they immediately resonate with them. But I’m talking about the people who like might benefit from this but they don’t quite grasp. How do you break through that barrier? [00:26:38] TG: Sure. Maybe the lay majority. [00:26:40] CC: Yeah, and how are people responding? [00:26:42] TG: Yeah. The great thing about Talos is that people understand pretty immediately what it is, how it works and why we’ve done it. The challenge I think for us and for anybody changing the way that operating systems work. Is it better enough than what I have today or what I had before? Is it worth the switch in costs? I think that switching cost is something that’s pretty well understood in the industry. People have gone through this process and they’ve moved from virtualization to containers, from Docker to Kubernetes, etc. They understand that process and they understand there’s a technical cost. There’s a people cost, etc. We have to show that value. I think that progress in our industry is incremental. Our industry is young. We’re not building bridges. We’re not at the level of like the internal combustion engine where the engineering is understood and we know how to build it and we know how to make it so that it doesn’t fall over and explode. Clearly, we’re not quite there yet in the broader world of computing. I think anywhere where we can show a little bit of incremental improvement where we can tackle one narrow slice of a problem and make it a little bit better and get to a point where computing is just a little bit safer and a little bit easier and a little bit faster. I think that’ll be a pretty compelling argument and there’s a lot of details involved and we have to talk about how do you get your applications from one operating system to the next? 15 years ago, it may have been a very big ask to ask someone to port their enterprise application from one operating system to another. They’re so inextricably linked. There’re a lot of connections between the OS and the applications, but today, we have these levels of abstraction. We have containers. We have the Kubernetes orchestration mechanisms and I think that switching cost is going down every release of Kubernetes and every step along the way as people change the way that applications are deployed that switching cost gets a little bit cheaper. It will be easier for us to prove that the value you gain by moving to a purpose-built operating system is greater than the switching cost. [00:28:41] CC: Very good points. [00:28:42] JS: I feel like there’s a lot of emphasis and focus on the move over. The first steps toward migrating to something new. There’s a lot of emphasis on bootstrapping a cluster. There’s a lot of emphasis on how do I get started. I’m part of a team called customer reliability engineering and we see operators running Kubernetes environments that are durable and have been in the field for many years. I think that there’s kind of a hidden cost in these day two operations where, like today, to effectively be a Kubernetes operator, you need to also have a great deal of understanding of Linux internal operating systems or Linux operating systems internals. These are abstractions on top, but sometimes those abstractions are leaky. So you need to be able to parse IP tables rules. You need to be able to understand how traffic gets routed, all of these aspects of it. I’m just wondering how do we kind of get folks shifted from this mindset of I’m going to start with something that’s general purpose and then I’m going to basically make it do what I want it to do by making all of these configuration changes and installing things on top of it to kind of make that not general purpose, but kind of specific focus on it and kind of get people to move back more fundamentally and think, “Well, what if we just started with something that is strictly for running workloads?” We don’t have to worry about installing a security suite on top of this or making this configuration change or hardening requirements or what have you. We’re fundamentally in a better place because we’ve started with something that’s arguably more secure. [00:30:21] BL: You know that – I mean, I’m old. I’m old now. I’m realizing this. When I started – Back in my day when we started with Linux, we went through this whole thing of Linux installers and there’re many iterations of Linux installers and it depended on, “Well, did you like what Red Hat was doing? Did you like what Debian project was doing? Oh! Did you like what Arch was doing? Oh! Did you want to do it yourself? Do you want to merge the world with gen 2?” Really, we come to this point now, no one ever talks about Linux installers anymore. You just put it on there. I think what I’m getting at is that we don’t actually know what we want. I mean we say that we want it to be simpler. We say we want it to be more secure, but we don’t know. Only time will tell, and I think it’s going to be a lot of chipping away at problems. Then people who are wanting to have the bold ideas are saying, “I’m going to out there and create a Kubernetes operating system.” In reality, it may work. We hope it works, or it may not work, but at least we gained just a little tiny bit more knowledge on how we want to run this thing. I think – And I’ll just say one more last thing, is that if you look at like Bell Labs, Bell Labs created the vacuum tube, and then like 20 years later, 20 or 30 years later, they created the transistor, twice actually. It took a long time to get the vacuum tube out because it kind of just worked and they just said, “We can’t throw it back. We just can’t throw that away.” Maybe we’re seeing a lot of that in Kubernetes. We’re holding on to some good things even though some greater things are going to come, but it might not be here this year or next year. It might be 18 months. It might be 24 months. We just got to really pay attention to that. [00:32:02] AR: Brian, when you said you were old, I was going to shake my head internally and then you brought up the vacuum tube and I’m like, “Okay.” [00:32:07] BL: I mean, I’m not that old. [00:32:09] JS: Yeah, I think that’s a good point, Brian. The thing I like to point out is the allegory of the cave. People have been living a certain way for so long they think that these shadows are real and they just know that way of life until some crazy comes along and says, “Hey, there’s a whole world out there,” and no one believes him. I think we just need to do – Like you said, we just need to do it. When you just create and make it happen and hopefully educate people in the process and just keep chipping away at it. Do the good work. [00:32:38] BL: That’s the important piece and that was the power of Bell Labs. You probably can tell. I just read a book about Bell Labs. I’m an expert now. But that was the power of Bell Labs. They didn’t just focus on making product for AT&T. They focused on changing the world, like literally. Who creates a transistor if you knew what one was? You just don’t create that. That’s like some really crazy stuff. I try to bring the parallel back to what we’re doing here. We can’t just create this perfect Kubernetes thing, because really, we don’t know what it is. I mean, we can be smart and say, “Well, it needs to be secure. It needs to be networking,” and all these stuff. But you know what? We don’t even have cgroups v2 support yet. We don’t even know where we are. Let’s figure out – Let’s just keep going down the path, but we will suss out these better patterns. [00:33:23] CC: Yeah, I like that. [00:33:24] BL: That’s it. It is incremental. Here’s the crazy part, and this is the real tough part. You know what? It is incremental, and reality says that not everybody can win. Don’t take your failures as a loss. Take them as, “well, maybe we shouldn’t have done that,” and keep on moving forward because there’s a lot of companies out there who got us at this point in tech that don’t exist anymore, but if they didn’t do what they did, we would not be here right now. It’s not [inaudible 00:33:52]. [00:33:53] CC: Why are we talking about failures? [00:33:55] BL: I’m sorry. It’s the ultimate success. [00:34:01] CC: Oh gosh! Let’s not end the show in such a downer. [00:34:04] BL: No. That’s a happy point though. Let me put the bow on the happy point and then I will stop talking. The thing is, is it’s not the glass is half empty. It is glass is half full. The path to success is littered with failure and it’s not a bad thing. It’s a good thing, because it’s good that we can continue making those failures because we know they lead to successes. That is actually a happy thing. [00:34:29] CC: I wonder if Andrew and Tim want to do a little bit of interrogating of us. I think that would be fair. [00:34:36] AR: I wouldn’t know what to interrogate you guys about. [00:34:40] CC: Well, we are coming up at the top of the hour. So it’s time to say goodbye. It was great having you, Andrew, and you, Tim, on the call. Jed, thank you for participating as well. I think it was very informative. With that, I will say, until next week. Bye everybody. [00:34:59] TG: Bye. Thanks for having us. [00:35:00] CC: My pleasure. [00:35:00] AR: Bye-bye. Thank you. [00:35:02] JS: Thank you. Bye. [END OF INTERVIEW] [0:35:05.3] ANNOUNCER: Thank you for listening to The Podlets Cloud Native Podcast. Find us on Twitter at https://twitter.com/ThePodlets and on the http://thepodlets.io/ website, where you'll find transcripts and show notes. We'll be back next week. Stay tuned by subscribing. [END]See omnystudio.com/listener for privacy information.

If you work in Kubernetes, cloud native, or any other fast-moving ecosystem, you might have found that keeping up to date with new developments can be incredibly challenging. We think this as well, and so we decided to make today’s episode a tribute to that challenge, as well as a space for sharing the best resources and practices we can think of to help manage it. Of course, there are audiences in this space who require information at various levels of depth, and fortunately the resources to suit each one exist. We get into the many different places we go in order to receive information at each part of the spectrum, such as SIG meetings on YouTube, our favorite Twitter authorities, the KubeWeekly blog, and the most helpful books out there. Another big talking point is the idea of habits or practices that can be helpful in consuming all this information, whether it be waiting for the release notes of a new version, tapping into different TLDR summaries of a topic, streaming videos, or actively writing posts as a way of clarifying and integrating newly learned concepts. In the end, there is no easy way, and passionate as you may be about staying in tune, burnout is a real possibility. So whether you’re just scratching the cloud native surface or up to your eyeballs in base code, join us for today’s conversation because you’re bound to find some use in the resources we share. Follow us: https://twitter.com/thepodlets Website: https://thepodlets.io Feeback: info@thepodlets.io https://github.com/vmware-tanzu/thepodlets/issues Hosts: Carlisia Campos Josh Rosso Duffie Cooley Olive Power Michael Gasch Key Points From This Episode: Audiences and different levels of depth that our guests/hosts follow Kubernetes at. What ‘keeping up’ means: merely following news, or actually grasping every new concept? The impossibility of truly keeping up with Kubernetes as it becomes ever more complex. Patterns used to keep up with new developments: the TWKD website, release notes, etc. Twitter’s helpful provision of information, from opinions to tech content, all in one place. How helpful Cindy Sridharan is on Twitter in her orientation toward distributed systems. The active side of keeping up such as writing posts and helping newcomers. More helpful Twitter accounts such as InfoSec. How books provide one source of deep information as opposed to the noise on Twitter. Books: Programming Kubernetes; Managing Kubernetes; Kubernetes Best Practices. Another great resource for seeing Kubernetes in action: the KubeWeeky blog. A call to watch the SIG playlists on the Kubernetes YouTube channel. Tooling: tab management and Michael’s self-built Twitter searcher. Live streaming and CTF live code demonstrations as another resource. How to keep a team updated using platforms like Slack and Zoom. The importance of organizing shared content on Slack. Challenges around not knowing the most important thing to focus on. Cognitive divergence and the temptation of escaping the isolation of coding by socializing. The idea that not seeing keeping up to date as being a personal sacrifice is dangerous. Using multiple different TLDR summaries to cement a concept in one’s brain. Incentives for users rather than developers of projects to share their experiences. The importance of showing appreciation for free resources in keeping motivation up. Quotes: “An audience I haven’t mentioned is the audience that basically just throws up their hands and walks away because there’s just too much to keep track of, right?” — @mauilion [0:05:15] “Maybe it’s because I’m lazy, I don’t know? But I wait until 1.17 drops, then I go to the release notes and really kind of ingest it because I’ve just struggled so much to kind of keep up with the day to day, ‘We merged this, we didn’t merge this,’ and so on.” — @joshrosso [0:10:18] “If you find value in being up to date with these things, just figure out – there are so many resources out there that address these different audiences and figure out what the right measure for you is. You don’t have to go deep on the code on everything.” — @mauilion [0:27:57] “Actually putting the right content in the right channel, at least from a higher level, helps me decide whether I want to like look at that channel today, and stuff that should be in the channel is not kind of in a conversation channel.” — @opowero [0:32:21] “When I see something that is going to give me the fundamentals, like I have other priorities now, I sort of always want to consume that to learn the fundamentals, because I think in the long term phase of, but then I neglect physically what I need to know to do in the moment.” — @carlisia [0:33:39] “Just do nothing, because our brain needs that. We need to not be listening, not be reading, just nothing. Just sit and look at the ceiling. Our brain needs that. Ideally, look at nature, like look outside, look at the air, go for a walk. We need that, because that recharges the brain.” — @carlisia [0:42:38] “Just consuming and keeping up, that doesn’t necessarily mean you don’t give back.” — @embano1 [0:49:32] Links Mentioned in Today’s Episode: Chris Short — https://chrisshort.net/ Last Week in Kubernetes Development — http://lwkd.info/ 1.17 Release Notes — https://kubernetes.io/docs/setup/release/notes/ Release Notes Filter Page — https://relnotes.k8s.io/ Cindy Sridharan on Twitter — https://twitter.com/copyconstruct InfoSec on Twitter — https://twitter.com/infosec?lang=en Programming Kubernetes on Amazon —https://www.amazon.com/Programming-Kubernetes-Developing-Cloud-Native-Applications/dp/1492047104 Managing Kubernetes on Amazon — https://www.amazon.com/Managing-Kubernetes-Operating-Clusters-World/dp/149203391X Brendan Burns on Twitter — https://twitter.com/brendandburns Kubernetes Best Practices on Amazon — https://www.amazon.com/Kubernetes-Best-Practices-Blueprints-Applications-ebook/dp/B081J62KLW/ KubeWeekly — https://kubeweekly.io/ Kubernetes SIG playlists on YouTube — https://www.youtube.com/channel/UCZ2bu0qutTOM0tHYa_jkIwg/playlists Twitch — https://www.twitch.tv/ Honeycomb — https://www.honeycomb.io/ KubeKon EU 2019 — https://events19.linuxfoundation.org/events/kubecon-cloudnativecon-europe-2019/ Aaron Crickenberger on LinkedIn — https://www.linkedin.com/in/spiffxp/ Stephen Augustus on LinkedIn — https://www.linkedin.com/in/stephenaugustus Office Hours — https://github.com/kubernetes/community/blob/master/events/office-hours.md Transcript: EPISODE 17[INTRODUCTION][0:00:08.7] ANNOUNCER: Welcome to The Podlets Podcast, a weekly show that explores Cloud Native one buzzword at a time. Each week, experts in the field will discuss and contrast distributed systems concepts, practices, tradeoffs and lessons learned to help you on your cloud native journey. This space moves fast and we shouldn’t reinvent the wheel. If you’re an engineer, operator or technically minded decision maker, this podcast is for you.[EPISODE][0:00:41.5] DC: Good afternoon everybody and welcome to The Podlets. In this episode, we’re going to talk about, you know, one of the more challenging things that we all have to do, just kind of keep up with cloud native and how we each approach that and what we do. Today, I have a number of cohosts with me, I have Olive Power.[0:00:56.6] OP: Hi.[0:00:57.4] DC: Carlisia Campos.[0:00:58.6] CC: Hi everybody.[0:00:59.9] DC: Josh Rosso.[0:01:01.3] JR: Hey all.[0:01:02.8] DC: And Michael.[0:01:01.1] MICHAEL: Hey, hello.[0:01:04.8] DC: This episode, we’re going to do something a little different than we normally do. In most of our episodes, we try to remain somewhat objective around the problem and the potential solutions for it, rather than prescribing a particular solution. In this episode, however, since we’re talking about how we keep up with all of the crazy things that happen in such a fast ecosystem, we’re going to probably provide quite a number of examples or resources that you yourself could use to drive and to try and keep up to date with what’s happening out there.Be sure to check out the notes after the episode is over at thepodlets.io and you will find a link to the episodes up at the top part, click down to this episode, and check out the notes. There will be tons of resources. Let’s get started.One of the things I think about that’s interesting about keeping up with something like, you know, a Kubernetes or a fast-moving project, regardless of what that project is, whether it’s Kubernetes or, you know, for a while, it was the Mesos that I was following or OpenStack or a number have been big infrastructure projects that have been very fast moving over time and I think what’s interesting is I find that there’s multiple audiences that we kind of address when we think about what it means to ‘keep up,’ right?Keeping up with something like a project is interesting because I feel like there’s an audience that it’s actually very interested in what’s happening with the design goals or the code base of the project, and there’s an audience that is very specific to wanting to understand at a high level – like, “Give me the State of the World report like every month or so just so I can understand generally what’s happening with the project, like is it thriving? Is it starting to kind of wane? Are there big projects that it’s taking on?”And then there’s like, then I feel like there’s an audience somewhere in the middle there where they really want to see people using the project and understand, and know how to learn from those people who are using it so that they can elevate their own use of that project. They’re not particularly interested in the codebase per se but they do want to understand, are they exploring this project at a depth that makes sense for themselves? What do you all think about that?[0:03:02.0] CC: I think one thing that I want to mention is that this episode, it’s not so much about on-boarding people onto Kubernetes and the Kubernetes ecosystem. We are going to have an episode soon to talk specifically about that. How you get going, like get started. I think Duffy mentioned this so we’re going to be talking about how we all keep up with things. Definitely, there are different audiences, even when we’re talking about keeping up.[0:03:32.6] JR: Yeah, I think what’s funny about your audience descriptions, Duffy, is I feel like I’ve actually slid between those audiences a bit, right? It’s funny, back in the day, Kubernetes like one-four, one-five days, I feel like I was much more like, “What’s going on in the code?” Like trying to keep track of like how things are progressing.Now my role is a lot more focused with working with customers and standing up cube and like making a production ready. I feel like I’m a lot more, kind of reactive and more interested to see like, what features have become stable and impact me, you know what I mean? I’m far less in the weeds than I used to be. It’s a super interesting thing.[0:04:08.3] OP: Yeah, I tend to – for my role, I tend to definitely fall into the number three first which is the kind of general keeping an eye on things. Like when you see like interesting articles pop up that maybe have been linked internally because somebody said, “Oh, check out this article. It’s really interesting.”Then you find that you kind of click through five or six articles similar but then you can kind of flip to that kind of like, “Oh, I’m kind of learning lots of good stuff generally about things that folks are doing.” To actually kind of having to figure out some particular solution for one of my customers and so having to go quite deep into that particular feature.You kind of go – I kind of found myself going right in and then back out, right in, going back out depending on kind of where I am on a particular day of the week. It’s kind of a bit tricky. My brain sometimes doesn’t kind of deal with that sort of deep concentration into one particular topic and then back out again. It’s not easy.I find it quite tough actually some of the time.[0:05:05.0] DC: Yeah, I think we can all agree on that. Keeping track of everything is – it’s why the episode, right? How do we even approach it? It seems – I feel like, an audience I haven’t mentioned is the audience that basically just throws up their hands and walks away because there’s just too much to keep track of, right? I feel like we are all that at some point, you know?I get that.[0:05:26.4] OP: That’s why we have Christmas holidays, right? To kind of refresh the brain.[0:05:31.4] CC: Yeah, I maybe purposefully or maybe not even – not trying to keep up because it is too much, it is a lot, and what I’m trying to do is, go deeper on the things that I already, like sort of know. And things that I am working with on a day to day basis. I only really need to know, I feel like, I really only need to know – because I’m not working directly with customers.My scope is very well defined and I feel that I really only need to know whenever there’s a new Kubernetes release. I need to know what the release is. We usually – every once in a while, we update our project to the – we bump up the Kubernetes release that we are working against and in general, yeah, it’s like if things come my way, if it’s interesting, I’ll take a look, but mostly, I feel like I work in a spiral.If I’m doing codes related to controllers and there’s a conference talk about controllers then okay, let me take a look at this to maybe learn how to design this thing better, implement in a better way if I know more about it. If I’m doing, looking at CRDs, same thing. I really like conference talks for education but that’s not so much keeping up with what’s new. Are we talking about educating ourselves with things that we don’t know about?Things that we don’t know about. Or are we talking about just news?[0:07:15.6] JR: I think it’s everything. That’s a great question. One of my other questions when we were starting to talk about this was like, what is keeping up even mean, right? I mean, does it mean, where do you find resources that are interesting that keep you interested in the project or are you looking for resources that just kind of keep you up to date with what’s changing? It’s a great question.[0:07:36.2] MICHAEL: Actually, there was some problem that I faced when I edit the links that I wanted to share in the show. I started writing the links and then I realized, “Well, most of the stuff is not keeping up with news, it’s actually understanding the technology,” because I cannot keep up.What does help me in understanding specific areas, when I need to dig into them and I think back five or four years into early days of Kubernetes, it was easy to catch up by the time because it was just about Kubernetes. Later right, it became this platform. We realized that it actually this platform thing. Then we extended Kubernetes and then we realized there are CICD-related stuff and operations and monitoring and so the whole ecosystem grew. The landscape grew so much that today, it’s impossible to keep up, right?I think I’m interested in all those patterns that you have developed over the years that help you to manage this, let’s say complexity or stream of information.[0:08:33.9] DC: Yeah, I agree. This year, I was thinking about putting up a talk with Chris Short, it was actually last year. That was about kind of on the same topic of keeping up with it. In that, I kind of did a little research into how that happens and I feel like some of the interesting stuff that came out of that was that there are certain patterns that a project might take on that make it easier or more approachable to, you know, stay in contact with what’s happening.If we take Kubernetes as an example, there are a number of websites I think that pretty much everybody here kind of follows to some degree, that helps, sort of, kind of, address those different audiences that we were talking about.One of the ones that I’ve actually been really impressed with is LWKD which stands for Last Week in Kubernetes Development, and as you can imagine, this is really kind of focused on, kind of – I wouldn’t say it’s like super deep on the development but it is watching for things that are changing, that are interesting to the people who are curating that particular blog post, right?They’ll have things in there like, you know, code freezes coming up on this date, IPV6, IPV4, duel stack is merging, they’ll have like some of the big mile markers that are happening in a particular release and where they are in time as it relates to that release. I think if that’s a great pattern and I think that – it’s a very narrow audience, right? It would really only be interesting to people who are interested in, or who are caught up in the code base, or just trying to understand like, maybe I want a preview of what the release notes might look like, so I might just like look for like a weekly kind of thing.[0:10:03.4] JR: Yeah, speaking of the release notes, right? It’s funny. I do get to look at Last Week in Kubernetes development every now and then. It’s an awesome resource but I’ve gotten to the point where the release notes are probably my most important thing for staying up to date.Maybe it’s because I’m lazy, I don’t know, but I wait till 1.17 drops, then I go to the release notes and really kind of ingest it because I’ve just struggled so much to kind of keep up with the day to day, “We merged this, we didn’t merge this,” and so on. That has been a huge help for me, you know, day to day, week to week, month to month.[0:10:37.0] MICHAEL: Well, what was also helpful just on the release notes that the new filter webpage that they put out in 1.15, starting 1.15. Have you all seen that?[0:10:44.4] JR: I’ve never heard of it.[0:10:45.4] DC: Rel dot, whatever it is. Rel dot –[0:10:47.7] MICHAEL: Yeah, if you can share it Duffy, that’s super useful. Especially like if you want to compare releases and features added and –[0:10:55.2] DC: I’ll have to dig it up as well. I don’t remember exactly what –[0:10:56.7] CC: I’m sorry, say? Which one is that again?[0:10:59.1] MICHAEL: The real notes. I’ll put it in the hackMD.[0:11:02.8] DC: Yeah relnotes.k8s.io which is an interesting one because it’s sort of like a comparison engine that allows you to kind of compare what it would have featured like how to feature relates to different versions of stuff.[0:11:14.4] CC: That’s great. I cannot encourage enough for the listeners to look at the show notes because we have a little document here that we – can I? The resources are amazing. There are so many things that I have never even heard about and sound great – is – I want to go to this whole entire list. Definitely check it out. We might not have time to mention every single thing. I don’t want people to miss on all the goodness that’s been put together.[0:11:48.7] DC: Agreed, and again, if you’re looking for those notes, you just go to the podlets.io. Click on ‘episodes’ at the right? And then look for this episode and you’ll find that it’s there.[0:11:58.0] CC: I can see that a lot of the content in those notes are like Twitter feeds. Speaking personally, I’m not sure I’m at the stage yet where I learn a lot about Twitter feeds in terms of technical content. Do you guys find that it’s more around people’s thoughts around certain things so thought-provoking things around Kubernetes and the ecosystem rather than actual technical content. I mean, that’s my experience so far.But looking at those Twitter feeds, maybe I guess I might need to follow some of those feeds. What do you all think?[0:12:30.0] MICHAEL: Do you mean the tweets are from those like learn [inaudible 0:12:32] or the person to be tweets?[0:12:35.3] OP: You’ve listed some of there, Michael, and some sort of.[0:12:37.6] MICHAEL: I just wanted to get some clarity. The reason I listed so many Twitter accounts there is because Twitter is my only kind of newsfeed if you will. I used Feedly and RSS and others before and emails and threads. But then I just got overwhelmed and I had this feeling of missing out on all of those times.That’s why I said, “Okay, let’s just use Twitter.” To your question, most of these accounts are people who have been in the Kubernetes space for very long, either running Kubernetes, developing on Kubernetes, having opinions about Kubernetes.Opinions in general on topics related to cloud native because we didn’t want to make the search just about Kubernetes. Most of these people, I really appreciate their thoughts and some of them also just a retweet things that they see which I missed somewhere else and not necessarily just opinions. I think It’s a good mix of these accounts, providing options, some guidance, and also just news that I miss out on because not being on the other channels.[0:13:35.6] OP: Yeah, I agree because sometimes you can kind of read – I tend to require a lot of sort of blog posts and sort of web posts which, you know, without realizing it can be kind of opinionated and then, you know, it’s nice to then see some Twitter feeds that kind of actually just kind of give like a couple of words, a kind of a different view which sometimes makes me think “Okay, I understand that topic from a certain article that I’ve read, it’s just really nice to hear a kind of a different take on it through Twitter.”[0:14:03.0] CC: I think some of the accounts, like fewer of the accounts – and there are a bunch of things that – there are listed accounts here that I didn’t know before so I’ll check them out. I think fewer of the accounts are providing technical content, for example, Cindy Sridharan, not pronouncing it correctly but Cindy is great, she puts out a lot of technical content and a lot of technical opinion and observations that is really good to consume. I wish I had time to just read her blog posts and Twitter alone.She’s very oriented towards distributed systems in general, so she’s not even specific just Kubernetes. Most of the accounts are very opinionated and the benefit for me is that sometimes I catch people talking about something that I didn’t even know was a thing. It’s like, “Oh, this is a thing I should know about for the work that I do,” and like Michael was saying, you know, sometimes I catch retweets that I didn’t catch before and I just – I’m not checking out places, I’m not checking – hash tagging Reddit.I rely on Twitter and the people who I follow to – if there is a blog post that sounds important, I just trust that somebody would, that I’m going to see it multiple times until like, “Okay, this is content that is related to something and I’m working on, that I want to get better at.” Then I’ll go and look at it. My sources are mainly Twitter and YouTube and it’s funny because I love blog posts but it’s like I haven’t been reading them because it takes a long time to read a blogpost.I give preference to video because I can just listen while I’m doing stuff. I sort of stopped reading blog post which is sad. I also want to start writing posts because it’s so helpful for me to engrain the things that I’m learning and hopefully it will be helpful to other people too. But in any case, go Duffy.[0:16:02.8] DC: A number of people that I follow – I have been cultivating my feed pretty carefully, trying to get a broad perspective of technical stuff that’s happening. But also I’ve been trying to develop my persona on Twitter a bit more, right? I’m actually trying to build my audience there. What’s interesting there is I’ve been trying to – to that end, what I’ve been doing is like trying to amplify voices that I think aren’t heard enough out there, right?If I see an article by somebody who is just coming into Kubernetes. or just coming into distributed systems and they’ve taken an effort to really lay out something that they found really interesting about pretty much anything, right? I’m like, “Okay, that’s pretty awesome,” and I’ll try to amplify that, right? Sometimes I even get involved or I’ll, not directly in public on Twitter but I’ll offer to help edit or help provide whatever our guidance I can provide around that sort of stuff.If I see people like having a difficult time with a particular project or something like that, I’ll reach out privately and say, “Hey, can I help you with it so you can go out there and do a great job,” you know? That is something I love to do. I think your point about like not necessarily going at Twitter for the deep knowledge stuff but more just like making sure that you have a broad enough awareness of what’s happening in different ecosystems that you’re not surprised by the things when the things change, right?A couple of other people that I follow are Akira Asuta, I can’t say enough about that person. They are amazing, they have been doing like, incredibly deep security stuff as it relates to containerization and stuff like that for quite a while. I’m always like, learning brand new things to me when following folks like that. I’ve been kind of getting more interested in InfoSec Twitter lately, learning how people kind of approach that problem.Also some of the bias arounds that which has been pretty interesting. Both the bias against people who are in InfoSec which seems weird to me. Also, how InfoSec approaches a problem, like do they put it like a learning experience or they approach it like an attack experience.It’s been kind of fascinating to get in there.[0:18:08.1] OP: You know, I kind of use Twitter as well for some of this stuff but you know, books are kind of a resource as well but in my head, kind of like at the opposite scale. You know, I obviously don’t read as many books as I read twitter feeds, right? It’s just kind of like, with Twitter, you can kind of digest the whole of the stuff and with books, it’s kind of like – I tend to be trying – because I know, I’m only going to read – like I’m only going to read maybe one/two books a year.I’ve kind of like – as I said before, blog posts seem to take up my reading time and books kind of tend to be for like on airplanes and stuff. So if – they’re just kind of two opposite resources for me but I find actually, the content of books are probably stuff that I digest a bit more because you know, it’s kind of like, I don’t know, back to the old days. It’s kind of a physical thing on hand and I can kind of read it and digest it a bit more than the kind of throwaway stuff that kind of keeps on Twitter.Because to be honest, I don’t know what’s on Twitter. Who is kind of a person to listen to or who is not or who is – I just try and form my own opinions and then, again, it kind of gets a bit overwhelming, because it’s a lot of content just streaming through continuously, whereas a book, it’s kind of like just one source of information that is kind of like a bit more personal that I can digest a bit more.[0:19:18.1] JR: Any particular book recommendation in 2019, Olive, that you found particularly interesting?[0:19:23.5] OP: I’m still reading, and it’s on the list for the episode notes actually, Programming Kubernetes. I just want to kind of get into that sort of CRD sort of mindset a bit. I think that’s kind of an area that’s interesting and an area that a lot of people will want to use in their organizations, right, because it’s going to do some of the extensibility to Kubernetes that’s just not there out of the box and everybody wants something that’s not out of the box or always in my experience.[0:19:47.4] MICHAEL: I found the Managing Kubernetes, I think was it, by – from Brendan Burns and some other folks which was just released I think in the end of last year. Super deep and that is kind of the opposite to the Programming Kubernetes, because I like that as well. That is more geared towards understanding architecture and operations.Operational concepts –[0:20:05.0] OP: They’re probably the two books I’ve read.[0:20:08.4] MICHAEL: Okay.[0:20:08.9] OP: One a year, remember?[0:20:11.4] MICHAEL: Yeah.[0:20:14.6] OP: Prolific reading.[0:20:19.6] CC: I think if you know what you need to learn about cloud native or Kubernetes, there’s amazing books out there, and if you are still exploring Kubernetes and trying to learn, I cannot recommend this book enough. If you are watching this on YouTube, you’ll see the cover. It’s called Kubernetes Best Practices because it’s about Kubernetes best practices but what they did simultaneously and maybe they didn’t even realize is just they gave a map for the entire thing.You go, “Oh, these are all the elements in Kubernetes.” Of course, it’s saying, “Okay, this is the best way to go about setting the stuff up,” and this is relatively thin but I just think that going through this book, you get really fast overview of the elements in Kubernetes. Then you can go to other books like Managing Kubernetes to go deep and understand all of the knobs and switches.[0:21:24.6] DC: I want to bring it back to the patterns that we see successful projects. Projects that you think are approachable but, you know, projects that are out there that make it easy for you to kind of stay – or easier at least to stay up to date with them, what some of those patterns are that you think are useful for projects.We’re talking about like having a couple of different entry points from kind of a weekly report mechanism, we’ve talked about the one that LWKD is, I don’t think we got to talk about KubeWeekly which is actually a weekly blog that is actually curated by a lot of the CNCF ambassadors. KubeWeekly is also broken up in different sections, so like sometimes they’ll just talk about – but they’re actually going out actively and trying to find articles of people using Kubernetes and then trying to post those.If you’re interested in understanding how people are actually out there using it, then that’s a great place to go find articles that are kind of related to that. What are some other patterns that we see that are out there that are useful for books?[0:22:27.6] DC: One that I really like. Kubernetes, for everyone listening has this notion of special interest groups, SIGs oftentimes. They’re focused on certain areas of the project. There’s some for networking and storage and life cycles of clusters and what’s amazing, I try to watch them somewhat weekly, I don’t always succeed.They’re all on YouTube and if you go to the Kubernetes project YouTube, there’s playlists for every SIG. A lot of times I’m doing work relating to life cycles of clusters. I’ll open up the cluster life cycle playlist and I’ll just watch the weekly meetings. While it doesn’t always pertain to completely to me, it lets me understand kind of where the developers and contributor’s heads are at and where they’re kind of headed with a lot of different things.There’s a link to that as well if anyone wants to check it out.[0:23:15.9] MICHAEL: Exactly, to add to that. If you don’t have the time to watch the videos, the meeting notes that these gentlemen and women put together are amazing. Usually, I just scroll through and if it’s something to triggers, I go into the episode and watch it.[0:23:28.7] OP: I almost feel like we should talk about tooling to handle all of this stuff, for example, right now, I think I have 200 tabs opened. I just started learning about some chrome extensions to manage tabs. I haven’t started really using them but I need. I don’t have a good system. My system is open a video that I’m pretty sure I want to watch and just get to that tab eventually until something happens in my chrome goes bust and I lose everything.I wanted to mention that when we say watch YouTube, some things you don’t need to sit there and actually watch, you can just listen to it and if you pay for the five bucks for YouTube premium – I don’t get a commission you people, but I’m just saying, for me, it’s so helpful. I can just turn off you know, put my phone on my pocket and keep listening to it without having to have the phone open and on the whole time. It’s very handy.It’s just like listening to a podcast. I also listen to podcasts lots of days.[0:24:35.1] MICHAEL: For tooling, since I’m just mostly on Twitter and by the time I was using or starting to use Twitter, they didn’t have this bookmark function, so I was basically abusing likes or favorites at the time, I think, to bookmark. What I realized later, my bookmarks grew, well, my likes grew.I wanted to go back and find something but that through the Twitter search was just impossible. I blew the tiny little go tool, kind of my first exercise there to just parse my likes and then use JQ because it’s all JSON to query and manipulate the stuff. I almost use it every day because I was like, that was a talk or blog post about scheduling and just correct for scheduling and the likes.I’m sure there’s a better tool or way of doing that but for me, that’s mine too. Because that’s my workflow.[0:25:27.6] DC: Both of the two blogs that you mentioned both KubeWeekly and LWKD, they both have the ability to take – you can submit stories to them. If you come across things that are interesting and you’d like to put that up on an aggregator somewhere, this is one of the ways to kind of solve that problem because at least if it gets cleared up on an aggregator, you know that you go back to the aggregator to see it, so that helps.Some other ones I’ve seen out there, I’ve seen people, I’ve seen a number of interesting startups now, starting to kind of like put out a podcast or – and I have started to see a number of people like you know, engaging with Twitch and also doing things like what we do with TJK.io which is like have sort of some kind of a weekly thing where you are just hacking on stuff live and just exploring it whether that is related to – if you think of about TJK is we’re going to do without being related necessarily to anything that we are doing at VMware just anything to do with the community but obviously if you are working for one of the small companies like Honeycomb or some other company.A smaller kind of startup, you can really just get people more aware of that because for some reason people love to watch others code. They love to understand how people go through that, what are their thought process is and I find it awesome as well. I think it is amazing to me how big a draw that is, you know?[0:26:41.1] OP: And is there lots of them out there Duffy? Is that kind of an easy searchable thing or is it like how do you know those things are going on?[0:26:48.4] DC: Oddly enough Twitter, most of the time, yeah. I mean, most of the time I see that kind of stuff happening on Twitter, like somebody will like – I will scope with this or a number of other people will say, “Hey, I am going to do a live stream during this period of time on this,” and I have actually seen a number of people doing live streams on CTFs, which are capture the flags. That one’s really been fascinating to me because it has been how do people think about approaching the security of an application.Like where do they look for weak spots and how do you determine, how do you approach that kind of a problem, which is fascinating. So yeah, I think it is important to remember that like you know, you are not the only one trying to keep up to date with all of this stuff, right? The one thing we all have said pretty consistently here is that it is a lot, and it is not just Kubernetes, right? Like any fast moving project. It could be your favorite Ruby module that has 200 contributors, right?It doesn’t matter what it is, it is a lot to keep a track of, and it represents some of that cognitive overheads that you have to think about. That is a lot to take on. Even if it is overwhelming, if you find value in being up to date with these things, just figure out – there are so many resources out there that address these different audiences and figure out what the right measure for you is. You don’t have to go deep on the code on everything.Sometimes it might be better to just try and find a source of information that gives you a high enough of a view. Maybe you are looking at the blog posts that come out on Kubernetes.io every release and you are just looking at the release notes and if you just read the release notes every release, that is already miles ahead of what I have seen a lot of folks out there when they are starting to ask me questions about how do you keep up to date.[0:28:35.9] JR: I’m curious, we have been talking a lot about keeping up as an individual. Do you all have strategies for how you help, let’s say your overall team, keep up with all the things that are going on? To give an example, Duffy, Olive and myself, at least at one point, were on the same team and we’d go out to disparate customers and see all of these different new things that they are trying to do or new projects that they are using.So we’d have to think about how do we get together and share that internally to make sure we are bringing the whole team along with what is going on in the ecosystem especially from a customer perspective. I know one of the ways that we do that is having demos and things of that nature that we share weekly. Are there other strategies that you all use with your teams to kind of share interesting information and news?[0:29:25.5] M: So what we do is mostly the way we share in our team, and we are a small team. We use Slack. We pre-filter in terms of like if there is stuff that I think is valuable for me and probably not for the whole team – obviously we are not going to share, but I think if it is related to something that the team has or to come grant and then I will share on Slack but we don’t have any formal way. I know people use some reports, weekly reports, or other platforms to distribute but we just use Slack.[0:29:53.0] DC: I think one of the things – one of the patters that we had at [inaudible 0:29:54] that I thought was actually super helpful was that we would engage a conversation. “I learned a cool new thing about whatever today,” and so we would say, “I am going to – ” and then we would start a Zoom call around that and then people could join if they wanted to, to be a part of the live discussion or not, and if they didn’t, they would still be able to see a recorded Zoom pop up in the channel later on.So even if your time zones don’t line up, like I know it is 2 AM or 3 AM or something like that for Olive right now, you can still go back to those recorded sessions and you’ll just see it on your daily Slack stuff. You would be able to see, “Oh there was a conversation about whether you should deploy Kubernetes crossed availibility zones or not. I would like to go see that,” and see what the inputs were, and so that can be helpful.[0:30:42.5] JR: Yeah, that is a super interesting observation. It is almost like remote-first teams that are used to these processes of recording everything and putting it in a Google doc. They are more equipped for that information sharing perhaps than like the water cooler conversations you’d have in the office.[0:30:58.5] OP: And on the Slack or any of the communication tool, we have different channels because we are all in lots of channels and to have channels dedicated to a particular subject is absolutely the way to go because otherwise in my previous company that seem to be kind of one main channel that all the architect used to discussed everything on and you know sometimes you join and you’re like, “What is everybody talking about?”There would be literally about a hundred messages on some sort of theme that I have never heard of. So you come away from that thinking that, “That is the main channel. Where is the bit – is there messages in the middle that I missed that were just normal discussions as opposed to in around the technical stuff,” and so it made me a bit sad, right? I would be like, “I haven’t understood something and there is a whole load of stuff on this channel that I don’t understand.”But it is the kind of central channel for everyone. So I think you end up then start looking up things that they are discussing and then realizing actually that is not really anything related to what I need to know about today or next week. It might be something for the future but I’ve got other stuff to focus on. So my point is that those communication channels for me sometimes can make me feel a little bit behind the curve or very much sort of reactive in trying to jump on things that are actually not really anything to do with me for me now and wasting my time slightly and kind of messing with my head a little bit in that like, “I really need to try and focus out stuff,” and actually putting the right content in the right channel, at least from a higher level, helps me decide whether I want to like look at that channel today, and stuff that should be in the channel is not kind of in a conversation channel. So organization of where that content is, is important to me.[0:32:37.6] CC: I am so in the same page with you Olive. That is the way my brain works as well. I want to have multiple channels, like if we are talking about Slack or any chat tool, but some people have such aversion to multiple channels. They really have a hard time dealing with too many – like testing their threshold of what they think is too many channels. So I am always mindful too, like it has to work for everybody but if it was up to me, there will be one channel per topic. So I know where to focus on.But you said something that is so interesting. How do we even just – like you were saying in the context of channel, multiple channels, and I go, if I need to pay attention to this this week as oppose to like, I don’t need to look at this until some time in the future. How do we even decide what we focus on that is useful for us in the moment versus it would be good for me to know but I don’t need to know right now.I am super bad at this. When I see something that is going to give me the fundamentals, like I have other priorities now, I sort of always want to consume that to learn the fundamentals because I think in the long term phase of, but then I neglect physically what I need to know to do in the moment and I am trying to sort of fish there and get focused on in the moment things. Anybody else have a hard time?[0:34:04.5] DC: You are not alone on that, yeah.[0:34:06.7] CC: It is terrible.[0:34:08.3] MICHAEL: Something that I wish I would do more often as like being a good citizen is like when you read a lot, probably 90% of my time is not writing but reading, maybe even more and then I share and then on Twitter, the tweet for them the most successful ones in terms of retweets or likes are the ones where I do like TLDR’s or some screen captures like too long to read. Where people don’t have the time, they might want to read the article but they don’t have the time.But if you put in like a TLDR like either a tweet or a thread on it, a lot of people would jump onto it because they can just easily capture it and they can still read the full article if they want but that is something that I learned and it is pretty – what is the right word? Helpful to my followers and the community but I just don’t do it that often unfortunately. If I am writing, summarizing, writing, I kind of remember. That is how the brain works. It is a nice side effect.[0:35:04.9] DC: I was saying, this is definitely one of those things where you can be the change you want to see if you, you know?[0:35:08.6] M: Yeah, I know.[0:35:10.0] DC: This is awesome. I would also say that what you just raised Carlisia is like a super valid point. I mean like not everybody’s brain works the same way, right? There are people who are neuro-divergent. There are people who think very linearly and they are very comfortable with that and there are people who don’t. So it is a struggle I think regardless of how your brain is wired to understand to how to prioritize the attention you will give any given subject.In some cases, your brain is not wired – your brain is almost wired against that whole idea, like you are just not set up for success when it comes to figuring out how to prioritize your attention.[0:35:49.0] CC: You hit the nail on the head. We are so set up for failure in that department because there are so many interesting conversations and you want to hop in and you want to be a part of the conversation and part of the group and socialize. Our work is so isolating to really put our heads down and just work, it can be so isolating. So it is great to participate in conversations out there even if it is for only via Twitter. I mean, obviously we are very biased towards Twitter here in this group.But I am not even this on Twitter so just keep that in mind that we are cognizant of that but in any case, I don’t know what the answer is but what I am trying always to cut down on that, those social activities that seem so appealing. I don’t know how to do that from working out.[0:36:43.9] JR: I am in the same boat. 2020, I am hoping to let more of that go and to your point, it is not that there is no value in it. It is just, I don’t know, I am not deriving the same amount of quality out of it because I am so just multiplexed all over the place, right? So we’ll see how it goes.[0:36:59.9] CC: Oh if any listener has opinions and obviously it seems that all of us are helpless in that department. Share with us, please.[0:37:12.5] DC: It is a tricky one. I think it is also interesting because I find that when we talk about things like work-life balance, we think of the idea of maybe work-life balance is that when you come at the end of the day and you go home and you don’t think about work, right? Sometimes we think that work-life balance means that you have a certain amount of time off that you can actually spend with your family and your friends or your community, what have you, and not be engaging on multiple fronts.Just be that – have that be your focus, but when it comes to things like keeping up, when it comes to things like learning or elevating your education and stuff, it seems like, for the most part, and this is just my own assumption, I am curious how you all feel about this, that we don’t – that that doesn’t enter into it, right? Your personal time is totally on the table when it comes to how do you keep up with these things. We don’t even think about it that way, right?I know I personally don’t. I definitely have to do more and cut back on the amount of time that I spend reading. I am right there with Michael on 90% of my time when my eyes are open, they are either reading or staring up on the sky while I try to think about what I am going to write next. You know one way or the other it is like that is what I am doing.[0:38:24.0] CC: Yeah.[0:38:25.1] MICHAEL: I noticed last year on my Twitter feed, more people than the years before will complain about like personal burn out. I saw a pattern, like reading those people’s tweets, I saw a pattern there. It wasn’t really like a spiral and then they realized and they shot down like deleted Twitter from their phones or any messaging and other stuff, and I think I am at the point where I also need to do that when it comes to vacation PDO, or whatever.Because I am just like, as you said Duffy, my free time is on the table when it comes to Twitter and catching up and keeping up because work-life balance in my mind is not work but what is not work for like – Kubernetes is exciting, adding in all the space, like what is not work there? I need to really get better at that because I think I might end in the same spiral of just soaking in more until I just –[0:39:17.7] CC: Yeah and like Josh said, it is not that there isn’t a value. Obviously we derive a huge value, that is why we’re on it, but you have to weigh things and what are your goals and is that the best way to your goals from where you are right now, and maybe you know, Twitter you use for a while, ramp up your knowledge, ramp up the connections because it is great for making connections, and then you step back and focus on something else, then to go on a cycle.This is how I am thinking now. It is just like what Olive was saying, you know, books are great, blog posts are great, and I absolutely agree with that. It is just that I don’t have even the time and when I have the time, I would be reading code and I would be reading things all day long, it is just really tiring for me at the end of the day to sit down and read more. I want to invest in learning how to speed read to solve that problem because I read a lot of books and blog posts. So something on my list.[0:40:22.8] DC: One of the biggest tips on speed reading I ever learned is that frequently when you read you think of saying the word and if you can get out of that habit, if you get out of the habit of saying the word even with your mouth or you just get out of that habit that will already increase the quickness of what you read.[0:40:39.5] CC: That is so interesting.[0:40:41.4] DC: Yeah, that is a trippy one.[0:40:43.1] CC: Because I think being bilingual, I totally like – that really helps me understand things, by saying the words.[0:40:52.9] DC: I think the point that we are all working around here is, there is a great panel that came out at KubeCon EU in 2019 was put on by Aaron Crickenberger, Esther McNaMara, Steven Augustus, these folks are all very high output people. I mean, they do a lot of stuff especially with regard to community and so they put on a panel that was talking about burn out and self-care and I think that it is definitely worth checking that one out.And actually also thinking about what keeping up means to you and making sure that you are measuring that against your ability to sustain, is incredibly important, right? I feel like keeping up is one of those subjects where we end up – it is almost insidious in its way to – it is a thing that we can just do all the time. We can just spend all of our time, any free moment that you have, you are sitting on the bus, you are trying to keep up with things.And because that happens so much, I feel like that is sort of one of the ways that we can feel burnt out as you are seeing today. We can feel like we did a lot of things but there was no real result to it and keep in mind that that’s part of it, right? Like when you are thinking about how we are keeping up with it, make sure that the value to your time is still something that you have some cognizance about, that you have some thought about, like is it worth it to me to just spend this six hours reading everything, right?Or would it be better for me to spend some amount of time just not reading, you know? Like doing something else, you know? Like bake a cake for crying out loud, you know?[0:42:29.5] CC: Something that a lot of times we don’t allow ourselves to do and I decided to speak for everybody I am sorry, I just do nothing, because our brain needs that. We need to not be listening, not be reading, just nothing. Just sit and look at the ceiling, our brain needs that. Ideally, look at nature, like look outside, look at the air, go for a walk. We need that, because that recharges the brain. Anyway, one thing also that I want to bring up, maybe we can mention real quick because we are coming up at the top of the hour.How do people, projects, how do we really help the users of those projects to be up to date with what they are doing?[0:43:18.4] DC: Well yeah I mean this is the different patterns that we are talking about. So I think the blog posts help. I like the idea of having blogs that are targeted towards different audiences. I like the idea of having an aggregate here for putting up a big project. I mean obviously Kubernetes is such a huge ecosystem that if you have things like KubeWeekly and I know that there are actually quite a number of things out there that try and do this.But if we can kind of agree on one like KubeWeekly I think is a pretty good one because it is actually run by the CNCF. So it kind of falls within that sort of governance as a model but having an aggregator where you can actually produce content or curate content as it relates to your project that’s helpful, and then office-hours I think is also helpful to Josh’s point. I mean office-hours and SIG hours are very similar things. I mean like office-hours there like how to developers think about what’s happening with the space.This is an opportunity for you as an end user to show up and ask questions, those sorts of patterns I think all are incredibly helpful as a project to figure out there to those things.[0:44:17.8] OP: Yeah, I know summary articles or the sort of TLDRs that Michael mentioned earlier, I think I need more of those things in my life because I do a lot of reading, because I think my brain is a bit weird in that I need to read something about five or six different times from five or six different articles for it to sort of frame in my head.So what I am trying to – like for 2020, I have almost tried to do this, is like if I think somebody knows all about this and it would save me reading those five, six, seven articles and if that person has the time, I try and sort of reach out to them and say, “Listen, have you got 20 minutes or so to explain this topic to me? Can I ask you questions about it?” It just saves me, saves my eyes reading the screen, and it just saves me time. I just need a TLDR summary of a project or a feature or something just so I can know what it is all about in my head and talk fairly sort of confidently about it.If I need to get in front and down under the weeds then there is more reading to kind of do for me maybe the coding on the technical side, but sometimes I can’t figure out what this feature sort of means and what is its use case in the real world and I have to read through lots of articles and sometimes kind of vendor specific ones and they’ve got a different slant than maybe an independent one and trying to marry those bits up my head is a bit hard for me and there is sort of wealth of information.So if you are interested in a topic and there is hundreds of articles and you start reading four or five and they are all slightly different, eventually you figure out that – you are confident and I understand what that product is about but it has taken a long time to get there and it is taken a lot of reading time. So TLDRs is like really work and I think as Josh mentioned before, we have this thing internally where we do bench demos.And that is like a TLDR and a show and tell really quickly, like, “This is what this does and this is why we need to know about it and this is why our customers needs to know about it, the end,” you know? And that’s really, really useful because that just saves a whole bunch of people a whole bunch of time figuring out A, whether they need to know about it and B, actually now understanding that product or feature at the end of the five, 10 minutes which is what they typically are. So they are very useful short snippets of information. Maybe we are back to Twitter.[0:46:37.8] JR: Similar to the idea of giving a demo Olive, you made me think of something and that is that I think one of the ways that I keep up with the space is actually through writing along with reading and I think the notion of like – and this admittedly takes up time and the whole quality of life conversation comes in but using writing to help develop your thoughts and kind of aggregate all of these crazy inputs and try to be somewhat concise, which I know I struggle with, around something I’ve learned.It’s helped me a ton and then that asset kind of becomes reusable to share with other people the thing that you wrote. So for people listening to this I guess maybe a call to action for 2020 if that is your style as well, consider starting to write yourself and becoming a resource, right? Because even if you are new to this space, you’d be amazed at just how writing from your perspective can help other people.[0:47:26.3] DC: I think another one that I actually have been impressed with lately is that a number of consumer companies like people out there like Lyft and companies like that have actually started to surface engineering blogs around how they are using technology and how they are using technology to solve things, which I think, as a service provider, as somebody who is involved in the community of Kubernetes, I find those to be incredibly valuable because I get to actually see how those things are doing.I mean at the same time, I see things like – we talked about KubeCon, which is a convention that they have every year. Obviously the project is large enough to support it but there is actually an incentive if you are a consumer of that project to go and talk about how you are using it, right? It is incentivized in that it is more likely your talk will be accepted if you are a consumer of the product than somebody building it, right? We hear from people building it all the time.I love that idea of incentivizing people who are using this thing get out there and talk about it or share their ideas about it or how they are using it, what problems did it solve for them. That is critical I think.[0:48:31.0] CC: Can I also make a suggestion – is to not so much following on the thread that we are talking about just now but kind of on the general thread of this episode. If you have resources that you do use to keep up with things, stop this recording right now and go and give them a like, give them a follow, give them a thumbs up, show somehow appreciation because what Duffy said just now, he was saying, “Oh it is so helpful when I read a blog post.”But people who are writing, they want to know that. So give them some indication, it counts a lot. It takes a lot of effort to sit down and write something or produce a podcast and if you take any, derive any benefit from it, show appreciation. It motivates people to keep doing it.[0:49:26.4] DC: Yeah, agreed.[0:49:27.9] M: I think that is a great bind maybe to close off this episode because it reiterates that just consuming and keeping up that doesn’t necessarily mean you don’t give back, right? So this is a way of giving back, which is really important to keep that flow and creativeness.[0:49:41.8] CC: I go through a lot of YouTube videos and sometimes I just play one after the other but sometimes, you know, I have been making a point of going back and liking it. Liking the ones that I like – obviously I don’t like everything. I mean things that I don’t like I don’t listen in but you know what I mean? It takes no effort but just so people know, “OK, you did a good job here.” By the way, go to iTunes and rate us. So we will know that you liked it and it will help people find our show, our podcast, and if you are watching us on YouTube, give us a like.[0:50:16.1] DC: All right, well unless anybody has any final thoughts, that is what we wanted to cover this session. So thank you all very, very much and I look forward to seeing you next week.[0:50:25.3] M: Bye-bye.[0:50:26.3] CC: Thank you so much.[0:50:27.4] OP: Bye.[0:50:28.1] JR: Bye.[END OF EPISODE][0:50:28.7] ANNOUNCER: Thank you for listening to The Podlets Cloud Native Podcast. Find us on Twitter at https://twitter.com/ThePodlets and on the http://thepodlets.io/ website, where you'll find transcripts and show notes. We'll be back next week. Stay tuned by subscribing.[END]See omnystudio.com/listener for privacy information.

פרק מספר 64 של באמפרס (383 למניין רברס עם פלטפורמה) - רן, אלון ודותן בבוקר גשום של תחילת ינואר (זהירות בשטפונות!) עם סקירה של טכנולוגיות ודברים מעניינים מהזמן האחרון.רן - שפה חדשה (לפחות לרן) בשם CUEשפת קונפיגורציה עם כמה פיצ’רים מעניינים, מימוש ב - Go ע”י מישהו ב - Google איפשהו באירופה.נניח שיש לכם תוכנית שמקבלת קובץ קוניפיגורציה (כקלט), או שאתם עובדים עם Kubernetes שצריך לקבל עשרות (או מאות) קבצי yml. - כנראה שיש לכם כמה בעיות בסיפור הזה:קודם כל - יש הרבה חזרות ואתם רוצים לעשות re-use לאיזשהו “אי של קונפיגורציה” במקום אחר, או אולי לקבע משתנים מסויימים שרלוונטיים בכמה מקומות/חוץ מזה - ולידציה: גם Data Types (אם אתם מצפים ל String כדאי שלא תקבלו Integer וכו’) וגם מבחינה לוגית (המינימום קטן או שווה למקסימום; גיל של אדם הוא לא 500 וכו’)את הבעיה הראשונה (יכולות re-use) שפת CUE לא כל כך פותרת . . . בשביל זה יש שפות אחרות (כמו Dhall למשל)שפת CUE כן פותרת יפה את הבעיה השנייה - היכולת להגדיר סכמה ולעשות ולידציה לסכמה הזו.לדוגמא - אפשר לקחת בנאדם ולהגדיר שיש לו שם פרטי, שם משפחה וגיל, ועל כל אחד מהם אפשר להגדיר גם Data Types וגם ולידציות סכמטיות (הגיל לא גדול מ-120 ולא מתחת ל-0, שם פרטי חייב להיות קיים אבל שם אמצעי לא חובה וכו’), הכל ניתן להגדרה בקבצים שונים.החלק המעניין בכל הסיפור - בסופו של דבר CUE לוקחת הכל ועושה איחוד, במובן של Graph unification: אתם למעשה מגדירים סדרה של אילוצים (הגיל לא קטן מ-0 וכו’) והתוכנית בסופו של דבר צריכה לקבל איזשהו ערך ממשי - ועושה ולידציה על הערכים הללו, ע”י איחוד של של כל האילוצים בקבצים השונים.אם יש סתירה - צועק . . .מאוד מזכיר תכנות לוגי - מי שכתב פעם ל - ProLog או שפות לוגיות אחרות ימצא המון דימיון בין זה לבין הגישה של CUE לקונפיגורציה - יש אוסף של Constraints ושל עובדות ובסופו של דבר נעשה איחוד על כל הגרף הזה, והתוצאה היא איזשהו ערך מעשי לכל אחד מהמשתנים והאם הוא עומד בכל אחד מהאילוצים הללו.(אלון) חייב להגיד שזה מעצבן ברמות קיצוניות - שונא Text-based configurations, כי בסוף אתה צריך לפתח כלי כדי לתחזק את זה . . . אני בגישה של Configuration as Code תמיד, וכל ה - “.yml-י ענק” האלה, שמצריכים כלי לניהול ה - .yml ועוד שפת תכנות לנהל את הכלי שמנהל את ה - .yml ועוד שפה לשפה . . . חזרנו לקוד מההתחלה, אז למה?(דותן) אתה רומז ל - Kubernetes? לא רק . . .לכאורה ה - use case הראשון הוא Kubernetes, אבל יכולים להיות אחרים.בחלק מהמקרים אתה אכן בונה את ה - Service ואתה מגדיר את הקונפיגורציה אז אתה לא חייב לסבול; מצד שני - אם אתה משתמש בכלים אחרים (כן, לדוגמא Kubernetes), האם באמת יש לך ברירה?אתה יכול להשתמש בשפות אחרות שמייצרות .yml או .json, אבל גם שם תצטרך לפתור את אותן בעיות . . .(אלון) ברור, אבל אני כועס על כל מי שמפתח לי משהו שה - Interface  שלו הוא .yml, כי בסוף זה ניהיה מפלצת - ה”קונפיגורצית פח” הזו שאי אפשר לשלוט עליה ולוקח שבועיים לעדכן משהו ומצריכה “100 ולידציות”, במקום Configuration as Code שכבר היה מתקמפל ויש את כל מה שכבר קיים בשפות תכנות והיית יכול גם להוסיף טסטים על הקונפיגורציה, Canary ומה שבא לך - במקום זה אנחנו ממציאים טקסט, ועליו שפת תכנות, והיא לא מספיק טובה אז ממציאים עוד שפת תכנות - ובסוף תנהל הכל ב - Go. אז מה עשינו בזה?(דותן) קצת מזכיר את התקופה של ה - .xml - לפני 15-20 שנה - הייתה XSD כסכמה של ה-xml . . ראיתי גם משהו מאוד דומה ל-XSD בעולם של Kubernetes, משהו שמוסיפים על ה-yml-ים ומייצר עוד yml-ים, עם Rules וכו’ - לגמרי אותו הדבר, רק ש-yml יותר “קליל” מבחינת ה-syntax אבל זה לא אומר שבמהות זה לא אותו הדבר בסוף.(אלון) חזרנו לאותה בעיה . . אני מוכרח להודות שה-Plug-in של VScode ל-Kubernetes הוא להיט - מוצא ועושה מלא ולידציות וכו’.לא ברמה של CUE כנראה ועדיין  -אם אני מרים Service של Configuration as Code וזה משהו מורכב של יותר מ-4 שורות - עזוב אותך . . בוא ניהיה ריאליים: ברוב המקרים שינויים כאלה מגיעים עם גרסא.לפעמים רוצים לשנות משהו קטן, אבל אני מעדיף Code על פני Text Configuration ברוב המקרים.(רן) אתה לא בהכרח בדעת מיעוט - אני חושב שיש מקרים שבהם זה לגמרי ולידי, אבל לא בכל המקרים אפשר להכיל את זה.לתחזוקה של Configuration as a code יש הרבה יתרונות, אבל במקומות שבהם יש ממשק עם “פחות-מתכנתים” (אנשי Ops? . . .) לפעמים צריך לספק קונפיגורציה שלא כקוד, ולפעמים יש מערכות שלא אתה כתבת (Kubernetes) שאתה צריך להתממשק אליהן, ואתה לא בעל הבית.פרויקט מעניין אחר שהוכרז באחד הכנסים האחרונים של GitHub, שמטרתו לשמר פרויקטי קוד פתוח לדורות הבאים - GitHub Archive Programכמה מאות או אלפי הדורות באים (או כמה שהקורונה ייתן) . . .התחילו עם פרויקטים שלהם ואחר כך אפשר היה גם להגיש נוספים - העבירו לכמה מדיות שונות (כולל הדפסה על נייר) - והצפינו בבונקר אי שם ליד גרינלנד בקרבת הקוטב הצפוני, בשרשת איים בשם Svalbard archipelagoהארכיון לא מיועד אך ורק עבור GitHub (למשל, יש מצב שהארכיון עם דגימות זרעים של כמעט כל היבולים בעולם תופס שם מקום קצת יותר משמעותי), אבל עכשיו בין השאר יש שם גם פרויקטים בקוד פתוח שמגיעים לשם ונשמרים עבור הדורות הבאים, מתוך הנחה ששם זה ישמר יותר טוב.קצת מלחיץ שלא סומכים על הגיבויים של Azure, לא?מיועד כנראה עבור החייזרים שיגיעו מתישהו וינסו לקרוא את האימוג’ים.וכיוון שלא דיברנו עדיין על Kubernetes היום - הנה בלוג של מישהו שעובד בגוגל (כן, על Kubernetes) וכתב על מה שהוא חושב שהולך להיות מעניין באיזור של Kubernetes ב-2020אנחנו רק בתחילת השנה, יהיו תחזיות נוספות . . .יש 5-6 תחזיות, מעניינת במיוחד זו של CRD explosion (הכוונה ל Common Resource Definitions)מדובר ב-Data Type שמגדירים ב Kubernetes (כן אלון - ב YAML) - ומאפשר לתאר Entities “שלך” (מה - Business domain שלך) עבור Kubernetes, ואז לעשות איתם כל מיני דברים מעניינים.למשל - אפשר להגדיר Services מיוחדים, כך שעבור כל Service כזה צריך לפחות שלושה Pods וה-Monitoring עם Prometheus, או משהו בסגנון.אז גם אפשר לקחת את ה-CRD שלך ולתרגם אותו באמצעות כלי נוסף (Operator)ה-CRD זו ההגדרה (Syntax), וה-Operator זה מה שמתגרם אותו למשהו שהוא יותר Actionable - ולשניהם יחד יש כוח מאוד גדול.כותב הבלוג צופה CRD explosion - שזה הולך להיות מאוד פופלארי ונראה הרבה כאלה, עד כדי “CRD Hubs” שיכילו את הנפוצים והשימושיים יותר (רוצים להתקין Redis? או Kafka? כאלה)נכון, יש גם פתרונות אחרים ב - Kubernetes (החל מהגדרה “בידיים” דרך מנהלי חבילות למיניהם), אבל הוא צופה שכולם בסוף “יתנקזו” לכיוון של CRD.(אלון) זה מחבר אותי למשהו מהתקופה האחרונה - תהיות בטוויטר לגבי ההייפ סביב Kubernetes: הרי בסוף אפשר לקבל הכל ב-Cloud, גם אם קצת (?) יותר קשה לניהול לבד עם ה-APIs של כל ספק.כאן מדובר על אפליקציות שהן לא Kubernetes אבל עם הקונפיגורציה של Kubernetes, וזו נקודה מאוד מעניינתנשמע הגיוני שניהול של ה-Cloud יהיה ניהול של AWS או GCP או Azure וכו’, עם ממשק אחיד, כך שתוכל לייתר את Kubernetes בעוד כמה שנים, כי יהיה אפשר לעשות הכל ישירות על ה-Cloudאולי לא ב-2020, אבל אם התחזית היא שנראה אפליקציות על בסיס אותה הקונפיגורציה השנה אז כנראה שבסוף נגיע לשם - ו-Kubernetes ישאר נקודת מעבר לעולם אבסטרקציה אחר.(רן) אגב - CRDs כאלה קיימים לא מעט כבר היום - יש CRD שמנהל עבורך S3 (ליצור Bucket או לקבוע הרשאות למשל) - מפעיל אופרטור שמבצע את הפעולה, קצת כמו שכלים כמו Chef או Puppet עובדים.ובהמשך למה שאלון אמר - ברגע שהחלפנו את ה-API הזה, אפשר להחליף את Kubernetes בכלי אחר מלמטה, עם אותו API רק במימוש אחר.אלון - אז נמשיך עם Kubernetes . . . כלי שפותח ב-Google בשם SKAFFOLD - ומאפשר Local K8s developmentעושה Init ,מכין את כל ה-YAML, כותב Dokcer, עושה את ה-Deploy . . .נראה חמוד, לא יצא לי (אלון) לעבוד איתו עדיין, אבל נראה מבטיח, גם אם עדיין שונא YAML.(דותן) מרגיש בנוח עם זה שיש עוד מישהו בסירה…שאלה למי שכן אוהב Kubernetes - כמה פעמים אתם מעדכנים Kubernetes בגלל בעיות Security? (רן) קשה להגיד . . . לא בהכרח כמי שאוהב ולא כמי שמריץ ב-Production. (אלון) אוהב, לא סגור על קצב העדכון, רץ יפה, יש דברים שאני אוהב ודברים שלא. עד רמה מסויימת של Scale זה מאוד נוח, אחר כך צריך ממש להתעסק עם הקונפיגורציות וצריך “להרים את מכסה המנוע” וזה מתחיל להיות מעצבן.(דותן) יש אתגר במקרה למשל בו יש לך לקוח ואתה מחוייב מולו חוזית לתקן בעיה תוך למשל שבועיים - בסביבה עם כל כך הרבה חלקים נעים, איך אפשר להגיע למצב שבו אתה משדרג כל הזמן? זו שאלה קשה, ולא קיבלתי בינתיים תשובה טובה.(אלון) אנחנו רצים על

A warm welcome to John Harris who will be joining us for his first time on the show today to discuss our exciting topic, CI and CD in cloud native! CI and CD are two terms that usually get spoken about together but are actually two different things entirely if you think about them. We begin by getting into exactly what these differences are, highlighting the regulatory aspects of CD in contrast to the future-focussed nature of CI. We then move on to a deep exploration of their benefits in optimizing processes in cloud native space through automation and surveillance from development to production environments. You’ll hear about the benefits of automatic building in container orchestration, the value of make files and local test commands, and the evolution of CI from its ‘rubber chicken’ days with Martin Fowler and Jez Humble. We take a deep dive into the many ways that containers differ from regular binary as far as deployment methods, build speed, automation, run targets, realtime reflections of changes, and regulation. Moreover, we talk to the challenges of transitioning between testing and production environments, getting past human error through automation, and using sealed secrets to manage clusters. We also discuss the benefits and drawbacks of different CI tools such as Kubebuilder, Argo, Jenkins X, and Tekton. Our conversation gets wrapped up by looking at some of the exciting developments on the horizon of CI and CD, so make sure to tune in! Follow us: https://twitter.com/thepodlets Website: https://thepodlets.io Feeback: info@thepodlets.io https://github.com/vmware-tanzu/thepodlets/issues Hosts: Bryan Liles Nicholas Lane Key Points From This Episode: • The difference between CI and CD.• Understanding the meaning of CD: ‘continuous delivery’ and ‘continuous deployment’.• Building an artifact that can be deployed in the future is termed ‘continuous integration’.• The benefits of continuous integration for container orchestration: automatic building.• What to do before starting a project regarding make files and local test commands.• Kubebuilder is a tool that scaffolds out the creation of controllers and web hooks.• Where CI has got to as far as location since its ‘rubber chicken’ co-located days.• The prescience of Martin Fowler and Jez Humble regarding continuous integration.• The value of running tests in a CI process for quality maintenance purposes.• What makes containers great as far as architecture, output, deployment, and speed.• The benefits of CD regarding deployment automation, reflection, and regulation.• Transitioning between testing and production environments using targets, clusters, pipelines.• Getting past human error through automation via continuous deployment.• What containers mean for the traditional idea of environments.• How labeling factors into the simplicity of transitioning from development to production.• What GitOps means for keeping track of changes in environments using tags.• How sealed secrets stop the need to change an app when managing clusters.• The tools around CD and what a good CD system should look like.• Using Argo and Spinnaker to take better advantage of hardware.• How JenkinsX helps mediate YAML when installing into clusters.• Why the customizable nature of CI tools can be seen as negative.• The benefits of using cloud native-built tools like Tekton.• Perspectives on what is missing in the cloud native space.• A definition of blue-green deployments and how they operate in service meshes.• The business abstraction elements of CI tools that are lacking.• Testing and data storage-related aspects of CI/CD that need to be developed. Quotes: “With the advent of containers, now it’s as simple as identifying the images you want and basically running that image in that environment.” — @bryanl [0:18:32] “The whole goal whenever you’re thinking about continuous delivery or continuous deployment is that any human intervention on the actual moving of code is a liability and is going to break.” — @bryanl [0:21:27] “Any time you’re in developer tooling, everyone wants to do something slightly differently. All of these tools are so tweak-able that they become so general.” — @johnharris85 [0:34:23] Links Mentioned in Today’s Episode: John Harris — https://www.linkedin.com/in/johnharris85/Jenkins — https://jenkins.io/CircleCI — https://circleci.com/Drone — https://drone.io/Travis — https://travis-ci.org/GitLab — https://about.gitlab.com/Docker — https://www.docker.com/Go — https://golang.org/Rust — https://www.rust-lang.org/Kubebuilder — https://github.com/kubernetes-sigs/kubebuilderMartin Fowler — https://martinfowler.com/Jez Humble — https://continuousdelivery.com/about/David Farley — https://dfarley.com/index.htmlAMD — https://www.amd.com/enIntel — https://www.intel.com/content/www/us/en/homepage.htmlWindows — https://www.microsoft.com/en-za/windowsLinux — https://www.linux.org/Intel 386 — http://www.computinghistory.org.uk/det/6192/Introduction-of-Intel-386/386SX — https://www.computerworld.com/article/2475341/flashback--remembering-the-386sx.html386DX — https://en.wikipedia.org/wiki/Intel_80386Pentium — https://www.intel.com/content/www/us/en/products/processors/pentium.htmlAMD64 — https://www.webopedia.com/TERM/A/AMD64.htmlARM — https://en.wikipedia.org/wiki/ARM_architectureTomcat — http://tomcat.apache.org/Netflix — https://www.netflix.com/za/GitOps — https://www.weave.works/technologies/gitops/Weave — https://www.weave.works/Argo — https://www.intuit.com/blog/technology/introducing-argo-flux/Spinnaker — https://www.spinnaker.io/Google X — https://x.company/Jenkins X — https://jenkins.io/projects/jenkins-x/YAML — https://yaml.org/Tekton — https://github.com/tektonCouncourse CI — https://concourse-ci.org/ Transcript: EPISODE 11 [INTRODUCTION] [0:00:08.7] ANNOUNCER: Welcome to The Podlets Podcast, a weekly show that explores Cloud Native one buzzword at a time. Each week, experts in the field will discuss and contrast distributed systems concepts, practices, tradeoffs and lessons learned to help you on your cloud native journey. This space moves fast and we shouldn’t reinvent the wheel. If you’re an engineer, operator or technically-minded decision maker, this podcast is for you. [EPISODE] [00:00:41] BL: Back to the Kubelets Podcast, episode 11. I’m Bryan Liles, and today we have Nicholas Lane. [00:00:50] NL: Hello! [00:00:51] BL: And joining us for the first time, we have John Harris. [00:00:55] JH: Hey everyone. How is it going? [00:00:56] BL: All right! So today we’re going to talk about CI and CD in cloud native. I want to start this off with this whole term CI and CD. We talk about them together, that are two different things almost entirely if you think about them. But CI stands for continuous integration, and then we have CD. What does CD stand for? [00:01:19] NL: Compact disk. [00:01:20] BL: Right. True, and actually I’ve used that term before. I actually do agree. But what else does CD stand for? [00:01:28] NL: It’s continuous deployment right? [00:01:30] BL: Yeah, and? [00:01:31] JH: Continuous delivery. [00:01:32] NL: Oh! I forgot about that one. [00:01:35] BL: Yeah, that’s the interesting thing, is that as we talk about tech and we give things acronyms, CD is just a great one. Change in directories, compact disk, continuous delivery and continuous deployment. Here’s the bonus question, does anyone here know the difference between continuous delivery and continuous deployment? [00:01:58] NL: Now that’s interesting. [00:01:59] JH: I would go ahead and say continuous delivery is the ability to move changes through the pipeline, but you still have the ability to do human intervention at any stage, and usually deployments production and continuous delivery would be a business decision, whereas continuous deployment is no gating and everything just go straight to product. [00:02:18] BL: Oh, John! Gold start for you, because that is one of the common ones. I just like to bring that up because we always talk about CI and CD as they are just one thing, but they’re actually way bigger topics and we’ve already introduced three things here. Let’s start at the beginning and let’s talk about continuous integration, a.k.a CI. I’ll start off. We have CI, and what is the goal of CI? I think that we always get boggled down with tech terms and all these technology and all these packages from all these companies. But I’d like to boil CI down to one simple thing. The process of continuous integration is to build an artifact that can be deployed somewhere at some future date at some future time by some future person, process. Everything else is a detail of the system you choose to use. Whether you use Jenkins, or CircleCI, or Drone, or you built your own thing, or you’re using Travis, or any of the other online CI tools. At the end of the day, you’re building either – If you’re doing web development. Maybe you’re building out Docker files, because we’re in cloud native. I mean docker images, because we’re in cloud native. But if you’re not, maybe you’re just building JARs, WARs, or EARs, or a ZIP file, or a binary, or something. I’d just like to start off, start this off with there. Any more thoughts on continuous integration? [00:03:48] NL: Yeah. I think the only times that I’ve ever used something that’s like continuous integration is when I’ve been doing like more container orchestration, like development, things on top of like things like Kubernetes, for instance. The thing I really like about it is like the concept of being able to like, from my computer, save and do an automatic save and push to a local repo and have all of the pieces get built for me automatically somewhere else, and I just love that so much because it saves so much brain thinky juice to run every command to make the binary you need. [00:04:28] BL: So did you actually create those scripts yourself? [00:04:30] NL: Some of them. When I’ve used things like GitLab, I use the pipeline that exists there and just fiddled around with like a little bit of code, like some bash there, but like not too much because GitLab has a pretty robust pipeline. Travis — I don’t think I needed to actually. Travis had a pretty good just go make Docker build, scripts already templated out for you. [00:04:53] JH: Yeah. I’d like to tell people whenever you start any project, whether it’s big or small, especially if it’s on – Not on Windows. I’ll tell you something different if it’s on Windows. But if you’re developing on a Mac or developing on Linux, the first thing you should do in your project is create a make file or your programming language equivalent of a make file, and then in that make file what you should do is write a command that will build your software that runs its tests locally, and also builds – whatever the process is. I mean, if you’re running in Go, you do a Go build. If you’re using Rust, build with Rust, or C++, or whatever before you even write any code. The reason why is because the hardest part is making your code build, and if you leave that to the end, you’re actually making it harder on yourself. If your code build works from the beginning, all you have to do is change it to fit what you’re doing rather than thinking about it when it’s crunch time. [00:05:57] NL: I actually ran into that exact scenario recently, because I’ve been building some tooling around some Kubernetes stuff, and the first one I did, I built it all manually by hand. Then at the end I was like – I gave it to the person who wanted it and they’re like, “So, where’s the make file?” I’m like, “Where’s the what?” So I had go in and like fill in the make file, and that was a huge pain in the butt. Then recently the other thing I’ve been using is Kubebuilder. John, you and I have been talking about Kubebuilder quite a bit, but using Kubebuilder, and one of the things it does for you is it scaffolds out and a make file for you, and that was like going from me doing it by myself to having it already exist for you or just having it at the beginning was so much better. I totally agree with you, Brian. [00:06:42] BL: So quick point of order here. For those of us who don’t know what Kubebuilder is. What is Kubebuilder? [00:06:48] NL: Kubebuilder is a tool that was created by members of the Kubernetes Community to scaffold out the creation of controllers and web hooks. What a controller is in Kubernetes is a piece of software that waits, sort of watches a specific object or many specific objects and reconciles them. If they noticed that something has changed and you want to make an action based on that change, the controller does that for you. [00:07:17] JH: Okay. So it actually makes the action of working with CRDs and Kubernetes much easier than creating it all yourself. [00:07:26] NL: Correct. Yeah. So, for instance, the one that I made for myself was a tool that watched, updated and watched a specific CRD, but it wasn’t necessarily a controller. It was just like flagging on whether or not a change occurred, and I used the dynamic client, and that was a huge headache on of itself. Kubebuilder has like the ability to watch not just CRDs, but any object in Kubernetes and then reconcile them based on changes. [00:07:53] NL: It’s pretty great. [00:07:54] BL: All right. So back to CI. John, do you have any opinions on CI or anecdotes or anything like that? [00:07:59] JH: Yeah. I think one of the interesting things about the original kind of philosophy of CI outside of tooling was like trunk-based development that every develop changes get integrated into trunk as soon as possible. You don’t get into integration hell and rebasing. I guess it’s kind of interesting when you apply that to a cloud native landscape where like when that stuff came out with like Martin Fowler or Jez Humble probably 10, 15 years ago almost now, a lot of dev teams were co-located. You could do CI. I think there was a rubber chicken method where you didn’t use a tool. It was just whoever had the chicken that’s responsible for the build. Just to pull everyone else’s changes. But now it seems like everything is branch-based. When you look at a project like Kubernetes, there’s a huge number of contributors all geographically displaced, different time zones, lots of different branches and features going on at the same time. It’s interesting how these original principles of continuous integration from the beginning now apply to these huge projects in the cloud native landscape. [00:08:56] BL: Yeah, that’s actually a great point of how prescient Martin Fowler has been for many, many years, and even with Jez Humble being able to see these problems 10, 15 years ago and be able to describe them. I believe Jez Humble wrote the CD book, the continuous delivery book. [00:09:15] JH: Yeah, with David Farley, I think. [00:09:18] NL: Yeah. Yeah, he did. So, John, you brought up some good things about CI. I try to simplify everything. I think the mark of someone who really knows what they’re talking about is being able to explain everything in the simplest words possible, and then you can work backwards when people understand. I started off by saying that CI produces an artifact. I didn’t talk about branches or anything like that, or even the integration piece. But now let’s go into that a little bit. There are a lot of misconceptions about CI in general, but one of the things that we talk about is that you have to run test. No, you don’t have to run test, but should you? Yes, 100% of the time. Your CI process, your integration process should actually build your software and run the test, because running the test on this dedicated service or hardware wherever it is ensures that the quality of your software is there at least as much as your developers have insured the quality in the test. It’s very important those run, and a lot of bugs of course can be spotted by running a CI. I mean, we are all sorts of developers here, and I tell you what, sometimes I forget to run the test locally and CI catches me before a commit makes it into master and it has a huge typo or a whole bunch of print lines in there. Moving on here, thinking about CI and cloud native. Whenever you’re creating a cloud native app, have you ever thought about the differences between let’s say creating just a regular binary that maybe runs on a server, but not in a container on somebody’s cloud native stack, i.e. Kubernetes? Have you ever thought about the differences of things to think about? [00:11:04] BL: Yeah. So part of it is – I would imagine or I believe it’s like things like resource, like what resources you need or what architecture you’re deploying into. You need the binary to make like run in this – With containerization, it’s easy because you’re like, “I know that the container is going to be this architecture,” but you can’t necessarily guarantee that outside of a containerized world. I mean, I suppose you can being like with the right tooling setup you can be like, “I only want to run on this.” But that isn’t necessarily guaranteed, because any computer that runs on could be just whatever architecture that happens to land on, right? Also, something to – I think of is like how do you start processes on disparate computers in a controlled fashion? Something like, again, with containers, you can trust that the container runtime will run it for you. But without that, it seems like a much harder task. [00:12:01] NL: Yeah, I would agree. Then I said that containers in general just help us out, because most of our workloads go on some AMD or Intel 64 bit and it’s Linux. We know what our output is going to be. So it’s not like in the old days where you had to actually figure out what your run target was. I mean, that’s even on Intel stacks. I mean, I’m updating myself here where you had like – When the 386 was out and then you had the 386SX and the 386DX, there were different things there, and you actually compile your code different. Then when the 46 came out and then when we had introduction of Pentium chips, things were different. But now we can pretty much all target AMD64, and in some cases, I mean, there are some chip things like the bigger encryption things that are in the newer chips. But for the most part, we know what our deployed target is going to be. But the cool thing is also that we don’t have to have Intel or AMD64. It could be ARM32 or ARM64, and with the addition to a lot of the work that has been going on in Windows land lately, we can have Windows images. I don’t know so many people were doing that yet. I’m not out and part of the field, but I like that the opportunity is there. [00:13:25] JH: Oh! I think one of the interesting things is the deployment method as well. Now with containers, everything is kind of an immutable rip and replace. Like if we develop an application, we know that the old container is going to stop when I deploy a new one. I think Netflix were doing a little bit of this before containers and some other folks with like baking AMIs and using that immutable method. But I think before that it was if we had a WAR file, we had to throw it back into Tomcat, let Tomcat pick it up or whatever. Everything was a little bit more flaky in terms of deployment. We had to do a lot of checks around deployment rather than just bring something out, bring something back in blue/green, whatever. [00:13:59] BL: Well, I actually like that you brought that up, because that’s actually one of the greatest parts of this whole cloud native thing, is that when we’re using containers and we’re deploying with containers, we know what our file system is going to look like, because we created it. There would not be some rogue file or another configuration there that will trip up our deployment, because at build time, we’ve created the environment. It’s much better than that facility that Netflix was doing with baking AMIs. In a previous life, I actually ran the facility for baking AMIs at a large company where we had thousands of developers on more than a thousand dev teams, and we had a lot of spyware. Whenever you had to build an image, it was fine in one account, but if you had let’s say a thousand accounts with the way that AWS works and encrypted images, you actually had to copy all the images to all the accounts. It couldn’t actually boot it from your account. That process would literally take all night to get it done across all of our accounts. If you made a mistake, guess what? You get to do it again. So I am glad that we actually have this thing called a container and all these things based on CRI, the container runtime, that we are able to quickly build containers. I don’t want to just limit this conversation to continuous integration. Let’s get into the other parts too with deployment and delivery. What is so novel about CD and the cloud native world? [00:15:35] NL: I think to me it’s the ability to have your code or your artifact or whatever it is, whatever you’re working on. When you make a change, you can see the change reflected in reality, whatever your reality looks like, without your intervention. I mean, you might have had to set up all the pipelines and all that jargon, but when you press save in VS code and it creates a branch and runs all your tests and then deploys it for you or delivers it for you into what you’d define as reality, that’s just so nice, because it really kind of sucks having to do the like, “Okay, I’ve got a new deployment. Destroy the old deployment. Put in the new one or like rev the new image tag or whatever in the deployment you’re doing.” All these manual steps, again, thinky-brain juice, it takes pieces of your attention away, and having these pieces like added for you is just so nice. [00:16:30] BL: Yeah, what do you think, John? [00:16:32] JH: Yeah. I think just something in the state of DevOps we’ve bought one of the best predictors for a company’s success is like cycle time of feature from ideation to production. I think like the faster we can get that cycle – It kind of gets me interested. How long does an application take to build? If it takes two hours, how good are you at getting features out there quickly? Maybe one of the drivers with microservices, smaller pieces independently deployed, we can get features out to production quicker, because I think the name of the game is just about enabling developers to put the decision in the hands of the business to decide when the customer should see that feature. I think the tighter we can make that cycle, the better for everyone. [00:17:14] BL: Oh, no! I agree. I love and hate web services, but what I do like is the idea of making these abstractions smaller, and if the abstractions are smaller, it’s less code. A lot of the languages we use now are faster compiling, let’s say, a large C++ project. That could take literally two hours to compile. But now when we have languages like Go, and Rust is not as fast, but it’s not slow as well. Then we have all of our interpret languages, whether it’d be Python, or JavaScript, or TypeScript, where we can actually go from an idea, run the test in a few minutes and build this image that we can actually run and see it almost in real-time. Now with the complexity of the tools, I mean, the features that are built in the tools, we can now easily manage multiple deployment environments, because think about before, you would have a dev environment, and that would be the Wild West. That would be literally where it would be awful. You might have to rebuild it every couple of months. Then you would have staging, and then maybe you would have some kind of pre-prod environment just as like your final smoke test, and then you would have your production. Maintaining all the software on all those was extremely hard. But now with the advent of containers, now it’s as simple as identifying the images you want and basically running that image in that environment. I like where we’ve ended up. But with all power comes new problems, and just because we can deploy quicker means we just run into a lot of different problems we didn’t run into before. The first one that I’ll bring up is the complexity. Auto conversion between environments, so moving code between test staging and production. How do we do that? Any ideas before I throw some out there? [00:19:11] NL: I guess you would have different, or maybe the same pipeline but different targets for like if say you’re using something like Kubernetes. You could have one part of your pipeline deploy initially to this Kubernetes context, which points to like one cluster. It’s building up clusters by environment type and then deploying into those, running your tests, see if it runs properly and then switch over to the next context to apply that image tag and that information and then just go down the chain until you go to production. [00:19:44] BL: Well, that’s interesting. One thing I’d like to throw out there, and I’m not advocating any particular product. But the idea of having pipelines for continuous integration and your CD process is great, where you can now have gates and you can basically automate the whole thing. Code goes into CI and we built an artifact, and a message can go out automatically to an approver or not, and that message could say, “Hey! This code is going to be integrated into our trunk or our master branch.” They can either do it themselves manually as a lot of people do or they can actually maybe click on a link or check a checkbox and this gets integrated in. Then what automatically could happen at this point is, and I’ve seen a lot of companies doing this, is now we take that software and we spin up a new whole environment and we just install that software. For that one particular feature that you worked on, you can actually get an automatic environment for that. Then what we can do is we can take that environment itself and we can now merge this maybe into a staging branch or tag it with a staging label, and that automatically gets moved to staging. Depending on how complicated you are, how advanced you are, now you can actually have it go out to your product people or people who make decisions, maybe your executives, and they can view the software in whatever context it happens to be in. Then they can say, “Okay.” Now that’s when we’re talking about now we can hit okay and the software just keeps on moving to the pipeline and it gets into production. The whole goal here, and this is actually where your goal should be just in general whenever you’re thinking about continuous delivery or continuous deployment is that any human intervention on the actual moving of code is a liability and is going to break, and it’s going to break because on Friday afternoon at 5:25 PM, someone’s thinking about the weekend and they’re not thinking about code, and they’re going to break your build. Our goal is to build these delivery systems that are Friday afternoon proof. We can push code anytime. It doesn’t matter. We trust our process. [00:22:03] JH: I think it’s a great point about environments. I think back in the day, an environment used to be a set of machines, and then test used to be – staging was where there were kind of more stable versions of APIs and folks were more coordinated pushing things into them. What really is an environment? Like you said, when we push micro services or whatever service, we can spin up an entire Kubernetes cluster just for that service. We can set it up. We can run whatever tests we want. We could tear it down. With the advent of Elastic compute, and now containers, they really enabled this world where like the traditional idea of an environment and what constitutes an environment is starting to get a bit kind of sloppy and blend into each other. [00:22:42] BL: I like it though. I think it’s progress. [00:22:45] NL: I totally agree. The one that scares me but I also find like really interesting, is the idea of having all of your environments in one set of machines. So clusters. Having a multi-tenanted set of machines for like dev staging and production, they’re all running in the same place and they’re all just separated by like what configuration of like connectivity from different networking and things like that set up. When a user hits your website, bryanliles.com, they should go to the production images, but those are binaries, and those binaries should be running in the same space essentially as the development ones. It’s scary, but it’s also like allows for like some really fast testing and integration. I find it to be very fascinating. [00:23:33] BL: I mean that’s where we want to be. I find more often than not that people have separate clusters for dev and staging and production. But using the Kubernetes API, you don’t have to do that, because what we can do is we can force deployment or workload to a set of machines based on their label. That’s actually one of the very strong positives for Kubernetes. Forget all the complexity. One of the things that makes it easy is to say that I want this particular deployment to only live on my development machines. Well, which development machine? I don’t care. What if we increase our development pool size? We just re-label nodes. It doesn’t matter. Now we can just control that. When it comes down to controlling cost and complexity, this is actually one idea that Kubernetes is leading and just making it easier to actually use more of your hardware. [00:24:31] NL: Yeah. Absolutely. That’s so great because if you think about it from a CI/CD standpoint, at that point all you have to do is just change the label to where you’re applying this piece of code. So you’re like, “Node selector, label equals dev. Okay, now it’s staging. Okay, now it’s prod.” [00:24:47] BL: So this brings me into the next part of what I want to talk about or introduce to you all today. We’re on a journey as you probably can tell. Now whenever we have our CI process and we’re building and we’re deploying, where do we store our configurations? [00:25:04] NL: [inaudible 00:25:04]. [00:25:06] BL: Ever thought about that? [00:25:08] NL: Okay. I mean, in a Kubernetes perspective, you might be using something like etcd to sort of – But like everything else, what if you’re using Travis? [inaudible 00:25:16] store everything. Everything should be versioned, right? Everything should be – [00:25:20] BL: Yeah, 100%. [00:25:24] NL: I would store everything these as much as possible. Now, do I do that all the time? God, no! Absolutely not. I’m a human being after all. [00:25:32] BL: I mean, that’s what I actually want to bring up, is this concept of GitOps. GitOps was a coined term by my friend, Alexis, who works at Weave. I think Weave created this. Really what it’s about is instead of having – basically, Kubernetes is declarative, and our configurations can be declarative too, because what we can do is make sure is we can have tech space configurations, and for one reason it’s because tech space means it can be versioned. It can be diffs. We take those text versions and we put them in our same repository we put our code in. How do we know what’s in production at any given time or any given time in the past? We just look at the tags of what we did. We had a push at 5:15 on August 13th. Of course, this is 5:15, you could see time, because any other time doesn’t exist in the computer land. So what we could do is we could just basically tag that particular version as like 2019-08-13. If I said 5-17-55, and we call 01 just so we could have 100 deploys in a day. If we started doing that, now not only can we control what we have, but we can also know what was on in any given environment at any given time. Because with Git and with Mercurial and any other of these – Well, only the popular ones, with Git and Mercurial, you can definitely do this. Any given commit can have multiple tags. You could actually have a tag that hit dev and then a tag that, let’s say, hits staging, and then a tag that hit production, the exact same code but three different tags. So you know at any given time what happened. [00:27:18] JH: Yeah, the config thing is so important. I think that was another Jez Humble quote where it was like, “Give me three hours access to your code and I’ll break it. But give me 5 minutes with your configurations and I’ll break it.” Almost like every big bug is, right, someone was accidentally pointing the prod server to the staging database like, “Oops! Their API was pointing to the wrong port, and everything came down,” or we changed the wrong versions or whatever. I think that’s one of the intersections of developers and operations folks. We kind of talked about like Dev Ops and things like that. I really love the idea of everything being kept in Git and using GitOps, but then we’ve got things like secrets and configuration that shouldn’t be seen or being able to be edited by developers, but need to be for ops folks. But we still want to keep the single point of truth. Things like sealed secrets have really enabled us to move along in this area where we can keep everything in text-based version. [00:28:08] BL: All right. Quick point of order here. Sealed secrets is a controller/CRD created by Bitnami. What it allows you do is, John – [00:28:23] JH: It allows you – It creates a CRD, which is sealed secret, which is a special resource type in your cluster and also creates a key, which is only available to that operator running in your cluster. You can submit a sealed secret in plain text or you can submit a secret in plain text and it will throw it back out as an encrypted secret with that key and then you can check that into version control. Then when you go to deploy your software, you can deploy that encrypted secret into the cluster. The operator will pick it up, decrypt it using only the key that it has access to and then put it back in the cluster as a regular secret. Your application just interacts with regular Kubernetes secrets. You don’t need to change your app. They deal with all the encryption outside of the user intervention. [00:29:03] BL: I think the most important part of what you said is that this allows us to have no excuses about what we can store in our repositories for our configuration, because someone is going to make the argument, “No, we can’t store secrets, because someone’s going to be able to see them.” Well, guess what? We never even stored an unencrypted secret in our repository. They’re all encrypted, and it’s still secrets. It’s [inaudible 00:29:25]. I don’t know if anyone’s cracked yet. I’m sure maybe a state level actor has thought of it. But for us regular people, even our companies, like even at VMware, or even at Google, they have not done it yet. So it’s still pretty safe. Thinking even further now, and really what I’m trying to paint the picture of is not just how do you do CD, but really what CD could look like and how it can actually make you happy rather than sad. The next item I wanted to think about was tools around CD and creating tools and what does a good continuous delivery system look like. I kind of hinted about this earlier whenever I was talking about pipelines. The ability to take advantage of your hardware, so we’re deploying to let’s say 100 servers. We’re pulling 5 or 6 services to 100 node cluster. We can do those all at once, and what we can do is you want to have a system that can actually run like this. I could think of a couple. From Intuit, there is Argo, and they have Argo CD. There is the tool created by Google and maybe Netflix. I want to have to look that one up. It’s funny, because they quoted – [00:30:40] JH: Spinnaker? [00:30:42] BL: Spinnaker. They quoted me in their book, and I don’t remember their name. I’m sorry anyone from Spinnaker product listening. Once again, not advocating any products, but they have the concept of doing pipelines. Then you also have other things for your projects, like if you’re using open source, Drone. Another X Google – I think it was X-Googler that made this. Basically, they have ways you can do more than one thing at a time. The most important piece about this is not only can you do more than one thing at a time, is that you have a programmatic check that it’ll make sure that you can verify that whatever you did was successful. We deployed to staging or we deployed to our smoke test servers for our smoke test, and that requires our testing people and an executive signoff. They can actually just wait until they get their signoff or maybe if it goes over a day or so, they can actually – It just fails, and now the build is done. But that part is pretty neat. Any other topics over here before I start throwing out more? [00:31:45] NL: I think I just have thoughts on some of the tools that we’ve used. Everyone Jenkins. Jenkins can do anything that you want it to do, but you really have to tighten the screws on it. It is super powerful. It’s kind of like Bash, like Bash scripting. It’s super powerful, but you have to know precisely what you’re doing, otherwise it can really hurt you. Actually, I have used Spinnaker in the past, and I’ve really liked it. It has a good UI, very good pipelines. Easy blue/green or canary deployment mechanism, I thought that was great. I’ve looked at Drone, believe it or not, but Drone is actually pretty cool. Check out Drone. I really liked it. [00:32:25] BL: Well, since we’re throwing out products, Jenkins, does have JenkinsX. I have not given it the full rundown yet. But what I do like about it, and I think everyone should pay attention to this if you’re doing a product in this space, is that when you install JenkinsX, you install it locally to your machine. You basically get this binary called JX, and you then tell JX to install it into your cluster. Instead of just doing kubectl apply-f a whole bunch of YAML, it actually ask you questions and it sets up GitHub repositories or wherever you need these repositories. It sets up [inaudible 00:33:01] spaces for you. There’s no just [inaudible 00:33:05] kubectl apply-f HTTPS: I just owned your system, because that’s actually a problem. Then it solves the YAML sprawl, because YAML and Kubernetes is something that is complained about a lot, but it’s how it’s configured. But it’s also just a detail what we’re supposed to be doing, and we actually work with Joe Beda and I could talk about this all the time, is that the YAML is the implementation, but it’s not the idea. The idea is that we build tools on top of that that create YAML so users have to see less YAML. I think that’s a problem with Jenkins, is that it’s so powerful and they’re like, “Well, we want powerful people or smart people to be able to do smart things. So here you go.” The problem with that is that where do I start? It’s a little daunting. So I do think that they definitely came with the much stronger game with this JX command. Just as a little sidebar, we do it as well with our Valero project, and I think that just speaks, should be like the bar for anything. If you’re installing something into a cluster, you should come up with a command line tool that helps you manage the lifecycle of whatever you’re installing to the operator, YAML, whatever. [00:34:18] JH: I think what’s interesting about the options, this is definitely one area where there’s so much nuance. Any time you’re in developer tooling, everyone wants to do something slightly differently. All of these tools are so tweak-able that they become so general. I think it’s probably one of the criticisms that could be leveraged against Jenkins is that you can do everything, and that’s actually a negative as well as a positive. Sometimes it’s too overwhelming. There are too many ways of doing things. I’m a fan of some of the more kind opinionated tools in that space. [00:34:45] BL: Yeah. I like opinionated tools as well, but the problem that we’re having in this cloud native space is that, yeah, Kubernetes is five-years-old now. We are just getting to the point where we actually understand what a good decision is, because there was a lot of guesses before and we’ve done a lot of things, and some of these have been good ideas, but in some cases they have not been great ideas. Even I ran the project case on it. Great idea on paper, but implementation, it required people to know too many things. We’d learned a lot of lessons from that. That’s what I think we’re going to find out in this space is that we’re going to learn little lessons. I say this project from my last project that I was going to bring up is something that I think has learned some of the lessons. Google sponsors a project called Tekton, and if you go to – It’s like I believe, and they have some continuous delivery stuff in there and they implement pipelines. But the neat part is, and this is actually the best part, it’s actually a cloud native built service. So every step of your delivery process, from creating images, to actually putting them on clusters, is backed by a Docker image or a container, and I think that part is pretty neat. So now you can define your steps. What is your step? Well, you can use one of their pre-baked, run this command, or if you have something special, like the example before I was giving out where you would say that you need an approval, maybe it’s a Slack approval. You send something with Slack and it has a checkbox, check yes if you like me. What we can do now is we can actually control that and it’s easy to write something a little Docker image that can actually make that call and then get the request and then it can move it on. If you’re looking at more of a toolkit full of good ideas, I do think that Tekton has definitely has some lots of industry. People are looking at it and it’s probably the best example of getting it right in the cloud native way. Because a lot of the products we have now are not cloud native. We’re talking about Jenkins. We’re talking about Spinnaker and we talk about Drone and Travis, which is totally a SaaS product. They’re not cloud native. Actually, the neat part about Tekton is that it actually comes with its own controllers and its own CRDs. So you can actually build these things up using your familiar Kubernetes tooling, which means in theory we could actually use the tooling that we are deploying. We can actually control it in the same way as our applications, because it’s just yet another object that goes in our cluster. [00:37:21] NL: That does sound pretty cool. One other that I meant to bring up was Concourse. Have you check out Concourse yet? [00:37:27] BL: CouncourseCI. I have not. I have used it, but never in a way where I would have a big opinion on it. [00:37:34] NL: I’m kind of in the same place. I think it’s a good idea. It seems really neat, but I need to kick the tires a little more. I will say that I really like the UI. The structure of the UI is really nice. Everything makes sense, and anything you can click on like drills into something a bit deeper. I think that’s pretty cool, but it is one of the shout that I went out to as well as like another tool that I’m aware of. [00:37:52] BL: Yeah, that’s pretty interesting. So we’ve gone about 40 minutes now. Let’s actually start winding this down, and the way that I’m going to suggest that we wind this down is thinking about where we are now. What’s missing in this space and what else could we actually be doing in the cloud native space to make this work out better? [00:38:12] NL: I think I’d like to see better structured or better examples of blue-green or canary deployments with tests associated, and that might just be like me not looking hard enough at this problem. But anytime I began looking at blue-green, I get the idea of what someone’s done, but I would love to see some implementation details, or any of these opinionated tools having opinions around blue-green and what they specifically do to test it. I feel like I’m just not seeing that. [00:38:41] BL: With blue-green, blue-green is hard to do in Kubernetes without an external tool, because for everyone, a blue-green deployment is, I have a software deployment and we’ll give it a color. We’ll call it blue, and I have the next version, and we’ll call it green. Really what I can do is I basically have two versions of my application deployed and I can use my load balancer, or in this case, my service to just change the label or the selector in my service and now I can point at at my green from my blue. Then I want to deploy again, I can just deploy another blue and then change my label selector again. The problem with this is that you can do it in Kubernetes, just fine. But out of the box with Kubernetes, you will drop traffic, because guess what? What happens to a connection that was initiated or a session that was initiated on the blue cluster when you went to green? Actually, this is a whole conversation in itself about service meshes and this is actually one of the reasons service mesh is a big topic, because you can do this blue-green, or another example would be Netflix and Redblack, or you get the creative people who are like rainbow deployments, because just having two is not good enough for them. So they want to have any number of deployments going at one time. I agree with that 100%. [00:39:57] JH: I think, yeah, integrating tools like launch. [inaudible 00:40:01] and I think there are more which enable – I think we’re missing the business abstractions on this stuff so far. Like you said, it’s kind of hard to do if you need to go into the gritty of it right now, but I think the business abstractions of if we deploy a different version to a certain subset of customers, can we get all of those metrics? Can we get those traces back in? Will you automate it, roll it out? Can we increase the percentage of customers that are seeing those things? Have that all controlled in a Kubernetes native way, but having roll it up to a business and more of an abstraction. I think that stuff is currently missing. I think the underpinning kind of technologies are coming up, stuff like service mesh, but I think it’s the abstraction that’s really going to make it useful, which doesn’t exist today. [00:40:39] BL: Yeah. Actually, that’s pretty close to what I was going to say. We built all these tooling that helps us basically as technologists, but really what it comes down to is the business. A lot of the things we’re talking about where we’re talking about CD is important to the business, but when we’re talking about metrics or trace collection, that’s not important to the business, because they only care about the SLA. This is on the SLO side. What we really need to do is mature our processes enough that we can actually marry our outputs to something that other people can understand that has no jargon and it’s sales going up, sales going down. Everything else is just a detail. So, anything else? [00:41:20] NL: Something I think I’d like to see is in our testing, if there was a good way to accurately show the effect of something at load in a CI/CD component. Because one of the things that I’ve run into is like I’ve got this great idea for how this code should work and when I deploy it, it works great. The like a thousand people touch it all at once and it doesn’t work right anymore. I’d love to have some tool along the way that can test things out of load and like show me something that I could fix before all those people touch it. [00:41:57] BL: Yes, that would be a good tool to have. So John, anything else for you? [00:42:02] JH: I’ll open a can of worms right at the end and say the biggest problem here is probably going to be data when we have a lot of systems we need to talk to each other and we need the data to align between those systems and we have now proliferation of environments and clusters. Like how do we get that data reliably into the place that it needs to be to make up testing robust enough to get things out there? It’s probably an episode on some – [00:42:23] BL: Yeah, that’s a big conversation that if we could answer it, we wouldn’t working at VMware. We would have our own companies doing all these great things. But we can definitely iterate on it. So with that, I think we’re going to wrap it up. Thanks for listening to the Kubelets. I’m Bryan Liles, and with me today was Nicholas Lane and John – Yeah, and John Harris. [00:42:47] JH: Thanks everyone. [00:42:47] BL: All right, we’ll see you next time. [END OF EPISODE] [00:42:50] ANNOUNCER: Thank you for listening to The Podlets Cloud Native Podcast. Find us on Twitter at https://twitter.com/ThePodlets and on the http://thepodlets.io/ website, where you'll find transcripts and show notes. We'll be back next week. Stay tuned by subscribing. [END]See omnystudio.com/listener for privacy information.

This week on The Podlets Cloud Native Podcast we have Josh, Carlisia, Duffie, and Nick on the show, and are also happy to be joined by a newcomer, Brian Liles, who is a senior staff engineer at VMWare! The purpose of today’s show is coming to a deeper understanding of the meaning of ‘stateful’ versus ‘stateless’ apps, and how they relate to the cloud native environment. We cover some definitions of ‘state’ initially and then move to consider how ideas of data persistence and co-ordination across apps complicate or elucidate understandings of ‘stateful’ and ‘stateless’. We then think about the challenging practice of running databases within Kubernetes clusters, which effectively results in an ephemeral system becoming stateful. You’ll then hear some clarifications of the meaning of operators and controllers, the role they play in mediating and regulating states, and also how important they are in a rapidly evolving but skills-scarce environment. Another important theme in this conversation is the CAP theorem or the impossibility of consistency, availability and partition tolerance all at once, but the way different databases allow for different combinations of two out of the three. We then move on to chat about the fundamental connection between workloads and state and then end off with a quick consideration about how ideas of stateful and stateless play out in the context of networks. Today’s show is a real deep dive offering perspectives from some the most knowledgeable in the cloud native space so make sure to tune in! Follow us: https://twitter.com/thepodlets Website: https://thepodlets.io Feeback: info@thepodlets.io https://github.com/vmware-tanzu/thepodlets/issues Hosts: Carlisia Campos Duffie Cooley Bryan Liles Josh Rosso Nicholas Lane Key Points From This Episode: • What ‘stateful’ means in comparison to ‘stateless’.• Understanding ‘state’ as a term referring to data which must persist.• Examples of stateful apps such as databases or apps that revolve around databases.• The idea that ‘persistence’ is debatable, which then problematizes the definition of ‘state’. • Considerations of the push for cloud native to run stateless apps.• How inter-app coordination relates to definitions of stateful and stateless applications.• Considering stateful data as data outside of a stateless cloud native environment.• Why it is challenging to run databases in Kubernetes clusters.• The role of operators in running stateful databases in clusters.• Understanding CRDs and controllers, and how they relate to operators.• Controllers mediate between actual and desired states.• Operators are codified system administrators.• The importance of operators as app number grows in a skill-scarce environment.• Mechanisms around stateful apps are important because they ensure data integrity.• The CAP theorem: the impossibility of consistency, availability, and tolerance.• Why different databases allow for different iterations of the CAP theorem.• When partition tolerance can and can’t get sacrificed.• Recommendations on when to run stateful or stateless apps through Kubernetes.• The importance of considering models when thinking about how to run a stateful app.• Varying definitions of workloads.• Pods can run multiple workloads• Workloads create states, so you can’t have one without the other.• The term ‘workloads’ can refer to multiple processes running at once.• Why the ephemerality of Kubernetes systems makes it hard to run stateful applications. • Ideas of stateful and stateless concerning networks.• The shift from server to browser in hosting stateful sessions. Quotes: “When I started envisioning this world of stateless apps, to me it was like, ‘Why do we even call them apps? Why don’t we just call them a process?’” — @carlisia [0:02:60] “‘State’ really is just that data which must persist.” — @joshrosso [0:04:26] “From the best that I can surmise, the operator pattern is the combination of a CRD plus a controller that will operate on events from the Kubernetes API based on that CRD’s configuration.” — @bryanl [0:17:00] “Once again, don’t let developers name them anything.” — @bryanl [0:17:35] “Data integrity is so important” — @apinick [0:22:31] “You have to really be careful about the different models that you’re evaluating when trying to think about how to manage a stateful application like a database.” — @mauilion [0:31:34] Links Mentioned in Today’s Episode: KubeCon+CloudNativeCon — https://events19.linuxfoundation.org/events/kubecon-cloudnativecon-north-america-2019/Google Spanner — https://cloud.google.com/spanner/CockroachDB — https://www.cockroachlabs.com/CoreOS — https://coreos.com/Red Hat — https://www.redhat.com/enMetacontroller — https://metacontroller.app/Brandon Philips — https://www.redhat.com/en/blog/authors/brandon-phillipsMySQL — https://www.mysql.com/ Transcript: EPISODE 009 [INTRODUCTION] [0:00:08.7] ANNOUNCER: Welcome to The Podlets Podcast, a weekly show that explores Cloud Native one buzzword at a time. Each week, experts in the field will discuss and contrast distributed systems concepts, practices, tradeoffs and lessons learned to help you on your cloud native journey. This space moves fast and we shouldn’t reinvent the wheel. If you’re an engineer, operator or technically minded decision maker, this podcast is for you. [INTERVIEW] [00:00:41] JR: All right! Hello, everybody, and welcome to episode 6 of The Cubelets Podcast. Today we are going to be discussing the concept of stateful and stateless and what that means in this crazy cloud native landscape that we all work. I am Josh Rosso. Joined with me today is Carlisia. [00:00:59] CC: Hi, everybody. [00:01:01] JR: We also have Duffie. [00:01:03] D: Hey, everybody. [00:01:04] JR: Nicholas. [00:01:05] NL: Yo! [00:01:07] JR: And a newcomer to the podcast, we also have Brian. Brian, you want to give us a little intro about yourself? [00:01:12] BL: Hi! I’m Brian. I work at VMWare. I do lots of community stuff, including sharing the KubeCon+CloudNativeCon. [00:01:22] JR: Awesome! Cool. All right. We’ve got a pretty good cast this week. So let’s dive right into it. I think one of the first things that we’ve been talking a bit about is the concept of what makes an application stateful? And of course in reverse, what makes an application stateless? Maybe we could try to start by discerning those two. Maybe starting with stateless if that makes? Does someone want to take that on? [00:01:45] CC: Well, I’m going to jump right in. I have always been a developer, as supposed to some of you or all of you have who have system admin backgrounds. The first time that I heard the stateless app, I was like, “What?” That wasn’t recent, okay? It was a long time ago, but that was a knot in my head. Why would you have a stateless app? If you have an app, you’re going to need state. I couldn’t imagine what that was. But of course it makes a lot of sense now. That was also when we were more in the monolithic world. [00:02:18] BM: Actually that’s a good point. Before you go into that, it’s a great point. Whenever we start with apps or we start developing apps, we think of an application. An application does everything. It takes input and it does stuff and it gives output. But now in this new world where we have lots of apps, big apps, small apps, we start finding that there’s apps that only talk and coordinate with other apps. They don’t do anything else. They don’t save any data. They don’t do anything. That’s what – where we get into this thing called stateless apps. Apps don’t have any type of data that they store locally. [00:02:53] CC: Yeah. It’s more like when I envision in my head. You said it brilliantly, Brian. It’s almost like a process. When I started envisioning this world of stateless apps, to me it was like, “Why do we even call them apps? Why don’t we just call them a process?” They’re just shifting back data and forth but they’re not – To me, at the beginning, apps were always stateless. They went together. [00:03:17] D: I think, frequently, people think of applications that have only locally relevant stuff that is actually not going to persist to disc, but maybe held in memory or maybe only relevant to the type of connection that’s coming through that application also as stateless, which is interesting, because there’s still some state there, but the premise is that you could lose that state and not lose the functionality of that code. [00:03:42] NL: Something that we might want to dive into really quickly when talking about stateless and stateful apps. What do we mean by the word state? When I first learned about these things, that was what always screwed me up. I’m like, “What do you mean state? Like Washington? Yeah. We got it over here.” [00:03:57] JR: Oh! State. That’s that word. State is one of those words that we use to sound smarter than we actually are 95% of the time, and that’s a number I just made up. When people are talking about state, they mean databases. Yeah. But there are other types of state as well. If you maintain local cache that needs to be persistent, if you have local files that you’re dealing with, like you’re opening files. That’s still state. State really is just that it’s data that must persist. [00:04:32] D: I agree with that definition. I think that state, whether persisted to memory or persisted to disc or persisted to some external system, that’s still what we refer to as state. [00:04:41] JR: All right. Makes sense and sounds about like what I got from it as well. [00:04:45] CC: All right. So now we have this world where we talk about stateless apps and stateful apps. Are there even stateful apps? Do we call a database an app? If we have a distributed system where we have one stateless app over here, another stateless app over there and then we have the database that’s connected to the two of them, are we calling the database a stateful app or is that whole thing – How do we call this? [00:05:15] NL: Yeah. The database is very much a state as an app with state. I’m very much – [00:05:19] D: That’s a close definition. Yeah. [00:05:21] NL: Yeah. Literally, it’s the epitome of a stateful app. But then you also have these apps that talk to databases as well and they might have local data, like data that – they start a transaction and then complete it or they have a long distributed type transaction. Any apps that revolve around a database, if they store local data, whether it’s within a transaction or something else, they’re still stateful apps. [00:05:46] D: Yup. I think you can modify and input data or modify state that has to be persisted in some way I think is a stateful app, even though I do think it’s confusing because of what – As I said before, I think that there are a bunch of applications that we think of, like not everybody considers Spark jobs to be stateful. Spark jobs, for example, are something that would bring data in, mutate that data in some way, produce some output and go away. The definition there is that Spark would generally push the resulting data into some other external system. It’s interesting, because in that model, Spark is not considered to be a stateful app because the Spark job could fail, go away, get recreated, pick up the pieces where it left off or just redo that work until all of the work is done. In many cases, people consider that to be a stateless application. That’s I think is like the crux – In my opinion, the crux of the confusion around what a stateful and stateless application is, is that people frequently – I think it’s more about where you store – what you mean by persistence and how that actually realizes in your application. If you’re pushing your state to an external database, is your application still stateful? [00:06:58] NL: I think it’s a good question, or if you are gathering data from an external source and mutating it in some way, but you don’t need data to be present when you start up, is that a stateful app or a stateless app? Even though you are taking in data, modifying it and checking it, sending out to some other mechanism or serving it in your own way, does that become like a stateless app? If that app gets killed and it comes back and it’s able to recover, is it stateful or stateless? That’s a bit of a gray area, I think. [00:07:26] JR: Yeah. I feel like a lot of the customers I work with, if the application can get killed even if it has some type of local state, they still refer to it as stateless usually, to me at least, when we talk about it because they think, “I can kind of restart this application and I’m not too worried about losing whatever it may have had.” Let’s say cached for simplicity, right? I think that kind of leads us into an interesting question. We’ve talked a lot on this podcast about cloud native infrastructure and cloud native applications and it seems like since the inception of cloud native, there’s always been this push that a stateless app is the best candidate to run or the easiest candidate to run. I’m just curious if we could dive into that for a moment. Why in the cloud native infrastructure area has there always been this push for running stateless applications? Why is it simpler? Those kinds of things. [00:08:15] BL: Before we dive into that, we have to realize – And this is just a problem of our whole ecosystem, this whole cloud native. We’re very hand-wavy in our descriptions for things. There’re a lot of ambiguous descriptions, and state is one of those. Just keep that in mind, that when we’re talking today, we’re really just talking about these things that store data and when that’s the state. Just keep that in mind as you’re listening to this. But when it comes to distributed systems in general, the easiest system is a system that doesn’t need coordination with any other system. If it happens to die, that’s okay. We can just restart it. People like to start there. It’s the easiest thing to start. [00:08:58] NL: Yeah, that was basically what I was going to say. If your application needs to tie into other applications, it becomes significantly more complicated to implement it, at least for your first time and in your system. These small applications that only – They don’t care about anybody else, they just take in data or not, they just do whatever. Those are super easy to start with because they’re just like, “Here. Start this up. Who cares? Whatever happens, it happens.” [00:09:21] CC: That could be a good boundary to define – I don’t want to jump back too far, but to define where is the stateless app to me is part of a system and just say it depends for it to come back up. Does it depend on something else that has state? [00:09:39] BL: I’ll give you an example. I can give you a good example of a stateless app that we use every day, every single one of us, none of us on this call, but when you search Google. You go to google.com and you go to the bar and you type in a search, what’s happening is there is a service at the beginning that collects that search and it federates the search over many different probably clusters of computers so they can actually do the search currently. That app that actually coordinates all that work is a stateless app most likely. All it does is just splits it up and allows more CPUs to do the work. Probably, that goes away. Probably not a problem. You probably have 10 more of them. That’s what I consider stateless. It doesn’t really own any of the data. It’s the coordinator. [00:10:25] CC: Yeah. If it goes down, it comes back up. It doesn’t need to reset itself to the state where it was before. It can truly be considered a stateless because it can just, “Okay. I reset. I’m starting from the beginning from this clear state.” [00:10:43] BL: Yes. That’s a good summary of that. [00:10:45] CC: Because another way to think about stateless – What makes an app stateful app, does it have to be combined or like deployed and shipped together with the part that maintains the state? That’s a more clear cut definition. Then that app is definitely a stateful app. [00:11:05] D: What we frequently talk about in like the cloud native space is like you know that you have a stateless app if you can just create 20 of them and not have to worry about the coordination of them. They are all workers. They are all going to take input. You could spread the load across those 20 in an identical way and not worry about which one you landed on. That’s stateless application. A stateful application is a very different thing. You have to have some coordination. You have to say how many databases can you have on a backend? Because you’re persisting data there, you have to be really careful about that you only write to the master database or to the writing database and you could read of any other memories of that database cluster, that sort of stuff. [00:11:44] CC: It might seem that we are going so deep into this differentiating between stateful and stateless, but this is so important because clusters are usually designed to be ephemeral. Ephemeral means obviously they die down, they are brought back up, the nodes, and you should worry as least as possible with the state of things. Then going back to what Joshua is saying, when we are in this cloud native world, usually we are talking about stateless apps, stateless workloads and then we’re going to just talk about what workload means. But then if that’s the case, where are the stateful apps? It’s like we have this vision that the stateful apps live outside the cloud native world? How does it work? But it’s supposed to work. [00:12:36] BL: Yup. This is the question that keeps a lot of people employed. Making sure my state is available when I need it. You know what? I’m not going to even use that word state. Making sure my data is available wherever I need it and when I need it. I don’t want to go too deep in right now, but this is actually a huge problem in the Kubernetes community in general, and we see it because there’s been lots of advice given, “Don’t run things like databases in your clusters.” This is why we see people taking the ideas of Google Spanner and like CockroachDB and actually going through a lot of work to make sure that you can run databases in Kubernetes clusters. The interesting piece about this is that we’re actually to the point where we can run these types of workloads in our clusters, but with a caveat, big star at the end, it’s very difficult and you have to know what you’re doing. [00:13:34] JR: Yeah. I want to dovetail on that Brian, because it’s something that we see all the time. I feel like when we first started setting up, let’s call them clusters, but in our case it was Kubernetes, right? We always saw that data level always being delegated to like if you’re in Amazon, some service that they hosted and so on. But now I think more and more of the customers that at least I’m seeing. I’m sure Nicholas and Duffie too, they’re interested in doing exactly what you just described. Cockroach is an example I literally just worked with recently, and it’s just interesting how much more thoughtful they have to be about their cluster operations. Going back to what you said Carlisia, it’s not as easy as just like trashing a cluster and instantiating a new one anymore, like they’re used to. They need to be more thoughtful about keeping that data integrity intact through things like upgrades and disaster recover. [00:14:18] D: Another interesting point kind to your point, Brian, is that like, frequently, people are starting to have conversations and concerns around data gravity, which means that I have a whole bunch of data that I need to work with, like to a Spark job, which I mentioned earlier. I need to basically put my compute where that data is. The way that I store that data inside the cluster and use Kubernetes to manage it or whether I just have to make sure that I have some way of bringing up compute workloads close to that data. It’s actually kind of introducing a whole new layer to this whole thing. [00:14:48] BL: Yeah! Whole new layer of work and a whole new layer of complexity, because that’s actually – The crux of all this is like where we slide the complexity too, but this is interesting, and I don’t want to go too far to this one definitely. This is why we’re seeing more people creating operators around managing data. I’ve seen operators who are bringing databases up inside of Kubernetes. I’ve seen operators that actually can bring up resources outside of Kubernetes using the Kubernetes API. The interesting thing about this is that I looked at both solutions and I said, “I still don’t know what the answer is,” and that’s great. That means that we have a lot to learn about the problem, and at least we have some paths for it. [00:15:29] NL: Actually, that kind of reminds me of the first time I ever heard the word stateful or stateless – I’m an infrastructure guy. Was around the discussion of operators, which there’s only a couple of years ago when operators were first introduced at CoreOS and some people were like, “Oh! Well, this is how you now operate a stateful mechanism inside of Kubernetes. This is the way forward that we want to propose.” I was just like, “Cool! What is that? What’s state? What do you mean stateful and stateless?” I had no idea. Josh, you were there. You’re like, “Your frontend doesn’t care about state and your backend does.” I’m like, “Does it? I don’t know. I’m not a developer.” [00:16:10] JR: Let’s talk about exactly that, because I think these patterns we’re starting to see are coming out of the needs that we’re all talking about, right? We’ve seen at least in the Kubernetes community a lot of push for these different constructs, like something called a stateful [inaudible 00:16:21], which isn’t that important right now, but then also like an operator. Maybe we can start by defining what is an operator? What is that pattern and why does it relate to stateful apps? [00:16:31] CC: I think that would be great. I am not clear what an operator is. I know there’s going to be a controller involved. I know it’s not a CRD. I am not clear on that at all, because I only work with CRDs and we don’t define – like the project I worked on with Velero, we don’t categorize it as an operator. I guess an operator uses specific framework that exists out there. Is it a Kubernetes library? I have no idea. [00:16:56] BL: We did it to ourselves again. We’re all doing these to ourselves. From the best that I can surmise, the operator pattern is the combination of a CRD plus a controller that will operate on events from the Kubernetes API based on that CRD’s configuration. That’s what an operator is. [00:17:17] NL: That’s exactly right. [00:17:18] BL: To conflate this, Red Hat created the operator SDK, and then you have [inaudible 00:17:23] and you have a Metacontroller, which can help you build operators. Then we actually sometimes conflate and call CRDs operators, and that’s pretty confusing for everyone. Once again, don’t let developers name anything. [00:17:41] CC: Wait. So let’s back up a little. Okay. There is an actual library that’s called an operator. [00:17:46] BL: Yes. There’s an operator SDK. [00:17:47] CC: Referred to as an operator. I heard that. Okay. Great. But let me back up a little because – [00:17:49] D: The word operator can [00:17:50] CC: Because if you are developing an app for Kubernetes, if you’re extending Kubernetes, you are – Okay, you might not use CRDs, but if you are using CRDs, you need a controller, right? Because how will you do actions? Then every app that has a CRD – because the alternative to having CRDs is just using the API directly without creating CRDs to reflect to resources. If you’re creating CRDs to reflect to resources, you need controllers. All of those apps, they have CRDs, are operators. [00:18:24] D: Yip [inaudible 00:18:25] is an operator. [00:18:26] CC: [inaudible 00:18:26] not an operator. How can you extend Kubernetes and not be qualified [inaudible 00:18:31] operator? [00:18:32] BL: Well, there’s a way. There is a way. You can actually just create a CRD and use a CRD for data storage, you know, store states, and you can actually query the Kubernetes API for that information. You don’t need a controller, but we couple them with controllers a lot to perform action based on that state we’ve saved to etcd. [00:18:50] CC: Duffie. [00:18:51] D: I want to back up just for a moment and talk about the controller pattern and what it is and then go from there to operators, because I think it makes it easier to get it in your head. A control pattern is effectively a way to understand desired state and real state and provide some logic or business code that will allow you to converge those two states, your actual state and your desired state. This is a pattern that we see used in almost everything within a distributed system. It’s like within Kubernetes, within most of the kind of more interesting systems that are out there. This control pattern describes a pretty good way of actually managing application flow across distributed systems. Now, operators, when they were initially introduced, we were talking about that this is a slightly different thing. Operators, when we introduced the idea, came more from like the operational burden of these stateful applications, things like databases and those sorts of stuff. With the database, etcd for example, you have a whole bunch of operational and runtime concerns around managing the lifecycle of that system. How do I add a new member to the cluster? What do I do when a member dies? How do I take action? Right now, that’s somebody like myself waking up at 2 in the morning and working through a run book to basically make sure that that service remains operational through the night. But the idea of an operator was to take that control pattern that we described earlier and make it wake up at 2 in the morning to fix this stuff. We’re going to actually codify the operational knowledge of managing the burden of these stateful applications so that we don’t have to wake up at 2 in the morning and do it anymore. Nobody wants to do that. [00:20:32] BL: Yeah. That makes sense. Remember back at KubCon years ago, I know it was one in Seattle where Brandon Philips was on stage talking about operators. He basically was saying if we think about SysOp, system operators, it was a way to basically automate or capture the knowledge of our system administrators in scripts or in a process or in code a la operators. [00:20:57] D: The last part that I’ll add to this thing, which I think is actually what really describes the value of this idea to me is that there are only so many people on the planet that do what the people in this blog post do. Maybe you’re one of them that listen to this podcast. People who are operating software or operating infrastructure at scale, there just aren’t that many of us on the planet. So as we add more applications, as more people adopt the cloud native regime or start coming to a place where they can crank out more applications more quickly, we’re going to have to get to a place where we are able to automate the burden of managing those applications, because there just aren’t enough of us to be able to support the load that is coming. There just aren’t enough people on the planet that do this to be able to support that. That’s the thing that excites me most about the operator pattern, is that it gives us a place to start. It gives us a place to actually start thinking about managing that burden over time, because if we don’t start changing the way we think about managing that burden, we’re going to run out of people. We’re not going to be able to do it. [00:22:05] NL: Yeah. It’s interesting. With stateful apps, we keep kind of bringing them – coming back to stateful apps, because stateful apps are hard and stateless apps are easy, and we’ve created all these mechanisms around operating things with state because of how just complicated it is to make sure that your data is ready, accessible and has integrity. That’s the big one that I keep not thinking about as a SysOps person coming into the Dev world. Data integrity is so important and making sure that your data is exactly what it needs to be and was the last time you checked it, is super important. It’s only something I’m really starting to grasp. That’s why I was like these things, like operators and all these mechanisms that we keep creating and recreating and recreating keep coming about, because making sure that your stateful apps have the right data at the right time is so important. [00:22:55] BL: Since you brought this up, and we just talked about why a state is so hard, I want to introduce the new term to this conversation, the whole CAP theorem, where data would typically be – in a distributed system at least, your data will be consistent or your data can be available, or if your distributed systems falls in multiple parts, you can have partition tolerance. This is one of those computer science things where you can actually pick two. You can have it be available and have partition tolerance, but your data won’t be consistent, or you can have consistency and availability, but you won’t have partition tolerance. If your cluster splits into two for some reason, the data will be bad. This is why it’s hard, this is why people have written basically lots of PhD dissertations on this subject, and this is why we are talking about this here today, is because managing state, and particularly managing distributed, is actually a very, very hard problem. But there’s software out there that will help us, and Kubernetes is definitely part of that and stateful sets are definitely part of that as well. [00:24:05] JR: I was just going to say on those three points, consistently, availability and partition tolerance. Obviously, we’d want all three if we could have them. Is there one that we most commonly tradeoff and give up or does it go case-by-case? [00:24:17] BL: Actually, it’s been proven. You can’t have all three. It’s literally impossible. It depends. If you have a MySQL server and you’re using MySQL to actually serve data out of this, you’re going to most likely get consistency and availability. If you have it replicated, you might not have partition tolerance. That’s something to think about, and there are different databases and this is actually one of the reasons why there are different databases. This is why people use things like relational databases and they use key value stores not because we really like the interfaces, but because they have different properties around the data. [00:24:55] NL: That’s an interesting point and something that I had recently just been thinking about, like why are there so many different types of databases. I just didn’t know. It was like in only recently heard of CAP theorem as well just before you mentioned it. I’m like, “Wow! That’s so fascinating.” The whole thing where you only pick two. You can’t get three. Josh, to kind of go back to your question really quickly, I think that partition tolerance is the one that we throw away the most. We’re willing to not be able to segregate our database as much as possible because C and A are just too important, I think. At least that’s what I’m saying, like I am wearing an [inaudible 00:25:26] shirt and [inaudible 00:25:27] is not partition tolerant. It’s bad at it. [00:25:31] BL: This is why Google introduced Spanner, and Spanner in some situations can get free with tradeoffs and a lot of really, really smart stuff, but most people can’t run this scale. But we do need to think about partition tolerance, especially with data whenever – Let’s say you run a store and you have multiple instances across the world and someone buys something from inventory, what is your inventory look like at any particular point? You don’t have to answer my question, of course, but think about that. These are still very important problems if fiber gets cut across the Atlantic and now I’ve sold more things than I have. Carlisia, speaking to you as someone who’s only been a developer, have you moved your thoughts on state any further? [00:26:19] CC: Well, I feel that I’m clear on – Well, I think you need to clarify your question better for me. If you’re asking if I understand what it means, I understand what it means. But I actually was thinking to ask this question to all of you, because I don’t know the answer, if that’s the question you’re asking me. I want to put that to the group. Do you recommend people, as in like now-ish, to run stateful workloads? We need to talk about workloads mean. Run stateful apps or database in sites if they’re running a Kubernetes cluster or if they’re planning for that, do you all as experts recommend that they should already be looking into doing that or they should be running for now their stateful apps or databases outside of the cloud native ecosystem and just connecting the two? Because if that’s what your question was, I don’t know. [00:27:21] BL: Well, I’ll take this first. I think that we should be spending lots of more time than we are right now in coming up community-tested solutions around using stateful sets to their best ability. What that means is let’s say if you’re running a database inside of Kubernetes and you’re using a stateful set to manage this, what we do need to figure out is what happens when my database goes down? The pod just kills? When I bring up a new version, I need to make sure that I have the correct software to verify integrity, rebuilt things, so that when it comes back up, it comes back up correctly. That’s what I think we should be doing. [00:27:59] JR: For me, I think working with customers, at least Kubernetes-oriented folks, when they’re trying to introduce Kubernetes as their orchestration part of their overall platform, I’m usually just trying to kind of meet them where they’re at. If they’re new to Kubernetes and distributed systems as a whole, if we have stateless, let’s call them maybe simpler applications to start with, I generally have them lean into that first, because we already have so much in front of us to learn about. I think it was either Brian or Duffie, you said it introduces a whole bunch more complexity. You have to know what you’re doing. You have to know how to operate these things. If they’re new to Kubernetes, I generally will advise start with stateless still. But that being said, so many of our customers that we work with are very interested in running stateful workloads on Kubernetes. [00:28:42] CC: But just to clarify what you said, Josh, because you spoke like an expert, but I still have beginner’s ears. You said something that sounded to me like you recommend that you go stateless. It sounded to me like that. What you really say is that they take out the stateless part of what they have, which they might already have or they might have to change and put the stateless. You’re not suggesting that, “Oh! You can’t do stateful anymore. You need to just do everything stateless.” What you’re saying is take the stateless part of your system, put that in Kubernetes, because that is really well-tested and keep the stateful outside of that ecosystem. Is that right? [00:29:27] JR: I think that’s a better way to put it. Again, it’s not that Kubernetes can’t do stateful. It’s more of a concept of biting off more than you can chew. We still work with a lot of people who are very new to these distributed systems concepts, and to take on running stateful workloads, if we could just delegate that to some other layer, like outside of the cluster, that could be a better place to start, at least in my experience. Nicholas and Duff might have different – [00:29:51] NL: Josh, you basically nailed it like what I was going to say, where it’s like if the team that I’m working with is interested in taking on the complexity of maintaining their databases, their stateful sets and making sure that they have data integrity and availability, then I’m all for them using Kubernetes for a stateful set. Kubernetes can run stateful applications, but there is all this complexity that we keep talking about and maintaining data and all that. If they’re willing to take on their complexity, great, it’s there for you. If they’re not, if they’re a little bit kind of behind as – Not behind, but if they’re kind of starting out their Kubernetes journey or their distributed systems journey, I would recommend them to move that complexity to somebody else and start with something a little bit easier, like a stateless application. There are a lot of good services that provide data as a service, right? You’ve got dataview as RDS is great for creating stateful application. You can leverage it anytime and you’ve got like dedicated wires too. I would point them to there first if they don’t want to take on like complexity. [00:30:51] D: I completely agree with that. An important thing I would add, which is in response to the stateful set piece here, is that as we’ve already described, managing a stateful application like a database does come with some complexity. So you should really carefully look at just what these different models provide you. Whether that model is making use of a stateful set, which provides you like ordinality, ensuring that things start up in a particular order and some of the other capabilities around that stuff. But it won’t, for example, manage some of the complexity. A stateful set won’t, for example, try and issue a command to the new member to make sure that it’s part of an existing database cluster. It won’t manage that kind of stuff. So you have to really be careful about the different models that you’re evaluating when trying to think about how to manage a stateful application like a database. I think because it’s actually why the topic of an operator came up kind of earlier, which was that like there are a lot of primitives within Kubernetes in general that provide you a lot of capability for managing things like stateful applications, but they may not entirely suit your needs. Because of the complexity with stateful applications, you have to really kind of be really careful about what you adopt and where you jump in. [00:32:04] CC: Yeah. I know just from working with Velero, which is a tool for doing backup and recovery migration of Kubernetes clusters. I know that we backup volumes. So if you have something mounted on a volume, we can back that up. I know for a fact that people are using that to backup stateful workloads. We need to talk about workloads. But at any case, one thing to – I think one of you mentioned is that you definitely also need to look at a backup and recovery strategy, which is ever more important if you’re doing stateful workloads. [00:32:46] NL: That’s the only time it’s important. If you’re doing stateless, who cares? [00:32:49] BL: Have we defined what a workload is? [00:32:50] CC: Yeah. But let me say something. Yeah, I think we should do an episode on that maybe, maybe not. We should do an episode on GitOps type of thing for related things, because even though you – Things are stateless, but I don’t want to get into it. Your cluster will change state. You can recover in stuff from like a fresh version. But as it goes through a lifecycle, it will change state and you might want to keep that state. I don’t know. I’m not the expert in that area, but let’s talk about workloads, Brian. Okay. Let me start talking about workloads. I never heard the term workload until I came into the cloud native world, and that was about a year ago or when they started looking in this space more closely. Maybe a little bit before a year ago. It took me forever to understand what a workload was. Now I understand, especially today, we’re talking about a little bit before we started recording. Let me hear from you all what it means to you. [00:34:00] BL: This is one of those terms, and I’m sure like the last any ex-Googlers about this, they’ll probably agree. This is a Google term that we actually have zero context about why it’s a term. I’m sure we could ask somebody and they would tell us, but workloads to me personally are anything that ultimately creates a pod. Deployments create replica sets, create pods. That whole thing is a workload. That’s how I look at it. [00:34:29] CC: Before there were pods, were there workloads, or is a workload a new thing that came along with pods? [00:34:35] BL: Once again, these words don’t make any sense to us, because they’re Google terms. I think that a pod is a part of a workload, like a deployment is a part of a workload, like a replica set is part of a workload. Workload is the term that encompasses an entire set of objects. [00:34:52] D: I think of a workload as a subset of an application. When I think of an application or a set of microservices, I might think of each of the services that make up that entire application as a workload. I think of it that way because that’s generally how I would divide it up to Brian’s point into different deployment or different stateful sets or different – That sort of stuff. Thinking of them each as their own autonomous piece, and altogether they form an application. That’s my think of it. [00:35:20] CC: To connect to what Brian said, deployment, will always run in the pods, which is super confusing if you’re not looking at these things, just so people understand, because it took me forever to understand that. The connection between a workload, a deployment and a pod. Pods contain – If you have a deployment that you’re going to shift Kubernetes – I don’t know if shift is the right word. You’re going to need to run on Kubernetes. That deployment needs to run somewhere, in some artifact, and that artifact is called a pod. [00:35:56] NL: Yeah. Going back to what Duffie said really quickly. A workload to me was always a process, kind of like not just a pod necessarily, but like whatever it is that if you’re like, “I just need to get this to run,” whatever that is. To me that was always a workload, but I think I’m wrong. I think I’m oversimplifying it. I’m just like whatever your process is. [00:36:16] BL: Yeah. I would give you – The reason why I would not say that is because a pod can run multiple containers at once, which ergo is multiple processes. That’s why I say it that way. [00:36:29] NL: Oh! You changed my mind. [00:36:33] BL: The reason I bring this up, and this is probably a great idea for a future show, is about all the jargon and terminology that we use in this land that we just take as everyone knows it, but we don’t all know it, and should be a great conversation to have around that. But the reason I always bring up the whole workload thing is because when we think about workloads and then you can’t have state without workloads, really. I just wanted to make sure that we tied those two things together. [00:36:58] CC: Why can you not have state without workloads? What does that mean? [00:37:01] BL: Well, the reason you can’t have state without workloads is because something is going to have to create that state, whether that workload is running in or out a cluster. Something is going to have to create it. It just doesn’t come out of nowhere. [00:37:11] CC: That goes back to what Nick was saying, that he thinks a workload is a process. Was that was you said, Nick? [00:37:18] NL: It is, yeah, but I’m renegading on that. [00:37:23] CC: At least I could see why you said that. Sorry, Brian. I cut you off. [00:37:28] BL: What I was saying is a workload ultimately is one or more processes. It’s not just a process. It’s not a single process. It could be 10, it could be 1. [00:37:39] JS: I have one final question, and we can bail on this and edit it out if it’s not a good one to end with. I hope it’s not too big, but I think maybe one thing we overlooked is just why it’s hard to run stateful workloads in these new systems like Kubernetes. We talked about how there’s more complexity and stuff, but there might be some room to talk about – People have been spinning up an EC2 server, a server on the web and running MySQL on it forever. Why in like the Kubernetes world of like pods and things is it a little bit harder to run, say, MySQL just [inaudible 00:38:10]. Is that something worth diving into? [00:38:13] NL: Yeah, I think so. I would say that for things like, say, applications, like databases particularly, they are less resilient to outages. While Kubernetes itself is dedicated to – Or most container orchestrations, but Kubernetes specifically, are dedicated to running your pods continuously as long as they will, that it is still somewhat of a shifting landscape. You do have priority and preemption. If you don’t set those things up properly of if there’s just like a total failure of your system at large, your stateful application can just go down at any time. Then how do you reconcile the outage in data, whatever data that might have gotten lost? Those sorts of things become significantly more complicated in an environment like Kubernetes where you don’t necessarily have access to a command line to run the commands to recover as easy. You may not, but it’s the same. [00:39:01] BL: Yes. You got to understand what databases do. Disk is slow, whether you have spinning disk or you have disk on chip, like SSD. What databases do in a lot of cases is they store things in memory. So if it goes away, didn’t get stored. In other cases, what databases do is they have these huge transactional logs, maybe they write them out in files and then they process the transaction log whenever they have CPU time. If a database dies just suddenly, maybe its state is inconsistent because it had items that were to be processed in a queue that haven’t been processed. Now it doesn’t know what’s going on, which is why – [00:39:39] NL: That’s interesting. I didn’t know that. [00:39:40] BL: If you kill MySQL, like kill MySQL D with a -9, why it might not come back up. [00:39:46] JR: Yeah. Going back to Kubernetes as an example, we are living in this newer world where things can get rescheduled and moved around and killed and their IPs changed and things. It seems like this environment is, should I say, more ephemeral, and those types of considerations becoming to be more complex. [00:40:04] NL: I think that really nails it. Yeah. I didn’t know that there were transactional logs about databases. I should, I feel like, have known that but I just have no idea. [00:40:11] D: There’s one more part to the whole stateful, stateless thing that I think is important to cover, but I don’t know if we’ll be able to cover it entirely in the time that we have left, and that is from the network perspective. If you think about the types of connections coming into an application, we refer to some of those connections as stateful and stateless. I think that’s something we could tackle in our remaining time, or what’s everybody’s thought? [00:40:33] JR: Why don’t you try giving us maybe a quick summary of it, Duffie, and then we can end on that. [00:40:36] CC: Yeah. I think it’s a good idea to talk about network and then address that in the context of network. I’m just thinking an idea for an episode. But give us like a quick rundown. [00:40:45] D: Sure. A lot of the kind of older monolithic applications, the way that you would scale these things is you would have multiple of them and then you would have some intelligence in the way that you’re routing connections down to those applications that would describe the ability to ensure that when Bob accesses a website and he authenticates, he’s going to authenticate to one specific instance of this application and the intelligence up in the frontend is going to handle the routing to make sure that Bob’s connection always comes back to that same instance. This is an older pattern. It’s been around for a very long time and it’s certainly the way that we first kind of learned to scale applications before we’ve decided to break into maker services and kind of handle a lot of this routing in a more resilient way. That was kind of one of the early versions of how we do this, and that is a pretty good example of a stateful session, and that there is actually some – Perhaps Bob has authenticated and he has a cookie that allows him, that when he comes back to that particular application, a lot of the settings, his browser settings, whether he’s using the dark theme or the light theme, that sort of stuff, is persisted on the server side rather than on the client side. That’s kind of what I mean by stateful sessions. Stateless sessions mean it doesn’t really matter that the user is terminating to the same end of point, because we’ve managed to keep the state either with the client. We’re handling state on the browser side of things rather on the server side of things. So you’re not necessarily gaining anything by pushing that connection back to the same specific instance, but just to a service that is more widely available. There are lots of examples of this. I mean, Brian’s example of Google earlier. Obviously, when I come back to Google, there are some things I want it to remember. I want it to remember that I’m logged in as myself. I want it to remember that I’ve used a particular – I want it to remember my history. I want it to remember that kind of stuff so that I could go back and find things that I looked at before. There are a ton of examples of this when we think about it. [00:42:40] JR: Awesome! All right, everyone. Thank you for joining us in episode 6, Stateful and Stateless. Signing off. I’m Josh Rosso, and going across the line, thank you Nicholas Lane. [00:42:54] NL: Thank you so much. This was really informative for me. [00:42:56] JR: Carlisia Campos. [00:42:57] CCC: This was a great conversation. Bye, everybody. [00:42:59] JR: Our new comer, Brian Liles. [00:43:01] BL: Until next time. [00:43:03] JR: And Duffie Cooley. [00:43:05] DCC: Thank you so much, everybody. [00:43:06] JR: Thanks all. [00:43:07] CCC: Bye! [END OF EPISODE] [0:50:00.3] ANNOUNCER: Thank you for listening to The Podlets Cloud Native Podcast. Find us on Twitter at https://twitter.com/ThePodlets and on the http://thepodlets.io/ website, where you'll find transcripts and show notes. We'll be back next week. Stay tuned by subscribing. [END]See omnystudio.com/listener for privacy information.

Today on the show we have esteemed Kubernetes thought-leader, Kelsey Hightower, with us. We did not prepare a topic as we know that Kelsey presents talks and features on podcasts regularly, so we thought it best to pick his brain and see where the conversation takes us. We end up covering a mixed bag of super interesting Kubernetes related topics. Kelsey begins by telling us what he has been doing and shares with us his passion for learning in public and why he has chosen to follow this path. From there, we then talk about the issue of how difficult many people still think Kubernetes is. We discover that while there is no doubting that it is complicated, at one point, Linux was the most complicated thing out there. Now, we install Linux servers without even batting an eyelid and we think we can reach the same place with Kubernetes in the future if we shift our thinking! We also cover other topics such as APIs and the debates around them, common questions Kelsey gets before finally ending with a brief discussion on KubeCon. From the attendance and excitement, we saw that this burgeoning community is simply growing and growing. Kelsey encourages us all to enjoy this spirited community and what the innovation happening in this space before it simply becomes boring again. Tune in today! Follow us: https://twitter.com/thepodlets Website: https://thepodlets.io Feeback: info@thepodlets.io https://github.com/vmware-tanzu/thepodlets/issues Hosts: Carlisia Campos Duffie Cooley Bryan Liles Michael Gasch Key Points From This Episode: Learn more about Kelsey Hightower, his background and why he teaches Kubernetes! The purpose of Kelsey’s course, Kubernetes the Hard Way. Why making the Kubernetes cluster disappear will change the way Kubernetes works. There is a need for more ops-minded thinking for the current Kubernetes problems. Find out why Prometheus is a good example of ops-thinking applied to a system. An overview of the diverse ops skillsets that Kelsey has encountered. Being ops-minded is just an end –you should be thinking about the next big thing! Discover the kinds of questions Kelsey is most often asked and how he responds. Some interesting thinking and developments in the backup space of Kubernetes. Is it better to backup or to have replicas? If the cost of losing data is very high, then backing up cannot be the best solution. Debates around which instances are not the right ones to use Kubernetes in. The Kubernetes API is the part everyone wants to use, but it comes with the cluster. Why the Kubernetes API is only useful when building a platform. Can the Kubernetes control theory be applied to software? Protocols are often forgotten about when thinking about APIs. Some insights into the interesting work Akihiro Suda’s is doing. Learn whether Kubernetes can run on Edge or not. Verizon: how they are changing the Edge game and what the future trajectory is. The interesting dichotomy that Edge presents and what this means. Insights into the way that KubeCon is run and why it’s structured in the way it is. How Spotify can teach us a lesson in learning new skills! Quotes: “The real question to come to mind: there is so much of that work that how are so few of us going to accomplish it unless we radically rethink how it will be done?” — @mauilion [0:06:49] “If ops were to put more skin in the game earlier on, they would definitely be capable of building these systems. And maybe they even end up more mature as more operations people put ops-minded thinking into these problems.” — @kelseyhightower [0:04:37] “If you’re in operations, you should have been trying to abstract away all of this stuff for the last 10 to 15 years.” — @kelseyhightower [0:12:03] “What are you backing up and what do you hope to restore?” — @kelseyhightower [0:20:07] “Istio is a protocol for thinking about service mesh, whereas Kubernetes provides the API for building such a protocol.” — @kelseyhightower [0:41:57] “Go to sessions you know nothing about. Be confused on purpose.” — @kelseyhightower [0:51:58] “Pay attention to the fundamentals. That’s the people stuff. Fundamentally, we’re just some people working on some stuff.” — @kelseyhightower [0:54:49] Links Mentioned in Today’s Episode: The Podlets on Twitter — https://twitter.com/thepodlets Kelsey Hightower — https://twitter.com/kelseyhightower Kelsey Hightower on GitHub — https://github.com/kelseyhightower Interaction Protocols: It's All about Good Manners — https://www.infoq.com/presentations/history-protocols-distributed-systems Akihiro Suda — https://twitter.com/_AkihiroSuda_ Carlisia Campos on LinkedIn — https://www.linkedin.com/in/carlisia/ Kubernetes — https://kubernetes.io/ Duffie Cooley on LinkedIn — https://www.linkedin.com/in/mauilion/ Bryan Liles on LinkedIn — https://www.linkedin.com/in/bryanliles/ KubeCon North America — https://events19.linuxfoundation.org/events/kubecon-cloudnativecon-north-america-2019/ Linux — https://www.linux.org/ Amazon Fargate — https://aws.amazon.com/fargate/ Go — https://golang.org/ Docker — https://www.docker.com/ Vagrant — https://www.vagrantup.com/ Prometheus — https://prometheus.io/ Kafka — https://kafka.apache.org/ OpenStack — https://www.openstack.org/ Verizon — https://www.verizonwireless.com/ Spotify — https://www.spotify.com/ Transcript: EPISODE 7 [INTRODUCTION] [0:00:08.7] ANNOUNCER: Welcome to The Podlets Podcast, a weekly show that explores Cloud Native one buzzword at a time. Each week, experts in the field will discuss and contrast distributed systems concepts, practices, tradeoffs and lessons learned to help you on your cloud native journey. This space moves fast and we shouldn’t reinvent the wheel. If you’re an engineer, operator or technically minded decision maker, this podcast is for you. [INTERVIEW] [00:00:41] CC: Hi, everybody. Welcome back to The Podlets, and today we have a special guest with us, Kelsey Hightower. A lot of people listening to us today will know Kelsey, but as usual, there are a lot of new comers in this space. So Kelsey, please give us an introduction. [00:01:00] KH: Yeah. So I consider myself a minimalist. So I want to keep this short. I work at Google, on Google Cloud stuff. I’ve been involved with the Kubernetes community for what? 3, 4, 5 years ever since it’s been out, and one main goal, learning in public and helping other people do the same. [00:01:16] CC: There you go. You do have a repo on your GitHub that it’s about learning Kubernetes the hard way. Are you still maintaining that? [00:01:26] KH: Yeah. So every six months or so. So Kubernetes is a hard way for those that don’t know. It’s a guide, a tutorial. You can copy and paste. It takes about three hours, and the whole goal of that guide was to teach people how to stand up a Kubernetes cluster from the ground up. So starting from scratch, 6 VMs, you install etcd, all the components, the nodes, and then you run a few test workloads so you can get a feel for Kubernetes. The history behind that was when I first joined Google, we were all concerned about the adaption of such a complex system that Kubernetes is, right? Docker Swarm is out at the time. A lot of people are using Mesos and we’re wondering like a lot of the feedback at that time was Kubernetes is too complex. So Kubernetes the hard way was built as an idea that if people understand how it worked just like they understand how Linux works, because that’s also complex, that if people just saw how the moving pieces fit together, then they would complain less about the complexity and have a way to kind of grasp it. [00:02:30] DC: I’m back. This is Duffie Colley. I’m back this week, and then we also have Michael and Bryan with us. So looking forward to this session talking through this stuff. [00:02:40] CC: Yeah. Thank you for doing that. I totally forgot to introduce who else is in this show, and me, Carlisia. We didn’t plan what the topic is going to be today. I will take a wild guess, and we are going to touch on Kubernetes. I have so many questions for you, Kelsey. But first and foremost, why don’t you tell us what you would love to talk about? One thing that I love about you is that every time I hear an interview of you, you’re always talking about something different, or you’re talking about the same thing in a different way. I love that about the way you speak. I know you offer to be on a lot of podcast shows, which is how we ended up here and I was thinking, “Oh my gosh! We’re going to talk about what everybody is going to talk about, but I know that’s not going to happen.” So feel free to get a conversation started, and we are VMware engineers here. So come at us with questions, but also what you would like to talk about on our show today. [00:03:37] KH: Yeah. I mean, we’re all just coming straight off the hills of KubeCon, right? So this big, 12,000 people getting together. We’re super excited about Kubernetes and the Mister V event, things are wrapping up there as well. When we start to think about Kubernetes and what’s going to happen, and a lot of people saw Amazon jump in with Fargate for EKS, right? So those unfamiliar with that offering, over the years, all the cloud providers have been providing some hosted Kubernetes offering, the ideas that the cloud provider, just like we do with hypervisors and virtual machines, would provide this base infrastructure so you can focus on using Kubernetes. You’ve seen this even flow down on-prem with VMware, right? VMware saying, “Hey, Kubernetes is going to be a part of this control plane that you can use to Kubernetes’ API to manage virtual machines and containers on-prem.” So at some point now, where do we go from here? There’s a big serverless movement, which is trying to eliminate infrastructure for all kinds of components, whether that’s compute, database as a storage. But even in the Kubernetes world, I think there’s an appetite when we saw this with Fargate, that we need to make the Kubernetes cluster disappear, right? If we can make it disappear, then we can focus on building new platforms that extend the API or, hell, just using Kubernetes as is without thinking about managing nodes, operating systems and autoscalers. I think that’s kind of been the topic that I’m pretty interested in talking about, because that feature means lots of things disappear, right? Programming languages and compilers made assembly disappear for a lot of developers. Assembly is still there. I think people get caught up on nothing goes away. They’re right. Nothing goes away, but the number of people who have to interact with that thing is greatly reduced. [00:05:21] BL: You know what, Kelsey? I’m going to have you get out of my brain, because that was the exact example that I was going to use. I was on a bus today and I was thinking about all the hubbub, about the whole Fargate EKS thing, and then I was thinking, “Well, Go, for example, can generate assembler and then it compiles that down.” No one complains about the length of the assembler that Go generates. Who cares? That’s how we should think about this problem. That’s a whole solvable problem. Let’s think about bigger things. [00:05:51] KH: I think it’s because in operations we tend to identify ourselves as the people responsible for running the nodes. We’re the people responsible for tuning the API server. When someone says it’s going to go away, in ops – And you see this in some parts, right? Ops, some people focus a lot more on observability. They can care less about what machine something runs on. They’re still going to try to observe and tune it. You see this in SRE and some various practices. But a lot of people who came up in a world like I have in a traditional ops background, you were the one that pixie-booted the server. You installed that Linux OS. You configured it with Puppet. When someone tells you, “We’re going to move on from that as if it’s a good thing.” You’re going to be like, “Hold up. That’s my job.” [00:06:36] DC: Definitely. We’ve touched this topic through a couple of different times on this show as well, and it definitely comes back to like understanding that, in my opinion, it’s not about whether there will be a worker for people who are in operations, people who want to focus on that. The real question that come to mind is like there is so much of that work that how are so few of us are going to be able to accomplish it unless we radically re-sync how it will be done. We’re vastly outnumbered. The number of people walking into the internet for the first time every day is mind-boggling. [00:07:08] KH: In early days, we have this goal of abstract or automating ourselves out of a job, and anyone that tried that a number of times knows that you’re always going to have something else to do. I think if we carry that to the infrastructure, I want to see the ops folks. I was very surprised that Docker didn’t come from operations folks. It came from the developer folks. Same thing for Vagrant and the same thing from Kubernetes. These are developer-minded folks that want to tackle infrastructure problems. If I think if ops were to put more skin in the game earlier on, definitely capable of building these systems and maybe they even end up more mature as more operations people put ops-minded thinking to these problems. [00:07:48] BL: Well, that’s exactly what we should do. Like you said, Kelsey, we will always have a job. Whenever we solve one problem, we could think about more interesting problems. We don’t think about Linux on servers anymore. We just put Linux on servers and we run it. We don’t think about the 15 years where it was little rocky. That’s gone now. So think about what we did there and let’s do that again with what we’re doing now. [00:08:12] KH: Yeah. I think the Prometheus community is a good example of operations-minded folks producing a system. When you meet the kind of the originators of Prometheus, they took a lot of their operational knowledge and kind of build this metrics and monitoring standard that we all kind of think about now when we talk about some levels of observability, and I think that’s what happens when you have good operations people that take prior experience, the knowledge, and that can happen over code these days. This is the kind of systems they produce, and it’s a very robust and extensible API that I think you start to see a lot of adaption. [00:08:44] BL: One more thing on Prometheus. Prometheus is six-years-old. Just think about that, and that’s not done yet, and it’s just gotten better and better and better. We go to give up our old thing so we can get better and better and better. That’s just what I want to add. [00:08:58] MG: Kelsey, if you look at the – Basically your own history of coming from ops, as I understood your own history, right? Now being kind of one of the poster childs in the Kubernetes world, you see the world changing to serverless, to higher abstractions, more complex systems on one hand, but then on the other side, we have ops. Looking beyond or outside the world of Silicon Valley into the traditional ops, traditional large enterprise, what do you think is the current majority level of these ops people? I don’t want to discriminate anyone here. I’m just basically throwing this out as a question. Where do you think do they need to go in terms of to keep up with this evolving and higher level abstractions where we don’t really care about nitty-gritty details? [00:09:39] KH: Yes. So this is a good, good question. I spent half of my time. So I probably spent time onsite with at least 100 customers a year globally. I fly on a plane and visit them in their home turf, and you definitely meet people at various skill levels and areas of responsibility. I want to make sure that I’m clear about the areas of responsibility. Sometimes you’re hired in an area of responsibility that’s below your skillset. Some people are hired to manage batch jobs or to translate files from XML to JSON. That really doesn’t say a lot about their skillset. It just kind of talks about the area of responsibility. So shout out to all the people that are dealing with main frames and having to deal with that kind of stuff. But when you look at it, you have the opportunity to rise up to whatever level you want to be in in terms of your education. When we talk about this particular question, some people really do see themselves as operators, and there’s nothing wrong with that. Meaning, they could come in. They get a system and they turn the knobs. You gave me a mainfrastructure me, I will tell you how to turn the knobs on that mainframe. You buy me a microwave, I’ll tell you how to pop popcorn. They’re not very interested in building a microwave. Maybe they have other things that are more important to them, and that is totally okay. Then you have people who are always trying to push the boundaries. Before Kubernetes, if I think back to 10 years ago, maybe 8. When I was working in a traditional enterprise, like kind of the ones you’re talking about or hinting at, the goal has always been to abstract away all of these stuff that it means to deploy an application the right way in a specific environment for that particular company. The way I manage to do it was say, “Hey, look. We have a very complex change in management processes.” I work in finance at that time. So everything had to have a ticket no matter how good the automation was. So I decided to make JIRA the ticketing system their front door to do everything. So you go to JIRA. There’ll be a custom field that says, “Hey, here are all the RPMs that have been QA’d by the QA team. Here are all the available environments.” You put those two fields in. That ticket goes to change in management and approval, and then something below the scenes automated everything, in that case it was Puppet, Red Hat and VMware, right? So I think what most people have been doing if you’re in the world of abstracting this stuff away and making it easier for the company to adapt, you’ve already been pushing these ideas that we call serverless now. I think the cloud providers put these labels on platforms to describe the contract between us and the consumer of the APIs that we present. But if you’re in operations, you should have been trying to abstract away all of these stuff for the last 10 or 15 years. [00:12:14] BL: I 100% agree. Then also, think about other verticals. So 23 years ago, I did [inaudible 00:12:22] work. That was my job. But we learned how to program in C and C++ because we were on old Suns, not even Spark machines. We’re on the old Suns, and we wanted to write things in CVE and we wanted to write our own Window managers. That is what we’re doing right now, and that’s why you see like Mitchell Hashimoto with Vagrant and you’re seeing how we’re pushing this thing. We have barely scratched the surface of what we’re trying to do. For a lot of people who are just ops-minded, understand that being ops-minded is just the end. You have to be able to think outside of your boundaries so you can create the next big thing. [00:12:58] KH: Of you may not care about creating the next big thing. There are parts of my life where I just don’t care. For example, I pay Comcast to get internet access, and my ops involvement was going to BestBuy and buying a modem and screwing it into the wall, and I troubleshoot this thing every once in a while when someone in the household complains the internet is down. But that’s just far as I’m ever going to push the internet boundaries, right? I am not really interested in pushing that forward. I’m assuming others will, and I think that’s one thing in our industry where sometimes we believe that we all need to contribute to pushing things forward. Look, there’s a lot of value in being a great operations person. Just be welcomed to saying that what we operate will change overtime. [00:13:45] DC: Yeah, that’s fair. Very fair. For me, personally, I definitely identify as an operations person. I don’t consider it my life’s goal to create new work necessarily, but to expand on the work that has been identified and to help people understand the value of it. I find I sit in between two roles personally. One is to help figure out all of the different edges and pieces and parts of Kubernetes or some other thing in the ecosystem. Second, to educate others on those things, right? Take what I’ve learned and amplify it. Having the amplifying effect. [00:14:17] CC: One thing that I wanted to ask you, Kelsey is – I work on the Valero project, and that does back and recovery of Kubernetes clusters. Some people ask me, “Okay. So tell me about the people who are doing?” I’m like, “I don’t want to talk about that. That’s boring. I wanted to talk about the people who are not doing backups.” “Okay. Let’s talk about why you should be doing maybe thinking about that.” Well, anyway. I wonder if you get a lot of questions in the area of Kubernetes operations or cloud native in general, infrastructure, etc., that in the back of your mind you go, “That’s the wrong question or questions.” Do you get that? [00:14:54] KH: Yeah. So let’s use your backup example. So I think when I hear questions, at least it lets me know what people are thinking and where they’re at, and if I ask enough questions, I can kind of get a pulse in the trend of where the majority of the people are. Let’s take the backups questions. When I hear people say, “I want to back up my Kubernetes cluster.” I rewind the clock in my mind and say, “Wow! I remember when we used to backup Linux servers,” because we didn’t know what config files were on the disk. We didn’t know where processes are running. So we used to do these PS snapshots and we used to pile up the whole file system and store it somewhere so we can recover it. Remember Norton Ghost? You take a machine and ghost it so you can make it again. Then we said, “You know what? That’s a bad idea.” What we should be doing is having a tool that can make any machine look like the way we want it. Config management is boring. So we don’t back those up anymore. So when I hear that question I say, “Hmm, what is happening in the community that’s keeping people to ask these questions?” Because if I hear a bunch of questions that already have good answers, that means those answers aren’t visible enough and not enough people are sharing these ideas. That should be my next key note. Maybe we need to make sure that other people know that that is no longer a boring thing, even though it’s boring to me, it’s not boring to the industry in general. When I hear these question I kind of use it as a keeps me up-to-date, keeps me grounded. I hear stuff like how many Kubernetes clusters should I have? I don’t think there’s a best practice around that answer. It depends on how your company segregates things, or depends on how you understand Kubernetes. It depends on the way you think about things. But I know why they’re asking that question, is because Kubernetes presents itself as a solution to a much broader problem set than it really is. Kubernetes manages a group of machines typically backed by IS APIs. If you have that, that’s what it does. It doesn’t do everything else. It doesn’t tell you exactly how you should run your business. It doesn’t tell you how you should compartmentalize your product teams. Those decisions you have to make independently, and once you do, you can serialize those into Kubernetes. So that’s the way I think about those questions when I hear them, like, “Wow! Yeah, that is a crazy thing that you’re still asking this question six years later. But now I know why you’re asking that question.” [00:17:08] CC: That is such a great take on this, because, yes, it in the area of backup, people who are doing backup in my mind – Yeah, they should be independent of Kubernetes or not. But let’s talk about the people who are not doing backups. What motivates you to not do backups? Obviously, backups can be done in many different ways. But, yes. [00:17:30] BL: So think about it like this way. Some people don’t exercise, because exercise is tough and it’s hard, and it’s easier to sit on the couch and eat a bag of potato chips than exercise. It’s the same thing with backups. Well, backing up my Kubernetes cluster before Valero was so hard that I’d rather just invest brain cycles in figuring out how to make money. So that’s where people come from when it comes to hard things like backups. [00:17:52] KH: There’s a trust element too, right? Because we don’t know if the effort we’re putting in is worth it. When people do unit testing, a lot of times unit testing can be seen as a proactive activity, where you write unit tests to catch bugs in the future. Some people only write unit test when there’s a problem. Meaning, “Wow! There’s an odd things in a database. Maybe we should write a test to prove that our code is putting odd things. Fix the code, and now the test pass.” I think it’s really about trusting that the investment is worth it. I think when you start to think about backups – I’ve seen people back up a lot of stuff, like every day or every couple of hours, they’re backing up their database, but they’d never restored the database. Then when you read their root cause analysis, they’re like, “Everything was going fine until we tried to restore a 2 terabyte database over 100 meg link. Yeah, we never exercised that part.” [00:18:43] CC: That is very true. [00:18:44] DC: Another really fascinating thing to think about the backup piece is that especially like in the Kubernetes with Valero and stuff, we’re so used to having the conversation around stateless applications and being able to ensure that you can redeploy in the case of a failure. You’re not trying to actually get back to a known state the way that like a backup traditionally would. You’re just trying to get back to a running state. So there’s a bit of a dichotomy there I think for most folks. Maybe they’re not conceptualizing the need for having to deal with some of those stateful applications when they start trying to just think about how Valero fits into the puzzle, because they’ve been told over and over again, “This is about immutable infrastructure. This is about getting back to running. This is not about restoring some complex state.” So it’s kind of interesting. [00:19:30] MG: I think part of this is also that for the stateful services that why we do backups actually, things change a lot lately, right? With those new databases, scale out databases, cloud services. Thinking about backup also has changed in the new world of being cloud native, which for most of the people, that’s also a new learning experiment to understand how should I backup Kafka? It’s replicated, but can I backup it? What about etcd and all those things? Little different things than backing up a SQL database like more traditional system. So backup, I think as you become more complex, stays if needed for [inaudible 00:20:06]. [00:20:06] KH: Yeah. The case is what are you backing up and what do you hope to restore? So replication, global replication, like we do with like cloud storage and S3. The goal is to give some people 11 9s of reliability and replicate that data almost as many geographies as you can. So it’s almost like this active backup. You’re always backing up and restoring as a part of the system design versus it being an explicit action. Some people would say the type of replication we do for object stores is much closer to active restoring and backing up on a continuous basis versus a one-time checkpoint. [00:20:41] BL: Yeah. Just a little bit of a note, you can back up two terabytes over 100 meg link in like 44 hours and a half. So just putting out there, it’s possible. Just like two days. But you’re right. When it comes to backups, especially for like – Let’s say you’re doing MySQL or Postgres. These days, is it better to back it up or is it better to have a replica right next to it and then having like a 10 minute delayed replica right next to that and then replicating to Europe or Asia? Then constantly querying the data that you’re replicating. That’s still a backup. What I’m saying here is that we can change the way that we talk about it. Backup started as conventional as they used to be. There are definitely other ways to protect your data. [00:21:25] KH: Yeah. Also, I think the other part too around the backup thing is what is the price of data loss? When you take a backup, you’re saying, “I’m willing to lose this much data between the last backup and the next.” That cost is too high than backing up cannot be your primary mode of operation, because the cost of losing data is way too high, then replication becomes a complementing factor in the whole discussion of backups versus real-time replication and shorter times to recovery. I have a couple of questions. When should people not use Kubernetes? Do you know what I mean? I visit a lot of customers, I work with a lot of eng teams, and I am in the camp of Kubernetes is not for everything, right? That’s a very obvious thing to say. But some people don’t actually practice it that way. They’re trying to jam more and more into Kubernetes. So I love to get your insights on where do you see Kubernetes being like the wrong direction for some folks or workloads. [00:22:23] MG: I’m going to scratch this one from my question list to Kelsey. [00:22:26] KH: I’ll answer it too then. I’ll answer it after you will answer it. [00:22:29] MG: Okay. Who wants to go first? [00:22:30] BL: All right. I’ll go first. There are cases when I’m writing a piece of software where I don’t care about the service discovery. I don’t care about ingress. It’s just software that needs to run. When I’m running it locally, I don’t need it. If it’s simple enough where I could basically throw it into a VM through a CloudNet script, I think that is actually lower friction than Kubernetes if it’s simple. Now, but I’m also a little bit jaded here, because I work for the dude who created Kubernetes, and I’m paid to create solutions for Kubernetes, but I’m also really pragmatic about it as well. It’s all about effort for me. If I can do it faster in CloudNet, I will. [00:23:13] DC: For my part, I think that there’s – I have a couple of – I got follow on questions to this real quick. But I do think that if you’re not actively trying to develop a distributed systems, something where you’re actually making use of the primitives that Kubernetes provides, then that already would kind of be a red flag for me. If you’re building a monolithic application or if you’re in that place where you’re just rapidly iterating on a SaaS product and you’re just trying to like get as many commits on this thing until it works and like just really rapidly prototype or even create this thing. Maybe Kubernetes isn’t the right thing, because although we’ve come a long way in improving the tools that allow for that iteration, I certainly wouldn’t say that we’re like all the way there yet. [00:23:53] BL: I would debate you that, Duffy. [00:23:55] DC: All right. Then the other part of it is Kubernetes aside, I’m curious about the same question as it relates to containerization. Is it containerization the right thing for everyone, or have we made that pronouncement, for example? [00:24:08] KH: I’m going to jump in and answer on this one, because I definitely think we need a way to transport applications in some way, right? We used to do it on floppy disks. We used to do it on [inaudible 00:24:18]. I think the container to me I treat as a glorified [inaudible 00:24:23]. That’s the way I’ve been seeing it for years. Registry store them. They replace [inaudible 00:24:28]. Great. Now we kind of have a more maybe universal packaging format that can handle simple use cases, scratch containers where it’s just your binary, and the more complex use cases where you have to compose multiple layers to get the output, right? I think RPM spec files used to do something very similar when you start to build those thing in [inaudible 00:24:48], “All right. We got that piece.” Do people really need them? The thing I get weary about is when people believe they have to have Kubernetes on their laptop to build an app that will eventually deploy to Kubernetes, right? If we took that thinking about the cloud, then everyone would be trying to install open stack on their laptop just to build an app. Does that even make sense? Does that make sense in that context? Because you don’t need the entire cloud platform on your laptop to build an app that’s going to take a request and respond. I think Kubernetes people, I guess because it’s easier to put your on laptop, people believe that it needs to be there. So I think Kubernetes is overused, because people just don’t quite understand what it does. I think there’s a case where you don’t use Kubernetes, like I need to read a file from a bucket. Someone uploaded an XML file and my app is going to translate it into JSON. That’s it. In that case, this is where I think functions as a service, something like Cloud Run or even Heroku make a lot more sense to me because the operational complexity is kind of hitting within a provider and is linked almost like an SDK to the overall service, which is the object store, right? The compute part, I don’t want to make a big deal about, because it’s only there to process the file that got uploaded, right? It’s almost like a plug-in to an FTP server, if you will. Those are the cases where I start to see Kubernetes become less of a need, because I need a custom platform to do such an obvious operation. [00:26:16] DC: Those applications that require the primitives that Kubernetes provides, service discovery, the ability to define ingress in a normal way. When you’re actually starting to figure out how you’re going to platform that application with regard to those primitives, I do see the argument for having Kubernetes locally, because you’re going to be using those tools locally and remotely. You have some way of defining what that platforming requirement is. [00:26:40] KH: So let me pull on that thread. If you have an app that depends on another app, typically we used to just have a command line flag that says, “This app is over there.” Local host when it’s on my laptop. Some DNS name when it’s in the cluster, or a config file can satisfy that need. So the need for service discovery usually arises where you don’t know where things are. But if you’re literally on your laptop, you know where the things are. You don’t really have that problem. So when you bring that problem space to your laptop, I think you’re actually making things worse. I’ve seen people depend on Kubernetes service discovery for the app to work. Meaning, they just assume they can call a thing by name and they don’t support IPs, and ports. They don’t support anything, because they say, “Oh! No. No. No. You’ll always be running into Kubernetes.” You know what’s going to happen? In 5 or 10 years, we’re going to be talking like, “Oh my God! Do you remember when you used to use Kubernetes? Man! That legacy thing. I built my whole career porting apps away from Kubernetes to the next thing.” The number one thing we’ll talk about is where people lean too hard on service discovery, or people who built apps that taught to config maps directly. Why are you calling the Kubernetes API from your app? That’s not a good design. I think we got to be careful coupling ourselves too much to the infrastructure. [00:27:58] MG: It’s a fair point too. Two answers from my end, to your question. So one is I just build an appliance, which basically priced to bring an AWS Lambda experience to the Vsphere ecosystem. Because we don’t – Or actually my approach is that I don’t want any ops people who needs to do some one-off things, like connect this guy to another guy. I don’t want him to learn Kubernetes for that. It should be as simple as writing a function. So for that appliance, we had to decide how do we build it? Because it should be scalable. We might have some function as a service component running on there. So we looked around and we decided to put it on Kubernetes. So build the appliance as a traditional VM using Kubernetes on top. For me as a developer, it gave me a lot of capabilities, like self-healing, the self-healing capabilities. But it’s also a fair point that you wrote, Kelsey, about how much do we depend or write our applications being depend on those auxiliary features from Kubernetes? Like self-healing, restarts, for example. [00:28:55] KH: Well, in your case, you’re building a platform. I would hate for you to tell me that you rebuilt a Kubernetes-like thing just for that appliance. In your case, it’s a great use case. I think the problem that we have as platform builders is what happens when things start leaking up to the user? You tell a user all they have to care about is functions. Then they get some error saying, “Oh! There’s some Kubernetes security context that doesn’t work.” I’m like, “What the hell is Kubernetes?” That leakage is the problem, and I think that’s the part where we have to be careful, and it will take time, but we don’t start leaking the underlying platform making the original goal untrue. [00:29:31] MG: The point is where I wanted to throw this question back was now these functions being written as simple scripts, whatever, and the operators put in. They run on Kubernetes. Now, the operators don’t know that it runs in Kubernetes. But going back to your question, when should we not use Kubernetes. Is it me writing in a higher level abstraction like a function? Not using Kubernetes in first sense, because I don’t know actually I’m using it. But on the covers, I’m still using it. So it’s kind of an answer and not an answer to your question because – [00:29:58] KH: I’ve seen these single node appliances. There’s only one node, right? They’re only there to provide like email at a grocery store. You don’t have a distributed system. Now, what people want is the Kubernetes API, the way it deploys things, the way it swaps out a running container for the next one. We want that Kubernetes API. Today, the only way to get it is by essentially bringing up a whole Kubernetes cluster. I think the K3S project is trying to simplify that by re-implementing Kubernetes. No etcd, SQLite instead. A single binary that has everything. So I think when we start to say what is Kubernetes, there’s the implementation, which is a big distributed system. Then there’s the API. I think what’s going to happen is if you want the Kubernetes API, you’re going to have so many more choices on the implementation that makes better sense for the target platform. So if you’re building an appliance, you’re going to look at K3S. If you’re a cloud provider, you’re going to probably look something like what we see on GitHub, right? You’re going to modify and integrate it into your cloud platform. [00:31:00] BL: Of maybe what happened with Kubernetes over the next few years is what happened with the Linux API, or the API. Firecracker and gVisor did this, and WSL did this. We can basically swap out Linux from the backend because we can just get on with the calls. Maybe that will happen with Kubernetes as well. So maybe Kubernetes will become a standard where Kubernetes standard and Kubernetes implementation that we have right now. I don’t even know about that one. [00:31:30] KH: We’re starting to see it, right? When you say here is my pod, and we can just look at Fargate for EKS as an example. When you give them a pod, their implementation is definitely different than what most people are thinking about running these days, right? One pod per VM. Not using Virtual Kube. So they’ve taken that pod spec and tried to uphold its means. But the problem with that, you get leaks. For example, they don’t allow you to bind to a host 4. Well, the pod spec says you can bind to a host 4. Their implementation doesn’t allow you to do it, and we see the same problem with gVisor. It doesn’t implement all the system calls. You couldn’t run the Docker daemon on top of gVisor. It wouldn’t work. So I think as long as we don’t leak, because when we leak, then we start breaking stuff. [00:32:17] BL: So we’re doing the same thing with Project Pacific here at VMware, where this concept of a pod is actually a virtual machines that loops in like a tenth of a second. It’s pretty crazy how they’ve been able to figure that out. If we can get this right, that’s huge for us. That means we can move out of our appliance and we can create better things that actually work. I’m VMware specific. I’m on AWS and I want this name space. I can use Fargate and EKS. That’s actually a great idea. [00:32:45] MG: I remember this presentation, Kelsey, that you gave. I think two or three years ago. It might be three years, where you took the Kubernetes architecture and you removed the boxes and the only thing remaining was the API server. This is where it clicked to me as like, “This is right,” because I was focused on the scheduler. I wanted to understand the scheduler. But then you zoomed out or your stripped off all these pieces and the only thing remaining was the API server. This is where it clicked to me. It’s like [inaudible 00:33:09] or like the syscall interface. It’s basically my API to do some crazy things that I would have write on my own and assembly kind of something before I could even get started. As well the breakthrough moment for me, this specific presentation. [00:33:24] KH: I’m working on an analogy to talk about what’s happening with the Kubernetes API, and I haven’t refined it yet. But when the web came out, we had all of these HTTP verbs, put post git. We have a body. We have headers. You can extract that out of the whole web, the web browser plus the web server. If you have tracked out that one piece, the instead of building web package, we can build APIs and GraphQL, because we can reuse many of those mechanisms, and we just call that RESTful interfaces. Kubernetes is going through the same evolution, right? The first thing we built was this container orchestration tool. But if you look at the CRDs, the way we do RBAC, the way we think about the status field in a custom object, if you extract those components out, then you end up with this Kubernetes style APIs where we start to treat infrastructure not as code, but as data. That will be the restful moment for Kubernetes, right? The web, we extracted it out, then we have REST interfaces. In Kubernetes, once we extracted out, we’ll end up with this declarative way of describing maybe any system. But right now, the fine, or the perfect match is infrastructure. Infrastructure as data and using these CRDs to allow us to manipulate that data. So maybe you start with Helm, and then Helm gets piped into something like Customize. That then gets piped into a mission controller. That’s how Kubernetes actually works, and that data model to API development I think is going to be the unique thing that lasts longer then the Kubernetes container platform does. [00:34:56] CC: But if you’re talking about – Correct me if I misinterpret it, platform as data. Data to me is meant to be consumed, and I actually have been thinking since you said, “Oh, developers should not be developing apps that connect directly to Kubernetes,” or I think you said the Kubernetes API. Then I was thinking, “Wait. I’ve heard so many times people saying that that’s one great benefit of Kubernetes, that the apps have that access.” Now, if you see my confusion, please clarify it. [00:35:28] KH: Yeah. Right. I remember early on when we’re doing config maps, and a big debate about how config maps should be consumed by the average application. So one way could be let’s just make a configs map API and tell every developer that they need to import a Kubernetes library to call the API server, right? Now everybody’s app doesn’t work anymore on your laptop. So we were like, “Of course not.” What we should do is have config maps be injected into the file system. So that’s why you can actually describe a config map as a volume and say, “Take these key values from the config map and write them as normal files and inject them into the container so you can just read them from the file system. The other option also was environment variables. You can take a config map and translate them into an environment variables, and lastly, you can take those environment variables and put them into command line flags. So the whole point of that is all three of the most popular ways of configuring an app, environment variables, command line flags and files. Kubernetes molded itself into that world so that developers would never tightly couple themselves to the Kubernetes API. Now, let’s say you’re building a platform, like you’re building a workflow engine like Argo, or you’re building a network control plane like Istio. Of course, you should use a Kubernetes API. You’re building a platform on top of a platform. I would say that’s kind of the exception to the rule if you’re building a platform. But a general application that’s leveraging the platform, I really think you should stay away from the Kubernetes API directly. You shouldn’t be making sys calls directly [inaudible 00:37:04] of your runtime. The unsafe package in Go. Once you start doing that, Go can’t really help you anymore. You start pining yourself to specific threads. You’re going to be in a bad time. [00:37:15] CC: Right. Okay. I think I get it. But you can still use Kubernetes to decouple your app from the machine by using objects to generate those dependencies. [00:37:25] KH: Exactly. That was the whole benefit of Kub, and Docker even, saying, “You know what? Don’t worry too much more about C groups and namespaces. Don’t even try to do that yourself.” Because remember, there was a period of time where people were actually trying to build C groups and network namespaces into the runtime. There’s a bunch of like Ruby and Python projects that they were trying to containerize themselves within the runtime. Whoa! What are we doing? Having that second layer now with Containerd on C, we don’t have to implement that 10,000 times for every programming language. [00:37:56] DC: One of the things I want to come back to is your point that you’d made about the Kubernetes API being like one of the more attractive parts of the projects, and people needing that to kind of move forward in some of these projects, and I wonder if it’s more abstract than that. I wonder if it’s abstract enough to think about in terms of like a level triggered versus edge triggered stuff. Taking control theory, the control theory that basically makes Kubernetes such a stable project and applying that to software architecture rather than necessarily bringing the entire API with you. Perhaps, what you should take from this is the lessons that we’ve learned in developing Kubernetes and apply that to your software. [00:38:33] KH: Yeah. I have the fortunate time to spend some time with Mark Burgess. He came out with the Promise Theory, and the Promise Theory is the underpinnings of Puppet Chef, Ansible, CF Engine, and this idea that we would make promises about something and eventually convergent to that state. The problem was with Puppet Chef and Ansible, we’re basically doing this with shell scripts and Ruby. We were trying to write all of these if, and, else statements. When those didn’t work, what did you do? You made an exec statement at the bottom and then you’re like, “Oh! Just run some batch, and who knows what’s going to happen?” That early implementations of Promise Theory, we didn’t own the resource that we were making promises about. Anyone could go behind this and remove the user, or the user could have a different user ID on different systems but mean the same thing. In the Kubernetes world, we push a lot of that if, else statements into the controller. Now, we force the API not have any code. That’s the big difference. If you look at the Kubernetes API, you can’t do if statements. Terraform, you can do if statements. So you kind of fall into the imperative trap at the worst moments when you’re doing dry runs or something like that. It does a really good of it. Don’t get me wrong. So the Kubernetes API says, “You know what? We’re going to go all-in on this idea.” You have to change the controller first and then update the API. There is no escape patches in the API. So it forces a set of discipline that I think gets us closer to the promises, because we know that the controller owns everything. There’s no way to escape in the API itself. [00:40:07] DC: Exactly. That’s exactly what I was pushing for. [00:40:09] MG: I have a somewhat related question and I’m just not sure how to frame it correctly. So yesterday I saw a good talk by someone talking about protocols, like they somewhat forgotten power of protocols in the world of APIs. We got Swagger. We got API definitions. But he made the very easy point of if I give you an open, a close and a write and read method, or an API, you’d still don’t know how to call them in sequence and which one to call it off. This is same for [inaudible 00:40:36] library if you look at that. So I always have to force myself, “Should I do anything [inaudible 00:40:40] or I’m not leaking some stuff.” So I look it up. Versus on protocols, if you look at the RFC definitions, they are very, very precise and very plainly outlined of what you should do, how you should behave, how you should communicate between these systems. This is more of a communication and less about the actual implementation of an API. I still have to go through that talk again, and I’m going to put it in the show notes. But this kind of opened my mind again a little bit to think more about communication between systems and contracts and promises, as you said, Carlisia. Because we make so many assumptions in our code, especially as we have to write a lot of stuff very quickly, which I think will make things brittle overtime. [00:41:21] KH: So the gift and the curse of Kubernetes that it tries to do both all the time. For some things like a pod or a deployment, we all feel that. If I give any Kubernetes cluster a deployment object, I’m going to get back out running pod. This is what we all believe. But the thing is it may not necessarily run on the same kernel. It may not run on the same OS version. It may not even run on the same type of infrastructure, right? This is where I think Kubernetes ends up leaking some of those protocol promises. A deployment gets you a set of running pods. But then we dropdown to a point where you can actually do your own API and build your own protocol. I think you’re right. Istio is a protocol for thinking about service mesh, whereas Kubernetes provides the API for building such a protocol. [00:42:03] MG: Yeah, good point. [inaudible 00:42:04]. [00:42:04] DC: On the Fargate stuff, I thought was a really interesting article, or actually, an interesting project by [inaudible 00:42:10], and I want to give him a shout out on this, because I thought that was really interesting. He wrote an admission controller that leverages autoscaler, node affinity and pod affinity to effectively do the same thing so that whenever there is a new pod created, it will spin up a new machine and associate only that pod with that machine. I was like, “What a fascinating project.” But also just seeing this come up from like the whole Fargate ECS stuff. I was like – [00:42:34] KH: I think that’s the thread that virtual kubelet is pulling on, right? This idea that you can simplify autoscalling if you remove that layer, right? Because right now we’re trying to do this musical chairs dance, right? Like in a cloud. Imagine if someone gave you the hypervisor and told you you’re responsible for attaching hypervisor workers and the VMs. It would be a nightmare. We’re going to be talking about autoscalling the way we do in the cloud. I think Kubernetes moving into a world where a one pod per resource envelope. Today we call them VMs, but I think at some point we’re going to drop the VM and we would just call it a resource envelope. VMs, this is the way we think about that, Firecrackers. Like, “Hey, does it really need to be a complete VM?” Firecracker is saying, “No. It doesn’t. It just needs to be a resource envelope that allows you to run their particular workload.” [00:43:20] DC: Yeah. Same thing we’re doing here. It’s just enough VM to get you to the point where you can drop those containers on to it. [00:43:25] CC: Kelsey, question. Edge? Kubernetes on edge. Yes or no? [00:43:29] KH: Again, it’s just like compute on edge has been a topic for discussion forever. Problem is when some people say compute on edge, they mean like go buy some servers from Dell and put it in some building somewhere close to your property as you can. But then you have to go build the APIs to deploy it to that edge. What people want, and I don’t know how far off it is, but Kubernetes has set the bar so high that the Kubernetes API comes with a way to low balance, attach storage, all of these things by just writing a few YAML files. What I hear people saying is I want that close to my data center or store as possible. When you say Kubernetes on the edge, that’s what they’re saying, is like, “But we currently have one at edge. It’s not enough.” We’ve been providing edge for a very longtime. Open stack was – Remember open stack? Oh! We’re going to do open stack on the edge. But now you’re a pseudo cloud provider without the APIs. I think what Kubernetes is bringing to the table is that we have to have a default low balancer. We have to have a default block store. We have to have a default everything and on or for to mean Kubernetes like it does today centralized. [00:44:31] BL: Well, Doors have been doing this forever in some form or another. 20 years ago I worked for a Duty Free place, and literally traveled all over the world replacing point of sale. You might think of point of sales as a cash register. There was a computer in the back and it was RS-232 links from the cash register to the computer in the back. Then there was dial-up, or [inaudible 00:44:53] line to our central thing. We’ve been doing edge for a long time, but now we can do edge. The central facility can actually manage the compute infrastructure. All they care about is basically CPU and memory and network storage now, and it’s a lot more flexible. The surety is long, but I think we’re going to do it. It’s going to happen, and I think we’re almost right – People are definitely experimenting. [00:45:16] KH: You know what, Carlisia? You know what’s interesting now though? I was watching the Reinvent announcement. Verizon is starting to allow these edge components to leverage 5G for the last mile, and that’s something game-changer, because most people are very skeptical about 5G being able to provide the same coverage as 4G because of the wavelength and point-to-point, all of these things. But for edge, this thing is a game-changer. Higher bandwidth, but shorter distance. This is exactly what edge want, right? Now you don’t have to dig up the ground and run fiber from point-to-point. So if you could buy in these Kubernetes APIs, plus concepts like 5G, and get in that closer to people, yeah, I think that’s going to change the way we think about regions and zones. That kind of goes away. We’re going to move closer to CDNs, like Cloudflare has been experimenting with their worker technology. [00:46:09] DC: On the edge stuff, I think that there’s also an interesting dichotomy happening, right? There’s a definition of edge that we referred to, which is storage stuff and one that you’re alluding to, which is that there may be like some way of actually having some edge capability and a point of presence in a 5G tower or some point with that. In some cases, edge means data gravity. You’re actually taking a bunch of data from sensors and you’re trying to store it in a place where you don’t have to pay the cost of moving all of the data form one point to another where you can actually centralize compute. So in those edge cases, you’re actually willing to invest in a high-end compute to allow for the manipulation of that data where that data lake is so that you can afford to move it into some centralized location later. But I think that that whole space is so complex right now, because there are so many different definitions and so many different levels of constraints that you have to solve for under one umbrella term, which is the edge. [00:47:04] KH: I think Bryan was pulling on that with the POS stuff, right? Because instead of you going to go buy your own cash registry and gluing everything together, that whole space got so optimized that you can just buy a square terminal. Plug it on some Wi-Fi and then there you go, right? You now have that thing. So once we start to do this for like ML capabilities, security capabilities, I think you’re going to see that POS-like thing expand and that computer get a little bit more robust to do exactly what you’re saying, right? Keep the data local. Maybe you ship models to that thing so that it can get smarter overtime, and then upload the data from various stores overtime. [00:47:40] DC: Yup. [00:47:40] MG: One last question from my end. Switching gears a bit, if allow it. KubeCon. I left KubeCon with some mixed feelings this years. But my perspective is different, because I’m not the typical, one of the 12,000 people, because most of them were new comers actually. So I looked at them and I asked myself, “If I would be new to this huge big world of CNCF and Kubernetes and all these stuff, what would I take from that?” I would be confused. Confused like how from [inaudible 00:48:10] talks, which make it sound like it’s so complex to run all these things through the keynotes, which seems to be like just a lineup of different projects that I all have to get through and install and run. I was missing some perspective and some clarity from KubeCon this year, especially for new comers. Because I’m afraid, if we don’t retain them, attract them, and maybe make them contributors, because that’s another big problem. I’m afraid that we’ll lose our base that is using Kubernetes. [00:48:39] BL: Before Kelsey says anything, and Kelsey was a Kub contrary before I was, but I was a Kub contrary this time, and I can tell you exactly why everything is like it is. Well, fortunately and unfortunately, this cloud native community is huge now. There’s lots of money. There are lots of people. There are lots of interests. If we went back to KubeCon when it was in San Francisco years ago, or even like the first Seattle one, that was a community event. We could make the event for the community. Now, there’s community. The people who are creating the products. There’s the end users, the people who are consuming the products, and there are these big corporations and companies, people who are actually financing this whole entire thing. We actually have to balance all three of those. As a person who just wants to learn, what are you trying to learn from? Are you learning from the consumption piece? Are you learning to be a vendor? Are you learning to be a contributor? We have to think about that. At a certain point, that’s good for Kubernetes. That means that we’ve been able to do the whole chasm thing. We’ve cross over to chasm. This thing is real. It’s big. It’s going to make a lot of people a lot of money one day. But I do see the issue for the person who’s trying to come in and say, “What do I do now?” Well, unfortunately, it’s like anything else. Where do you start? Well, you got to take it all in. So you need to figure out where you want to be. I’m not going to be the person that’s going to tell you, “Well, go do a sig.” That’s not it. What I want to tell you is like anything else that we’d have to learn is real hard, whether it’s a programming language or a new technique. Figure out where you want to be and you’re going to have to do some research. Then hopefully you can contribute. I’m sure Kelsey has opinions on this as well. [00:50:19] KH: I think Brian is right. I mean, I think it’s just like a pyramid happening. A the very bottom, we’re new. We need to get everybody together in one space and it becomes more of a tradeshow, like an introductory, like a tasting, right? When you’re hungry and you go and just taste everything. Then when you figure out what you want, then that will be your focus, and that’s going to change every year for a lot of people. Some people go from consumer to contributor, and they’re going to want something out of the conference. They’re only going to want to go to the contributor day and maybe some of the deep-dive technical tracks. You’re trying to serve everybody in two or three days. So you’re going to start to have like everything pulling for your attention. I think what you got to do is commit. If you go and you’re a contributor, or you’re someone what’s building on top, you may have to find a separate event to kind of go with it, right? Someone told me, “Hey, when you go to all of these conferences, make sure you don’t forget to invest in the one-on-one time.” Me going to Oslo and spending an evening with Mark Burgess and really talk about Promise Theory outside of competing for attention with the rest of the conference. When I go, I’d like to meet new people. Sit down with them. Out of the 12,000 people, I call it a win if I can meet three new people that I’ve never met before. You know what? I’ll do a follow-up hangout with them to go deeper in some areas. So I think it’s more of a catch all. It’s definitely has a tradeshow feel now, because it’s big and there’s a lot of money and opportunity involved. But at the same time, you got to know that, “Hey, you got to go and seek out.” You go to Spotif

Daniel Smith is co-Chair and co-TL of SIG API Machinery, as well as TL of the corresponding Google team. Daniel has been working on Kubernetes since before it was open sourced, and is one of the top overall contributors to the codebase. He joins Adam and Craig to discuss CRDs and extensibility. Do you have something cool to share? Some questions? Let us know: web: kubernetespodcast.com mail: kubernetespodcast@google.com twitter: @kubernetespod Chatter of the week Old Man’s Journey Rocketman Funeral For A Friend/Love Lies Bleeding Aladdin (2019) Aladdin (1992) News of the week Kubevirt joins the CNCF KubeCon San Diego Contributor Summit ServiceMeshCon 2019 schedule announced GKE Intranode Visibility #KUBE100; hosted k3s from Civo k8s vs k3s by Andy Jeffries Docker: Designing your first application on Kubernetes Docker raising funds IBM launches Apache CouchDB operator 90% of all PaaS and SaaS on IBM Cloud is on Kubernetes Kubecost: Requests and Limits by Webb Brown Kubeadvisor 1.0 from Magalix Kubernetes Liveness Probes are Dangerous! by Henning Jacobs Links from the interview DevStats says Daniel is number 2 or number 3 contributor to Kubernetes, in either case just behind Tim Hockin from Episode 41 Either way, someone is wrong on the Internet! Carina star constellation and having to rename it from that The Kubernetes API API Machinery First proposal for API plugins - issue 991! Third party resources (deprecated in 1.7) Operator packaging Custom Resources Moving TPRs to CRDs by Nikhita Raghunath API Aggregator Extension via webhooks 1.15 release blog talks about CRD extensibility Daniel’s KubeCon talks: Life of an API Request (slides) The hand-drawn trilogy: Kubernetes-Style APIs of the Future (slides) A Vision For API Machinery: Coming to Terms with the Platform We Built (slides) The Kubernetes Control Plane for Busy People Who Like Pictures (slides) The Nut That Ties Everything Together Daniel Smith on Twitter

S01 E09: AWS en el día a día de un practicante DevOps expatriado - Conducido por @domix y @_marKox - -Septiembre-2019 Revisión de las noticias * [VM world 2019](https://blog.kasten.io/posts/vmworld-2019-san-francisco-highlights/) * [F5 Acquires NGINX ](https://www.nginx.com/press/f5-acquires-nginx-to-bridge-netops-and-devops) * Splunk shopping * [Splunk has agreed to acquire @signalfx](https://twitter.com/splunk/status/1164267179123937280) * [Splunk has agreed to acquire Omnition](https://twitter.com/splunk/status/1169220204796305409) Twitter! * [What CloudNative technologies are you using? Survey](https://twitter.com/dankohn1/status/1168696344044871681) * [CRDs are officially GA now with 1.16](https://twitter.com/the_sttts/status/1167002806961758211?s=21) * [ETCD 3.4](https://twitter.com/etcdio/status/1169626982432116736) * [Introducing Maesh by the @Traefik team](https://twitter.com/containous/status/1169235939895521282) Referencias y Recursos * [Kubernetes-based Event Driven Autoscaling](https://github.com/kedacore/keda) * [Balena: IoT platform](https://www.balena.io) * [Google Cloud Certification](https://inthecloud.withgoogle.com/cloud-certification#!/#benefits) Repos chingones de código * [Find files with SQL-like queries](https://github.com/jhspetersson/fselect) * [Terminal session recorder](https://github.com/asciinema/asciinema) * [Swiss Army Knife for macOS](https://github.com/rgcr/m-cli) * [A cd command that learns](https://github.com/wting/autojump) * [Good-lookin' diffs](https://github.com/so-fancy/diff-so-fancy) Eventos * [MySQL: a Cloud Native Database](https://www.meetup.com/Cloud-Native-Mexico/events/264549922/) * [ServiceMeshCon](https://twitter.com/cra/status/1170743614726713346) Tema del día [Entrevista] AWS en el día a día de un practicante DevOps expatriado

Last Week in AWS - https://www.lastweekinaws.com/ Corey Quinn - https://twitter.com/QuinnyPig Rancher Rio - https://github.com/rancher/rio Helm - https://cloudblogs.microsoft.com/opensource/2019/05/21/helm-3-release/ Spotify Deleting Production K8S Cluster - https://kccnceu19.sched.com/event/MQbb/keynote-how-spotify-accidentally-deleted-all-its-kube-clusters-with-no-user-impact-david-xia-infrastructure-engineer-spotify Service Mesh Interface - https://cloudblogs.microsoft.com/opensource/2019/05/21/service-mesh-interface-smi-release/ Episode TranscriptionWelcome back to The Byte. In this episode we're going to do a KubeCon recap. KubeCon 2019. It's been a heck of a week last week. We were traveling to Austria for some customer visits, and I just completely missed out on recording some episodes. So, I'm back. And I had plenty of time to actually review all of the news coming out of KubeCon. It was an incredible amount of news. Corey Quinn, you know, from last week and AWS was actually attending KubeCon, which is great 'cause he's a really great person to listen to and understand his viewpoint on the technologies, and he really is critical on the technologies, and he several times said, "Everyone's trying to manage Kubernetes. Everyone's trying to roll their own version of it," et cetera. So he has a very interesting viewpoint on the Kubernetes world and how that's going...But the announcements out of KubeCon were... They're slowly becoming more standard releases. There are no shockers coming out anymore because the community is maturing. That's really the key message here, is the community is still growing rapidly, unbelievably, but we're starting to see, not even a plateau, but we're starting to get to a top of the curve where we're... The height cycle is not completely there yet but you can definitely see that the technology is mature enough that people are using it, and it's becoming more stable.Now some key announcements out from KubeCon... Actually, before KubeCon actually launched was BitNami, the provider of all the Docker images, and packaged software was purchased by VMware shortly before the conference. And that's pretty big news because BitNami's a nice service. I use them for several different projects, because they package together, for example, Wordpress. They document the heck out of it. They tell you all the ins and outs, where you should look, how you should operate it, how you should grow it. If you want to do high availability... And they maintain it, which is really awesome. It's a great, great product. I recommend if you ever look for an image, check out BitNami Images, 'cause they're very well documented as I said, and they're battle-tested.Another announcement out of KubeCon was Rancher launched Rio. So Rancher launched not so long ago k3s, which is the slimmed-down version of Kubernetes. Now, on top of that, they've launched Rio, which is a micro-platforms and service, based on top of k3s. So it's a micro-platform as a service, and the idea is to get closer to the edge and start bringing more services to the edge. I think it's a brilliant model, and Rancher continually surprises us on the features they keep announcing.But the real shocker here was Microsoft. Microsoft is the one that had all the announcements. First, they announced visual studio code Kubernetes 8... a new Kubernetes extension which is now all supported. It's actually a certified extension, and this is quite big. Visual studio code is now becoming the standard, and now they're really throwing their weight behind creating the toolset to actually support it.The next thing out of Microsoft camp was the virtual cubelet, Hit 1.0. That's basically a server-less Kubernetes distribution. It allows you to run Azure container instances and bringing server-less as a complete package offering within Kubernetes. I find this quite cool. I haven't played with it yet, so it's new to me as well. I'll have to dig into it a little bit more.Helm 3. Helm is obviously the de facto standard for packaging and deploying Kubernetes applications, and Microsoft announced the first alpha of Helm 3. Also a big announcement because they're throwing all their resources behind making RBAC and CRDs, they're making it part of Helm 3, which is what everyone's been asking for.Now what really shook everybody, the biggest announcement from the conference, was Service Mesh Interface, and what that is, is it's a new standard interface across all service meshes. So Istio, Envoy, it doesn't matter the service mesh, but we're going to have a standardized interface to all these. And why is that important? Because all these service meshes popped up so quickly and grew so quickly, they developed their own ecosystems, their own APIs. Now if you're a company that runs several service meshes, you also have to integrate all these different APIs. Well this new service mesh allows us to actually... The Service Mesh Interface really standardizes across all service meshes and allow us to define traffic polices, traffic telemetry, traffic management, across all these different service meshes. If you look at it, it's like standardizing the gas nozzle in cars. Every car has a gas nozzle, but if they're all different, it's a bit difficult to operate. You can obviously operate it, no problem individually, but it'd be much easier if they're all standardized. And that's what SMI is doing. It's really standardizing the Istio interface to make it easier to operate and manage.That's really the KubeCon recap. There was some great news coming out of the ecosystem. The ecosystem's continuing to grow. One of my favorites so far, what I've seen so far is my favorite talk from KubeCon is the Spotify talk, where Spotify talked about on the keynote how they accidentally deleted all its cube clusters in production. Yeah.They deleted... What'd they say, about 50 nodes or something like that? 50-node cluster, and zero user impact. They were actually trying to do a migration from one of their other cloud providers to Google Compute Engine, and it just went horribly wrong. They deleted the cluster, then it walked you through how they recovered, how long it took to recover, how a lot of scripts weren't ready and things were not in place to actually do this recovery, and how they went for it and is learning. And this just shows you the Spotify culture is all about learning and embracing failure, and I think more companies can learn from this as well. It was a brilliant talk, it's really nice to hear somebody, "Hey, we're not doing everything right. We do fail once in a while, and this is how we did it and this is what we learned."It brings us back to the Kubernetes fail stories. The same type of situation, but they're actually talking about KubeCon, and I thought that was quite nice.That's all we have for this episode of The Byte. Look forward to some more episodes coming up. I have a whole queue in my queue to get up and running, so bear with us, have a great day, and we'll see you next episode.

SHOW: 68SHOW OVERVIEW: Brian talks with Rob Szumski (@robszumski, Sr. Manager Product Management @OpenShift) about the evolution of Operators, the emerging capabilities in Kubernetes to support Operators, OperatorHub, Helm Operators and how OpenShift 4 is integrating the Operator experience. SHOW NOTES:Try OpenShift 4 - http://try.openshift.comOperator FrameworkOperatorHub Maturing Operators (Rob’s Keynote at KubeCon 2018)OpenShift Commons - State of Operators OpenShift Commons Gathering - Operator FrameworkDiscussing Operator Framework with Brandon Philips (Eps.33)SHOW TOPICS:Topic 1 - Welcome to the show. Tell us a little about your background, and how you’re involved in Kubernetes operators. Topic 2 - Last year (May 2018) we spoke with Brandon Philips around the launch of Operator Framework. How has the ecosystem around Operators evolved over the last year? Topic 3 - We spoke with Clayton Coleman and Derek Carr about how Operators are now core to the architecture of OpenShift 4, but what role do Operators play for applications running on Kubernetes or OpenShift?Topic 4 - How are complex applications getting turned into Operators? What’s the model to get them engaged with the SDK and Metering frameworks? Topic 5 - How is OpenShift 4 interacting with OperatorHub? FEEDBACK?Email: PodCTL at gmail dot comTwitter: @PodCTLWeb: http://podctl.com

Ann Wallace and Michael Wallman are here today to teach Aja and Mark about Professional Services Organization (PSO) at Google Cloud. PSO is the “post sales” department, helping clients come up with solutions for security, data migration, AI, ML, and more. Listen in to this episode to learn more about the specifics of the PSO! Ann Wallace Ann Wallace is the Global Security Practice Lead for Google PSO. She has spent the last 6 months building out the security practice. Ann is passionate about inclusion in tech. She is the West regional lead for Google Cloud EDII and a volunteer with Women Who Code Portland. Before Google Ann spent 14 years at Nike in various engineering and architecture roles. CloudNOW named her one of the top 10 Women in Cloud in 2015. When not working, Ann can be found ultra-trail running around the world. Michael Wallman Michael Wallman is a TPM, working on Cloud Migration for internal Alphabet companies and acquisitions. He also serves as the America’s infrastructure practice lead. He is in his 3rd year at Google. Prior to Google, Michael is Cloud “OG”, and spent almost 5 years growing the AWS Professional Services organization from 5 to 700+. Before sticking his head in the clouds, Michael helped found 2 start-ups: Aspera and SensysNetworks. Outside of work Michael spends his time chasing his 2 toddlers and mountain lions around the Berkeley Hills. Ann and Michael actually met 5 years ago, working on Nike’s first cloud migration project. This encompassed reverse engineering a custom Perl configuration management system. (Who doesn’t love Perl?) It’s a small cloud world. Cool things of the week Amy built an app that uses Cloud Vision to identify key features of images texted to it link Want to Change the Game? Design your own with Google Play blog Change the Game site The team based game of life app we demoed during the keynote is still up site How we search for bow wows and meows blog Why do cats and dogs…? site Interview G Suite site Chrome site GKE site Kubernetes site Anthos (the new Cloud Services Platform) site Pub/Sub site GCS site GCS Dual-Region Buckets site Grafeas site CRDS site Exploring container security: Digging into Grafeas container image metadata blog CRE site SRE site Cloud Consulting Services site Question of the week How do I cache files between builds in Cloud Build? Cloud Builders Community site Where can you find us next? Mark will be at IO, Open Source in Gaming Day which is co-located with Open Source North America Summit, and CFP. Aja will be online! She has blog posts coming on assessing coding during interviews, using Ruby + GCP for weird stuff, and many other things. Our guests will be at Kubecon EU.

Please welcome our guests this week, Alli and Latasha of IKR! IKR is a podcast for women by women and is associated with Crossroads Church in Cincinnati. We're so excited to have them with us!

Après avoir décrypté quelques mesures de la loi de finances 2019, place maintenant à la loi de financement de la sécurité sociale 2019. Elle a été publiée au journal officiel le 23 décembre dernier, et elle contient évidemment, quelques mesures phares que va analyser et décrypter pour nous, Pascal Lavielle, le responsable du service ingénierie patrimoniale et du support juridique et fiscal de BNP Paribas Cardif. La loi de financement de la sécurité sociale pour 2019 et la loi MUES viennent modifier les prélèvements sociaux, essentiellement pour les retraités, avec une atténuation de la hausse de la CSG. Le taux de droit commun maintenant, est de 8,3 au niveau de la CSG, mais le taux réduit est de 3,8 voire 0% en fonction du revenu fiscal de référence de l'année N - 2. La loi de financement pour la sécurité sociale pour 2019 est donc venue assouplir le passage dans le taux plein de CSG, au taux de 8,3, à la condition qu'il y ait eu franchissement d'un certain seuil, deux années consécutives. Dans le cadre de la loi de financement pour la sécurité sociale de 2019, il y a eu également, une refonte des prélèvements sociaux, pour organiser la répartition entre l'Etat et la sécurité sociale. Ainsi la décomposition des prélèvements sociaux au taux de 17,2 va se faire 7,5% pour l'Etat, 9,7% pour les organismes de sécurité sociale. Il faut savoir qu'en février 2015, Monsieur de Ruyter avait fait un recours en disant qu'il était assujetti sur le revenu du capital à la CSG, CRDS aux prélèvements sociaux, alors qu'il relevait d'une sécurité sociale autre que la sécurité sociale française. Or Monsieur de Ruyter a obtenu gain de cause au niveau du conseil d'Etat de la CGE (même si Il y a eu des jurisprudences qui sont sorties contraires à cet avis). Ainsi, la refonte des prélèvements sociaux s'accompagne d'une mesure qui exonère toutes les personnes qui relèvent d'une caisse de sécurité sociale de l'Union Européenne autre que la France, du taux de 9,7%, c'est-à-dire la CSG et la CRDS. Ces personnes seront néanmoins assujetties au taux de 7,5% qui est affecté à l'état. Vous pouvez retrouver dans nos flashs, les mesures qui nous paraissent importantes : vous trouverez un flash sur la loi de finances, un flash sur la loi de financement de la sécurité sociale qui reprend les mesures relatives aux prélèvements sociaux, ainsi que la loi MUES.

Show: 54Overview: Brian and Tyler talk about how well the industry has created or evolved Kubernetes-Native platforms and services. Show Notes:Topic 1 - We’re more than 3yrs into Kubernetes, and almost at the 2yr anniversary of the 1st big CloudNativeCon / KubeCon in Seattle (we’ll be back again this year). So let’s ask a big question - how has the industry evolved to actually deliver Kubernetes-Native?Topic 2 - What is Kubernetes-Native? Is it specific to containers?Is it specific to Kubernetes scheduling?Is it specific to Kubernetes extensibility?Topic 3 - Was reading a report recently that separated the concepts of DevOps from PlatformOps. We know Developers experiences and expectations are never the same and always evolving. But should the PlatformOps side of things be standardizing on something Kubernetes-native? Topic 4 - What are some of the common things you’ve seen in the Kubernetes community (products, platforms, services) that have gained some traction, but aren’t really aligned to Kubernetes? Most Developer FrameworksCI/CD PipelinesStorage (CSI framework)ITIL ProcessesFeedback?Email: PodCTL at gmail dot comTwitter: @PodCTLWeb: http://podctl.com

Show: 51Show Overview: Brian and Tyler talk about updates to Kubernetes v1.12 Show Notes:Kubernetes 1.12 Updates (Official Kubernetes blog)What’s new in Kubernetes 1.12 (Red Hat CoreOS blog)OpenShift Commons Briefing on October 4 at 9 AM PT to discuss Kubernetes 1.12Operator FrameworkTopic 1 - Kubelet TLS Bootstrap moves to GA - simplify how nodes are securely added/removed into a cluster. As an add-on, server certificate rotation functionality moves into beta, and this will be tied in with Cluster Operators and Application Operators.Topic 2 - Azure Virtual Machine Scale Sets (VMSS) and Cluster-Autoscaler is Now StableTopic 3 - On the network security front, two NetworkPolicy components graduate to GA: egress and ipBlock.Topic 4 - Multi-Tenancy: In this release comes the ability to support priority on the various resource quotas via the new ResourceQuotaScopeSelector feature. This enhances the existing priority and preemption feature that was delivered in Kubernetes 1.11.Topic 5 - CSI now supports the notion of topology awareness and this functionality moves to beta in Kubernetes 1.12. What this means is that stateful workloads can now have a conceptual understanding of where storage resources live, whether it be a rack, datacenter, availability zone, or region.Topic 6 - Kubectl Plugins: With kubectl plugins, developers can engineer extensions to kubectl, which accommodate their administration scenarios, while not being baked into the core kubectl codebase. This is going to allow teams to develop and deliver kubectl functionality faster and in a more consistent manner. (example: OpenShift “oc commands”) Topic 7 - Let’s discuss the upgrading process of Kubernetes (again). Other noteworthy features:Snapshot / restore functionality for Kubernetes and CSI is being introduced as an alpha feature. This provides standardized APIs design (CRDs) and adds PV snapshot/restore support for CSI volume drivers. Improvements that will allow the Horizontal Pod Autoscaler to reach proper size faster are moving to beta. Vertical Scaling of Pods is now in beta, which makes it possible to vary the resource limits on a pod over its lifetime. In particular, this is valuable for pets (i.e., pods that are very costly to destroy and re-create). Encryption at rest via KMS is now in beta. This adds multiple encryption providers, including Google Cloud KMS, Azure Key Vault, AWS KMS, and Hashicorp Vault, that will encrypt data as it is stored to etcd. Feedback?Email: PodCTL at gmail dot comTwitter: @PodCTLWeb: http://podctl.com

Show: 46Show Overview: Brian and Tyler talk with Steve Gordon (@xsgrodon, Principal Product Manager @RedHat) about the intersection of containers, Kubernetes and virtual machines with the KubeVirt project and Container Native Virtualization. Show Notes:KubeVirt - Building a Virtualized API for KubernetesKubevirt-dev Google Group#virtualization on Slack#kubevirt on IRCIntro to Container Native Virtualization (CNV)CNV Demo - Red Hat SummitTopic 1 - Welcome to the show. Tell us about some of the areas you’re focused on these days.Topic 2 - Let’s talk about some of the basics of KubeVirt. How does it work? What problem is this trying to solve?Topic 3 - What are some of the technical challenges that have to be overcome for Kubernetes to understand how to deal with virtual machines?Topic 4 - Looking at the project today, what are some of the things that are possible, and what are some of the goals to add over the next 6 or 12 months?Topic 5 - What has been the feedback you’ve heard from companies as you’ve introduced them to KubeVirt and CNV?Feedback?Email: PodCTL at gmail dot comTwitter: @PodCTLWeb: http://podctl.com

Show: 44Show Overview: Brian and Tyler talk about how Kubernetes has evolved over the last three years, from the community to the technology to new things coming down the road. Show Notes:Kubernetes 3rd AnniversaryTopic 1 - Let’s start with people and community. How have you seen the Kubernetes community evolve over the past 3 years? What’s working well, and where have there been struggles?Topic 2 - Technology-wise, where would you place the highlights for Kubernetes? This could be the technology itself, or how it’s been adopted, or maybe just the overall architecture.Topic 3 - Technology-wise, where would you place the challenges for Kubernetes? This could be the technology itself, or how it’s been adopted, or maybe just the overall architecture.Topic 4 - There seems to be a new chorus of pushback on Kubernetes, around the complexity of managing complex environments (e.g. DR for Stateful apps) and the serverless fans. Do you see this as a problem, a distraction, or valid criticisms?Topic 5 - What do you see making a lot of headlines vs. being the important things for end-users to focus on for the next year?Feedback?Email: PodCTL at gmail dot comTwitter: @PodCTLWeb: http://podctl.com

One of the most interesting announcements from Google Cloud Next was Knative, a framework for building serverless products on top of Kubernetes. Craig and Adam talk to Google Director of Product Management, Oren Teich, about the launch. Do you have something cool to share? Some questions? Let us know: web: kubernetespodcast.com mail: kubernetespodcast@google.com twitter: @kubernetespod News of the week Google’s Cloud Services Platform: Recapping GKE On-Prem and Knative Cloud Services Platform session video with Chen Goldberg and Aparna Sinha Google Cloud Build GitHub integration Knative analysis: Joe Beda’s TGI Kubernetes on Knative Using the Knative build system by itself Visual descriptions: Kubernetes: the theme park analogy The Kubernetes Comic Kubernetes blog posts: KubeVirt: Extending Kubernetes with CRDs for Virtualized Workloads Feature highlight: CPU Manager Links from the interview Oren Teich on Twitter About Knative: Launch blog post Knative page at Google Cloud GitHub Slack Google Cloud Next videos: Serverless at Google Cloud, with Oren Teich High-level video intro to GKE Serverless add-on and Knative, with DeWitt Clinton and Ryan Gregg Request early access to the Serverless add-on for GKE Developer video intro to Knative, with Ville “Fifth Beatle” Aikas and Mark Chmarny Mark’s Knative samples IBM “Zed Series”

Show: 41Show Overview: Brian and Tyler talk about the new Kubernetes 1.11 release, the new features and capabilities. Show Notes:Kubernetes 1.11 ReleaseKubernetes 1.11 - Custom Resources, Pod Priority & Preemption, and moreKubernetes Ramps Up Custom Resource DefinitionsTopic 1 - Let’s review for anybody that’s a new listener how the Kubernetes community identifies the maturity level of features and how they should consider interpreting those classifications.Topic 2 - Kubernetes release usually have a few new GA features, and then lots of Beta or Tech Preview features. What were the highlights of this release for you, or some of the core areas you suggest people focus on?Topic 3 - Let’s walk through some of the most mentioned capabilities:IPVS-Based In-Cluster Service Load Balancing Graduates to General Availability CoreDNS Promoted to General AvailabilityDynamic Kubelet Configuration Moves to Beta Custom Resource Definitions Can Now Define Multiple Versions Resizing Persistent Volumes using KubernetesFeedback?Email: PodCTL at gmail dot comTwitter: @PodCTLWeb: http://podctl.com