Podcasts about mongodb atlas

In this episode of MongoDB TV, join Shane McAllister along with MongoDB experts Sabina Friden and Frank Sun as they explore the powerful observability suite within MongoDB Atlas. Discover how these tools can help you optimize database performance, reduce costs, and ensure reliability for your applications. From customizable alerts and query insights to performance advisors and seamless integrations with enterprise tools like Datadog and Prometheus, this episode covers it all. Whether you're a developer, database administrator, or just getting started with MongoDB, learn how to leverage these observability tools to gain deep insights into your database operations and improve your application's efficiency. Tune in for a live demo showcasing how MongoDB's observability suite can transform your database management experience. Perfect for anyone looking to enhance their MongoDB skills and take their database performance to the next level.

In this episode of Flying High with Flutter, we're joined by Arek Borucki, author of MongoDB in Action, Third Edition and a seasoned Principal Database Engineer. Arek shares his journey with MongoDB, discusses running databases on Kubernetes, and compares MongoDB to other databases. We also explore MongoDB 8's latest features, ACID compliance, and when MongoDB might not be the right choice. Plus, Arek dives into MongoDB Atlas, Atlas CLI, and how to get started with these powerful tools.

In this engaging discussion, Evin Roesle, Lead Product Manager at MongoDB, shares valuable insights about the importance of backups and the latest features of Ops Manager. Recorded live at MongoDB Local London, Evin discusses the newly announced Ops Manager 8.0, which enhances backup automation and management for both on-premise and cloud deployments. Learn about the critical aspects developers need to consider regarding backups in MongoDB Atlas, including point-in-time recovery, scheduling, and compliance policies. Whether you're a developer or an IT professional, this video provides essential knowledge to help you safeguard your data effectively. Don't miss out on these expert tips!

Register here for AWS re:Invent 2024, Dec 2-6, Las Vegas, NV-------Benjamin Flast, Director, Product Management at MongoDB discusses vector search capabilities, integration with AWS Bedrock, and its transformative role in enabling scalable, efficient, and AI-powered solutions.Topics Include:Introduction to MongoDB's vector search and AWS BedrockCore concepts of vectors and embeddings explainedHigh-dimensional space and vector similarity overviewEmbedding model use in vector creationImportance of distance functions in vector relationsVector search uses k-nearest neighbor algorithmEuclidean, Cosine, and Dot Product similarity functionsApplications for different similarity functions discussedLarge language models and vector search explainedIntroduction to retrieval-augmented generation (RAG)Combining external data with LLMs in RAGMongoDB's document model for flexible data storageMongoDB Atlas platform capabilities overviewUnified interface for MongoDB document modelApproximate nearest neighbor search for efficiencyVector indexing in MongoDB for fast queryingSearch nodes for scalable vector search processingMongoDB AI integrations with third-party librariesSemantic caching for efficient response retrievalMongoDB's private link support on AWS BedrockFuture potential of vector search and RAG applicationsExample use case: Metaphor Data's data catalogExample use case: Okta's conversational interfaceExample use case: Delivery Hero product recommendationsFinal takeaways on MongoDB Atlas vector searchParticipants:Benjamin Flast - Director, Product Management, MongoDBSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

In this episode, we catch up with Igor, Principal Partner Solutions Architect from AWS, as he shares insights on the collaboration between AWS and MongoDB. With a focus on enhancing developer experiences, we discuss the latest advancements in Amazon Q Developer, AI-driven migration and modernization tools, and the integration of MongoDB Atlas with AWS services.

MongoDB Atlas is a managed NoSQL database that uses JSON-like documents with optional schemas. The platform recently released new vector search capabilities to facilitate building AI capabilities. Ben Flast is the Director of Product Management at MongoDB. He joins the show to talk about the company's developments with vector search. This episode is hosted by The post MongoDB Vector Search with Ben Flast appeared first on Software Engineering Daily.

MongoDB Atlas is a managed NoSQL database that uses JSON-like documents with optional schemas. The platform recently released new vector search capabilities to facilitate building AI capabilities. Ben Flast is the Director of Product Management at MongoDB. He joins the show to talk about the company’s developments with vector search. This episode is hosted by The post MongoDB Vector Search with Ben Flast appeared first on Software Engineering Daily.

No episódio de hoje, falaremos sobre as melhores práticas para garantir a segurança dos seus dados no MongoDB Atlas. Vamos discutir as funcionalidades de segurança oferecidas pela plataforma, desde autenticação e controle de acesso até criptografia e monitoramento. Você vai aprender a implementar estratégias eficazes para proteger suas informações e manter a integridade do seu banco de dados. Além disso, trouxemos cases de sucesso e dicas práticas que você pode aplicar imediatamente. Não perca, junte-se a nós e descubra como manter seus dados seguros no mundo digital! Quer saber mais? Acesse: mdb.link/FM00026

MongoDB Podcast Episode with customer (Pankaj Prasad & Vijai Anand from Airwave) to discuss Airwave, how they are using MongoDB Atlas to support their RAG/AI chatbot application and why they decided to migrate to Atlas + replace their existing vector database.

In deze podcastaflevering ontvangen Jan en Ronald Simon Koudijs, Technical Product Manager bij ShipitSmarter. Simon duikt diep in de wereld van Kubernetes en GitOps, waarbij hij essentiële tips en best practices deelt voor een succesvolle implementatie en beheer.Simon opent het gesprek met een cruciale overweging bij het gebruik van operators voor Kubernetes-clusters. Hij legt uit dat een zorgvuldige afweging van workloads en het gebruik van GitOps cruciaal is voor een efficiënte applicatiebeheer. Met GitOps kun je je infrastructuur en applicaties op een declaratieve manier beheren, wat zorgt voor consistentie en eenvoud in het deploymentproces.Daarnaast bespreekt Simon de recente updates van ArgoCD, die nu de mogelijkheid biedt om applicaties in aparte namespaces te plaatsen. Dit vergemakkelijkt een betere scheiding en organisatie van klantapplicaties, en voorkomt veelvoorkomende problemen bij eerdere deploys in de standaard namespaces.Verder gaat Simon in op de integratie van MongoDB Atlas met Terraform via HashiCorp-modules. Deze combinatie biedt een krachtige manier om MongoDB efficiënt te beheren. Hoewel zijn team momenteel nog aan Terraform vasthoudt, overweegt hij een toekomstige overstap naar OpenTofu als een open-source alternatief.Simon deelt ook waardevolle GitHub-tips, zoals het “Archive on Deletion”-beleid, waarmee je repositories kunt archiveren in plaats van direct te verwijderen. Dit biedt extra veiligheid en flexibiliteit, vooral voor testomgevingen en langdurige opslag.Tune in voor deze informatieve aflevering vol strategische inzichten en praktische adviezen!ShipitSmarter - Effective shippingStuur ons een bericht.

Neste episódio mergulhamos no fascinante mundo do Atlas Vector Search e exploramos como esta poderosa ferramenta está revolucionando a forma como interagimos com dados. Vamos além da tradicional barra de busca para descobrir como as buscas vetoriais estão transformando a experiência do usuário e permitindo uma recuperação de informações mais eficiente e precisa.Nosso especialista convidado, Eluizio Barretto, compartilha insights sobre a tecnologia por trás do Atlas Vector Search, discutem suas aplicações práticas em diversos setores e oferecem dicas valiosas sobre como implementar e otimizar essa funcionalidade nas suas próprias soluções com MongoDB Atlas. Seja você um desenvolvedor, arquiteto de dados ou entusiasta de tecnologia, este episódio é essencial para quem deseja estar na vanguarda das inovações em busca e recuperação de dados.Não perca essa oportunidade de aprender como o Atlas Vector Search pode levar suas aplicações a um novo patamar, oferecendo uma experiência de busca mais intuitiva e poderosa. Quer saber mais? Acesse: mdb.link/FM00022

No episódio de hoje do Fala MongoDB, mergulhamos no caso de uso da Clearsale, uma empresa líder em soluções de prevenção a fraudes. Descubra como a Clearsale utiliza o MongoDB Atlas para aprimorar seus processos de detecção de fraudes, garantindo maior segurança e eficiência em suas operações de alto volume de dados. Conversamos com Thiago Cabral, Diretor de Tecnologia da Informação da Clearsale, sobre os desafios enfrentados, as soluções implementadas e os resultados alcançados. Este episódio é imperdível para quem deseja entender o papel crucial que o MongoDB Atlas desempenha na proteção contra fraudes e como ele pode transformar a segurança em diversas indústrias.

Descubra como aproveitar ao máximo as capacidades de análise de dados da plataforma líder em banco de dados NoSQL. Neste episódio, compartilhamos insights valiosos sobre como utilizar o Atlas para análises avançadas, integrando dados de diferentes fontes e obtendo inteligência acionável para impulsionar sua tomada de decisão. Se você está buscando extrair o máximo valor dos seus dados com eficiência e escalabilidade, este episódio é para você! Quer saber mais? Acesse: mdb.link/FM00019

Join us in this enlightening episode of the MongoDB Podcast as we sit down with Viraj Thakrar, a distinguished MongoDB Community Creator. We delve into Viraj's fascinating journey as a MongoDB enthusiast and explore the depths of his recent presentation on "Unified Workloads with AWS and MongoDB" at the AWS Community Day. This episode promises to shed light on the integration of MongoDB with AWS, discussing why unified workloads are essential for modern applications, and revealing the intricacies and advantages of MongoDB Atlas within the AWS ecosystem. Whether you're a developer, a database administrator, or just a technology enthusiast, this conversation will provide valuable insights into leveraging MongoDB for efficient, scalable, and secure applications in the cloud.

Join us for an episode of the MongoDB Podcast featuring Shrey Batra, founder of Cosmo Cloud and a MongoDB Community member. With extensive experience in software development, Shrey discusses the creation of Cosmo Cloud—a no-code platform for backend development, emphasizing how it enhances developer productivity through features like instant deployments and integration with MongoDB Atlas. This conversation delves into the challenges of transitioning from developer to entrepreneur, the role of AI in future software development, and the importance of community engagement. Shrey's insights offer valuable lessons for developers and tech enthusiasts alike.

Join us in this enlightening episode of the MongoDB Podcast as we sit down with Ricardo Mello, a distinguished developer within the MongoDB community. Dive deep into Ricardo's fascinating journey into MongoDB, from his initial steps to becoming a pivotal part of the community. In our conversation, we explore the intricacies of deploying MongoDB Atlas instances, the strategic importance of replication for data consistency, and the potential for local on-premise instances. Ricardo shares his personal insights on overcoming challenges, engaging with public speaking, and his valuable contributions through the Guest Author Program. Whether you're a seasoned MongoDB user or just starting out, Ricardo's experiences and advice offer a wealth of knowledge on navigating the MongoDB landscape, embracing community, and the power of sharing knowledge. Tune in to discover how to leverage MongoDB for your projects, learn best practices, and get inspired by the journey of a fellow MongoDB enthusiast.Links:https://mdb.link//community-ji2RxQKkKwwhttps://medium.com/predict/understanding-mongodb-replication-a-step-by-step-tutorial-on-building-a-replica-set-cluster-b4267e4e2737https://medium.com/predict/mongodb-compass-optimizing-performance-with-indexes-and-explain-plan-3fc15914a4a7https://itnext.io/mongodb-relational-migrator-e84c49220cefhttps://itnext.io/mongodb-atlas-charts-importing-json-file-and-crafting-powerful-visualizations-915e20759a89

In this episode, we dive into the world of generative AI and its impact on the tech industry with a special focus on DocsGPT, an innovative open-source documentation assistant developed by Arc53. Our guest, Alex Tushynski (alex@arc53.com), co-founder of Arc53, will discuss the journey from conception to implementation of DocsGPT, how MongoDB Atlas has been instrumental in this process, and the future of AI in enhancing user experiences.

Join us as we delve into the innovative world of AI with Gradient and MongoDB Atlas. We'll discuss how Gradient's Accelerator Blocks, combined with MongoDB Atlas's capabilities, are simplifying and enhancing AI development. Learn about the integration of these technologies and their impact on various industries, particularly finance and healthcare.Key Themes:Introduction to Gradient's Accelerator BlocksIntegration with MongoDB Atlas and its BenefitsImpact on AI Development Speed and Cost-EfficiencyApplications in Finance and HealthcareResources:Building AI With MongoDB: How Gradient Accelerator Blocks Take You From Zero To AI in Seconds

Join us for a fascinating conversation with Yelena Shtykel, Head of Public Cloud Data at Citi, in this episode of the MongoDB Podcast. Yelena shares her journey from a full-stack developer to leading public cloud data initiatives, focusing on diverse cloud service providers and the complexities of handling data in a large organization like Citi. She delves into the challenges of cloud adoption, cost optimization, the role of MongoDB Atlas in Citi's infrastructure, and the importance of partnership in technology. Yelena also discusses her strategies for staying updated in the fast-paced tech world and her perspectives on generative AI. Tune in for insightful lessons and experiences from a leader in cloud data management.

In this podcast, Krish explores the various connectors available in Confluent Cloud. He starts by recapping the previous podcasts and the basics of Confluent Cloud. Krish then focuses on connectors, explaining their value and why they can reduce the need for writing code. He explores different connectors, such as the data gen source connector and the MongoDB Atlas connectors. Krish also discusses different data formats, including Avro, Protobuf, and JSON. He briefly touches on implementing custom connectors. Krish explores the topic of connectors in Confluent Cloud. He discusses the process of creating connectors and the different types of connectors available. Krish also delves into configuring connectors and defining configuration parameters. He explores the concept of custom connector configuration and the use of connector properties files. Krish then explores existing connectors, such as the HTTP source and sync connectors, and discusses the process of publishing custom connectors. He concludes by mentioning the Confluent CLI for managing connectors. Takeaways Connectors in Confluent Cloud provide value by reducing the need for writing code. Different connectors are available for various data sources and destinations, such as MongoDB, Amazon S3, and Elasticsearch. Data formats like Avro, Protobuf, and JSON can be used with connectors. Implementing custom connectors allows for more flexibility and integration with specific systems. Connectors enable seamless data integration and propagation between different systems. Connectors in Confluent Cloud allow for seamless integration with various systems and services. Custom connectors can be created and published to Confluent Cloud. Configuration parameters for connectors can be defined and managed. The Confluent CLI provides a command-line interface for managing connectors. Chapters 00:00 Introduction 00:35 Recap of Previous Podcasts 01:05 Focus on Connectors in Confluent Cloud 02:16 Exploring Data Gen Source Connector 03:43 Different Formats: Avro, Protobuf, JSON 08:07 Differences Between Avro and Protobuf 10:03 Exploring Other Connectors 11:14 Using MongoDB Atlas Connectors 12:08 Testing Different Formats with Connectors 13:36 Handling Avro Format with Consumer 16:58 Exploring More Connectors: Snowflake, Amazon S3, Elasticsearch 20:33 Implementing Custom Connectors 27:31 Exploring More Connectors: Salesforce, Oracle, Jira 35:16 Exploring More Connectors: SQL Server, MySQL 38:43 Implementing Custom Connectors 43:24 Exploring More Connectors: Kafka, File 46:20 Understanding Connector Implementation 49:06 Creating Custom Connectors 50:00 Summary and Conclusion 50:59 Creating Connectors 52:04 Configuring Connectors 54:00 Custom Connector Configuration 56:08 Defining Configuration Parameters 57:38 Configuration Properties 59:49 Self-Managed Connectors 01:00: 27 Connector Properties File 01:01:28 Creating Custom Connectors 01:02: 09 Publishing Custom Connectors 01:03: 37Existing Connectors 01:04: 14HTTP Source Connector 01:06:40 HTTP Sync Connector 01:08:34 Other Connectors 01:10:34 Managing Connectors 01:12:14 Confluent CLI Snowpal Products Backends as Services on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AWS Marketplace⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Mobile Apps on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠App Store⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Play Store⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Web App⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Education Platform⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for Learners and Course Creators

Après un grave incident de sécurité qui a touché l'éditeur de jeux vidéo Insomniac Games début décembre, Ubisoft vient à son tour d'échapper de justesse à une situation similaire. Le studio français, célèbre pour ses succès tels que Assassin's Creed, Rayman, FarCry, et plus récemment Avatar : Frontiers of Pandora, a réussi à contrecarrer une tentative de piratage massif.C'est le 20 décembre, que l'entreprise est visée par une attaque semblable à celle subie par Insomniac Games. Les hackers tentent alors de dérober 900 Go de données, comprenant des informations liées aux utilisateurs d'un de ses jeux phares. Sans entrer dans les détails, l'entreprise a ouvert une enquête afin de faire la lumière sur toute cette histoire. Reste une question en suspens : que voulaient voler les pirates précisément et que s'est-il exactement passé ?Dans le détail, des hackers affiliés à une entité actuellement inconnu n'ayant pas revendiqué l'attaque, ont réussi à pénétrer dans les systèmes d'Ubisoft et à s'y maintenir pendant près de 48 heures. Les pirates ont clairement fait savoir qu'ils étaient sérieux en publiant des captures d'écran de leur intrusion, démontrant leur accès au serveur Ubisoft SharePoint, au logiciel de travail collaboratif Confluence, aux conversations sur Microsoft Teams, ainsi qu'au service cloud MongoDB Atlas. À ce stade, on ignore comment les pirates ont réussi à s'infiltrer dans le système. Ce qui est certain, c'est qu'ils cherchaient à obtenir les données des utilisateurs de Rainbow Six Siege, mais leur tentative a heureusement échoué. Ubisoft a donc réussi à sécuriser ses systèmes à temps. A ce stade, vous vous dites peut-être : c'est tout ? Et bien oui, malheureusement. Une enquête pour retracer le parcours des hackeurs et découvrir leur identité est en cours. Davantage d'informations devraient être dévoilées une fois qu'Ubisoft aura progressé dans ses recherches.   Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Après un grave incident de sécurité qui a touché l'éditeur de jeux vidéo Insomniac Games début décembre, Ubisoft vient à son tour d'échapper de justesse à une situation similaire. Le studio français, célèbre pour ses succès tels que Assassin's Creed, Rayman, FarCry, et plus récemment Avatar : Frontiers of Pandora, a réussi à contrecarrer une tentative de piratage massif. C'est le 20 décembre, que l'entreprise est visée par une attaque semblable à celle subie par Insomniac Games. Les hackers tentent alors de dérober 900 Go de données, comprenant des informations liées aux utilisateurs d'un de ses jeux phares. Sans entrer dans les détails, l'entreprise a ouvert une enquête afin de faire la lumière sur toute cette histoire. Reste une question en suspens : que voulaient voler les pirates précisément et que s'est-il exactement passé ? Dans le détail, des hackers affiliés à une entité actuellement inconnu n'ayant pas revendiqué l'attaque, ont réussi à pénétrer dans les systèmes d'Ubisoft et à s'y maintenir pendant près de 48 heures. Les pirates ont clairement fait savoir qu'ils étaient sérieux en publiant des captures d'écran de leur intrusion, démontrant leur accès au serveur Ubisoft SharePoint, au logiciel de travail collaboratif Confluence, aux conversations sur Microsoft Teams, ainsi qu'au service cloud MongoDB Atlas. À ce stade, on ignore comment les pirates ont réussi à s'infiltrer dans le système. Ce qui est certain, c'est qu'ils cherchaient à obtenir les données des utilisateurs de Rainbow Six Siege, mais leur tentative a heureusement échoué. Ubisoft a donc réussi à sécuriser ses systèmes à temps. A ce stade, vous vous dites peut-être : c'est tout ? Et bien oui, malheureusement. Une enquête pour retracer le parcours des hackeurs et découvrir leur identité est en cours. Davantage d'informations devraient être dévoilées une fois qu'Ubisoft aura progressé dans ses recherches.   Learn more about your ad choices. Visit megaphone.fm/adchoices

Neste episódio falaremos sobre como começar a usar o MongoDB Atlas através da camada gratuita disponível - sem a necessidade de cadastrar cartão de crédito para aproveitar da nossa tecnologia! Descubra como avançar do nível gratuito para os níveis mais avançados e descubra mais sobre MongoDB Atlas. Quer saber mais sobre MongoDB? Acesse https://mdb.link/FM0007

Durante a conversa com William Lino, DBRE no C6 Bank, você poderá entender os principais motivos de MongoDB Atlas ser a melhor escolha para ambientes corporativos críticos. Quer conhecer outros casos de uso MongoDB? Acesse https://mdb.link/FM0006.

Peder Ulander, Chief Marketing & Strategy Officer at MongoDB, joins Corey on Screaming in the Cloud to discuss how MongoDB is paving the way for innovation. Corey and Peder discuss how Peder made the decision to go from working at Amazon to MongoDB, and Peder explains how MongoDB is seeking to differentiate itself by making it easier for developers to innovate without friction. Peder also describes why he feels databases are more ubiquitous than people realize, and what it truly takes to win the hearts and minds of developers. About Peder Peder Ulander, the maestro of marketing mayhem at MongoDB, juggles strategies like a tech wizard on caffeine. As the Chief Marketing & Strategy Officer, he battles buzzwords, slays jargon dragons, and tends to developers with a wink. From pioneering Amazon's cloud heyday as Director of Enterprise and Developer Solutions Marketing to leading the brand behind cloud.com's insurgency, Peder's built a legacy as the swashbuckler of software, leaving a trail of market disruptions one vibrant outfit at a time. Peder is the Scarlett Johansson of tech marketing — always looking forward, always picking the edgy roles that drive what's next in technology.Links Referenced:MongoDB: https://mongodb.com 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: Welcome to Screaming in the Cloud. I'm Corey Quinn. This promoted guest episode of Screaming in the Cloud is brought to us by my friends and yours at MongoDB, and into my veritable verbal grist mill, they have sent Peder Ulander, their Chief Marketing Officer. Peder, an absolute pleasure to talk to you again.Peder: Always good to see you, Corey. Thanks for having me.Corey: So, once upon a time, you worked in marketing over at AWS, and then you transitioned off to Mongo to, again, work in marketing. Imagine that. Almost like there's a narrative arc to your career. A lot of things change when you change companies, but before we dive into things, I just want to call out that you're a bit of an aberration in that every single person that I have spoken to who has worked within your org has nothing but good things to say about you, which means you are incredibly effective at silencing dissent. Good work.Peder: Or it just shows that I'm a good marketer and make sure that we paint the right picture that the world needs to see.Corey: Exactly. “Do you have any proof of you being a great person to work for?” “No, just word of mouth,” and everyone, “Ah, that's how marketing works.”Peder: Exactly. See, I'm glad you picked up somewhere.Corey: So, let's dive into that a little bit. Why would you leave AWS to go work at Mongo. Again, my usual snark and sarcasm would come up with a half dozen different answers, each more offensive than the last. Let's be serious for a second. At AWS, there's an incredibly powerful engine that drives so much stuff, and the breadth is enormous.MongoDB, despite an increasingly broad catalog of offerings, is nowhere near that level of just universal applicability. Your product strategy is not a Post-It note with the word ‘yes' written on it. There are things that you do across the board, but they all revolve around databases.Peder: Yeah. So, going back prior to MongoDB, I think you know, at AWS, I was across a number of different things, from the developer ecosystem, to the enterprise transformation, to the open-source work, et cetera, et cetera. And being privy to how customers were adopting technology to change their business or change the experiences that they were delivering to their customers or increase the value of the applications that they built, you know, there was a common thread of something that fundamentally needed to change. And I like to go back to just the evolution of tech in that sense. We could talk about going from physical on-prem systems to now we're distributed in the cloud. You could talk about application constructs that started as big fat monolithic apps that moved to virtual, then microservices, and now functions.Or you think about networking, we've gone from fixed wire line, to network edge, and cellular, and what have you. All of the tech stack has changed with the exception of one layer, and that's the data layer. And I think for the last 20 years, what's been in place has worked okay, but we're now meeting this new level of scale, this new level of reach, where the old systems are not what's going to be what the new systems are built on, or the new experiences are built on. And as I was approached by MongoDB, I kind of sat back and said, “You know, I'm super happy at AWS. I love the learning, I love the people, I love the space I was in, but if I were to put my crystal ball together”—here's a Bezos statement of looking around corners—“The data space is probably one of the biggest spaces ripe for disruption and opportunity, and I think Mongo is in an incredible position to go take advantage of that.”Corey: I mean, there's an easy number of jokes to make about AmazonBasics MongoDB, which is my disparaging name for their DocumentDB first-party offering. And for a time, it really felt like AWS's perspective toward its partners was one of outright hostility, if not antagonism. But that narrative no longer holds true in 2023. There's been a definite shift. And to be direct, part of the reason that I believe that is the things you have said both personally and professionally in your role as CMO of Mongo that has caused me to reevaluate this because despite all of your faults—a counted list of which I can provide you after the show—Peder: [laugh].Corey: You do not say things that you do not believe to be true.Peder: Correct.Corey: So, something has changed. What is it?Peder: So, I think there's an element of coopetition, right? So, I would go as far as to say the media loved to sensationalize—actually even the venture community—loved to sensationalize the screen scraping stripping of open-source communities that Amazon represented a number of years ago. The reality was their intent was pretty simple. They built an incredibly amazing IT stack, and they wanted to run whatever applications and software were important to their customers. And when you think about that, the majority of systems today, people want to run open-source because it removes friction, it removes cost, it enables them to go do cool new things, and be on the bleeding edge of technology.And Amazon did their best to work with the top open-source projects in the world to make it available to their customers. Now, for the commercial vendors that are leaning into this space, that obviously does present itself threat, right? And we've seen that along a number of the cohorts of whether you want to call it single-vendor open-source or companies that have a heavy, vested interest in seeing the success of their enterprise stack match the success of the open-source stack. And that's, I think, where media, analysts, venture, all kind of jumped on the bandwagon of not really, kind of, painting that bigger picture for the future. I think today when I look at Amazon—and candidly, it'll be any of the hyperscalers; they all have a clone of our database—it's an entry point. They're running just the raw open-source operational database capabilities that we have in our community edition and making that available to customers.We believe there's a bigger value in going beyond just that database and introducing, you know, anything from the distributed zones to what we do around vector search to what we do around stream processing, and encryption and all of these advanced features and capabilities that enable our customers to scale rapidly on our platform. And the dependency on delivering that is with the hyperscalers, so that's where that coopetition comes in, and that becomes really important for us when we're casting our web to engage with some of the world's largest customers out there. But interestingly enough, we become a big drag of services for an AWS or any of the other hyperscalers out there, meaning that for every dollar that goes to a MongoDB, there's, you know, three, five, ten dollars that goes to these hyperscalers. And so, they're very active in working with us to ensure that, you know, we have fair and competing offers in the marketplace, that they're promoting us through their own marketplace as well as their own channels, and that we're working together to further the success of our customers.Corey: When you take a look at the exciting things that are happening at the data layer—because you mentioned that we haven't really seen significant innovation in that space for a while—one of the things that I see happening is with the rise of Generative AI, which requires very special math that can only be handled by very special types of computers. I'm seeing at least a temporary inversion in what has traditionally been thought of as data gravity, whereas it's easier to move compute close to the data, but in this case, since the compute only lives in the, um, sparkling us-east-1 regions of Virginia, otherwise, it's just generic, sparkling expensive computers, great, you have to effectively move the mountain to Mohammed, so to speak. So, in that context, what else is happening that is driving innovation in the data space right now?Peder: Yeah, yeah. I love your analogy of, move the mountain of Mohammed because that's actually how we look at the opportunity in the whole Generative AI movement. There are a lot of tools and capabilities out there, whether we're looking at code generation tools, LLM modeling vendors, some of the other vector database companies that are out there, and they're all built on the premise of, bring your data to my tool. And I actually think that's a flawed strategy. I think that these are things that are going to be features in core application databases or operational databases, and it's going to be dependent on the reach and breadth of that database, and the integrations with all of these AI tools that will define the victor going forward.And I think that's been a big core part of our platform. When we look at Atlas—111 availability zones across all three hyperscalers with a single, unified, you know, interface—we're actually able to have the customers keep their operational data where it's most important to them and then apply the tools of the hyperscalers or the partners where it makes the most sense without moving the data, right? So, you don't actually have to move the mountain to Mohammed. We're literally building an experience where those that are running on MongoDB and have been running on MongoDB can gain advantage of these new tools and capabilities instantly, without having to change anything in their architectures or how they're building their applications.Corey: There was a somewhat over-excited… I guess, over-focus in the space of vector databases because whatever those are—which involves math, and I am in no way shape, or form smart enough to grasp the nuances thereof, but everyone assures me that it's necessary for Generative AI and machine learning and yadda, yadda, yadda. So, when in doubt, when I'm confronted by things I don't fully understand, I turn to people who do. And the almost universal consensus that I have picked up from people who track databases for a living—as opposed to my own role of inappropriately using everything in the world except databases as a database—is that vector is very much a feature, not a core database type.Peder: Correct. The best way to think about it—I mean, databases in general, they're dealing with structured and unstructured data, and generally, especially when you're doing searches or relevance, you're limited to the fact that those things in the rows and the columns or in the documents is text, right? And the reality is, there's a whole host of information that can be found in metadata, in images, in sounds, in all of these other sources that were stored as individual files but unsearchable. Vector, vectorization, and vector embeddings actually enable you to take things far beyond the text and numbers that you traditionally were searching against and actually apply more, kind of, intelligence to it, or apply sounds or apply sme—you know, you can vectorize smells to some extent. And what that does is it actually creates a more pleasing slash relevant experience for how you're actually building the engagements with your customers.Now, I'll make it a little more simple because that was trying to define vectors, which as you know, is not the easiest thing. But imagine being able to vectorize—let's say I'm a car company—we're actually working with a car company on this—and you're able to store all of the audio files of cars that are showing certain diagnostic issues—the putters and the spurts and the pings and the pangs—and you can actually now isolate these sounds and apply them directly to the problem and resolution for the mechanics that are working on them. Using all of this stuff together, now you actually have a faster time to resolution. You don't want mechanics knowing the mechanics of vectors in that sense, right, so you build an application that abstracts all of that complexity. You don't require them to go through PDFs of data and find all of the options for fixing this stuff.The relevance comes back and says, “Yes, we've seen that sound 20 times across this vehicle. Here's how you fix it.” Right? And that cuts significant amount of time, cost, efficiency, and complexity for those auto mechanics. That is such a big push forward, I think, from a technology perspective, on what the true promise of some of these new capabilities are, and why I get excited about what we're doing with vector and how we're enabling our customers to, you know, kind of recreate experiences in a way that are more human, more relevant.Corey: Now, I have to say that of course you're going to say nice things about your capabilities where vector is concerned. You would be failing in your job if you did not. So, I feel like I can safely discount every positive thing that you say about Mongo's positioning in the vector space and instead turn to, you know, third parties with no formalized relationship with you. Yesterday, Retool's State of AI report came across my desk. I am a very happy Retool customer. They've been a periodic sponsor, from time-to-time, of my ridiculous nonsense, which is neither here nor there, but I want to disclaim the relationship.And they had a Gartner Magic Quadrant equivalent that on one axis had Net Promoter Score—NPS, which is one of your people's kinds of things—and the other was popularity. And Mongo was so far up and to the right that it was almost hilarious compared to every other entrant in the space. That is a positioning that I do not believe it is possible to market your way into directly. This is something that people who are actually doing these things have to use the product, and it has to stand up. Mongo is clearly effective at doing this in a way that other entrants aren't. Why?Peder: Yeah, that's a good question. I think a big part of that goes back to the earlier statement I made that vector databases or vector technology, it's a feature, it's not a separate thing, right? And when I think about all of the new entrants, they're creating a new model where now you have to move your data out of your operational database and into their tool to get an answer and then push back in. The complexity, the integrations, the capabilities, it just slows everything down, right? And I think when you look at MongoDB's approach to take this developer data platform vision of getting all of the core tools that developers need to build compelling applications with from a data perspective, integrating it into one seamless experience, we're able to basically bring classic operational database capabilities, classic text search type capabilities, embed the vector search capabilities as well, it actually creates a richer platform and experience without all of that complexity that's associated with bolt-on sidecar Gen AI tool or vector database.Corey: I would say that that's one of those things that, again, can only really be credibly proven by what the market actually does, as opposed to, you know, lip-sticking the heck out of a pig and hoping that people don't dig too deeply into what you're saying. It's definitely something we're seeing adoption of.Peder: Yeah, I mean, this kind of goes to some of the stuff, you know, you pointed out, the Retool thing. This is not something you can market your way into. This is something that, you know, users are going to dictate the winners in this space, the developers, they're going to dictate the winners in the space. And so, what do you have to do to win the hearts and minds of developers, you have to make the tech extremely approachable, it's got to be scalable to meet their needs, not a lot of friction involved in learning these new capabilities and applying it to all of the stuff that has come before. All of these things put together, really focusing on that developer experience, I mean, that goes to the core of the MongoDB ethos.I mean, this is who we were when we started the company so long ago, and it's continued to drive the innovation that we do in the platform. And I think this is just yet again, another example of focusing on developer needs, making it super engaging and useful, removing the friction, and enabling them to just go create new things. That's what makes it so fun. And so when, you know, as a marketer, and I get the Retool chart across my desk, we haven't been pitching them, we haven't been marketing to them, we haven't tried to influence this stuff, so knowing that this is a true, unbiased audience, actually is pretty cool to see. To your point, it was surprising how far up and to the right that we sat, given, you know, where we were in just—we launched this thing… six months ago? We launched it in June. The amount of customers that have signed up, are using it, and engaged with us on moving forward has been absolutely amazing.Corey: I think that there has been so much that gets lost in the noise of marketing. My approach has always been to cut through so much of it—that I think AWS has always done very well with—is—almost at their detriment these days—but if you get on stage, you can say whatever you want about your company's product, and I will, naturally and lovingly, make fun of whatever it is that you say. But when you have a customer coming on stage and saying, “This is how we are using the thing that they have built to solve a very specific business problem that was causing us pain,” then I shut up, and I listen because it's very hard to wind up dismissing that without being an outright jerk about things. I think the failure mode of that is, taken too far, you lose the ability to tell your own story in a coherent way, and it becomes a crutch that becomes very hard to get rid of. But the proof is really in the pudding.For me, like, the old jokes about—in the early teens—where MongoDB would periodically lose data as configured by default. Like, “MongoDB. It's Snapchat for databases.” Hilarious joke at the time, but it really has worn thin. That's like being angry about what Microsoft did in 2005 and 2006. It's like, “Yeah, okay, you have a point, but it is also ancient history, and at some point you need to get with the modern era, get with the program.”And I think that seeing the success and breadth of MongoDB that I do—you are in virtually every customer that I talk to, in some way, shape, or form—and seeing what it is that they're doing with you folks, it is clear that you are not a passing fad, that you are not going away anytime soon.Peder: Right.Corey: And even with building things in my spare time and following various tutorials of dubious credibility from various parts of the internet—as those things tend to go—MongoDB is very often a default go-to reference when someone needs a database for which a SQLite file won't do.Peder: Right. It's fascinating to see the evolution of MongoDB, and today we're lucky to track 45,000-plus customers on our platform doing absolutely incredible things. But I think the biggest—to your point—the biggest proof is in the pudding when you get these customers to stand up on stage and talk about it. And even just recently, through our .local series, some of the customers that we've been highlighting are doing some amazing things using MongoDB in extremely business-critical situations.My favorite was, I was out doing our .local in Hong Kong, where Cathay Pacific got up on stage, and they talked a little bit about their flight folder. Now, if you remember going through the airport, you always see the captains come through, and they had those two big boxes of paperwork before they got onto the plane. Not only was that killing the environment with all the trees that got cut down for it, it was cumbersome, complex, and added a lot of time and friction with regards to flight operations. Now, take that from a single flight over all of the fleet that's happening across the world.We were able to work with Cathay Pacific to digitize their entire flight folder, all of their documentation, removing the need for cutting down trees and minimizing a carbon footprint form, but at the same time, actually delivering a solution where if it goes down, it grounds the entire fleet of the airline. So, imagine that. That's so business-critical, mission-critical, has to be there, reliable, resilient, available for the pilots, or it shuts down the business. Seeing that growth and that transformation while also seeing the environmental benefit for what they have achieved, to me, that makes me proud to work here.Similarly, we have companies like Ford, another big brand-name company here in the States, where their entire connected car experience and how they're basically operationalizing the connection between the car and their home base, this is all being done using MongoDB as well. So, as they think of these new ideas, recognizing that things are going to be either out at the edges or at a level of scale that you can't just bring it back into classic rows and columns, that's actually where we're so well-suited to grow our footprint. And, you know, I remember back to when I was at Sun—Sun Microsystems. I don't know if anybody remembers that company. That was an old one.But at one point, it was Jonathan that said, “Everything of value connects to the network.” Right? Those things that are connecting to the network also need applications, they need data, they need all of these services. And the further out they go, the more you need a database that basically scales to meet them where they are, versus trying to get them to come back to where your database happens to sit. And in order to do that, that's where you break the mold.That's where—I mean, that kind of goes into the core ethos of why we built this company to begin with. The original founders were not here to build a database; they were building a consumer app that needed to scale to the edges of the earth. They recognized that databases didn't solve for that, so they built MongoDB. That's actually thinking ahead. Everything connecting to the network, everything being distributed, everything basically scaling out to all the citizens of the planet fundamentally needs a new data layer, and that's where I think we've come in and succeeded exceptionally well.Corey: I would agree. Another example I like to come up with, and it's fun that the one that leaps to the top of my mind is not one of the ones that you mentioned, but HSBC—the massive bank—very publicly a few years ago, wound up consolidating, I think it was 46 relational databases onto MongoDB. And the jokes at the time wrote themselves, but let's be serious for a second. Despite the jokes that we all love to tell, they are a bank, a massive bank, and they don't play fast-and-loose or slap-and-tickle with transactional integrity or their data stores for these things.Because there's a definite belief across the banking sector—and I know this having worked in it myself for years—that if at some point, you have the ATMs spitting out the wrong account balances, people will begin rioting in the streets. I don't know if that's strictly accurate or hyperbole, but it's going to cause massive amounts of chaos if it happens. So, that is something that absolutely cannot happen. The fact that they're willing to engage with you folks and your technology and be public about it at that scale, that's really all you need to know from a, “Is this serious technology or clown shoes technology?”Peder: [laugh]. Well, taking that comment, now let's exponentially increase that. You know, if I sit back, and I look at my customer base, financial services is actually one of our biggest verticals as a business. And you mentioned HSBC. We had Wells Fargo on the stage last year at our world event.Nine out of the top ten world's banks are using MongoDB in some of their applications, some at the scale of HSBC, some are still just getting started. And it all comes down to the fact that we have proven ourselves, we are aligned to mission-critical business environments. And I think when it comes down to banks, especially that transactional side, you know, building in the capabilities to be able to have high frequency transactions in the banking world is a hard thing to go do, and we've been able to prove it with some of the largest banks on the planet.Corey: I also want to give you credit—although it might be that I'm giving you credit for a slow release process; I hope not—but when I visit mongodb.com, it still talks up front that you are—and I want to quote here—oh, good lord, it changes every time I load the page—but it talks about, “Build faster, build smarter,” on this particular version of the load. It talks about the data platform. You have not effectively decided to pivot everything you say in public to tie directly into the Generative AI hype bubble that we are currently experiencing. You have a bunch of different use cases, and you're not suddenly describing what you do in Gen AI terms that make it impossible to understand just what the company-slash-product-slash-services actually do.Peder: Right.Corey: So, I want to congratulate you on that.Peder: Appreciate that, right? Look, it comes down to the core basics. We are a developer data platform. We bring together all of the capabilities, tools, and functions that developers need when building apps as it pertains to their data functions or data layer, right? And that's why this integrated approach of taking our operational database and building in search, or stream processing, or vector search, all of the things that we're bringing to the platform enable developers to move faster. And what that says is, we're great for all use cases out there, not just Gen AI use cases. We're great for all use cases where customers are building applications to change the way that they're engaging with the customers.Corey: And what I like about this is that you're clearly integrating this stuff under the hood. You are talking to people who are building fascinating stuff, you're building things yourself, but you're not wrapping yourself in the mantle of, “This is exactly what we do because it's trendy right now.” And I appreciate that. It's still intelligible, and I wouldn't think that I had to congratulate someone on, “Wow, you build marketing that a human being can extract meaning from. That's amazing.” But in 2023, the closing days thereof, it very much is.Peder: Yep, yep. And it speaks a lot to the technology that we've built because, you know, on one side—it reminds me a lot of the early days of cloud where everything was kind of cloud-washed for a bit, we're seeing a little bit of that in the hype cycle that we have right now—sticking to our guns and making sure that we are building a technology platform that enables developers to move quickly, that removing the friction from the developer lifecycle as it pertains to the data layer, that's where the success is right, we have to stay on top of all of the trends, we have to make sure that we're enabling Gen AI, we have to make sure that we're integrating with the Amazon Bedrocks and the CodeWhisperers of the world, right, to go push this stuff forward. But to the point we made earlier, those are capabilities and features of a platform where the higher-level order is to really empower our customers to develop innovative, disruptive, or market-leading technologies for how they engage with their customers.Corey: Yeah. And that it's neat to be able to see that you are empowering companies to do that without feeling the need to basically claim their achievements as your own, which is an honest-to-God hard thing to do, especially as you become a platform company because increasingly, you are the plumbing that makes a lot of the flashy, interesting stuff possible. It's imperative, you can't have those things without the underlying infrastructure, but it's hard to talk about that infrastructure, too.Peder: You know, it's funny, I'm sure all of my colleagues would hate me for saying this, but the wheel doesn't turn without the ball bearing. Somebody still has to build the ball bearing in order for that sucker to move, right? And that's the thing. This is the infrastructure, this is the heart of everything that businesses need to build applications. And one of the—you know, another kind of snide comment I've made to some of my colleagues here is, if you think about every market-leading app, in fact, let's go to the biggest experiences you and I use on a daily basis, I'm pretty sure you're booking travel online, you're searching for stuff on Google, you're buying stuff through Amazon, you're renting a house through Airbnb, and you're listening to your music through Spotify. What are those? Those are databases with a search engine.Corey: The world is full of CRUD applications. These are, effectively, simply pretty front-ends to a database. And as much as we'd like to pretend otherwise, that's very much the reality of it. And we want that to be the case. Different modes of interaction, different requirements around them, but yeah, that is what so much of the world is. And I think to ignore that is to honestly blind yourself to a bunch of very key realities here.Peder: That kind of goes back to the original vision for when I came here. It's like, look, everything of value for us, everything that I engage with, is—to your point—it's a database with a great experience on top of it. Now, let's start to layer in this whole Gen AI push, right, what's going on there. We're talking about increased relevance in search, we're talking about new ways of thinking about sourcing information. We've even seen that with some of the latest ChatGPT stuff that developers are using that to get code snippets and figure out how to solve things within their platform.The era of the classic search engine is in the middle of a complete change, and the opportunity, I think, that I see as this moves forward is that there is no incumbent. There isn't somebody who owns this space, so we're just at the beginning of what probably will be the next. Google's, Airbnb's, and Uber's of the world for the next generation. And that's really exciting to see.Corey: I'm right there with you. What are the interesting founding stories at Google is that they wound up calling typical storage vendors for what they needed, got basically ‘screw on out of here, kids,' pricing, so they shrugged, and because they had no real choice to get enterprise-quality hardware, they built a bunch of highly redundant systems on top of basically a bunch of decommissioned crap boxes from the university they were able to more or less get for free or damn near it, and that led to a whole innovation in technology. One of the glorious things about cloud that I think goes under-sold is that I can build a ridiculous application tonight for maybe, what, 27 cents IT infrastructure spend, and if it doesn't work, I round up to dollar, it'll probably get waived because it'll cost more to process the credit card transaction than take my 27 cents. Conversely, if it works, I'm already building with quote-unquote, “Enterprise-grade” components. I don't need to do a massive uplift. I can keep going. And that is no small thing.Peder: No, it's not. When you step back, every single one of those stories was about abstracting that complexity to the end-user. In Google's case, they built their own systems. You or I probably didn't know that they were screwing these things together and soldering them in the back room in the middle of the night. Similarly, when Amazon got started, that was about taking something that was only accessible to a few thousand and now making it accessible to a few million with the costs of 27 cents to build an app.You removed the risk, you removed the friction from enabling a developer to be able to build. That next wave—and this is why I think the things we're doing around Gen AI, and our vector search capabilities, and literally how we're building our developer data platform is about removing that friction and limits and enabling developers to just come in and, you know, effectively do what they do best, which is innovate, versus all of the other things. You know, in the Google world, it's no longer racking and stacking. In the cloud world, it's no longer managing and integrating all the systems. Well, in the data world, it's about making sure that all of those integrations are ready to go and at your fingertips, and you just focus on what you do well, which is creating those new experiences for customers.Corey: So, we're recording this a little bit beforehand, but not by much. You are going to be at re:Invent this year—as am I—for eight nights—Peder: Yes.Corey: Because for me at least, it is crappy cloud Hanukkah, and I've got to deal with that. What have you got coming up? What do you plan to announce? Anything fun, exciting, or are you just there basically, to see how many badges you can actually scan in one day?Peder: Yeah [laugh]. Well, you know, it's shaping up to be quite an incredible week, there's no question. We'll see what brings to town. As you know, re:Invent is a huge event for us. We do a lot within that ecosystem, a lot of the customers that are up on stage talking about the cool things they're doing with AWS, they're also MongoDB customers. So, we go all out. I think you and I spoke before about our position there with SugarCane right on the show floor, I think we've managed to secure you a Friends of Peder all-access pass to SugarCane. So, I look forward to seeing you there, Corey.Corey: Proving my old thesis of, it really is who you know. And thank you for your generosity, please continue.Peder: [laugh]. So, we will be there in full force. We have a number of different innovation talks, we have a bunch of community-related events, working with developers, helping them understand how we play in the space. We're also doing a bunch of hands-on labs and design reviews that help customers basically build better, and build faster, build smarter—to your point earlier on some of the marketing you're getting off of our website. But we're also doing a number of announcements.I think first off, it was actually this last week, we made the announcement of our integrations with Amazon—or—yeah, Amazon CodeWhisperer. So, their code generation tool for developers has now been fully trained on MongoDB so that you can take advantage of some of these code generation tools with MongoDB Atlas on AWS. Similarly, there's been a lot of noise around what Amazon is doing with Bedrock and the ability to automate certain tasks and things for developers. We are going to be announcing our integrations with Agents for Amazon Bedrock being supported inside of MongoDB Atlas, so we're excited to see that, kind of, move forward. And then ultimately, we're really there to celebrate our customers and connect them so that they can share what they're doing with many peers and others in the space to give them that inspiration that you so eloquently talked about, which is, don't market your stuff; let your customers tell what they're able to do with your stuff, and that'll set you up for success in the future.Corey: I'm looking forward to seeing what you announce in conjunction with what AWS announces, and the interplay between those two. As always, I'm going to basically ignore 90% of what both companies say and talk instead to customers, and, “What are you doing with it?” Because that's the only way to get truth out of it. And, frankly, I've been paying increasing amounts of attention to MongoDB over the past few years, just because of what people I trust who are actually good at databases have to say about you folks. Like, my friends at RedMonk always like to say—I've stolen the line from them—“You can buy my attention, but not my opinion.”Peder: A hundred percent.Corey: You've earned the opinion that you have, at this point. Thank you for your sponsorship; it doesn't hurt, but again, you don't get to buy endorsements. I like what you're doing. Please keep going.Peder: No, I appreciate that, Corey. You've always been supportive, and definitely appreciate the opportunity to come on Screaming in the Cloud again. And I'll just push back to that Friends of Peder. There's, you know, also a little bit of ulterior motive there. It's not just who you know, but it's [crosstalk 00:34:39]—Corey: It's also validating that you have friends. I get it. I get it.Peder: Oh yeah, I know, right? And I don't have many, but I have a few. But the interesting thing there is we're going to be able to connect you with a number of the customers doing some of these cool things on top of MongoDB Atlas.Corey: I look forward to it. Thank you so much for your time. Peder Ulander, Chief Marketing Officer at MongoDB. I'm Cloud Economist Corey Quinn and this has been a promoted guest episode of Screaming in the Cloud, brought to us by our friends at Mongo. 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 in your podcast platform of choice, along with an angry, insulting comment that I will ignore because you basically wrapped it so tightly in Generative AI messaging that I don't know what the hell your point is supposed to be.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.

Cada vez mais empresas estão considerando migrar seus aplicativos existentes de um banco de dados relacional para um banco de dados NoSQL mais moderno. Neste episódio descobrirá as vantagens de uma transformação digital migrando aplicações para MongoDB.Quer saber mais sobre MongoDB? Acesse: https://mdb.link/FM0005

In this exciting episode of the MongoDB Podcast, host Michael Lynn shares essential background information about an incredible new innovation in the MongoDB Atlas Platform: Vector Search and how's enabling Game-changing capabilities for developers looking to leverage Artificial Intelligence. Tune in to hear about the future of MongoDB, the launch of Vector Search, and how MongoDB is evolving into a "build anything" platform for operational data. Whether you're a developer, data enthusiast, or just curious about the latest in tech, this episode is a must-listen.

Cada vez mais empresas estão considerando migrar seus aplicativos existentes de um banco de dados relacional para um banco de dados NoSQL mais moderno. Neste episódio você descobrirá as vantagens de uma transformação digital migrando aplicações para MongoDB Atlas e como utilizar dados relacionais em um modelo de documento. Cerca de 30% de todos os projetos MongoDB são agora migrações de bancos de dados relacionais. O MongoDB foi projetado para atender às demandas de aplicativos modernos com uma base tecnológica que permite: 1. O modelo de dados do documento – apresentando a melhor maneira de trabalhar com dados. 2. Um design de sistemas distribuídos – permitindo que você coloque dados de forma inteligente onde quiser. 3. Uma experiência unificada que lhe dá a liberdade de trabalhar em qualquer lugar – permitindo que você prepare seu trabalho para o futuro e elimine a dependência do fornecedor.Assista e descubra como migrar para MongoDB Atlas.Quer saber mais sobre MongoDB? Acesse mdb.link/Dicas-e-truques

(0:00) Intro(0:38) Taking the CEO job at MongoDB(2:34) First things Dev changed at MongoDB(5:53) When unicorns were actually rare(7:50) Overcoming Monetization Challenges of Open Source(9:54) MongoDB Atlas and the license change?(19:18) What is the job of the CEO?(22:49) Vulnerability is a strength(27:03) The power of self-awareness as a Leader(29:37) Building an A+ culture(32:43) Holding people accountable(35:04) Keeping feedback loops tight(36:22) How hybrid work helps MongoDB thrive(38:09) RIFs(40:20) 3 steps for holding people accountable(42:03) Why you should always be recruiting(43:55) Dev's unique recruiting tactics(45:56) Favorite interview questions(46:53) Hiring internally vs externally(50:53) Finding passion for sales(52:58) The perfect job doesn't exist(55:00) Running BladeLogic(57:18) Ben Horowitz, Mark Andreessen, and John McMahon(1:02:36) How does AI compare to past tech trends?(1:05:47) Conventional Silicon Valley wisdom Dev disagrees with Mixed and edited: Justin HrabovskyProduced: Rashad AssirExecutive Producer: Josh MachizMusic: Griff Lawson 

In this special episode recorded live from the MongoDB .local London Conference, Shane McAllister sits down with Max Marcon, the Lead Product Manager for Developer Tools at MongoDB. They discuss the new local experience for MongoDB Atlas and the Atlas CLI, the future of Atlas Search and Vector Search, and much more.Timestamps:[00:00:00] Introduction[00:00:19] Welcoming Max Marcon[00:00:40] The Importance of a Local Experience for MongoDB Atlas[00:02:02] How Developers Managed Before This Announcement[00:03:26] What's Included in the New Local Experience[00:05:40] The Effort Behind the New Feature[00:07:12] Main Use Cases for Atlas Search and Vector Search[00:09:37] The Future of AI and Vector Search in MongoDB[00:11:33] Why Developers Prefer Local Environments[00:14:30] How New Developers Will Experience MongoDB Differently[00:16:39] Impact on CI/CD Pipelines[00:18:23] Cost Benefits of Local Development[00:20:50] Future Plans for the Tool[00:22:59] How to Give Feedback[00:25:07] Closing RemarksKey Takeaways:Local Experience for MongoDB Atlas: The new feature aims to make developers more efficient by allowing them to spin up local environments quickly.Atlas Search and Vector Search: These features are now integral parts of the MongoDB Atlas platform, enabling more robust search capabilities.Community Feedback: MongoDB is actively seeking feedback from the community to improve and add new features.CI/CD Pipelines: The new local experience can significantly speed up CI/CD pipelines by allowing quick and isolated testing environments.Future Plans: MongoDB plans to continue expanding the local experience based on user feedback and emerging technologies.Resources:Learn More about the MongoDB Atlas CLI

On this episode of The Six Five – On The Road, hosts Daniel Newman and Patrick Moorhead welcome MongoDB's Sahir Azam, Chief Product Officer, for a discussion during MongoDB's .local NYC event. Their discussion covers: An overview of MongoDB's long term vision for Atlas, including the latest updates on Atlas Search The value developers receive from using Vector Search through MongoDB Atlas Search The capabilities Atlas Stream Processing, another big product update from MongoDB Sahir shares some use cases for incorporating real-time analytical capabilities into applications and how MongoDB Atlas is addressing this trend Be sure to subscribe to The Six Five Webcast, so you never miss an episode.

In this episode, we're taking you inside the Game Developers Conference, where our team showcased a custom-built game powered by MongoDB Atlas and MongoDB App Services. You'll hear firsthand experiences from the team who attended the conference, discussing the incredible passion and competitiveness they witnessed from gamers trying to top the leaderboard.We'll dive deep into how MongoDB's real-time analytics and visualizations brought data to life, allowing players to see their own gaming data in action. Plus, you'll get a glimpse into how MongoDB's tech stack made it all possible. Be sure to visit https://mdb.link/gaming for links, resources and more information about MongoDB at Game Developers Conference 2023

In this episode, Michael interviews Julian Busch, Growth Marketing Manager at MongoDB, to discuss the MongoDB for Startups program. Julian shares insights about the program's evolution, benefits, and goals for supporting startups around the world. Key takeaways from this episode include:MongoDB for Startups aims to help founders scale their businesses by providing access to MongoDB Atlas's developer data platform, credits for MongoDB Cloud products, free technical advisor sessions, and co-marketing opportunities.Technical advisor sessions connect founders with MongoDB experts who offer valuable guidance on optimizing their technology stack.The recent launch of MongoDB Ventures further strengthens the company's commitment to supporting startups through corporate venture capital.MongoDB for Startups is suitable for founders at various stages, from ideation to MVP and beyond.Tune in to learn more about the MongoDB for Startups program and how it can benefit your startup venture.Visit: https://mdb.link/startups-live for more information

The history of computing has been a story of moving up levels of abstraction: from hard-coding algorithms and directly manipulating memory addresses with assembly languages to using more natural language constructs in high-level general purpose languages to abstracting the hardware of the computer in cloud compute. Now serverless functions take that abstraction even further. We've made the algorithms that process data simple and natural; MongoDB wants to do the same for how we persist data. On this sponsored episode of the podcast, we chat with Andrew Davidson, SVP Products at MongoDB, about how they're turning a database into a fully-managed service that developers can use in a more natural way. Along the way, we discuss how the cost bottleneck has moved from the storage media to developers' minds, how greater abstractions can enable developers, and how to get insights from production data faster. Episode notesTry MongoDB Atlas on AWS for free.You can get started with MongoDB Atlas directly from the AWS Marketplace. If you're at a startup, you can take advantage of their special offer for startups. The community edition of their classic database is available to download as well. If you're looking to learn a thing or two before diving in, check out MongoDB University. Our thanks to Great Question badge winner Derek 朕會功夫 for asking How can I reverse an array in JavaScript without using libraries? You know the rarest kung fu of all: asking great questions.

Modern networked applications generate a lot of data, and every business wants to make the most of that data. Most of the time, that means moving production data through some transformation process to get it ready for the analytics process. But what if you could have in-app analytics? What if you could generate insights directly from production data?On this sponsored episode of the podcast, we talk with Stanimira Vlaeva, Developer Advocate at MongoDB, and Fredric Favelin, Technical Director, Partner Presales at MongoDB, about how a serverless database can minimize the distance between producing data and understanding it.Episode notes:Stanimira talked a lot about using BigQuery with MongoDB Atlas on Google Cloud Run. If you need to skill up on these three tools, check out this tutorial. Once you've got the hang of it, get your data connected with Confluent Connetors. With Atlas, you can transform your data in JavaScript. Connect with Stanimira on LinkedIn and Twitter. Connect with Fredric on LinkedIn. Congrats to Stellar Question winner SubniC  for  Get name of current script in Python. 

Harness is The Modern Software Delivery Platform that uses AI to optimize software delivery. Harness leverages MongoDB Atlas as a part of their platform to optimize every stage of software delivery and cost optimization. Surya Bhagvat, and Dave Nielsen from Harness join Michael Lynn to talk about the key benefits of using Harness and how their leveraging MongoDB.

The Six Five On the Road at AWS reInvent 2022. Patrick Moorhead and Daniel Newman sit down with Andrew Davidson, SVP, Product Management, MongoDB. Their discussion covers: Evolution of the MongoDB & AWS partnership How customers are utilizing MongoDB Atlas on AWS to build cutting-edge applications Data-driven approach to the cloud Cloud strategy in a hybrid world

Andrew Davidson (SVP Products, @MongoDB) talks about MongoDB's evolution from a software company to a cloud services company (MongoDB Atlas), how developers traditionally interacted with databases, and the need for Developer Data Platforms going forward.SHOW: 671CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:Datadog Security Solution: Modern Monitoring and SecurityStart investigating security threats before it affects your customers with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.CDN77 - CDN Focused on VOD and SecurityCDN77 - ask for a free trial with no duration or traffic limits.CloudZero - Cloud Cost Intelligence for Engineering TeamsSHOW NOTES:Press Release: MongoDB Unveils Vision for a Developer Data Platform at MongoDB World 2022Forbes: MongoDB Extends Developer Data Platform For Modern ApplicationsTechCrunch: MongoDB puts a spotlight on its developer data platformTopic 1 - Welcome to the show. Let's talk about your background, and what you focus on at MongoDB.Topic 2 - Data is a weird beast. It's cheap to create, it's expensive to move, and it's complicated to use because there's so many ways to interact with it depending on the use-case. So for someone that thinks about data a lot, how do you frame up the challenges of how applications interact with data?   Topic 3 - People tend to think about MongoDB as a database company, and then a Cloud database company. What did the company learn as it moved to the cloud, as a lot of barriers for developers got knocked down in that transition? Topic 4 - As a developer today, do I still need to think about the relationship between the underlying data and the database access model needed to make that useful to an application, or are any of those lines blurring or going away?Topic 5 - Databases have traditionally followed the CAP theorem, and different choices have different strengths and tradeoffs. As you start to think about this concept of developer data platform, how do you try and reframe those tradeoffs? Do any of them go away?   Topic 6 - What are some examples of how companies and their developers are able to think differently about how their new applications can be built with this new platform approach to data?FEEDBACK?Email: show at the cloudcast dot netTwitter: @thecloudcastnet

MongoDB Atlas has a new command-line interface and on today's episode of the podcast, Michael Lynn interviews Bianca Lisle, and Jakub Lazinski to learn about how this new interface works and what developers can accomplish using it.[1:21] Bianca Lisle Introduction[1:33] Jakub Lisinski Introduction[5:23] Jakub describes the Atlas CLI and functionality[6:58] What's the difference between the Atlas Admin API, and the Atlas CLI?[9:56] How to get started with Atlas CLI[24:15] Roadmap for Atlas CLI

LuminPDF was founded in 2014 as a better way for people to annotate and collaborate on PDF files.Today, 70 million people use Lumin to meet their administrative needs and bring their documents to life.On this episode, we chat with Max Ferguson, Founder & CEO of LuminPDF, to learn more about building LuminPDF as a student and his lessons about growth and startup experiences, as well as how LuminPDF uses MongoDB Atlas.LuminPDF and MongoDB Blog Postshttps://www.luminpdf.com/blog/scaling-for-success-how-lumins-partners-are-super-charging-our-platform/Conversation Highlights: [01:23] LuminPDF[02:08] Pandemic growth[03:07] Where did the idea come from, and how it came together[05:09] LuminPDF's capabilities and how data is stored in MongoDB[07:09] What the MongoDB infrastructure looks like for Lumin[08:16] Running a company for the first time[09:24] Advice to other founders[11:45] Max's relationship with coding nowadays[12:27] Python, MongoDB, and products in the portfolio[15:14] What's next in the pipeline[17:12] A great experience with MongoDB, and the Lumin API

We do love AWS, but sometimes we have to admit that it's not always a silver bullet. There are definitely use cases where it might be worth considering alternatives to AWS. In this episode we will discuss some of these use cases and try to highlight what are the advantages that other platforms or services can have over AWS in very specific circumstances. First of all we clarify why we like AWS and why (and when) it's worth sticking with it. Then, we discuss what are some of the reasons why it might be worth considering alternatives to AWS. At this point we go into the specifics and talk about authentication services (Auth0), search services (ElasticSearch, Algolia), CDN Services (GitHub Pages, Netlify, Vercel, CloudFlare, Fastly, Akamai), Databases (MongoDB Atlas, Digital Ocean managed databases, IBM Compose, CloudFlare D1, Upstash, Confluent Kafka), Headless CMS services (ContentFul, Storyful, AirTable, Google Spreadsheet), Virtual Machine services (Digital Ocean, Linode). In this episode, we mentioned the following resources: - Episode 3. "​​How do you deploy a static website on AWS?”: https://awsbites.com/3-how-do-you-deploy-a-static-website-on-aws/ - Auth0: https://auth0.com/ - Amazon OpenSearch: https://aws.amazon.com/opensearch-service/the-elk-stack/what-is-opensearch/ - Elastic Cloud: https://www.elastic.co/cloud/ - Algolia: https://www.algolia.com/ - Vercel: https://vercel.com/ - Netlify: https://www.netlify.com/ - MongoDB Atlas: https://www.mongodb.com/atlas/database - Digital Ocean managed database: https://try.digitalocean.com/managed-databases/ - Compose (now IBM Cloud Databases): https://www.compose.com/ - Upstash: https://upstash.com/ - Confluent: https://www.confluent.io/ - AirTable: https://airtable.com/ - Linode: https://www.linode.com/ This episode is also available on YouTube: https://www.youtube.com/AWSBites You can listen to AWS Bites wherever you get your podcasts: - Apple Podcasts: https://podcasts.apple.com/us/podcast/aws-bites/id1585489017 - Spotify: https://open.spotify.com/show/3Lh7PzqBFV6yt5WsTAmO5q - Google: https://podcasts.google.com/feed/aHR0cHM6Ly9hbmNob3IuZm0vcy82YTMzMTJhMC9wb2RjYXN0L3Jzcw== - Breaker: https://www.breaker.audio/aws-bites - RSS: ​​https://anchor.fm/s/6a3312a0/podcast/rss Do you have any AWS questions you would like us to address? Connect with us on Twitter: - https://twitter.com/eoins - https://twitter.com/loige

On this episode of the Traction podcast, host Lloyed Lobo of Boast.AI welcomes Sahir Azam, Chief Product Officer at MongoDB.   Sahir shares how MongoDB transformed from a traditional software company—sales driven, longer cycles, etc.—into more of a consumer-style self-service model.   Overseeing the growth of MongoDB's Atlas, Sahir shares his learnings (the good, the bad, and the ugly) about building and bringing to market one of the fastest-growing cloud products of any scale (70% YoY, $400M ARR, 26K+ customers).   In this session, Sahir discusses: 7:44 - MongoDB sales-led model prior to going product-led 10:31 - What main KPIs were focused on 16:01 - Recommendations and best practices for building teams 20:07 - Tactics to make sure that cross-functional dialogue is happening regularly 26:57 - The ideal squad structure for a cross-functional team 32:46 - The product development framework at MongoDB 37:34 - Best practices for developing a go-to-market strategy for a product-led company 41:36 - Product marketing roles vs product manager roles 52:29 - What kickstarted growth for the MongoDB Atlas customer base 55:31 - Top pieces of advice that were learned the hard way 57:54 - Recommended books and resources   Learn more at https://tractionconf.io   Connect with Sahir Azam: https://www.linkedin.com/in/sahirazam/   Learn more about MongoDB at https://www.mongodb.com/   This episode is brought to you by:   Each year the U.S. and Canadian governments provide more than $20 billion in R&D tax credits and innovation incentives to fund businesses. But the application process is cumbersome, prone to costly audits, and receiving the money can take as long as 16 months. Boast automates this process, enabling companies to get more money faster without the paperwork and audit risk. We don't get paid until you do! Find out if you qualify today at https://Boast.AI.   Launch Academy is one of the top global tech hubs for international entrepreneurs and a designated organization for Canada's Startup Visa. Since 2012, Launch has worked with more than 6,000 entrepreneurs from over 100 countries, of which 300 have grown their startups to seed and Series A stage and raised over $2 billion in funding. To learn more about Launch's programs or the Canadian Startup Visa, visit https://LaunchAcademy.ca    Content Allies helps B2B companies build revenue-generating podcasts. We recommend them to any B2B company that is looking to launch or streamline its podcast production. Learn more at https://contentallies.com  

About Kevin JerniganKevin started his career on the first product management team at Oracle, with responsibilities for utilities, benchmarks, and Oracle Parallel Server. After Oracle, he built a consulting business focused on data warehousing and high end transactional systems, and then built a SaaS business providing booking capabilities to the health club industry. He returned to Oracle to manage a team delivering storage and performance features in Oracle Database, and then joined AWS to launch Aurora PostgreSQL, which he helped build into the fastest-growing service in the history of AWS. In early 2021, Kevin joined the Atlas Serverless product team, and is focusing on bringing the Serverless from preview to general availability, and on working with customers to ensure it exceeds customer expectations in all dimensions, including ease of use, performance, pricing, scalability, functionality, and integration with the broader serverless application landscape. Twitter: @kjerniga LinkedIn: https://www.linkedin.com/in/kevinjernigan/  MongoDB Atlas: https://www.mongodb.com/atlas  MongoDB Atlas Serverless: https://www.mongodb.com/use-cases/serverless

Proper tooling is perhaps the primary key to unlocking developer productivity. With the right tools and frameworks, developers can be productive in minutes versus having to toil over boilerplate code. And as data-hungry use cases such as AI and machine learning emerge, data tooling is becoming paramount. This was evident at the recent MongoDB World conference in New York City where TNS Founder and Publisher Alex Williams recorded this episode of The New Stack Makers podcast featuring Peggy Rayzis, senior director of developer experience at Apollo GraphQL; Lee Robinson, vice president of developer experience at Vercel; Ian Massingham, vice president of developer relations and community at MongoDB; and Søren Bramer Schmidt, co-founder and CEO of Prisma, discussing how their companies' offerings help unlock developer productivity.Apollo GraphQL and SupergraphsApollo GraphQL unlocks developers by helping them build supergraphs, Raysiz said. A supergraph is a unified network of a company's data services and capabilities that is accessible via a consistent and discoverable place that any developer can access with a GraphQL query. GraphQL is a query language for communicating about data. “And what's really great about the supergraph is even though it's unified, it's very modular and incrementally adoptable. So you don't have to like rewrite all of your backend system and API's,” she said. “What's really great about the Super graph is you can connect like your legacy infrastructure, like your relational databases, and connect that to a more modern stack, like MongoDB Atlas, for example, or even connected to a mainframe as we've seen with some of our customers. And it brings that together in one place that can evolve over time. And we found that it just makes developers so much more productive, helps them shave, shave months off of their development time and create experiences that were impossible before.”[sponsor_note slug="mongodb" ][/sponsor_note]Vercel: Strong DefaultsMeanwhile, Robinson touted the virtues of Next.js, Vercel's popular React-based framework, which provides developers with the tools and the production defaults to make a fast web experience. The goal is to enable frontend developers to be able to move from an idea to a global application in seconds. Robinson said he believes it's important for a tool or framework to have good, strong defaults, but to also be extensible and available for developers to make changes such that they do not have necessarily eject fully out of the tool that they're using, but to be able to customize without having to leave the framework library tool of choice. “If you can provide that great experience for the 90% use case by default, but still allow maybe the extra 10% power, you know, power developer who needs to modify something without having to just rewrite from scratch, you can get go pretty far,” he said.Data ToolingWhen it comes to data tooling, MongoDB is trying to help developers manipulate and work with data in a more productive and effective way, Massingham said. One of the ways MongoDB does this is through the provision of first-party drivers, he said. The company offers 12 different programming language drivers for MongoDB, covering everything from Rust to Java, JavaScript, Python, etc. “So, as a developer, you're importing a library into your environment,” Massingham said. “And then rather than having to construct convoluted SQL statements -- essentially learning another language to interact with the data in your database or data store -- you're going to manipulate data idiomatically using objects or whatever other constructs that are normal within the programming language that you're using. It just makes it way simpler for developers to interact with the data that's stored in MongoDB versus interacting with data in a relational database.”MongoDB and PrismaBramer Schmidt said while a truism in software engineering is that code moves fast and data moves slow, but now we are starting to see more innovation around the data tooling space. “And Mongo is a great example of that,” he said. “Mongo is a database that is much nicer to use for developers, you can express more different data constructs, and Mongo can handle things under the hood.” Moreover, Prisma also is innovating around the developer experience for working with data, making it easier for developers to build applications that rely on data and do that faster, Bramer Schmidt said. “The way we do that in Prisma is we have the tooling introspect your database, it will go and assemble documents in MongoDB, and then generate a schema based on that, and then it will pull that information into your development environment, such that you can, when you write queries, you will get autocompletion, and the IDE will tell you if you're making a mistake,” he said. “You will have that confidence in your environment instead of having to look at the documentation, try to remember what fields are where or how to do things. So that is increasing the confidence of the developer enabling them to move faster.

About RickI lead the developer relations team for strategic accounts at MongoDB. My responsibilities include defining technical standards for the global strategic accounts team and consulting with the largest customers and opportunities for the business. My role spans technology sectors and as part of my engagements I routinely provide guidance on industry best practices, technology transformation, distributed systems implementation, cloud migration, and more. I led the architecture and design effort at Amazon for migrating thousands of relational workloads from RDBMS to NoSQL and built the center of excellence team responsible for defining the best practices and design patterns used today by thousands of Amazon internal service teams and AWS customers. I currently operate as the technical leader for our global strategic account teams to build the market for MongoDB technology by facilitating center of excellence capabilities within our customer organizations through training, evangelism, and direct design consultation activities.30+ years of software and IT expertise.9 patents in Cloud Virtualization, Complex Event Processing, Root Cause Analysis, Microprocessor Architecture, and NoSQL Database technology.Links: MongoDB: https://www.mongodb.com/ Twitter: https://twitter.com/houlihan_rick 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: The company 0x4447 builds products to increase standardization and security in AWS organizations. They do this with automated pipelines that use well-structured projects to create secure, easy-to-maintain and fail-tolerant solutions, one of which is their VPN product built on top of the popular OpenVPN project which has no license restrictions; you are only limited by the network card in the instance. To learn more visit: snark.cloud/deployandgoCorey: This episode is sponsored by our friends at Oracle Cloud. Counting the pennies, but still dreaming of deploying apps instead of “Hello, World” demos? Allow me to introduce you to Oracle's Always Free tier. It provides over 20 free services and infrastructure, networking, databases, observability, management, and security. And—let me be clear here—it's actually free. There's no surprise billing until you intentionally and proactively upgrade your account. This means you can provision a virtual machine instance or spin up an autonomous database that manages itself, all while gaining the networking, load balancing, and storage resources that somehow never quite make it into most free tiers needed to support the application that you want to build. With Always Free, you can do things like run small-scale applications or do proof-of-concept testing without spending a dime. You know that I always like to put asterisks next to the word free? This is actually free, no asterisk. Start now. Visit snark.cloud/oci-free that's snark.cloud/oci-free.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. A year or two before the pandemic hit, I went on a magical journey to a mythical place called Australia. I know, I was shocked as anyone to figure out that this was in fact real. And while I was there, I gave the opening keynote at a conference that was called Latency Conf, which is great because there's a heck of a timezone shift, and I imagine that's what it's talking about.The closing keynote was delivered by someone I hadn't really heard of before, and he started talking about single table design with respect to DynamoDB, which, okay, great; let's see what he's got to say. And the talk started off engaging and entertaining and a high-level overview and then got deeper and deeper and deeper and I felt, “Can I please be excused? My brain is full.” That talk was delivered by Rick Houlihan, who now is the Director of Developer Relations for Strategic Accounts over at MongoDB, and I'm fortunate enough to be able to get him here to more or less break down some of what he was saying back then, catch up with what he's been up to, and more or less suffer my slings and arrows. Rick, thank you for joining me.Rick: Great. Thanks, Corey. I really appreciate—you brought back some memories, you know, trip down memory lane there. And actually, interestingly enough, that was the world's introduction to single table design was that. That was my dry-run rehearsal for re:Invent 2018 is where I delivered that talk, and it has become since the most positive—Corey: This was two weeks before re:Invent, which was just a great thing. I'd been invited to go; why not? I figured I'd see a couple of clients I had out in that direction. And I learned things like Australia is a big place. So, doing a one-week trip, including Sydney, Melbourne, and Perth. Don't do that.Rick: I had no idea that it took so long to fly from one side to the other, right? I mean, that's a long plane [laugh] [crosstalk 00:02:15]—Corey: Oh, yeah. And you were working at AWS at the time—Rick: Absolutely.Corey: —so I can only assume that they basically stuffed you into a dog kennel and threw you underneath the seating area, given their travel policy?Rick: Well, you know, I have the—[clear throat] actually at the time, they just upgraded the policy to allow the intermediate seating, right? So, if you wanted to get the—Corey: Ohhh—Rick: I know—Corey: Big spender. Big spender.Rick: Yes, yes. I can get a little bit extra legroom, so I didn't have my knees shoved into some of these back. But it was good.Corey: So, let's talk about, I guess… we'll call it the elephant in the room. You were at MongoDB, where you were a big proponent of the whole no-SQL side of the world. Then you went to go work at AWS and you carried the good word of DynamoDB far and wide. It made an impression; I built my entire newsletter pipeline production system on top of DynamoDB. It has the same data in three different tables because I'm not good at listening or at computers.But now you're back at Mongo. And it's easy to jump to the conclusion of, “Oh, you're just shilling for whoever it is that happens to sign your paycheck.” And at this point, are you—what's the authenticity story? But I've been paying attention to what you've been saying, and I think that's a bad take because you have been saying the same things all along since before you were on the Dynamo side of it. I do some research for this show, and you've been advocating for outcomes and the right ways to do things. How do you view it?Rick: That's basically the story here, right? I've always been a proponent of NoSQL. You know, what I took—the knowledge—it was interesting, the knowledge I took from MongoDB evolved as I went to AWS and I delivered, you know, thousands of applications and deployed workloads that I'd never even imagined I would have my hands on before I went there. I mean, honestly, what a great place it was to cut your teeth on data modeling at scale, right? I mean, that's the—there is no greater scale.That's when you learn where things break. And honestly, a lot of the lessons I took from MongoDB, well, when I applied them at scale at AWS, they worked with varying levels of success, and we had to evolve those into the sets of design patterns, which I started to propose for DynamoDB customers, which had been highly effective. I still believe in all those patterns. I would never tell somebody that they need to drop everything and run to MongoDB, but, you know, again, all those patterns apply to MongoDB, too, right? A very—a lot—I wouldn't say all of them, but many of them, right?So, I'm a proponent of NoSQL. And I think we talked before the call a little bit about, you know, if I was out there hocking relational technology right now and saying RDBMS is the future, then everybody who criticizes anything I say, I would absolutely have to, you know, say that there's some validity there. But I'm not saying anything different I've ever said. MongoDB announced Serverless, if you remember, in July, and that was a big turning point for me because the API that we offer, the developer experience for MongoDB is unmatched, and this is what I talk to people now. And it's the patterns that I've always proposed, I still model data the same way, I don't do it any different, and I've always said, if you go back to my earlier sessions on NoSQL, it's all the same.It doesn't matter if it's MongoDB, DynamoDB, or any other technology. I've always shown people how to model their data and NoSQL and I don't care what database you're using, I've actually helped MongoDB customers do their job better over the years as well. So.Corey: Oh, yeah. And looking back at some of your early talks as well, you passed my test for, “Is this person a shill?” Because you wound up in those talks, addressing head-on when is a relational model the right thing to do? And then you put the answers up on a slide, and this—and what—it didn't distill down to, “If you're a fool.”Rick: [laugh].Corey: Because there are use cases where if you don't [unintelligible 00:05:48] your access patterns, if you have certain constraints and requirements, then yeah. That you have always been an advocate for doing the right thing for the workload. And in my experience, for my use cases, when I looked at MongoDB previously, it was not a fit for me. It was very much a you run this on an instance basis, you have to handle all this stuff. Like three—you kno, keeping it in triplicate in three different DynamoDB tables, my newsletter production pipeline now, including backups and the rest, of DynamoDB portion has climbed to the princely sum of $1.30 a month, give or take.Rick: A month. Yes, exactly.Corey: So, there's no answer for that there. Now that Mongo Serverless is coming out into the world, oh, okay, this starts to be a lot more compelling. It starts to be a lot more flexible.Rick: I was just going to say, for your use case there, Corey, you're probably looking at the very similar pricing experience now, with MongoDB Serverless. Especially when you look at the pricing model, it's very close to the on-demand table model. It actually has discounted tiering above it, which I haven't really broken it down yet against a provision capacity model, but you know, there's a lot of complexity in DynamoDB pricing. And they're working on this, they'll get better at it as well, but right now you have on-demand, you have provisioned throughput, you have [clear throat] reserved capacity allocations. And, you know, there's a time and place for all of those, but it puts the—again, it's just complexity, right?This is the problem that I've always had with DynamoDB. I just wish that we'd spent more time on improving the developer experience, right, enhancing the API, implementing some of these features that, you know, help. Let's make single table design a first-class citizen of the DynamoDB API. Right now it's a red—it's a—I don't want to say redheaded stepchild, I have two [laugh] I have two redhead children and my wife is redhead, but yeah. [laugh].Corey: [laugh]. That's—it's—Rick: That's the way it's treated, right? It's treated like a stepchild. You know, it's like, come on, we're fully funding the solutions within our own umbrella that are competing with ourselves, and at the same time, we're letting the DynamoDB API languish while our competitors are moving ahead. And eventually, it just becomes, you know, okay, guys, I want to work with the best tooling on the market, and that's really what it came down to. As long as DynamoDB was the king of serverless, yes, absolutely; best tooling on the market.And they still are [clear throat] the leader, right? There's no doubt that DynamoDB is ahead in the serverless landscape, that the MongoDB solution is in its nascency. It's going to be here, it's going to be great, that's part of what I'm here for. And that's again, getting back to why did you make the move, I want to be part of this, right? That's really what it comes down to.Corey: One of the things that I know that was my own bias has always been that if I'm looking at something like—that I'm looking at my customer environments to see what's there, I can see DynamoDB because it has its own line item in the bill. MongoDB is generally either buried in marketplace charges, or it's running on a bunch of EC2 instances, or it just shows up as data transfer. So, it's not as top-of-mind for the way that I view things in… through the lens of you know, billing. So, that does inform my perception, but I also know that when I'm talking to large-scale companies about what they're doing, when they're going all-in on AWS, a large number of them still choose things like Mongo. When I've asked them why that is, sometimes you get the answer of, “Oh, legacy. It's what we built on before.” Cool—Rick: Sure.Corey: —great. Other times, it's a, “We're not planning to leave, but if we ever wanted to go somewhere else, it's nice to not have to reimagine the entire data architecture and change the integration points start to finish because migrations are hard enough without that.” And there is validity to the idea of a strategic exodus being possible, even if it's not something you're actively building for all the time, which I generally advise people not to do.Rick: Yeah. There's a couple things that have occurred over the last, you know, couple of years that have changed the enterprise CIO and CTO's assessment of risk, right? Risk is the number one decision factor in a CTOs portfolio and a CIO's, you know, decision-making process, right? What is the risk? What is the impact of that risk? Do I need to mitigate that risk, or do I accept that risk? Okay?So, right now, what you've seen is with Covid, people have realized that you know, on-prem infrastructure is a risk, right? It used to be an asset; now it's a risk. Those personnel that have to run that on-prem infrastructure, hey, what happens when they're not available? The infrastructure is at risk. Okay.So, offloading that to cloud providers is the natural solution. Great. So, what happens when you offload to a cloud provider and IAD goes down, or you know, us-east-1 goes down—we call it IAD or we used to call it IAD internally at AWS when I was there because, you know, the regions were named by airport codes, but it's us-east-1—how many times has us-east-1 had problems? Do you want to really be the guy that every time us-east-1 goes down, you're in trouble? What happens when people in us-east-1 have trouble? Where do they go?Corey: Down generally speaking.Rick: [crosstalk 00:10:37]—well, if they're well-architected, right, if they're well-architected, what do they do? They go to us-west-2. How much infrastructure is us-west-2 have? So, if everybody in us-east-1 is well-architected, then they all go to us-west-2. What happens in us-west-2? And I guarantee you—and I've been warning about this at AWS for years, there's a cascade failure coming, and it's going to be coming because we're well-architecting everybody to failover from our largest region to our smaller regions.And those smaller regions, they cannot take the load and nobody's doing any of that planning, so, you know, sooner or later, what you're going to see is dominoes fall, okay? [clear throat]. And it's not just going to be us-east-1, it's going to be us-east-1 failed, and the rollover caused a cascade failure in us-west-2, which caused a cascade—Corey: Because everyone's failing over during—Rick: That's right. That's right.Corey: —this event the same way. And also—again, not to dunk on them unnecessarily, but when—Rick: No, I'm not dunking.Corey: —us-east-1 goes, down a lot of the control plane services freeze up—Rick: Oh, of course they do.Corey: —like [unintelligible 00:11:25].Rick: Exactly. Oh, we not single point of failure, right? Uh-huh, exactly. There you go, Route 53, now—and that actually surprised me is DynamoDB instead of Route 53 is your primary database. So, I'm actually must have had some impact on you—Corey: To move one workload off of Dynamo to Route 53 [crosstalk 00:11:39] issue number because I have to practice what I preach.Rick: That's right. Exactly.Corey: It was weird; they the thing slower and little bit less, uh—Rick: [laugh]. I love it when [crosstalk 00:11:45]—yeah, yeah—Corey: —and a little bit [crosstalk 00:11:45] cache-y. But yeah.Rick: —sure. Okay, I can understand that. [laugh].Corey: But it made the architecture diagram a little bit more head-scratching, and really, that's what it's all about. Getting a high score.Rick: Right. So, if you think about your data, right, I mean, would you rather be running on an infrastructure that's tied to a cloud provider that could experience these kinds of regional failures and cascade failures, or would you rather have your data infrastructure go across cloud providers so that when provider has problems, you can just go ahead and switch the light bulb over on the other one and ramp right back up, right? You know? And honestly, you're running active, active configurations and that kind of, [clear throat] you know, deployment, you know, design, and you're never going to go down. You're always going—Corey: The challenge I've had—Rick: —to be the one that stays up.Corey: The theory is sound, but the challenge I've had in production with trying these things is that one, the thing that winds up handling the failover piece is often causes more outage than the underlying stuff itself.Rick: Well, sure. Yeah.Corey: Two, when you're building something to run a workload to run in multiple cloud providers, you're forced to use a lot of—Rick: Lowest common denominator?Corey: Lowest common denominator stuff. Yeah.Rick: Yeah, yeah totally. I hear that all the time.Corey: Unless you're actively running it in both places, it looks like a DR Plan, which doesn't survive the next commit to the codebase. It's the—Rick: I totally buy that. You're talking about the stack, stack duplication, all that kind of—that's an overhead and complexity, I don't worry about at the data layer, right?Corey: Oh, yeah.Rick: The data layer—Corey: If you're talking about—Rick: —[crosstalk 00:12:58]Corey: —[crosstalk 00:12:58] data layer, oh, everything you're saying makes perfect sense.Rick: Makes perfect sense, right? And honestly, you know, let's put it this way: If this is what you want to do—Corey: What do you mean identity management and security handover working differently? Oh, that's a different team's problem. Oh, I miss those days.Rick: Yeah, you know, totally right. It's not ideal. But you know, I mean, honestly, it's not a deal that somebody wants to manage themselves, is moving that data around. The data is the lock-in. The data is the thing that ties you to—Corey: And the cost of moving it around in some cases, too.Rick: That's exactly right. You know, so you know, having infrastructure that spans providers and spans both on-prem and cloud, potentially, you know, that can span multiple on-prem locations, man, I mean, that's just that's power. And MongoDB provides that; I mean, DynamoDB can't. And that's really one of the biggest limitations that it will always have, right? And we talked about, and I still believe in the power of global tables, and multi-region deployments, and everything, it's all real.But these types of scenarios, I think this is the next generation of failure that the cloud providers are not really prepared for, they haven't experienced it, they don't know what it's even going to look like, and I don't think you want to be tied to a single provider when these things start happening, right, if you have a large amount of infrastructure deployed someplace. It just seems like [clear throat] that's a risk that you're running at these days, and you can mitigate that risk somewhat by going with a MongoDB Atlas. I agree, all those other considerations. But you know, I also heard—it's a lot of fun, too, right? There's a lot of fun in that, right?Because if you think about it, I can deploy technologies in ways on any cloud provider, they're going to be cloud provider agnostic, right? I can use, you know, containerized technologies, Kubernetes, I can use—hell, I'm not even afraid to use Lambda functions, and just, you know, put a wrapper around that code and deploy it both as a Lambda or a Cloud Function in GCP. The code's almost the same in many cases, right? What it's doing with the data, you can code this stuff in a way—I used to do it all the time—you abstract the data layer, right? Create a DAL. How about a CAL? A cloud [laugh] cloud access layer, right, you know? [laugh].Corey: I wish, on some level, we could go down some of these paths. And someone asked me once a while back of, “Well, you seem to have a lot of opinions on this. Do you think you could build a better cloud than AWS?” And my answer—Rick: Hell yes.Corey: —look them a bit by surprise of, “Absolutely. Step one, I want similar resources, so give me $20 billion to spend”—Rick: I was going to say, right?Corey: —”then I'm going to hire the smart people.” Not that we're somehow smarter or better or anything else than the people who built AWS originally, but now—Rick: We have all those lessons learned.Corey: —we have fifteen years of experience to fall back on.Rick: Exactly.Corey: “Oh. I wouldn't make that mistake again.”Rick: Exactly. Don't need to worry about that. Yeah exactly.Corey: You can't just turn off a cloud service and relaunch it with a completely different interface and API and the rest.Rick: People who criticize, you know, services like DynamoDB, like—and other AWS services—look, these things are like any kind of retooling of the services, it's like rebuilding the engine on the airplane while it's flying.Corey: Oh, yeah.Rick: And you have to do it with a level of service assurance that—I mean, come on. DynamoDB provides four nines out of the box, right? Five nines if you turn on global tables. And they're doing this at the same time as they have pipeline releases dropping regularly, right? So, you can imagine what kind of, you know, unit testing goes on there, what kind of Canary deployments are happening.It's just, it's an amazing infrastructure that they maintain, incredibly complex, you know? In some ways, these are lessons that we need to learn in MongoDB if we're going to be successful operating a shared backplane serverless, you know, processing fabric. We have to look at what DynamoDB does right. And we need to build our own infrastructure that mirrors those things, right? And in some ways, these things are there, in some ways, they're working on, in some ways, we got a long ways to go.But you know, I mean, it's this is the exciting part of that journey for me. Now, in my case, I focus on strategic accounts, right? Strategic accounts are big, you know, they're the potential to be our whale customers, right? These are probably not customers who would be all that interested in serverless, right? They're customers that would be more interested in provisioned infrastructure because they're the people that I talked to when I was at DynamoDB; I would be talking to customers who are interested in like, reserved capacity allocations, right? If you're talking about—Corey: Yeah, I wanted to ask you about that. You're developer advocacy—which I get—for strategic accounts.Rick: Right.Corey: And I'm trying to wrap my head around—Rick: Why [crosstalk 00:17:19]—Corey: [crosstalk 00:17:19] strategic accounts are the big ones, potential spend lots of stuff. Why do they need special developer advocacy?Rick: [laugh]. Well, yeah, it's funny because, you know, one of the reasons why it started talking to Mark Porter about this, you know, was the fact that, you know, the overlap is really around [clear throat] the engagements that I ran when I was doing the Amazon retail migration, right? When Amazon retail started to move to NoSQL, we deprecated 3000 Oracle server instances, we moved a large percentage of those workloads to NoSQL. The vast majority probably just were lift-and-shift into RDS and whatnot because they were too small, too old, not worth upgrading whatnot, but every single tier, what we call tier-one service, right, every money-making service was redesigned and redeployed on DynamoDB, right? So, we're talking about 25,000 developers that we had to ramp. This is back four years ago; now we have, like, 75,000.But back then we had 25,000 global developers, we had [clear throat] a technology shift, a fundamental paradigm shift between relational modeling and NoSQL modeling, and the whole entire organization needed to get up to speed, right? So, it was about creating a center of excellence, it was about operating as an office of the CTO within the organization to drive this technology into the DNA of our company. And so that exercise was actually incredibly informative, educational, in that process of executing a technology transformation in a major enterprise. And this is something that we want to reproduce. And it's actually what I did for Dynamo as well, really more than anything.Yes, I was on Twitter, I was on Twitch, I did a lot of these things that were kind of developer advocate, you know, activities, but my primary job at AWS was working with large strategic customers, enabling their teams, you know, teaching them how to model their data in NoSQL, and helping them cross the chasm, right, from relational. And that is advocacy, right? The way I do it is I use their workloads. [clear throat]. I use their—the customers, you know, project teams themselves, I break down their models, I break down their access patterns when I leave, essentially—with the whole day of design reviews, we'll walk through 12 or 15 workloads, and when I leave these guys have an idea: How would I do it if I wanted to use NoSQL, right?Give them enough breadcrumbs so that they can actually say, “Okay, if I want to take it to the next step, I can do it without calling up and say, ‘Hey, can we get a professional services team in here?'” right? So, it's kind of developer advocacy and it's kind of not, right? We're kind of recognizing that these are whales, these are customers with internal resources that are so huge, they could suck our Developer's Advocacy Team in and chew it up, right? So, what we're trying to do is form a focus team that can hit hard and move the needle inside the accounts. That's what I'm doing. Essentially, it's the same work I did for [clear throat] AWS for DynamoDB. I'm just doing it for, you know—they traded for a new quarterback. Let's put it that way. [laugh].Corey: This episode is sponsored in part by our friends at Sysdig. Sysdig is the solution for securing DevOps. They have a blog post that went up recently about how an insecure AWS Lambda function could be used as a pivot point to get access into your environment. They've also gone deep in-depth with a bunch of other approaches to how DevOps and security are inextricably linked. To learn more, visit sysdig.com and tell them I sent you. That's S-Y-S-D-I-G dot com. My thanks to them for their continued support of this ridiculous nonsense.Corey: So, one thing that I find appealing about the approach maps to what I do in the world of cloud economics, where I—like, in my own environment, our AWS bill is creeping up again—we have 14 AWS accounts—and that's a little over $900 a month now. Which, yeah, big money, big money.Rick: [laugh].Corey: In the context of running a company, that no one notices or cares. And our customers spend hundreds of millions a year, pretty commonly. So, I see the stuff in the big accounts and I see the stuff in the tiny account here. Honestly, the more interesting stuff is generally in on the smaller side of the scale, just because you're not going to have a misconfiguration costing a third of your bill when a third of your bill is $80 million a year. So—Rick: That's correct. If you do then that's a real problem, right?Corey: Oh yeah.Rick: [laugh].Corey: It's very much a two opposite ends of a very broad spectrum. And advice for folks in one of those situations is often disastrous to folks on the other side of that.Rick: That's right. That's right. I mean, at some scale, managing granularity hurts you, right? The overhead of trying to keep your costs, you know, it—but at the same time, it's just different, a different measure of cost. There's a different granularity that you're looking at, right? I mean, things below a certain, you know, level stop becoming important when, you know, the budget start to get a certain scale or a certain size, right? Theoretically—Corey: Yeah, for there's certain workloads, things that I care about with my dollar-a-month Dynamo spend, if I were to move that to Mongo Serverless, great, but my considerations are radically different than a company that is spending millions a month on their database structure.Rick: That's right. Really, that's what it comes down to.Corey: Yeah, we don't care about the pennies. We care about is it going to work? How do we back it up? What's the replication factor?Rick: And that—but also, it's more than that. It's, you know, for me, from my perspective, it really comes down to that, you know, companies are spending millions of dollars a year in database services. These are companies that are spending ten times that, five times that, in you know, in developers, you know, expense, right? Building services, maintaining the code that runs—that the services run.You know, the biggest problem I had with MongoDB is the level of code complexity. It's a cut after cut after cut, right? And the way I kind of describe the experience—and other people have described it to me; I didn't come up with this analogy. I had a customer tell me this as they were leaving DynamoDB—“DynamoDB is death by a thousand cuts. You love it, you start using it, you find a little problem, you start fixing it. You start fixing it. You start fixing—you come up with a pattern. Talk to Rick, he'll come up with something. He'll tell you how to do that.” Okay?And you know, how many customers did I would do this with? You know, and it's honestly, they're 15-minute phone calls for me, but every single one of those 15-minute phone calls turns into eight hours of developer time writing the code, debugging it, deploying it over and over again, it's making sure it's going the way it's [crosstalk 00:23:02]—Corey: Have another 15-minute call with Rick, et cetera, et cetera. Yeah.Rick: Another 15—exactly. And it's like okay, that's you know—eventually, they just get tired of it, right? And I actually had a customer that tell me—a big customer—tell me flat out, “Yeah, you proved that the DynamoDB can support our workload and it'll probably do it cheaper, but I don't have a half-a-dozen Ricks on my team, right? I don't have any Ricks on my team. I can't be getting you in here every single time we have to do a complex data model overhaul, right?”And this was—granted, it was one of the more complex implementations that I've ever done. In order to make it work. I had to overload the fricking table with multiple access patterns on the partition key, something I never done in my life. I made it work, but it was just—honestly, that was an exercise to me that taught me something. If I have to do this, it's unnatural, okay?And that's—[laugh] you know what I mean? And honestly, there's API improvements that we could have done to make that less of a problem. It's not like we haven't known since the last, I don't know, I joined the company that a thousand WCUs per storage partition was pretty small. Okay? We've kind of known that for I don't know, since DynamoDB, was invented. As matter of fact is, from what I know, talking to people who were around back then, that was a huge bone of contention back in the day, right? A thousand WCUs, ten gigabytes, there were a lot of the PEs on the team that were going, “No way. No way. That's way too small.” And then there were other people that were like, “Nah, nobody's ever going to need more than that.” And you know, a lot of this was based on the analysis of [crosstalk 00:24:28]—Corey: Oh, nothing ever survives first contact from—Rick: Of course.Corey: —customer, particularly a customer who is not themselves deeply familiar with what's happening under the hood. Like, I had this problem back when I was traveling trainer for Puppet for a while. It was, “Great. Well, Puppet is obviously a piece of crap because everyone I talked to has problems with it.” So, I was one of the early developers behind SaltStack—Rick: Oh nice.Corey: —and, “Ah, this is going to be a thing of beauty and it'll be awesome.” And that lasted until the first time I saw what somebody's done with it in the wild. It was, “Oh, okay, that's an [unintelligible 00:25:00] choice.”Rick: Okay, that's how—“Yeah, I never thought about that,” right? Happy path. We all love the happy path, right? As we're working with technologies, we figure out how we like to use it, we all use it that way. Of course, you can solve any problem you want the way that you'd like to solve it. But as soon as someone else takes that clay, they mold a different statue and you go, “Oh, I didn't realize it could look like that.” Right, exactly.Corey: So, here's one for you that I've been—I still struggle with this from time to time, but why would I, if I'm building something out—well, first off, why on earth would I do that? I have people for that who are good at things—but if I'm building something out and it has a database layer, why would someone choose NoSQL over—Rick: Oh, sure.Corey: —over SQL?Rick: [crosstalk 00:25:38] question.Corey: —and let me be clear here—and I'm coming at this from the perspective of someone who, basically me a few years ago, who has no real understanding of what databases are. So, my mental model of a database is Microsoft Excel, where I can fire up a [unintelligible 00:25:51] table of these things—Rick: Sure. [laugh]. Hey, well then, you know what? Then you should love NoSQL because that's kind of the best analogy of what is NoSQL. It's like a spreadsheet, right? Whereas a relational database is like a bunch of spreadsheets, each with their own types of rows, right? So—[laugh].Corey: Oh, my mind was blown with relational stuff [unintelligible 00:26:07] wait, you could have multiple tables? It's, “What do you think relational meant there, buddy?” My map of NoSQL was always key and value, and that was it. And that's all it can be. And sure, for some things, that's what I use, but not everything.Rick: That's right. So, you know, the bottom line is, when you think about the relational database, it all goes back to, you know, the first paper ever written on the relational model, Edgar Codd—and I can't remember the exact title, but he wrote the distributed model, the data model for distributed systems, something like that. He discussed, you know, the concept of normalization, the power of normalization, why you would want this. And the reason why we wanted this, why he thought this was important, this actually kind of demonstrates how—boy, they used to write killer abstracts to papers, right? It's like the very first sentence, this is why I'm write in this paper. You read the first sentence, you know: “Future users of modern computer systems must have a way to be able to ask questions of the data without knowing how to write code.”I mean, I don't know if those were the words, but that was basically what he said, that was why he invented the normalized data model. Because, you know, with the hierarchical management systems at the time, everyone had to know everything about the data in order to be able to get any answers, right? And he was like, “No, I want to be able to just write a question and have the system answer that.” Now, at the time, a lot of people felt like that's great, and they agreed with his normalized model—it was elegant—but they all believe that the CPU overhead at the time was way too high, right? To generate these views of data on the fly, no freaking way. Storage is expensive. But it ain't that expensive, right?Well, this little thing called Moore's Law, right? Moore's Law balanced his checkbook for, like, 40 years, 50 years, it balanced the relational database checkbook, okay? So, as the CPUs got faster and faster, crunching, the data became less and less of a problem, okay? And so we crunched bigger and bigger data sets, we got very, very happy with this. Up until about 2014.At 2014, a really interesting thing happened. If you look at the top 500, which is the supercomputers, the top 500 supercomputing clusters around the world, and you look at their performance increases year-to-year after 2014, it went off a cliff. No longer beating Moore's Law. Ever since, they've been—and per-core performance, you know, CPU, you know, instructions executed per second, everything. It's just flattening. Those curves are flattening. Moore's Law is broken.Now, you'll get people argue about it, but the reality is, if it wasn't broken, the top 500 would still be cruising away. They're not. Okay? So, what this is telling us is that the relational database is losing its horsepower. Okay?Why is it happening? Because, you know, gate length has an absolute minimum, it's called zero, right? We can't have a logic gate that's the—with negative distance, right? [laugh]. So, you know, these things—but storage, storage, hey, it just keeps on getting cheaper and cheaper, right?We're going the other way with storage, right? It's gigabytes, it's terabytes, it's petabytes, you know, with CPU, we're going smaller and smaller and smaller, and the fab cost is increasing. There's just—it's going to take a next-generation CPU technology to get back on track with Moore's Law.Corey: Well, here's the challenge. Everything you're saying makes perfect sense from where your perspective is. I reiterate, you are working with strategic accounts, which means ‘big.' When I'm building something out in the evenings because I want to see if something is possible, performance considerations and that sort of characteristic does not factor into it. When I'm a very small-scale, I care about cost to some extent—sure, whatever—but the far more expensive aspect of it, in the ways that matter have been what is the expensive—what—the big expensive piece is—Rick: We've talked about it.Corey: —engineering time—Rick: That's what we just talked about, right?Corey: —where it's, “What I'm I familiar with?”Rick: As a developer, right, why would I use MongoDB over DynamoDB? Because the developer experience [crosstalk 00:29:33]—Corey: Exactly. Sure, down the road there are performance characteristics and yeah, at the time I have this super-large, scaled-out, complex workload, yeah, but most workloads will not get to that.Rick: Will not ever get there. Ever get there. [crosstalk 00:29:45]—Corey: Yeah, so optimizing for [crosstalk 00:29:45], how's it going to work when I'm Facebook-scale? It's—Rick: So, first of—no, exactly, Facebook scale is irrelevant here. What I'm talking about is actually a cost ratchet that's going to lever on midsize workloads soon, right? Within the next four to five years, you're going to see mid-level workloads start to suffer from significant performance cost deficiencies compared to NoSQL workloads running on the same. Now you—hell, you see it right now, but you don't really experience it, like you said, until you get to scale, right? But in midsize workloads, [clear throat] that's going to start showing up, right? This cost overhead cannot go away.Now, the other thing here that you got to understand is, just because it's new technology doesn't make it harder to use. Just because you don't know how to use something, right, doesn't mean that it's more difficult. And NoSQL databases are not more difficult than the relational database. I can express every single relationship in a NoSQL database that I express in a relational database. If you think about the modern OLTP applications, we've done the analysis, ad nauseum: 70% of access patterns are for a single object, a single row of data from a single table; another 20% are for a row of datas—a range of rows from a single table. Okay, that leaves only 10% of your access patterns involve any kind of complex table traversal or entity traversals. Okay?And most of those are simple one-to-many hierarchies. So, let's put those into perspective here: 99% of the access patterns in an OLTP application can be modeled without denormalization in a single table. Because single table doesn't require—just because I put all the objects in one place doesn't mean that it's denormalized. Denormalized requires strong redundancies in the stored set. Duplication of data. Okay?Edgar Codd himself said that the normalized data model does not depend on storage, that they are irrelevant. I could put all the objects in the same document. As long as there's no duplication of data, there's no denormalization. I know, I can see your head going, “Wow,” but it's true, right? Because as long as I can clearly express the relationships of the data without strong redundancies, it is a normalized data model.That's what most people don't understand. NoSQL does not require denormalization. That's a decision you make, and it usually happens when you have many-to-many relationships; then we need to start duplicating the data.Corey: In many cases, at least my own experience—because again, I am bad at computers—I find that the data model is not something that is sat out—that you sit down and consciously plan very often. It's rather something—Rick: Oh yeah.Corey: —happens to you instead. I mean—Rick: That's right. [laugh].Corey: —realistically, like, using DynamoDB for this is aspirational. I just checked, and if I look at—so I started this newsletter back in March of 2017. I spun up this DynamoDB table that backs it, and I know it's the one that's in production because it has the word ‘test' in its name, because of course it does. And I'm looking into it, and it has 8700 items in it now and it's 3.7 megabytes. It's—Rick: Sure, oh boy. Nothing, right?Corey: —not for nothing, this could have been just as easily and probably less complex for my level of understanding at the time, a CSV file that I—Rick: Right. Exactly, right.Corey: —grabbed from a Lambda out of S3, do the thing to it, and then put it back.Rick: [unintelligible 00:32:45]. Right.Corey: And then from a performance and perspective side on my side, it would make no discernible difference.Rick: That's right because you're not making high-velocity requests against the small object. It's just a single request every now and then. S3 performance would probably—you might even be less. It might even cost you less to use S3.Corey: Right. And 30 to 100 of the latest ones are the only things that are ever looked at in any given week, the rest of it is mostly deadstock that could be transitioned out elsewhere.Rick: Exactly.Corey: But again, like, now that they have their lower cost infrequent access storage, then great. It's not item level; it's table levels, so what's the point? I can knock that $1.30 a month down to, what, $1.10?Rick: Oh well, yeah, no, I mean, again, Corey for those small workloads, you know what? It's like, go with what you know. But the reality is, look, as a developer, we should always want to know more, and we should always want to know new things, and we should always be aware of where the industry is headed. And honestly, I've heard through—I'm an old, old school, relational guy, okay, I cut my teeth on—oh, God, I don't even know what version of MS SQL Server it was, but when I was, you know, interviewing at MongoDB. I was talking to Dan Pasette, about the old Enterprise Manager, where we did the schema designer and all this, and we were reminiscing about, you know, back in the day, right?Yeah, you know, reality of things are is that if you don't get tuned into the new tooling, then you're going to get left behind sooner or later. And I know a lot of people who that has happened to over the years. There's a reason why I'm 56 years old and still relevant in tech, okay? [laugh].Corey: Mainframes, right? I kid.Rick: Yes, mainframes.Corey: I kid. You're not that much older than I am, let's be clear here.Rick: You know what? I worked on them, okay? And some of my peers, they never stopped, right? They just kind of stayed there.Corey: I'm still waiting for AWS/400. We don't see them yet, but hope springs eternal.Rick: I love it. I love that. But no, one of the things that you just said that I think it hit me really, it's like the data model isn't something you think about. The data model is something that just happens, right? And you know what, that is a problem because this is exactly what developers today think. They think know the relational database, but they don't.You talk to any DBA out there who's coming in after the fact and cleaned up all the crappy SQL that people like me wrote, okay? I mean, honestly, I wrote some stuff in the day that I thought, “This is perfect. There's no way that could be anything better than this,” right? Nice derived table joins insi—and you know what? Then here comes the DBA when the server is running at 90% CPU and 100% percent memory utilization and page swapping like crazy, and you're saying we got to start sharding the dataset.And you know, my director of engineering at the time said, “No, no, no. What we need is somebody to come in and clean up our SQL.” I said, “What do you mean? I wrote that SQL.” He's like, “Like I said, we need someone to come and clean up our SQL.”I said, “Okay, fine.” We brought the guy in. 1500 bucks an hour, we paid this guy, I was like, “There's no way that this guy is going to be worth that.” A day and a half later, our servers are running at 50% CPU and 20% memory utilization. And we're thinking about, you know, canceling orders for additional hardware. And this was back in the day before cloud.So, you know, developers think they know what they're doing. [clear throat]. They don't know what they're doing when it comes to the database. And don't think just because it's a relational database and they can hack it easier that it's better, right? Yeah, it's, there's no substitute for knowing what you're doing; that's what it comes down to.So, you know, if you're going to use a relational database, then learn it. And honestly, it's a hell of a lot more complicated to learn a relational database and do it well than it is to learn how to model your data in NoSQL. So, if you sit two developers down, and you say, “You learn NoSQL, you learn relational,” two months later, this guy is still going to be studying. This guy's going to be writing code for seven weeks. Okay? [laugh]. So, you know, that's what it comes down to. You want to go fast, use NoSQL and you won't have any problems.Corey: I think that's a good place to leave it. If people want to learn more about how you view these things, where's the best place to find you?Rick: You know, always hit me up on Twitter, right? I mean, @houlihan_rick, that's my—underbar rick, that's my Twitter handle. And you know, I apologize to folks who have hit me up on Twitter and gotten no response. My Twitter as you probably have as well, my message request box is about 3000 deep.So, you know, every now and then I'll start going in there and I'll dig through, and I'll reply to somebody who actually hit me up three months ago if I get that far down the queue. It is a Last In, First Out, right? I try to keep things as current as possible. [laugh].Corey: [crosstalk 00:36:51]. My DMs are a trash fire. Apologies as well. And we will, of course, put links to it in the [show notes 00:36:55].Rick: Absolutely.Corey: Thank you so much for your time. I really do appreciate it. It's always an education talking to you about this stuff.Rick: I really appreciate being on the show. Thanks a lot. Look forward to seeing where things go.Corey: Likewise.Rick: All right.Corey: Rick Houlihan Director of Developer Relations, Strategic Accounts at MongoDB. 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 an upset comment talking about how we didn't go into the proper and purest expression of NoSQL non-relational data, DNS TXT records.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.

The MongoDB Data API lets you read and modify data in MongoDB Atlas over HTTP. You don't need any additional MongoDB drivers, libraries, or connection strings; just a standard HTTP client and a valid API key. The Data API's endpoints expose actions that are similar to the standard query methods available in MongoDB drivers. You can call them to create, read, update, delete, or aggregate documents in your cluster.  Sumedha Mehta is the Product Manager responsible for the Data API and she joins Michael for a brief introduction to the product, how it works as well as its benefits.  Be sure to check the links below for resources, examples and documentation to help get you started. Screencast Tutorial (Youtube):  https://youtu.be/aVRnDu_BYy8 Documentation: https://docs.atlas.mongodb.com/api/data-api/ Blog Article by John Page: https://www.mongodb.com/developer/quickstart/atlas_data_api_introduction/  

With MongoDB Atlas Online Archive you can automatically tier your data across fully managed databases and cloud object storage while preserving the ability to query all your data through a single endpoint. Create a rule to automatically archive infrequently accessed data from your MongoDB Atlas database to optimize cost and performance. On today's episode, we chat with Benjamin Flast, Sr. Product Manager for MongoDB Atlas - Online Archive and Data Lake.

Shane McAllister returns to help guide a discussion on the Realm Mobile Database JavaScript SDK with our guest Kraen Hansen.  In this episode, we're talking with Kraen about Realm and JavaScript, its background, features and what's coming in the future. To join the conversation on the MongoDB Community Forums, visit: https://community.mongodb.com To get started with MongoDB Atlas, and MongoDB Realm, visit https://cloud.mongodb.com This episode is brought to you by MongoDB.local - MongoDB.local London is a uniquely hybrid experience offering education, exploration, and entertainment curated for those joining live in person at Evolution London, live from home, or on-demand on your own schedule.  Visit https://events.mongodb.com/dotlocallondon for more information and to register today!

The transition of @MongoDB from an open source project to commercially successful public company to cloud provider has been an interesting transition. One that many other software companies are looking to emulate. SHOW: 550CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:Datadog Synthetic Monitoring: Frontend and Backend Modern MonitoringStart detecting user-facing issues with API and browser tests with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.CBT Nuggets: Expert IT Training for individuals and teamsSign up for a CBT Nuggets Free Learner account AWS Data Backup for Dummies (Veeam)Choose Your Own Cloud Adventure with Veeam and AWSSHOW NOTES:History of MongoDB (wikipedia)MongoDB Atlas is launched (DBaaS) - 2016Amazon launches DocumentDB (with MongoDB compatibility) - 2019MongoDB IPO - 2019SaaS and Moving Downmarket - MongoDB's TransformationEvolution of Commercial OSS (Cloudcast Eps.492)How Cloud is Changing OSS Licensing (Cloudcast Eps.493) FROM OPEN TO COMMERCIAL TO IPO TO CLOUDMany software companies are trying to make the evolution from customer-operated to cloud-operated business models. MongoDB is an early lighthouse is showing the blueprint for success. CHANGING (OR GROWING NEW) MARKETS IS VERY DIFFICULTSolve a technical problemCreate a unique value proposition (simplicity)[Marketing] Create (and lead) a growing community of users - via open source[Monetization] Create open-core features to differentiate and solve unique problems [New GTM, New Markets] Evolve the product to new delivery modelsGrow into new markets, through different customer engagement models FEEDBACK?Email: show at the cloudcast dot netTwitter: @thecloudcastnet

SUSE's new era kicks off this week, CentOS users get some relief, and how Docker managed to piss off their users. Plus RISC-V gets a surprising benefactor, and the kernel feature we never thought would get merged that was just approved by Linus.

SUSE's new era kicks off this week, CentOS users get some relief, and how Docker managed to piss off their users. Plus RISC-V gets a surprising benefactor, and the kernel feature we never thought would get merged that was just approved by Linus.

SUSE's new era kicks off this week, CentOS users get some relief, and how Docker managed to piss off their users. Plus RISC-V gets a surprising benefactor, and the kernel feature we never thought would get merged that was just approved by Linus.

Fire departments and fire rescue professionals are facing unprecedented volumes of incidents in an ever-increasing battle to save lives. Every year, there's an average of 358,300 home-based fires.  In 2017, there were at least 1,319,500 fires (wildfire, house fire, and commercial) in the United States that resulted in 3,400 deaths. Fire departments and fire services responded to fires in the United States every 24 seconds in 2018. Tablet Command is a mobile incident command and response solution that increases situational awareness, speeds incident response, streamlines incident management and improves firefighter accountability. ...  Tablet Command leverages MongoDB Atlas, automated scalability, automated backups and through our partnership with AWS, they've achieved seamless, native high availability and scalability. In this episode, Jesse, and Nic chat with Will Pigeon, CTO of Tablet Command to explore how they're leveraging the MongoDB Platform for their incident command response solution that's helping to save countless lives and improving the efficiency and safety of fire rescue professionals.

The network edge has been one of the most explosive cloud computing opportunities in recent years. As mobile contactless experiences become the norm and as businesses move ever-faster to digital platforms and services, edge computing is positioned as a faster, cheaper, and more reliable alternative for data processing and compute at scale. While mobile devices continue to increase their hardware capabilities with built-in GPUs, custom chipsets, and more storage, even the most cutting-edge devices will suffer the same fundamental problem: each device serves as a single point of failure and, thus, cannot effectively serve as a persistent data storage layer. Said differently, wouldn't it be nice to have the high-availability of the cloud but with the topological distance to your end users of the smartphone? Mobile edge computing promises to precisely address this problem—bringing low latency compute to the edge of networks with the high-availability and scale of cloud computing. Through Verizon 5G Edge with AWS Wavelength, we saw the opportunity to explore how to take existing compute-intensive workflows and overlay a data persistence layer with MongoDB, utilizing the MongoDB Atlas management platform, to enable ultra-immersive experiences with personalized experience—reliant on existing database structures in the parent region with the seamlessness to extend to the network edge. In this episode, we welcome Robbie Belson of Verizon to help us understand this fascinating landscape and its potential. If you're curious about how 5G, and Mobile Edge Computing and the impact it can have on your applications, listen in and check out an in-depth article on the topic on the MongoDB Developer Hub: https://www.mongodb.com/developer/how-to/real-time-data-architectures-with-mongodb-cloud-manager-and-verizon-5g-edge/  

Xixi Zhang is a Senior Curriculum Engineer at MongoDB University and she's created a course designed specifically to introduce you to the power and flexibility of MongoDB Charts, the best way to create, share and embed visualizations from MongoDB Atlas and Atlas Data Lake.  In, this course, A131 Introduction to MongoDB Charts, you'll learn about MongoDB Charts, how to share and embed them, and how to adjust their viewing permissions so that you can make data-driven action plans. You will build charts to illustrate correlations, patterns, and outliers in your dataset.

Stephen Cooper joins the Adventure to discuss the ngTemplateOutlet, how it's used and where you'd add it to your application. It allows you to put a template into place where you have the outlet so you can specify what to put into the spot you have the template in and then specify the variables that it uses. This allows you to have a custom template for a specific item. Panel Charles Max Wood Sani Yusuf Subrat Mishra Guest Stephen Cooper Sponsors Dev Influencers Accelerator Raygun | Click here to get started on your free 14-day trial  Links ngTemplateOutlet: The secret to customisation Twitter: Stephen Cooper ( @SCooperDev ) Picks Charles- Monday.com Sani- MongoDB Atlas Stephen- Adding a layer of more explicit typings on top of 3rd party library interfaces Subrat- Tools Of Titans Contact Charles: Devchat.tv DevChat.tv | Facebook Twitter: DevChat.tv ( @devchattv ) Contact Sani: Angular.Training Sani Yusuf Sani Yusuf - Medium Twitter: Sani Yusuf ( @saniyusuf ) GitHub: Sani Yusuf ( saniyusuf ) Contact Subrat: Fun Of Heuristic – YouTube GitHub: Fun Of Heuristic ( funOfheuristic ) Twitter: Subrat Kumar Mishra ( @subrat_msr )

Stephen Cooper joins the Adventure to discuss the ngTemplateOutlet, how it's used and where you'd add it to your application. It allows you to put a template into place where you have the outlet so you can specify what to put into the spot you have the template in and then specify the variables that it uses. This allows you to have a custom template for a specific item. Panel Charles Max Wood Sani Yusuf Subrat Mishra Guest Stephen Cooper Sponsors Dev Influencers Accelerator Raygun | Click here to get started on your free 14-day trial  Links ngTemplateOutlet: The secret to customisation Twitter: Stephen Cooper ( @SCooperDev ) Picks Charles- Monday.com Sani- MongoDB Atlas Stephen- Adding a layer of more explicit typings on top of 3rd party library interfaces Subrat- Tools Of Titans Contact Charles: Devchat.tv DevChat.tv | Facebook Twitter: DevChat.tv ( @devchattv ) Contact Sani: Angular.Training Sani Yusuf Sani Yusuf - Medium Twitter: Sani Yusuf ( @saniyusuf ) GitHub: Sani Yusuf ( saniyusuf ) Contact Subrat: Fun Of Heuristic – YouTube GitHub: Fun Of Heuristic ( funOfheuristic ) Twitter: Subrat Kumar Mishra ( @subrat_msr )

Stephen Cooper joins the Adventure to discuss the ngTemplateOutlet, how it's used and where you'd add it to your application. It allows you to put a template into place where you have the outlet so you can specify what to put into the spot you have the template in and then specify the variables that it uses. This allows you to have a custom template for a specific item. Panel Charles Max Wood Sani Yusuf Subrat Mishra Guest Stephen Cooper Sponsors Dev Influencers Accelerator Raygun | Click here to get started on your free 14-day trial  Links ngTemplateOutlet: The secret to customisation Twitter: Stephen Cooper ( @SCooperDev ) Picks Charles- Monday.com Sani- MongoDB Atlas Stephen- Adding a layer of more explicit typings on top of 3rd party library interfaces Subrat- Tools Of Titans Contact Charles: Devchat.tv DevChat.tv | Facebook Twitter: DevChat.tv ( @devchattv ) Contact Sani: Angular.Training Sani Yusuf Sani Yusuf - Medium Twitter: Sani Yusuf ( @saniyusuf ) GitHub: Sani Yusuf ( saniyusuf ) Contact Subrat: Fun Of Heuristic – YouTube GitHub: Fun Of Heuristic ( funOfheuristic ) Twitter: Subrat Kumar Mishra ( @subrat_msr )

Watch the live stream: Watch on YouTube About the show Sponsored by us: Check out the courses over at Talk Python And Brian's book too! Special guest: Simon Willison Michael #1: MongoDB 5 Native Time Series: Designed for IoT and financial analytics, our new time series collections, clustered indexing, and window functions make it easier, faster, and lower cost to build and run time series applications MongoDB automatically optimizes your schema for high storage efficiency, low latency queries, and real-time analytics against temporal data. The Versioned API future-proofs your applications. You can fearlessly upgrade to the latest MongoDB releases without the risk of introducing backward-breaking changes that require application-side rework New MongoDB Shell we have introduced syntax highlighting, intelligent auto-complete, contextual help and useful error messages creating an intuitive, interactive experience for MongoDB users (use mongosh rather than mongo on the CLI). Also launched preview release of serverless instances on MongoDB Atlas You can watch the MongoDB keynote here. Brian #2: Python 3.11 : Enhanced error locations in tracebacks Yes, 3.11. Even though 3.10 is still in Beta, we're already excited about 3.11 tracebacks now point to the exact expression that caused the error within the line: Traceback (most recent call last): File "distance.py", line 11, in [HTML_REMOVED] print(manhattan_distance(p1, p2)) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "distance.py", line 6, in manhattan_distance return abs(point_1.x - point_2.x) + abs(point_1.y - point_2.y) ^^^^^^^^^ AttributeError: 'NoneType' object has no attribute 'x' even deeply nested calls Traceback (most recent call last): File "query.py", line 37, in [HTML_REMOVED] magic_arithmetic('foo') ^^^^^^^^^^^^^^^^^^^^^^^ File "query.py", line 18, in magic_arithmetic return add_counts(x) / 25 ^^^^^^^^^^^^^ File "query.py", line 24, in add_counts return 25 + query_user(user1) + query_user(user2) ^^^^^^^^^^^^^^^^^ File "query.py", line 32, in query_user return 1 + query_count(db, response['a']['b']['c']['user'], retry=True) ~~~~~~~~~~~~~~~~~~^^^^^ TypeError: 'NoneType' object is not subscriptable and math expressions: Traceback (most recent call last): File "calculation.py", line 54, in [HTML_REMOVED] result = (x / y / z) * (a / b / c) ~~~~~~^~~ ZeroDivisionError: division by zero Simon #3: fly.io multi-region PostgreSQL and last mile Redis fly.io are a hosting provider that specialize in running your code in containers that are geographically close to your users What I find interesting about them is that they are taking something that used to be INCREDIBLY hard - like geographically sharding your database - and describing patterns for doing that which make it easy-enough that I might actually do it Their writing is really good. I'm learning a ton from them about designing code to run globally that applies even if I don't end up using their service Michael #4: django-unicorn A magical full-stack framework for Django Quickly add in simple interactions to regular Django templates without learning a new templating language. Building a feature-rich API is complicated. Skip creating a bunch of serializers and just use Django. Early days if you want to contribute Brian #5: Blue : The somewhat less uncompromising code formatter than black Suggested by Chris May Code from Black, mods by Grant Jenks and Barry Warsaw It's not a fork, it's a patched version of black. Kind of a “containment over inheritance” thing. Deltas: blue defaults to single-quoted strings. except docstrings and triple quoted strings (TQS). Those are still double quotes. blue defaults to line lengths of 79 characters. black is 88. line lengths are customizable with all related tools. blue preserves the whitespace before the hash mark for right hanging comments. making comment blocks off to the side possible blue supports multiple config files: pyproject.toml, setup.cfg, tox.ini, and .blue. Interesting quote from the docs: “We'd prefer not to fork or monkeypatch. Instead, our hope is that eventually we'll be able to work with the black maintainers to add just a little bit of configuration and merge back into the black project. “ My take Probably stick with black most of the time. For some large exiting projects with lots of strings that have standardized to single quote strings already, black is jarring. Also, strings with double quotes in them are untouched by black, so if you have lots of those, strings will be inconsistent, making the code harder to read and confusing to maintain. And the choice isn't really black or blue. It's often nothing due to the non-starter of switching to double quote strings by default. blue is better than nothing. See also # fmt: off, # fmt: on for both blue and black # tell black/blue to not reformat this table # fmt: off some_table = [ 1, 2, 3, 100, 200, 300 ] # fmt: on Simon #6: Organize and Index Your Screenshots (OCR) on macOS I've been wanting to figure out how to use Tesseract OCR for years, and this post finally unlocked it for me brew install tesseract tesseract image.png output-file -l eng pdf (use txt instead of pdf to get plain text) I wrote a TIL about this at https://til.simonwillison.net/tesseract/tesseract-cli It's really good! Even works against photos I've taken. And the PDFs it produces have copy-and-paste text in them (despite looking visually identical to the image) and can be searched using Spotlight. There's a pytesseract library but it actually just works by running that Tesseract CLI tool in a subprocess Extra: Using SQL to find my best photo of a pelican according to Apple Photos Extras Michael: Strong Typing follow up typed nametuple: strongtyping.readthedocs.io/en/latest/namedtuple/ now classes: github.com/FelixTheC/strongtyping/issues/65 We are finally rid of tracking on the podcast sites. But it took some neat tech work Simon https://pythonbytes.fm/episodes/show/237/separate-your-sql-and-python-asynchronously-with-aiosql talked about Textual but it's worth marveling at how far along it has already come, one of the fastest pieces of development-in-the-open I've ever seen - follow along on Will's Twitter account, he posts a lot of videos and screenshots e.g. https://twitter.com/willmcgugan/media and the videos in his README at https://github.com/willmcgugan/textual/blob/main/README.md Joke A “Query tale”? Song from Brett Cannon (take on Pinky and the Brain theme song) What do you want to do today, Brian? Same thing we do every Wednesday, Michael. Help Python take over the world. It's Michael and the Brain! Yes, Michael and the Brain! One's into testing, the other GUIs! They're both into making Python seem sane! They're Michael, they're Michael and the Brain, Brain, Brain, Brain, Brain!

Welcome to the final episode in a series we're calling The Road to Atlas.  In this series, my co-hosts, Jesse Hall, and Nic Raboy will talk with some of the people responsible for building, and launching the platform that helped to transform MongoDB as a company. beginning with Episode 1, the On ramp to Atlas we chatted with Sahir Azam, Chief Product Officer, and Andrew Davidson, VP of Product about the strategic shift from a software company to a software as a service business. In episode 2, Zero to Database as a Service, we chatted with Cailin Nelson, Executive Vice President of Cloud, and Cory Mintz, Vice President of Engineering - about Atlas as a product and how it was built and launched. In episode 3, entitled Going Mobile, we talked with Alexander Stigsen, Founder of the Realm Mobile Database which has become a part of the Atlas Platform.  And finally, In this, episode 4, we'll wrap the series up with a panel discussion and review some of our valued customer comments about the platform with Cailin Nelson, Executive Vice President of Cloud and Sahir Azam, Chief Product Officer. Many thanks to Jim McClarty, Software Architect at Keller Williams Realty, Inc. and Gaspard Petit, Software Architect at Square Enix for their feedback and comments about MongoDB and the MongoDB Atlas platform.

Today, we are joined by Julia Oppenheim, Associate Product Manager at MongoDB. Julia chats with us and shares details of a set of features within MongoDB Atlas designed to help developers improve the design of their schemas to avoid common anti-patterns. 

Tapani Otala is the VP of Engineering at Tidepool, an open source, not-for-profit company focused on liberating data from diabetes devices, supporting researchers, and providing great, free software to people with diabetes and their care teams. He joins us today to share details of the Tidepool solution, how it enables enhanced visibility into Diabetes data and enables people living with this disease to better manage their condition.  Visit https://tidepool.org for more information.   Did you know that MongoDB is helping developers to fight Covid-19? We're offering Atlas credits for developers working on projects battling the pandemic. For more than a year, the world has been living and struggling with COVID-19. Vaccines are now being rolled out in many countries, but the global situation is still critical. In fact, many regions are battling through the most severe phase of the pandemic. Throughout it all, technologists have been coming together to develop applications to help detect, understand, and stop the spread of COVID-19. We are incredibly grateful to everyone who is working hard to tackle the virus, and this program is our small way of helping out. If you are working on a project to help combat COVID-19, apply on our web site and give us a bit of detail. Qualified applications intended to help fight this COVID-19 battle will receive $300 of MongoDB Atlas credits.    

Alexey Glazunov joins us to talk about how Funnelytics leveraged MongoDB to displace Postgres and prepared to scale their startup for the next phase of their journey.  Funnelytics is a simple and aesthetically pleasing funnel mapping software that you can use to design, track and analyze your marketing funnels. ... Mikael Dia created Funnelytics after being frustrated that there wasn't a better tool out there for mapping funnels and tracking analytics all in one place. More information: MongoDB Atlas: https://www.mongodb.com/atlas MongoDB Community: https://community.mongodb.com Register for MongoDB.live 2021 today! Registration is open for MongoDB.live, MongoDB's biggest annual user event.  Join us on July 13th and 14th for this free, virtual streaming event that will feature a solid lineup of cutting-edge keynotes, dozens of breakout sessions, live Ask Me Anything panels, “brain break” activities, and so much more!    Head to mongodb.com/live to register and to get updates on what is in store for July!  

Where would you like your Mongo? Carl and Richard chat with James Kovacs and Rachelle Palmer about the latest at MongoDB, the open-source document database. While MongoDB's origins are in open web projects, today it is very popular with the enterprise development crowd and so the libraries for Java and C# are excellent. The conversation also turns to MongoDB Atlas, which is the cloud offering that runs on AWS, Azure and GCP - so you can have MongoDB-as-a-Service in the cloud provider of your choice!

Where would you like your Mongo? Carl and Richard chat with James Kovacs and Rachelle Palmer about the latest at MongoDB, the open-source document database. While MongoDB's origins are in open web projects, today it is very popular with the enterprise development crowd and so the libraries for Java and C# are excellent. The conversation also turns to MongoDB Atlas, which is the cloud offering that runs on AWS, Azure and GCP - so you can have MongoDB-as-a-Service in the cloud provider of your choice!Support this podcast at — https://redcircle.com/net-rocks/donations

Where would you like your Mongo? Carl and Richard chat with James Kovacs and Rachelle Palmer about the latest at MongoDB, the open-source document database. While MongoDB's origins are in open web projects, today it is very popular with the enterprise development crowd and so the libraries for Java and C# are excellent. The conversation also turns to MongoDB Atlas, which is the cloud offering that runs on AWS, Azure and GCP - so you can have MongoDB-as-a-Service in the cloud provider of your choice!Support this podcast at — https://redcircle.com/net-rocks/donations

Brian Jones, Infrastructure Cloud Architect,  and Brian Poirier Sr. Infrastructure Engineer from Liberty Mutual Insurance join the show today to talk about their roles in shared services, about the stack of technologies they use and support and how they're working toward migration from a primarily on-premises server environment to one that incorporates a variety of cloud services including MongoDB Atlas.

SHOW: Season 1, Show 5OVERVIEW: From the creators of the Internet's #1 Cloud Computing podcast, The Cloudcast, Aaron Delp (@aarondelp) and Brian Gracely (@bgracely) introduce this new podcast,  Cloudcast Basics.  What does database mean in the cloud? Relational, Non-Relational, Key-Value, In-Memory, Time Series, Document How are databases allocated? Purpose, Capacity, Performance, Availability, Geographic LocationHow were databases allocated before cloud computing? DBAsWhat does the cloud computing provider do with a database offering (responsibilities vs. customer responsibilities? Lots of variety, depending on the serviceWhy are there so many variations of databases? (lots of different application needs, DB technology has advanced quite a bit in the last decade)Does it matter where the database is located? How do clouds organize databases(availability zones, regions, etc.)?How much do databases cost in the cloud? What are the various ways you can buy security? Native services vs. 3rd-party services.Examples:AWS - https://aws.amazon.com/products/security/Azure - https://azure.microsoft.com/en-us/product-categories/security/Google Cloud - https://cloud.google.com/securityOracle Cloud - https://www.oracle.com/security/IBM Cloud - https://www.ibm.com/cloud/securitySnowflake - https://www.snowflake.com/MongoDB Atlas - https://www.mongodb.com/cloud/atlasSUBSCRIBE: Please subscribe anywhere you get podcasts (Apple Podcasts, Google Podcasts, Spotify, Stitcher, Amazon Music, Pandora, etc.).CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwLEARNING CLOUD COMPUTING:Here are some great places to begin your cloud journey, if you're interested in getting hands-on experience with the technology, or you'd like to build your skills towards a certification. CBT Nuggets - Training and CertificationsA Cloud Guru - Training and CertificationsCloud Academy - Training and CertificationsKatakoda - Self-Paced, Interactive LearningGitHub - Code Samples and CollaborationFEEDBACK?Web: Cloudcast Basics Email: show at cloudcastbasics dot netTwitter: @cloudcastbasics

In this episode, Alan Chhabra, SVP of Partners and SVP of Asia Sales at MongoDB, talks about MongoDB, a high-performance database best suited for Big Data applications and Agile software development practices. It offers a flexible data model, elastic scalability, and high performance. Microsoft Azure is one of the best places to run MongoDB workloads securely and efficiently.Alan discusses trends to be watched in the non-relational database space, MongoDB for website development, as well as the many other uses of the platform, how their experience has been from his side in offering MongoDB Atlas on Azure, and how he sees the future of MongoDB evolving within Azure.Episode LinksShow TranscriptMongoDB WebsiteAutomated MongoDB Service on Microsoft AzureFollow MongoDB on Twitter or LinkedIn.GuestAlan Chhabrais responsible for Worldwide Partners as well as running Asia Sales at MongoDB.He is a frequent speaker at industry events where he regularly leads discussions on how cloud computing, IoT, and big data can help CIOs meet their business objectives.Follow him on Twitter or LinkedIn.HostsPaul Maher is General Manager of the Marketplace Onboarding, Enablement, and Growth team at Microsoft. Follow him on LinkedIn and Twitter.David Starr is a Principal Azure Solutions Architect in the Marketplace Onboarding, Enablement, and Growth team at Microsoft. Follow him on LinkedIn and Twitter.

Ansible is an open-source automation tool, used for configuration management, application deployment, orchestration, and provisioning. Martin Schurz, who works for T-Systems in Germany, has done extensive work with Ansible explains how he's built Ansible playbooks to automate aspects of deploying and managing MongoDB instances in MongoDB Atlas.  Find more information at https://github.com/T-Systems-MMS/ansible-collection-mongodb-atlas

MongoDB Connectors and Translators include tools like the BI Connector, and mongomirror. In this episode we talk with the engineers responsible for maintaining these and similar products. The MongoDB BI Connector lets you use MongoDB as a data source for your BI and analytics (e.g. Tableau, Qlik and similar). Seamlessly creating the visualizations and dashboards that will help you extract the insights and hidden value in your MongoDB data. mongomirror is a utility for migrating data from an existing MongoDB replica set to a MongoDB Atlas replica set.  It can also be used for performing a one-time migration of a dataset from one Atlas cluster into another Atlas cluster. Tim Fogarty, Varsha Subrahmanyam, and Evgeni Dobranov stop by to help us understand how these products work. https://mongodb.com/products/bi-connector https://docs.atlas.mongodb.com/import/mongomirror/ Be sure to check out MongoDB Late Night - a fun, free event hosted by MongoDB. There will be live trivia, a home shopping network that will feature some amazing SWAG! https://bit.ly/mongodblatenight to RSVP! Thursday, December 3rd | 5:00 pm ET - 9:00 pm ET  

On this episode, we welcome Marissa Jasso, Product Marketing Manager at MongoDB to the show to tell us about the MongoDB Early Access Program (EAP).  EAP gives access to pre-release features to MongoDB Atlas users in order to get feedback to help shape and improve the products. In this first phase of the program, users accepted into the program will get access to Autopilot Mode for Creating Indexes. To learn more, visit https://mongodb.com/early-access

Lead Product Manager rejoins Nic and I to continue the automation discussion and we focus on automated scalability. Automated scalability refers to the capacity of a system to automatically adjust resources to meet demand. MongoDB Atlas has this capability, built-in. Rez helps us understand exactly how this works, and how we might use it to enhance the cost structure and flexibility of our apps.  Read More About Cluster Autoscale: https://docs.atlas.mongodb.com/cluster-autoscaling/

This week in MongoDB - MongoDB Developer Advocate Adrienne Tacke joins Michael Lynn to discuss the latest news and events from the world of MongoDB for the week of November 9th, 2020.  1. MongoDB University's new Social Accomplishment Share - Share your course completions on social media, and LinkedIn.  Log in to MongoDB University and navigate to your completed course page to view the new Share Your Proof of Completion feature. 2. MongoDB Atlas in Italy We're delighted to announce our first foray into Italy with the launch of MongoDB Atlas on the AWS Europe (Milan) region. MongoDB Atlas is now available in 20 AWS regions around the world, including 6 European regions. 3. MongoDB.live regional events and official pre-game events happening this week This week:  Nov 10 Northern Europe (pre-game event: Dublin User Group, Nov 9th) Main event: https://www.mongodb.com/live-northern-europe Pre-game: https://live.mongodb.com/events/details/mongodb-dublin-presents-dublin-user-groups-mongodblive-2020-pre-game-event/  Nov 11 A/NZ (pre-game event: Sydney User Group, Nov 10) Main event: https://www.mongodb.com/live-anz  Pre-game: https://live.mongodb.com/events/details/mongodb-sydney-presents-sydney-user-groups-mongodblive-2020-pre-game-event/  4. Coming this week on twitch.tv/mongodb - Joe Karlsson and Max Marcon sit down with Nic and I for a discussion about the MongoDB VSCode extension. If you use MongoDB and VSCode, you'll want to make sure you catch this episode. We'll be going live at 12noon ET, 9:00AM Pacific at https://twitch.tv/mongodb See https://dev.to/mongodb for additional updates. https://twitch.tv/mongodb https://twitter.com/mongodb

Multi-cloud clusters - a feature available in MongoDB Atlas, a global cloud database service - takes the concept a step further by enabling a single application to use multiple clouds. With multi-cloud clusters, data is distributed across different public clouds (Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure), enabling deployment of a single database across multiple providers simultaneously.  In this episode, Nic and I sit down with Andrew Davidson, VP of Cloud Product at MongoDB to discuss this latest innovation to MongoDB Atlas. Sign up for a free Atlas account and take a look at this feature in action. 

This week in MongoDB - MongoDB Developer Advocate Adrienne Tacke joins Michael Lynn to discuss the latest news and events from the world of MongoDB for the week of November 2, 2020.  1. Hacktoberfest Update: 233 PRs created, all merged! Many first-time contributors who were afraid to participate finally did by contributing to the Wild Aid app! https://charts.mongodb.com/charts-sheeri-jymux/public/dashboards/5f83a62a-eede-4b7d-8162-29b7bd67bd55 2. MongoDB Atlas Multi-cloud https://www.mongodb.com/blog/post/introducing-multicloud-clusters-on-mongodb-atlas 3, MongoDB Charts - Lookup Field in Charts  https://www.mongodb.com/blog/post/new-lookup-fields-build-charts-data-multiple-collections 4. MongoDB Engineering adopts a new, more rapid quarterly release schedule coming in 2021 https://www.mongodb.com/blog/post/new-quarterly-releases-starting-with-mongodb-5-0 5. Hasna Kourda built Save Your Wardrobe, a fashion tech startup building a digital wardrobe management platform to enable sustainable living. Part of our #BuiltWithMongoDB series, Hasna shares her experience working with MongoDB Atlas to rapidly grow this company! Check out full blog post at https://www.mongodb.com/blog/post/built-save-your-wardrobe See https://dev.to/mongodb for additional updates. https://twitch.tv/mongodb https://twitter.com/mongodb

This week we discuss database automation with Lead Product Manager Rez Kahn. This is the first of a multi-part series on database automation and in this episode, Rez talks about the importance of indexes and index management as well as how MongoDB Atlas provides automation to ensure that your applications continue to perform efficiently.  MongoDB Docs: Performance Advisor https://docs.atlas.mongodb.com/performance-advisor/   MongoDB Docs: Remove Unnecessary Indexes https://docs.atlas.mongodb.com/schema-advisor/too-many-indexes/#indexes-anti-pattern   MongoDB Docs: Indexes https://docs.mongodb.com/manual/indexes/   MongoDB Docs: Compound Indexes — Prefixes https://docs.mongodb.com/manual/core/index-compound/#prefixes   MongoDB Docs:  Indexing Strategies https://docs.mongodb.com/manual/applications/indexes/      

This week on How I Launched This: A SaaS Story, Stephanie Wong (@swongful) is pleased to welcome Lena Smart from MongoDB. MongoDB is a force in the database industry, offering indexing and storage capabilities for any document.We start the show with a thorough discussion of Lena's background and her journey to becoming one of the top Chief Information Security Officers in the business. With the vital importance of security online and the ever-changing laws and regulations proliferating the space, Lena tells us that security should be part of a business's culture. She offers tips for achieving this ideal, including instituting a policy of mandatory security awareness training and supporting your strongest link - your employees.The episode continues as Lena tells the story of MongoDB's founding. With the growth of mobile and cloud technologies, it became clear that the world needed a better database. MongoDB rose to the challenge by providing an intuitive, easy, secure solution for companies that is scalable and customizable. We learn about MongoDB Atlas, a global database platform with out-of-the-box layered security measures and additional available add-ons like Atlas Data Lake. Lena explains this layered approach to MongoDB security, comparing it to the physical securities a brick-and-mortar business or home might employ. We learn about MongoDB's field level encryption specifically and how it's changing database security.To wrap up the show, Lena talks about the hiring process for security personnel and how a few good team members can help influence and mentor others. She stresses the security culture mindset, emphasizing cooperation between departments. We talk about the partnership between Google and MongoDB and how these two companies have learned from each other. Lena leaves us with a powerful message to be yourself and continue to grow and learn.Episode Links:MongoDBMongoDB AtlasMongoDB RealmMongoDB Atlas Data Lake

We dive into low-code and no-code application development with AppFarm co-founders Marius Tuft Mathisen and Ole Borgersen. Learn how they're using MongoDB Atlas on GCP to build and scale their rapid application development platform.

There's never been a more important time to reduce the amount of money you're spending on your application infrastructure. This brief episode will provide some important ways you can reduce your overall costs while managing and maintaining your applications and data in MongoDB Atlas.

Sara reveals that she won a $500 gift card at a MongoDB hackathon, building an app that removed mustaches from people's pictures.  This was many years ago, and no we were not paid in JetBlue gift cards to have Eliot on the show, although MongoDB is a client of Stack Overflow in other areas.Mongo comes from humongous, cause, ya know, scale. That, plus HumongousDB.com was already taken and is a real mouthful to say. Eliot talks about the frustrations he and his co-founder, Dwight Merriman, experienced while working together at DoubleClick and ShopWiki. DoubleClick began as a New York City ad tech company and evolved into the heart of Google's real-time ad business after being acquired. Frustrations with the database systems available at both these companies led the pair to decide it was time for a better mousetrap. Today, MongoDB is a public company  worth north of $7 billion and a staff of more than 1900 peopleWe chat about why relational databases are still the core of computer science education in high school and college across the United States, and whether or not this will ever change. During the show we skimmed some of the latest questions on Stack Overflow related to Mongo. Eliot took it back to his team and Tom Hollander, the PM for Mongo's chart product, delivered a great answer! Can you believe this website is free?

Sara reveals that she won a $500 gift card at a MongoDB hackathon, building an app that removed mustaches from people's pictures.  This was many years ago, and no we were not paid in JetBlue gift cards to have Eliot on the show, although MongoDB is a client of Stack Overflow in other areas.Mongo comes from humongous, cause, ya know, scale. That, plus HumongousDB.com was already taken and is a real mouthful to say. Eliot talks about the frustrations he and his co-founder, Dwight Merriman, experienced while working together at DoubleClick and ShopWiki. DoubleClick began as a New York City ad tech company and evolved into the heart of Google’s real-time ad business after being acquired. Frustrations with the database systems available at both these companies led the pair to decide it was time for a better mousetrap. Today, MongoDB is a public company  worth north of $7 billion and a staff of more than 1900 peopleWe chat about why relational databases are still the core of computer science education in high school and college across the United States, and whether or not this will ever change. During the show we skimmed some of the latest questions on Stack Overflow related to Mongo. Eliot took it back to his team and Tom Hollander, the PM for Mongo's chart product, delivered a great answer! Can you believe this website is free?

On the podcast today we have a fascinating interview from our time at Cloud Next ‘19! Mark and Jon went in-depth with Andrew Davidson about MongoDB to find out what they do and how they do it. MongoDB is a document database that stores JSON natively, making it super easy for developers to work with data in a way that’s similar to how they think about building applications. The database is scalable, highly available by default with built-in replication, has an intuitive query language, and can be run anywhere. MongoDB Atlas is a global database service that runs on Google Cloud; it automates deployment and provisioning, and ongoing operations such as maintenance, upgrades, and scaling with no downtime. Atlas is a declarative model to manage your databases easily, is easy to migrate to, and offers advanced features such as global clusters for low latency read and write access anywhere in the world. In the future, Andrew sees a world where we think in terms of JSON-style documents instead of just tables. MongoDB can help make that happen. Andrew Davidson Andrew Davidson, a Silicon Valley native who lives in NYC, is the Director of Cloud Products at MongoDB with a focus on MongoDB Atlas, MongoDB’s global database as a service. He previously worked on scaling global mapping operations at Google, has a background in physics, and has lived extensively in South Asia. Cool things of the week Level up on Android with Indie Games Accelerator blog Berglas site American Cancer Society uses Google Cloud machine learning to power cancer research blog Efficiently scale ML and other compute workloads on NVIDIA’s T4 GPU, now generally available blog GCP Podcast Episode 168: NVIDIA T4 with Ian Buck and Kari Briski podcast After school, this teen tracks climate change with NASA blog Interview MongoDB site MongoDB Atlas site JSON site Virtual Private Cloud (VPC) site Kubernetes site MongoDB Charts site MondgoDB Stitch site MongoDB University site MongoDB.local site MongoDB World site Question of the week How can I access Google Cloud Shell from any terminal? Introducing the ability to connect to Cloud Shell from any terminal blog gcloud alpha cloud-shell ssh site gcloud alpha cloud-shell scp site gcloud alpha cloud-shell get-mount-command site Where can you find us next? Jon and Mark will be at IO.

SHOW: 395DESCRIPTION: Brian talks with Dr. Steve Herrod (@herrod, Managing Director at General Catalyst @gcvp) about the transition from CTO to VC, the role of AI and Security in today’s startups, the impact the public cloud has on his evaluations, and tips for selecting the right companies and leaders.SHOW SPONSOR LINKS:MongoDB Atlas - Automated cloud MongoDB serviceVisit mongodb.com/cloudcast to learn more. MongoDB Atlas handles all the costly database operations and admin tasks that you’d rather not spend time on, like security, high availability, data recovery, monitoring, and elastic scaling. Try MongoDB Atlas today!Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtGet 20% off VelocityConf passes using discount code CLOUDCLOUD NEWS OF THE WEEK:Ford partners with Amazon to build cloud services for connected carsFord invests $500M in Rivian; companies plan electric vehicleElectric truck start-up Rivian announces $700 million investment round led by AmazonApple spends more than $30 million on Amazon's cloud every month, making it one of the biggest AWS customersTinder’s move to KubernetesSHOW INTERVIEW LINKS:Steve’s Bio at General Catalyst Steve Herrod on Episode 161SHOW NOTES:Topic 1 - Welcome back to the show. It’s now been 6 years since your transition from VMware to the VC world. What are some of the lessons you’ve learned?Topic 2 - When you were a CTO, you were building a comprehensive portfolio. How does that perspective change when you’re looking at a broad range of portfolio companies? Topic 3 - Your companies tend to skew towards cybersecurity, where AI is going to play a significant role. How do you think about them from a technology perspective, and how much does the cloud’s resources for data modeling help or challenge them?Topic 4 - What’s your perspective on the role of open source software for enabling your companies?Topic 5 - Given your background, how much do you get involved in growing the engineering talent at your portfolio companies?Topic 6 - Any tips for potential startups wanting to pitch high-level VCs?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet and @ServerlessCast

SHOW: 394DESCRIPTION: Brian talks with Evan Kaplan (@evankaplan, CEO of InfluxData) about why companies choose time-series databases, commons use-cases, how time-series patterns align to changing business goals, and how to translate business demands to developer capabilities. SHOW SPONSOR LINKS:Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtMongoDB Atlas - Automated cloud MongoDB serviceVisit mongodb.com/cloudcast to learn more. MongoDB Atlas handles all the costly database operations and admin tasks that you’d rather not spend time on, like security, high availability, data recovery, monitoring, and elastic scaling. Try MongoDB Atlas today!Get 20% off VelocityConf passes using discount code CLOUDCLOUD NEWS OF THE WEEK:GCP partners with Open-Source CompaniesPentagon narrows JEDI Cloud contract down to AWS and AzureSHOW INTERVIEW LINKS:InfluxData Homepage The InfluxData TICK Stack (Telegraf, InfluxDB, Chronograf, Kapacitor)InfluxData closes $60M Round of Funding (Feb 2019)SHOW NOTES:Topic 1 - Welcome to the show. You’ve been the CEO of InfluxData for a few years, but please share with the audience your background and how you came to lead InfluxData.Topic 2 - For many decades, most data-centric applications were built around Relational Databases (SQL Databases). These days, application patterns and use-cases have expanded significantly. How do time-series databases fit into these new trends?Topic 3 - With all the new patterns emerging, there are both business reasons and technical reasons for choosing the right platform. How do you find the business-level thought process happening (contributing, influencing) around platform choice? How do you find the technical-level thought process happening (contributing, influencing) around platform choice?Topic 4 - Every company that’s involved with the commercialization of open source projects is trying to figure out the best way to manage a portfolio between OSS, software offerings and cloud offerings. How does InfluxData think about that mix, and what are you seeing in terms of customer-demand trends? Topic 5 - Getting developer momentum and mass around a set of patterns is critical. How does InfluxData think about enabling developers, and what are some of things you’ve done to accelerate their success and consistent learning? FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet and @ServerlessCast

Welcome to day three of Next! More awesome interviews await in this episode, as hosts Mark Mirchandani, Aja Hammerly, Mark Mandel, Jon Foust and their guests explore more of Next. To start, Dan of Viacom joins Mark and Jon to talk about his job in the TV business and why he loves Istio. Host-turned-guest Aja and Lauren of the Developer Relations team sat in the booth to talk with the Marks about the developer keynote at Next. Aja and Lauren elaborate on how they work to promote Next and put together content inclusive of all aspects of Google Cloud. Mark and Mark hear how Yuri from Scotiabank is using Kubernetes to help advance Scotiabank’s latest projects. Anthony from Google joins the conversation, too. And lastly, we tease you with a short interview with Andrew of MongoDB to speak more on the partnership between MongoDB Atlas and Google Cloud. Andrew will be joining us for a full interview on the podcast later this year! Interviews Cloud Next site Next On Air site Google Cloud Next ‘19: Day 3 Run Channel video Google Cloud Next ‘19: Day 3 Build Channel video Google Cloud Next ‘19: Day 3 Collaborate Channel video Day 3 at Next ‘19: A look back at an amazing week blog Playlist: All Sessions - Google Cloud Next ‘19 videos Viacom site How Viacom modernized its Intelligent Content Discovery Platform with Google Cloud blog GKE site Anthos site Istio site Developer Keynote: Get to the Fun Part (Cloud Next ‘19) video Jenkins site Slack site Cloud Run site Announcing Cloud Run, the newest member of our serverless compute stack blog GCP Podcast Episode 167: World Pi Day with Emma Haruka Iwao podcast Dev Zone Walkthrough (Cloud Next ‘19) video Dev Zone Experiment Pizza Authenticator (Cloud Next ‘19) video Scotiabank site Kubernetes site Google Cloud Next ‘19: Day 2 Product Innovation Keynote (Justin Arbuckle at 25:23) video Securing Kubernetes Secrets (Cloud Next ‘19) video MongoDB site MongoDB Atlas site Where can you find us next? The GCP Podcast will be back to its regular schedule next week!

SHOW: 393DESCRIPTION: Brian talks with Matt Oswalt (@mierdin, NRE @JuniperNetworks) and Derick Winkworth (@cloudtoad, Product Marketing Manager @JuniperNetworks) about how networking has adapted to DevOps and SRE, internally marketing the evolution to teams, and how NRE Labs are helping network engineers get up to speed. SHOW SPONSOR LINKS:MongoDB Atlas - Automated cloud MongoDB serviceVisit mongodb.com/cloudcast to learn more. MongoDB Atlas handles all the costly database operations and admin tasks that you’d rather not spend time on, like security, high availability, data recovery, monitoring, and elastic scaling. Try MongoDB Atlas today!Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtGet 20% off VelocityConf passes using discount code CLOUDCLOUD NEWS OF THE WEEK:Google announces Hybrid Cloud platform - "Anthos"SHOW INTERVIEW LINKS:Keeping It Classless (Matt Oswalt’s Blog)Network Reliability Engineer (NRE)What is DevNetOps? NRE Learning “Antidote” Derick’s “Network Interrupted” blog on Packet PushersMatt Oswalt on The Cloudcast (Eps. 285) - “Automation, Devops and Reddit”SHOW NOTES:Topic 1 - Welcome to the show Derick and welcome back Matt. Tell us about your background and some of the things you’re working on now at Juniper.Topic 2 - We talked a couple weeks ago with Gustavo Franco from Google about SRE, you guys have been working on something you’re calling “NRE”. Tell us about the NRE concept and how this fits into the world of Networking and DevOps.Topic 3 - Networking hasn’t been a very static thing in a long time (DHCP, WiFi access, VPNs), but now we also have applications joining and changing on a regular basis (CI/CD pipelines, containers, etc.). So how is that world changing the demands on “DevNetOps”? Topic 4 - What are you guys working on to tangibly move people forward in this space? Are there any resources or projects they should be aware of?Topic 5 - When you’re a foundational technology, such as networking or storage, it can be tough to adapt rapid DevOps type activities or culture. How much of NRE or DevNetOps is tooling (automation, controllers) and how much is culture changes? Topic 6 - Change is always a journey. What are some of the steps that you’re seeing people take towards NRE or DevNetOps, and maybe what are some of the common early mistakes they make?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet and @ServerlessCast

SHOW: 392DESCRIPTION: Brian talks with Uma Chingunde (@the_umac, Engineering Manager at @Stripe) about engineering career paths as an IC or Manager, how managers can be effective mentors, job rotations, and how diversity is an opportunity for every team. SHOW SPONSOR LINKS:Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtMongoDB Atlas - Automated cloud MongoDB serviceVisit mongodb.com/cloudcast to learn more. MongoDB Atlas handles all the costly database operations and admin tasks that you’d rather not spend time on, like security, high availability, data recovery, monitoring, and elastic scaling. Try MongoDB Atlas today!Get 20% off VelocityConf passes using discount code CLOUDCLOUD NEWS OF THE WEEK:Microsoft announces Azure Stack HCIChef announces fully open-source softwareAqua Security announces $62M funding roundThe Rise of Progressive Delivery for Systems ResilienceWe Looked at 101 Startup CEO Salaries – Here’s What We FoundWhy Today's Business Schools Teach Yesterday's ExpertiseSHOW INTERVIEW LINKS:Uma Chingunde’s Background: https://conferences.oreilly.com/velocity/vl-ca/public/schedule/speaker/336620Navigating the Mid-Career Plateau (Uma’s Velocity Talk)Stripe Homepage - Online payment processing for internet businessesSHOW NOTES:Topic 1 - Welcome to the show. Tell us about your background, as well as some of the things you’re working on these days at Stripe. Topic 2 - We’ve discussed the career mindset of people more on the sales/marketing side of companies, but you’re beginning to look at this within engineering teams. Let’s start with the framework of how you think about that for yourself and then for people within your team. Topic 3 - What are traditional vs non traditional IC and manager paths you can explore?Topic 4 - How do you think about the engineer vs manager track? Does it always have to be these two options, or are you seeing other paths, maybe more senior options as an IC?Topic 5 - What are some variations on the above for underrepresented groups?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet and @ServerlessCast

SHOW: 391DESCRIPTION: Brian talks with Gustavo Franco (@stratus, Customer Reliability Engineer at Google) about real-world experience as SRE/SRE Manager and CRE Manager, a discussion about how to measure SRE success, as well as how to onboard the SRE/CRE concepts and processes to new teams. SHOW SPONSOR LINKS:MongoDB Atlas - Automated cloud MongoDB serviceVisit mongodb.com/cloudcast to learn more. MongoDB Atlas handles all the costly database operations and admin tasks that you’d rather not spend time on, like security, high availability, data recovery, monitoring, and elastic scaling. Try MongoDB Atlas today!Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtGet 20% off VelocityConf passes using discount code CLOUDCLOUD NEWS OF THE WEEK:The Continuous Delivery Foundation was announced by the Linux FoundationKubernetes v1.14 released - Adds Windows Container supportGoogle introduces Cloud-based (streaming) Gaming Service called StadiaUPS To Send Nurses For In-Home VaccinationsSHOW INTERVIEW LINKS:Gustavo's Background: https://conferences.oreilly.com/velocity/vl-ca/public/schedule/speaker/150125“Scaling SRE, the Journey from 1 to Many Teams” (Gustavo’s talk at Velocity) DevOps and SRETuning up SLIs SHOW NOTES:Topic 1 - Welcome to the show. Tell us about your background, and some of the things you work on today as it relates to SRE and CRE teams. Topic 2 - Let's talk about what SRE is intended to do, and maybe how it differs (or is the same) from existing teams that might be labeled "Ops" or "DevOps". Maybe we can also talk about some of the types of skills that highlight what SRE does.Topic 3 - What are some of the ways to avoid an SRE (or CRE) team just becoming the band-aid team to fix all the things that developers don't want to put into code because they are under deadlines (security, bug fixed, scalability, etc.)?Topic 4 - We're hearing more about these terms "AIOps" and "ChaosEngineering". How much can SRE/CRE teams augment applications through tools that either bring deeper insight (e.g. AIOps) or create scenarios that developers can't emulate (e.g. Chaos)?Topic 5 - You've been around SRE/CRE for a while now. What are some of the positive and negative lessons you've learned and could share with the audience?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet and @ServerlessCast&a

Michael Lynn and Drew Dipalma join us to talk about a new way to manage your data using MongoDB Atlas, a managed database from MongoDB.

Michael Lynn and Drew Dipalma join us to talk about a new way to manage your data using MongoDB Atlas, a managed database from MongoDB.

Mass spectrometry is the gold standard for determining chemical compositions, with spectrometers often measuring the mass of a compound down to a single electron. This level of granularity produces an enormous amount of hierarchical data that doesn't fit well into rows and columns. In this talk, learn how Thermo Fisher is using MongoDB Atlas on AWS to allow their users to get near real-time insights from mass spectrometry experiments—a process that used to take days. We also share how the underlying database service used by Thermo Fisher was built on AWS.