Podcasts about Kubernetes

Guest: Sindre Iversen Language: Norwegian Duration: 18:33   In this episode of IT Talks, Sindre, a system consultant at Redpill Linpro in Oslo, talks about his role and daily work. He shares his experience of tackling clients' operational challenges, with a focus on Kubernetes, CI/CD, and managing legacy systems that have not yet been migrated.

Cloud Posse holds LIVE "Office Hours" every Wednesday to answer questions on all things related to AWS, DevOps, Terraform, Kubernetes, CI/CD. Register at https://cloudposse.com/office-hoursSupport the show

Eine weitere Woche ohne DNS-Katastrophen. Zumindest bei Sandra und Daniel. Dafür eine Woche mit Kochen, Brettspiel, Kubernetes und Frontend.

SHOW: 975Rohan Sathe, CEO and Co-Founder of Nightfall AI, discusses the rise of Shadow AI, where employees unknowingly leak sensitive corporate data through generative AI tools like ChatGPT. We explore how Nightfall's AI-native approach transforms autonomous systems to defend against AI-powered data exfiltration across SaaS apps, endpoints, and browsers. SHOW TRANSCRIPT: The Cloudcast #975 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS:[Mailtrap] Try Mailtrap for free[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:Sunday Perspective touches on Shadow AINightfall websiteTopic 1 - Welcome to the show, Rohan. Give everyone a brief introduction, including your time at Uber Eats.Topic 2 - How do you define Shadow AI? We hear Shadow AI compared to Shadow IT back at the start of cloud. However, this looks different because everyone's learning curve is much smaller. For Shadow IT to happen, you had to know IT (servers, storage, etc.). Is this the correct way to think about the problem?Topic 3 - How big is the Shadow AI problem today?Topic 4 - Normally, data leaks would be discovered by traditional DLP (data loss prevention) tools. In my experience, those tools have been cumbersome and clunky, and you often face the classic trade-off between user productivity and security, as well as the need to lock down access. How has this mindset evolved in the era of AI? Topic 5 - What happens when AI-powered attacks meet AI-powered defense?Topic 6 - Let's talk about the technical architecture. How does Nightfall actually work across SaaS apps, endpoints, browsers, and AI tools?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

#325: KubeCon NA 2025 wrapped in Atlanta with unseasonably cold weather and some significant shifts in the cloud native ecosystem. The conference showed fewer vendors backing CNCF projects on the show floor, with key concerns emerging around maintainer burnout—exemplified by NGINX Ingress being deprecated despite running on 40% of Kubernetes clusters worldwide. The event revealed a maturing ecosystem where AI moved from buzzword to operational reality, with focus shifting toward conformance standards, security policies, and enterprise readiness rather than the hype cycle of previous years. The discussions revealed a consolidation pattern where larger corporations like AWS, Microsoft, and Google are increasingly the only ones who can sustain open source project maintenance. Startups and smaller companies face difficult choices: maintain existing revenue streams, pivot entirely to AI, or attempt both and fail at both. Meanwhile, AI adoption in the ops space remains behind other sectors, with developers emerging as the primary buyers for AI tooling—a shift that's reshaping go-to-market strategies across vendors. Platform engineering continues as a parallel major theme, focusing on operationalizing infrastructure at scale.   Whitney's contact information: X: https://x.com/wiggitywhitney LinkedIn: https://www.linkedin.com/in/whitneylee/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

In this episode of the Ardan Labs Podcast, Bill Kennedy talks with Catherine Johnson, VP of Global Solutions Engineering at Hydrolix, about her career journey through data management, scalability, and innovation. With a background spanning leadership roles at Hydrolix, Grafana Labs, and Oracle, Catherine shares insights into balancing engineering, entrepreneurship, and mentorship. She discusses the evolution of real-time data systems, the economics of storage, and the importance of data-driven decision-making. Catherine also opens up about taking a break from tech to teach dance, and how her passion for innovation and continuous learning fuels her leadership today.00:00 Introduction03:03 Data Management and Scalability05:58 Explosion of Data and Storage Needs09:01 Real-Time Data in Business14:49 Economics of Data Storage20:41 Education and Early Career31:09 Career Transitions and Growth46:10 Teaching Dance and Finding Balance53:16 Returning to Tech at Oracle01:08:10 Joining Elastic and Facing Burnout01:15:45 Leadership and Innovation at Hydrolix01:27:07 AI in Tech and Its LimitationsConnect with Catherine: LinkedIn: https://www.linkedin.com/in/catjopdx/Mentioned in this Episode:Hydrolix: https://hydrolix.io/Want more from Ardan Labs? You can learn Go, Kubernetes, Docker & more through our video training, live events, or through our blog!Online Courses : https://ardanlabs.com/education/ Live Events : https://www.ardanlabs.com/live-training-events/ Blog : https://www.ardanlabs.com/blog Github : https://github.com/ardanlabs

Neste Kubicast, recebemos o Chico (Francisco Rodrigues) e o França, da Qive, para um papo técnico e divertido sobre como instrumentamos uma aplicação legada em PHP com OpenTelemetry e destravamos visibilidade de ponta a ponta. Contamos como foi a descoberta, o desenho da arquitetura e as primeiras vitórias: da auto‑instrumentação às correções cirúrgicas que derrubaram a latência no p95 e eliminaram instabilidades intermitentes.Falamos de decisões práticas: por que escolher OpenTelemetry em um monólito Zend antigo, como alinhar a coleta com o ecossistema Grafana (Tempo, Loki, dashboards, alertas) e qual o impacto real em consumo de CPU/memória versus os ganhos na operação. Também abrimos o jogo sobre trade‑offs de transporte (gRPC/Protobuf), overhead na request e como padronizamos spans para tornar o tracing “quase APM”, mas com stack aberta.De quebra, exploramos experiência do time (SRE e Eng. de Software) para acelerar adoção, self‑service e developer experience. Se você quer entender auto‑instrumentação em PHP, custos/benefícios, stack de observabilidade com Grafana e boas práticas de tracing distribuído, este episódio é para você.Links Importantes: - Marcelo França - https://www.linkedin.com/in/marceloluizfranca - Francisco Rodrigues - https://www.linkedin.com/in/fcoedno - Artigo inspirador - https://medium.com/engenharia-arquivei/instrumente-sua-aplica%C3%A7%C3%A3o-php-com-opentelemetry-cb3460a64d04 - Conheça a Qive - https://qive.com.br/institucional/ - Opentelemetry PHP - https://opentelemetry.io/docs/languages/php/ - João Brito - https://www.linkedin.com/in/juniorjbn/O Kubicast é uma produção da Getup, empresa especialista em Kubernetes e projetos open source para Kubernetes. Os episódios do podcast estão nas principais plataformas de áudio digital e no YouTube.com/@getupcloud.

Oscar Wieman bouwde ooit Minecraft-servers voor de lol, nu sleutelt hij aan de infrastructuur van de IND. Aan tafel met Randal en Annelies duikt hij in containers, Kubernetes en het automatiseren van deploys. Waarom werkt het “on my machine” wél en elders niet? Hoe voorkom je dat developers eindeloos zipjes mailen? En wat doe je als de overheid meer regeltjes heeft dan jij testomgevingen (of juist niet)? Shownotes It works on my machine… Fosdem.org Advertentie: Rabobank ITWil je weten hoe IT-professionals bij Rabobank stappen maken richting duurzamer IT-gebruik? Bekijk https://rabobank.jobs/IT Tijdschema0:00:00 Wie is Oscar en wat doet ‘ie bij de IND?0:04:30 DevOps, sysadmin of vliegende kiep?0:10:00 Containerisatie, Docker en dat soort dingen0:16:20 Waarom Kubernetes nodig werd0:22:40 Oscars route van hobby naar professie0:28:10 Overheidsprojecten en bureaucratische tape0:35:00 CI/CD, Git en containers bouwen0:42:00 “Works on my machine” en hoe Docker dat oplost0:50:00 Real-life use case: Rabobank-app en microservices0:58:00 Wat draait er allemaal achter de schermen bij de IND? #devops #docker #kubernetes #containers #infra #platformengineering #opensource #automation #overheid #MNOTSee omnystudio.com/listener for privacy information.

Major banks once built their own Linux kernels because no distributions existed, but today commercial distros — and Kubernetes — are universal. At KubeCon + CloudNativeCon North America, AWS's Jesse Butler noted that Kubernetes has reached the same maturity Linux once did: organizations no longer build bespoke control planes but rely on shared standards. That shift influences how AWS contributes to open source, emphasizing community-wide solutions rather than AWS-specific products.Butler highlighted two AWS EKS projects donated to Kubernetes SIGs: KRO and Karpenter. KRO addresses the proliferation of custom controllers that emerged once CRDs made everything representable as Kubernetes resources. By generating CRDs and microcontrollers from simple YAML schemas, KRO transforms “glue code” into an automated service within Kubernetes itself. Karpenter tackles the limits of traditional autoscaling by delivering just-in-time, cost-optimized node provisioning with a flexible, intuitive API. Both projects embody AWS's evolving philosophy: building features that serve the entire Kubernetes ecosystem as it matures into a true enterprise standard.Learn more from The New Stack about the latest in Kube Resource Orchestrator and Karpenter:  Migrating From Cluster Autoscaler to Karpenter v0.32How Amazon EKS Auto Mode Simplifies Kubernetes Cluster Management (Part 1) Kubernetes Gets a New Resource Orchestrator in the Form of KroJoin our community of newsletter subscribers to stay on top of the news and at the top of your game.  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

As Kubernetes® continues to reign as the worldwide container orchestration system of choice, many organizations and independent software vendors (ISVs) are realizing that its capabilities could be an essential key to ongoing and future business success.Blog: https://www.nutanix.com/blog/how-a-complete-and-open-kubernetes-platform-can-future-proof-your-business by Dan CiruliHost: Phil Sellers, XenTegraCo-Host: Jirah Cox, NutanixCo-Host: Andy Greene, XenTegraCo-Host: Chris Calhoun, XenTegra

Welcome to AI Unraveled: Your daily strategic briefing on the business impact of AI.Today's Highlights: We are switching to "Special Episode" status for a critical infrastructure deep dive. We tackle the GPU Scheduling Nightmare—why your expensive H100s are sitting idle, why default Kubernetes fails at AI orchestration, and the new playbook enterprises are using to reclaim millions in wasted compute.Strategic Pillars & Topics

In this episode, we talk with Abdel Sghiouar and Mofi Rahman, Developer Advocates at Google and (guest) hosts of the Kubernetes Podcast from Google. Together, we dive into one central question: can you truly run LLMs reliably and at scale on Kubernetes?It quickly becomes clear that LLM workloads behave nothing like traditional web applications:GPUs are scarce, expensive, and difficult to schedule.Models are massive — some reaching 700GB — making load times, storage throughput, and caching critical.Containers become huge, making “build small containers” nearly impossible.Autoscaling on CPU or RAM doesn't work; new signals like GPU cache pressure, queue depth, and model latency take over.LLMs don't run in parallel, so batching and routing through the Inference Gateway API become essential.Device Management and Dynamic Resource Allocation (DRA) are forming the new foundation for GPU/TPU orchestration.Security shifts as rootless containers often no longer work with hardware accelerators.Guardrails (input/output filtering) become a built-in part of the inference path.And then there's the occasional request from customers who want deterministic LLM output — to which Mofi dryly responds: “You don't need a model — you need a database.”Powered by: ACC ICTStuur ons een bericht.ACC ICT Specialist in IT-CONTINUÏTEIT Bedrijfskritische applicaties én data veilig beschikbaar, onafhankelijk van derden, altijd en overalSupport the showLike and subscribe! It helps out a lot.You can also find us on:De Nederlandse Kubernetes Podcast - YouTubeNederlandse Kubernetes Podcast (@k8spodcast.nl) | TikTokDe Nederlandse Kubernetes PodcastWhere can you meet us:EventsThis Podcast is powered by:ACC ICT - IT-Continuïteit voor Bedrijfskritische Applicaties | ACC ICT

In this Technology Reseller News, Podcast, Doug Green interviews Don Boxley, CEO and Co-Founder of DH2i, for a deep dive into one of the biggest challenges facing IT teams today: the migration gap between legacy Windows-based SQL Server deployments and the containerized, Linux-driven future that modern applications increasingly require. DH2i, a long-time Microsoft and Red Hat partner, delivers high availability, secure communication, and cross-platform mobility for SQL Server, Oracle, and MySQL environments. Their flagship platform, DX Enterprise, enables customers to run the same production-grade SQL instance across Windows, Linux, and Kubernetes — and move between them with seamless failover. As Boxley explains, this eliminates the traditional roadblocks that keep enterprises locked into aging infrastructure. With SQL Server 2025 bringing new support for AI-driven applications, Microsoft tapped DH2i to deliver mission-critical HA capabilities for these next-generation workloads. The company also introduced a hands-on, step-by-step Minikube tutorial, allowing DBAs and MSPs to experiment safely with Kubernetes-based SQL deployments on their own PCs before ever touching production. “Most teams think they're stuck on Windows — they're not. With DX Enterprise, you can move SQL Server to Linux or containers without disruption, and your customers won't even know the difference,” Boxley notes. DH2i's developer edition is available as a free download, complete with 30-day support, giving IT teams a no-risk path to testing, learning, and modernizing their database infrastructure. Learn more at https://dh2i.com/. Software Mind Telco Days 2025: On-demand online conference Engaging Customers, Harnessing Data

Is the current level of AI funding and investment rational or irrational? Is it possible that it's both at the same time? Let's look at some numbers and the thought process behind them.SHOW: 976SHOW TRANSCRIPT: The Cloudcast #976 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.SHOW NOTES:A whole bunch of AI-related statsSam Altman on BG2 podcastDO WE HAVE ANY IDEA HOW TO MEASURE THE IMPACT OF AI?How much is one model better than another (e.g. Gemini vs. CoPilot)?How much improvement should a software developer get?How much improvement should a knowledge worker get?How much cost savings should a chatbot provide?How long should it take to make a model understand a company's data?How many workers can a company displace with AI?OpenAI in 2030 - 26 gigawatts could power between 3.7 million to 17.3 million modern GPU serversOpenAI in 2035 - 50 gigawatts could power between 37 million to 173 million modern GPU serversFEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

Policy-as-Code is reshaping how modern teams enforce security and compliance. In this episode, we break down how organizations are replacing manual checks with automated, code-driven policies that integrate directly into CI/CD pipelines. If you're working with cloud, DevOps, or DevSecOps, this is a must-listen session to understand how PaC boosts consistency, scalability, and audit readiness.

At JupyterCon 2025, Jupyter Deploy was introduced as an open source command-line tool designed to make cloud-based Jupyter deployments quick and accessible for small teams, educators, and researchers who lack cloud engineering expertise. As described by AWS engineer Jonathan Guinegagne, these users often struggle in an “in-between” space—needing more computing power and collaboration features than a laptop offers, but without the resources for complex cloud setups. Jupyter Deploy simplifies this by orchestrating an entire encrypted stack—using Docker, Terraform, OAuth2, and Let's Encrypt—with minimal setup, removing the need to manually manage 15–20 cloud components. While it offers an easy on-ramp, Guinegagne notes that long-term use still requires some cloud understanding. Built by AWS's AI Open Source team but deliberately vendor-neutral, it uses a template-based approach, enabling community-contributed deployment recipes for any cloud. Led by Brian Granger, the project aims to join the official Jupyter ecosystem, with future plans including Kubernetes integration for enterprise scalability. Learn more from The New Stack about the latest in Jupyter AI development: Introduction to Jupyter Notebooks for DevelopersDisplay AI-Generated Images in a Jupyter Notebook Join our community of newsletter subscribers to stay on top of the news and at the top of your game.   Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Cloud Posse holds LIVE "Office Hours" every Wednesday to answer questions on all things related to AWS, DevOps, Terraform, Kubernetes, CI/CD. Register at https://cloudposse.com/office-hoursSupport the show

A gente sentou com um trio do Mercado Livre para abrir a caixa-preta do Fury, a plataforma que sustenta milhares de serviços e times. Falamos sobre como transformar Kubernetes em um produto de plataforma consumível, com autonomia para os times e guardrails que não viram algemas. Sim, é sobre Platform Engineering de verdade, com aprendizados que doem no bolso e no pager.Entramos em detalhes de experiência do desenvolvedor (DX), SDKs, templates e Golden Path no Backstage, além das escolhas que tornaram o Fury utilizável por centenas de times sem precisar “fazer kubectl em produção”. Também discutimos arquitetura multi-cloud, clusters por criticidade, autoscaling (Karpenter/KEDA) e como democratizar observabilidade sem expor todo mundo ao PromQL às 3 da manhã.Para fechar com chave de ouro, falamos de governança e segurança no dia a dia (DevSecOps na prática), SLIs/SLOs e o dilema entre padronização e liberdade. Tem história de guerra, roadmap, trade-offs e até as dicas de carreira dos convidados. Todos os links citados (Backstage, ArgoCD/GitOps, Karpenter, KEDA e materiais sobre Platform Engineering) estão na seção de DESTAQUES abaixo para você explorar.Links:Saiba mais sobre o Fury - https://medium.com/mercadolibre-tech/subpage/79a519305008Julia Pedroza - https://www.linkedin.com/in/julianunesp/Juliano Martins - https://www.linkedin.com/in/julianommartins/Marcelo Quadros - https://www.linkedin.com/in/quadros-marcelo/João Brito - https://www.linkedin.com/in/juniorjbn/O Kubicast é uma produção da Getup, empresa especialista em Kubernetes e projetos open source para Kubernetes. Os episódios do podcast estão nas principais plataformas de áudio digital e no YouTube.com/@getupcloud.

Today we delve into the tech expertise deficit and why technical depth and decades of doing the work matter more than social media followers and content creation hype. Our guest is Russ White, engineer, author, teacher, and certification developer. We begin with current events in AI, and then investigate the differences between career and influence... Read more »

SHOW: 975SHOW TRANSCRIPT: The Cloudcast #975 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:LaunchAny websiteapicoach.io (note)Lessons learned after a decade of API StrategyLatest book: “Principles of Web API Design: Delivering Value with APIs and Microservices (Addison-Wesley under the Vaughn Vernon signature series)Upcoming report on AI-Assisted API DesignJames on The Cloudcast #153James on The Cloudcast #435Topic 1 - Welcome back to the show James. It's hard to believe it's been 11 years since we last spoke on the show! Give everyone a brief introduction.Topic 2 - To say we've come a long way with APIs as an industry is an understatement. But let's set the table for everyone. In your interactions with Enterprise customers, what trends or standards are currently top of mind? Topic 3 - You wrote an article (link in show notes) titled Lessons after a Decade of API Strategy. What struck me from the article was the combination of technology, business, and even culture, all of which have to come together. When talking to Enterprises these days, have we moved past understanding what APIs are and straight to solving problems with APIs?Topic 4 - What are the most common use cases you see today? API transformation? API sprawl and consolidation/documentation? Integration of SaaS/3rd party services?Topic 5 - No conversation would be complete without a discussion about AI and AI's impact on API's. I view this in several different ways. AI is creating APIs, and AI is being consumed through APIs. How do you think about AI and its impact? What's changed and what has stayed the same?Topic 6 - Second aspect to the AI topic, where and how does security fit into this intersection of AI and APIs?Topic 7 - If anyone is interested, what's the best way to get started?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

#324: Kubernetes has reached a mature state where boring releases signal stability rather than stagnation. While the platform continues evolving with features like in-place resource updates in version 1.33, the real challenge lies in optimizing AI workloads that demand significantly more resources than traditional applications. The discussion reveals how auto-scaling capabilities become crucial for managing these resource-intensive workloads, with vertical and horizontal scaling finally working together through new features that allow pod resizing without restarts. The conversation explores the ongoing tension between cloud costs and data center investments, particularly as companies navigate uncertain AI requirements. While cloud providers offer flexibility for experimentation, the hidden costs of skilled personnel and infrastructure management often make cloud solutions more economical than initially apparent. The debate extends to startup strategies, where outsourcing infrastructure complexity allows teams to focus on core business value rather than operational overhead. Omer Hamerman joins Darin and Viktor to examine the common misconceptions about resource allocation, arguing that developers fundamentally cannot predict CPU and memory requirements accurately. This limitation makes automated right-sizing and intelligent scaling essential for modern Kubernetes deployments, especially as AI workloads continue pushing infrastructure boundaries.   Omer's contact information: LinkedIn: https://www.linkedin.com/in/omer-hamerman/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

At KubeCon 2025, the CNCF launched the Certified Kubernetes AI Conformance Program to standardize AI and ML workloads on Kubernetes, ensuring portability across hybrid and sovereign clouds and preventing platform lock-in. Supported by companies like Google, Microsoft, Oracle, Broadcom, and Red Hat, the initiative promotes interoperability, scalability, and efficient production deployment. Arm showcased its Neoverse platform alongside Google Cloud's Axion N4A VMs, enabling energy-efficient, scalable AI workloads, while partnerships with CNCF projects like Harbor, OPA, Kedify, and AuthZed help developers build secure, portable, and cost-effective cloud-native systems from edge to cloud. This and more on the Tech Field Day News Rundown recorded live at Commvault Shift with Tom Hollingsworth and Stephen Foskett. Time Stamps:0:00 - Welcome to the Tech Field Day News Rundown1:17 - VAST Data makes $1.17B Deal with CoreWeave4:42 - Spektrum Labs Uses Cryptography to Prove Cyber Resilience7:37 - HPE Drops Qumulo, Scality, and WEKA to Focus on Its Own Storage10:56 - Red Hat Unveils Major OpenShift 4.20 Updates for AI, Security, and Edge13:57 - AWS Builds Transatlantic Fastnet Cable to Boost Cloud and AI17:31 - Pentagon Expects Industry to Train AI, Not Pay for It20:34 - CNCF Standardizes AI Workloads on Kubernetes25:17 - Arm and CNCF Showcase Efficient Cloud-Native Systems at KubeCon 202529:26 - Thank You Commvault for Hosting Tech Field Day31:01 - The Weeks Ahead32:55 - Thanks for Watching the Tech Field Day News RundownFollow our hosts ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Follow Tech Field Day ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mastodon⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Dive into KubeVirt with the vBrownBag crew and guest Eric Shanks!

Andy Pernsteiner is the Field CTO at VAST Data, working on large-scale AI infrastructure, serverless compute near data, and the rollout of VAST's AI Operating System.The GPU Uptime Battle // MLOps Podcast #346 with Andy Pernsteiner, Field CTO of VAST Data.Huge thanks to VAST Data for supporting this episode!Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractMost AI projects don't fail because of bad models; they fail because of bad data plumbing. Andy Pernsteiner joins the podcast to talk about what it actually takes to build production-grade AI systems that aren't held together by brittle ETL scripts and data copies. He unpacks why unifying data - rather than moving it - is key to real-time, secure inference, and how event-driven, Kubernetes-native pipelines are reshaping the way developers build AI applications. It's a conversation about cutting out the complexity, keeping data live, and building systems smart enough to keep up with your models. // BioAndy is the Field Chief Technology Officer at VAST, helping customers build, deploy, and scale some of the world's largest and most demanding computing environments.Andy has spent the past 15 years focused on supporting and building large-scale, high-performance data platform solutions. From humble beginnings as an escalations engineer at pre-IPO Isilon, to leading a team of technical Ninjas at MapR, he's consistently been in the frontlines solving some of the toughest challenges that customers face when implementing Big Data Analytics and next-generation AI solutions.// Related LinksWebsite: www.vastdata.comhttps://www.youtube.com/watch?v=HYIEgFyHaxkhttps://www.youtube.com/watch?v=RyDHIMniLro The Mom Test by Rob Fitzpatrick: https://www.momtestbook.com/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Andy on LinkedIn: /andypernsteinerTimestamps:[00:00] Prototype to production gap[00:21] AI expectations vs reality[03:00] Prototype vs production costs[07:47] Technical debt awareness[10:13] The Mom Test[15:40] Chaos engineering[22:25] Data messiness reflection[26:50] Small data value[30:53] Platform engineer mindset shift[34:26] Gradient description comparison[38:12] Empathy in MLOps[45:48] Empathy in Engineering[51:04] GPU clusters rolling updates[1:03:14] Checkpointing strategy comparison[1:09:44] Predictive vs Generative AI[1:17:51] On Growth, Community, and New Directions[1:24:21] UX of agents[1:32:05] Wrap up

Fredrik snackar med först Johan Thelin och sedan Daniel Raniz Raneland om paradigm, och om konferensen Lindholmen software development day som alla tre nyss deltagit i. Konferensen firade tjugo år och hade just paradigm som tema, vilket fick Fredrik att undra dels vilka trender som egentligen betytt mycket under de senaste årens utvecklande, dels varför man måste ta till så stora ord hela tiden. Det blir tankar om expertens död, att skydda folk från möten, fördelar och nackdelar med molnet, Kubernetes vara eller inte vara, en nypa funktionell programmering, och givetvis lite om själva konferensen. Och: går för få seniora utvecklare på konferenser? Ett stort tack till Cloudnet som sponsrar vår VPS! Har du kommentarer, frågor eller tips? Vi är @kodsnack, @thieta, @krig, och @bjoreman på Mastodon, har en sida på Facebook och epostas på info@kodsnack.se om du vill skriva längre. Vi läser allt som skickas. Gillar du Kodsnack får du hemskt gärna recensera oss i iTunes! Du kan också stödja podden genom att ge oss en kaffe (eller två!) på Ko-fi, eller handla något i vår butik. Länkar Paradigm Lindholmen software development day Johan Thelin Tidigare avsnitt med Johan Raniz Raneland Tidigare avsnitt med Raniz Øredev The pragmatic programmer The mythical man-month 996-kulturen Wirelesscar Johan på Mastodon Nextcloud Pi desk rack - Deskpi rackmate NUC Pi-hole - blockerar annonser Stöd oss på Ko-fi F# Lars Cloud exit Amazon-nedtiden för ett par veckor sedan Function as a service Kubernetes Minikube Openstack Webrtc Electron och prestandaproblemet på Mac Postman Bruno Tauri HTMX AJAX Jquery Onshape Wordpress Gutenberg Testdriven utveckling Accelerate Titlar Prat om paradigm Nerd at heart Stort, flummigt ord Expertens död Hur hög är en vertikal? Matris av kompetens Möten om kod Det finns inget idealiskt Komplexiteten ligger i systemet Statisk länkning av idag Glada molnmänniskor Vad gör faster idag? Landa i en e-postadress Det sämsta av två världar Jag duckade temat lite Svårt att tänka i paradigmer Stort kluven till Kubernetes Uppfriskande lättviktigt Magkänsla och erfarenhet

In the history of technology era changes, things tend to change slowly at first, and then quickly all at once. We've now reached the beginning of the all-at-once era of AI change. SHOW: 974SHOW TRANSCRIPT: The Cloudcast #974 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.SHOW NOTES:The Benefit of Bubbles (Stratechery)Cube Research - Energy needs of AIAre we building AI for Progress or Power? (Prof G Markets)Amazon earnings call (Oct 2025) transcriptMicrosoft Azure earnings call (Oct 2025) transcriptWHAT WAS THE LEADING AI TREND FOR EACH YEAR?2022 - What is ChatGPT2023 - What can GenAI do? (Jobs, Skills, etc.)2024 - Alternatives to OpenAI and NVIDIA, Where is Google?, Where is AWS?2025 - Open source in AI, AI Regulations, AI Partnerships, Deep Seek, AI Agents, AI Funding, AI Power Challenges, AI Gov't Involvement2026 - ???FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

If you think managing Kubernetes clusters is hard, what about managing Kubernetes clusters across three different public clouds? We dive into the challenges that arises from running multi-cloud Kubernetes workloads. These challenges include workload identity, DNS query resolutions, and security. Here to help us navigate this complexity and offer possible solutions is Goutam Tadi, Staff... Read more »

If you think managing Kubernetes clusters is hard, what about managing Kubernetes clusters across three different public clouds? We dive into the challenges that arises from running multi-cloud Kubernetes workloads. These challenges include workload identity, DNS query resolutions, and security. Here to help us navigate this complexity and offer possible solutions is Goutam Tadi, Staff... Read more »

Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, @SoftwareDefTalk) discuss the top stories in Cloud and AI from October 2025.SHOW: 973SHOW TRANSCRIPT: The Cloudcast #973 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST:  "CLOUDCAST BASICS"SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:Link to October 2025 News and ArticlesFEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

In this episode of the Ardan Labs Podcast, Bill Kennedy talks with Salah Mahmud, a medical researcher specializing in epidemiology and medical statistics. Salah shares his journey from growing up in Libya under Gaddafi's regime to conducting cutting-edge research in Canada on the connection between influenza and heart attacks. He discusses the challenges of running large-scale observational studies, the bureaucratic barriers to accessing medical data, and the importance of diversity in health research. Salah also reflects on his early entrepreneurial ventures, his discovery of programming during medical school, and how resilience and adaptability shaped his personal and professional journey.00:00 Introduction02:03 Research on Influenza and Heart Attacks05:53 Challenges in Data Access16:51 Life in Libya Under Gaddafi21:32 From Medicine to Programming41:18 WHO Collaboration and Education Abroad57:13 Disappearance and New Beginnings01:09:33 Immigration and Adaptation in Canada01:15:45 Balancing Medicine and Technology01:21:22 Family, Culture, and Reflection01:25:37 Current Research and Future GoalsConnect with Salah: Email: salah.mahmud@umanitoba.caLinkedIn: https://www.linkedin.com/in/salah-mahmud-4177285a/Mentioned in this Episode:Golang: https://go.dev/Want more from Ardan Labs? You can learn Go, Kubernetes, Docker & more through our video training, live events, or through our blog!Online Courses : https://ardanlabs.com/education/ Live Events : https://www.ardanlabs.com/live-training-events/ Blog : https://www.ardanlabs.com/blog Github : https://github.com/ardanlabs

If you think managing Kubernetes clusters is hard, what about managing Kubernetes clusters across three different public clouds? We dive into the challenges that arises from running multi-cloud Kubernetes workloads. These challenges include workload identity, DNS query resolutions, and security. Here to help us navigate this complexity and offer possible solutions is Goutam Tadi, Staff... Read more »

Cloud Posse holds LIVE "Office Hours" every Wednesday to answer questions on all things related to AWS, DevOps, Terraform, Kubernetes, CI/CD. Register at https://cloudposse.com/office-hoursSupport the show

AWS Morning Brief for the week of November 3rd, with Corey Quinn. Links:Beyond pilots: A proven framework for scaling AI to productionNew Amazon CloudWatch metrics to monitor EC2 instances exceeding I/O performanceProcessing Amazon S3 objects at scale with AWS Step Functions Distributed Map S3 prefixWhat's the difference between AWS ParallelCluster and AWS Parallel Computing Service?France Télévisions prepared for 2024 Olympic Games with AWS Countdown PremiumAmazon Kinesis Data Streams now supports 10x larger record sizesAmazon DocumentDB (with MongoDB compatibility) announces upgraded query planner that can run queries up to 10x fasterAnnouncing AWS X-Ray SDKs/Daemon End-of-Support and OpenTelemetry MigrationAmazon S3 adds conditional write functionality to copy operationsIntroducing the Capacity Reservation Topology API for AI, ML, and HPC instance typesHow to deploy a SQL Server Failover Cluster Instance across three Availability Zones using Storage Spaces Direct Reduce CAPTCHAs for AI agents browsing the web with Web Bot Auth (Preview) in Amazon Bedrock AgentCore BrowserUsing Kubernetes Labels to Split and Track Application Costs on Amazon EKSIntroducing AWS Lambda event source mapping tools in the AWS Serverless MCP Server Split Cost Allocation Data for Amazon EKS supports Kubernetes labels

Patterns in technology tend to eventually repeat themselves (or at least rhyme), and Amazon is beginning to repeat some of the patterns of Cisco from the early 2000s SHOW: 972SHOW TRANSCRIPT: The Cloudcast #972 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.SHOW NOTES:Staying nimble and continuing to strengthen our organization (Amazon, Oct 2025)Strengthening our culture and teams (Amazon, Sept 2024)Amazon Leadership PrinciplesWHERE ARE THE BIGGEST AI RISKS?Significant changes from one industry era to the next (Internet to SaaS, Cloud to AI)Once dominant position in a market now appears less dominant (Worth more than next 20 competitors; 7yr head start)Guiding cultural principles well-known within the company - start adding more and more to themEmployee motivation driving by stock price as much as work activitiesCulture evolves and erodes over time as the business changes and evolves - it's nearly impossible to reset the company cultureCompanies can rebound from being lost in the woods, but it's very, very difficultDeath by 1000 cuts in a virtuous cycle - employees are constantly more worried about job status than project status - the perception of who gets to make mistakes and who is responsible for mistakesFEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

Shane has teething issues with his Kubernetes homelab, Sean ran a bootable containers workshop at Texas Linux Fest, and the case for enterprise rolling distros.         Support us on patreon and get an ad-free RSS feed with early episodes sometimes           Subscribe to the RSS feed.  

Shane has teething issues with his Kubernetes homelab, Sean ran a bootable containers workshop at Texas Linux Fest, and the case for enterprise rolling distros.         Support us on patreon and get an ad-free RSS feed with early episodes sometimes           Subscribe to the RSS feed.  

Aproveitamos a AWS fora do ar e o linkedin cheio de especialistas para falar um pouco sobre DevOps e SRE: o que realmente falhou, como dependências globais amplificam incidentes e por que comunicação e telemetria mudam o jogo quando o provedor está cambaleando. Falamos de estratégias de resiliência multi‑região, desenho de failure domains e decisões pragmáticas de RTO/RPO. Discutimos feature flags para degradar funcionalidades com graça, circuit breakers e backoff nos clientes, priorização de runbooks e exercícios de caos que realmente medem MTTR. Também passamos por impactos colaterais em serviços gerenciados (EKS, IAM, KMS, DynamoDB), observabilidade em modo de guerra e os limites do “gerenciado”.Fechamos com lições acionáveis para times de produto e plataforma: desde budget de disponibilidade e custos até testes de recuperação orientados a cenários. Dois tópicos‑chave que destacamos: resiliência multi‑região na prática e como treinar a organização para incidentes de baixa probabilidade e alto impacto.Por fim, damos um giro de lições aprendidas para equipes de produto e plataforma: feature flags para fallback de integrações, rotas alternativas para planos de controle, circuit breakers em clientes, e playbooks para comunicação com stakeholders. Dois tópicos que merecem atenção especial neste papo: resiliência multi-região na prática e como preparar sua organização para incidentes “quase improváveis”.#Links Importantes:- Lucas Azevedo - https://www.linkedin.com/in/lazevedo-devops/- Comunidade DevOps no Discord - https://discord.com/invite/k6wPagw4tV- João Brito - https://www.linkedin.com/in/juniorjbn/- Assista ao FilmeTEArapia - https://youtu.be/M4QFmW_HZh0?si=HIXBDWZJ8yPbpflM## Hashtags#DevOps #SRE #AWS #Outage #DNS #DynamoDB #AltaDisponibilidade #Resiliencia #Observabilidade #ChaosEngineering #IncidentResponse #Runbooks #FeatureFlags #CircuitBreaker #RTO #RPO #Kubernetes #DevSecOps #Kubicast #Containers #GetupO Kubicast é uma produção da Getup, empresa especialista em Kubernetes e projetos open source para Kubernetes. Os episódios do podcast estão nas principais plataformas de áudio digital e no YouTube.com/@getupcloud.

Join William Collins and Evyonne Sharp as they catch up on all things AI. They discuss the AI bubble and how it relates to venture capital, stock, and company evaluations. They talk about the AI experience for the average person, the adoption rate of AI tools, and how the AI infrastructure buildout might affect the... Read more »

GKE turned 10 in 2025! In this episode, we talk with GKE PM Gari Singh about GKE's journey from early container orchestration to AI-driven ops. Discover Autopilot, IPPR, and a bold vision for the future of Kubernetes. Do you have something cool to share? Some questions? Let us know: web: kubernetespodcast.com mail: kubernetespodcast@google.com X: @kubernetespod bluesky: @kubernetespodcast.com News of the week Cloud Native Computing Foundation Announces Knative's Graduation llm-d 0.3: Wider Well-Lit Paths for Scalable Inference vllm-project/semantic-router on github Announcing the Certified Meshery Contributor (CMC) Introducing Headlamp Plugin for Karpenter - Scaling and Visibility Links from the interview Kelsey Hightower's Kubernetes the Hard Way MiniKube Kind Docker Compose Docker Swarm GKE Autopilot Dynamic Resource Allocation (DRA) Google Cloud TPUs Node Auto Provisioning (GKE) Jax (Machine Learning Framework) Horizontal Pod Autoscaling (HPA) Serverless on Google Cloud Grafana Prometheus Kubectl-ai Vertical Pod Autoscaler (VPA) Kubernetes v1.33: In-Place Pod Resize Graduated to Beta In-place Vertical Scaling of Pods - Resize CPU and Memory Resources assigned to Containers GKE under the hood: Container-optimized compute delivers fast autoscaling for Autopilot

Soham Mazumdar, CEO and Co-Founder of WisdomAI, discusses how organizations can break free from the "drowning in data but starving for insights" paradox that plagues modern enterprises. We explore his journey from Google's TeraGoogle project to co-founding and scaling Rubrik through its $5.6 billion IPO, and why he left that success to build an agentic AI approach to Business Intelligence (BI) that transforms how businesses extract value from their data investments.SHOW: 971SHOW TRANSCRIPT: The Cloudcast #963 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:WisdomAI websiteTopic 1 - Welcome to the show, Soham. We overlapped briefly at Rubrik. Give everyone a quick introduction and tell everyone a bit about your time at Google prior to RubrikTopic 2 - You helped scale Rubrik from inception to a $5.6 billion IPO in 2024. What was the "aha moment" that made you leave that success to tackle the enterprise data analytics problem with WisdomAI?Topic 3 - Let's define the core problem. Organizations invest heavily in modern data platforms - Snowflake, Databricks, etc. - but there is the term "drowning in data but starving for insights." What's broken in the traditional BI stack that prevents business users from getting answers?Topic 4 - How do agentic AI and BI fit together? WisdomAI introduces the concept of "Knowledge Fabric" and agentic data insights. Break this down for us - how does this fundamentally differ from traditional dashboards and BI tools?Topic 5 - One of the biggest challenges with GenAI in enterprise settings is hallucination. You've emphasized that WisdomAI separates GenAI from answer generation. How does your approach tackle this critical trust issue?Topic 6 - Let's talk about data integration complexity. Your platform works with both structured and unstructured data - Snowflake, BigQuery, Redshift, but also Excel, PDFs, PowerPoints. How do you handle this "dirty" data reality that most enterprises face?Topic 6a - With so much data, how do most organizations get started? What's a typical use case for adoption?Topic 7 - If anyone is interested, what's the best way to get started?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

Why are 95% of AI projects struggling to create positive ROI, according to a recent MIT study? Do businesses need help getting those first few AI projects started and driven to success?SHOW: 970SHOW TRANSCRIPT: The Cloudcast #970 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.SHOW NOTES:MIT Study - The State of AI in Business (2025)The Information - Interview with Vihod Khosla (Oct 2025)WHERE ARE THE BIGGEST AI RISKS?Why are Businesses struggling with AI projects in 2025?What are simple steps to make AI projects successful?FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

eBPF holds the potential for true automatic instrumentation for observability. OpenTelemetry eBPF Instrumentation (OBI) is a new addition to the OpenTelemetry project, which brings the promise of a multi-language, multi-protocol auto-instrumentation, thanks to a code donation by Grafana Labs. Our guest today is Mario Macías, Principal Software Engineer at Grafana Labs and OpenTelemetry eBFP Instrument maintainer. Macías joins Horovits to share about OBI, its origins, capabilities and how it fits into the broader OpenTelemetry project. Mario holds a Ph.D. in Computer Architecture and for the last 8 years he's been working in observability at different companies. He also authored books in Spanish language, such as "Programación en Go" or "Introducción a Apache Spark". You can read the recap post: https://medium.com/p/377cb0432bf1Show Notes:00:00 - episode intro02:11 - guest intro05:15 - Beyla origins08:45 - OBI for app monitoring14:46 - no-code multi-language instrumentation 23:12 - OBI trace support33:58 - OBI components43:39 - Beyla project new focus47:21 - OTel instrumentation SIG51:34 - collaboration with other OTel components and SIGs 54:59 - OBI roadmap59:26 - outro Resources:OBI on GitHub: https://github.com/open-telemetry/opentelemetry-ebpf-instrumentation/ Grafana Beyla donation: https://grafana.com/blog/2025/05/07/opentelemetry-ebpf-instrumentation-beyla-donation/ eBPF for continuous profiling and the Parca project: https://medium.com/p/8afd5bafd498eBPF for tracing and OTel GoLang Auto-instrumentation SIG: https://www.youtube.com/watch?v=VFykWV1mLAI&list=PLd57eY2edRXz4djMETYTm-2p8WGTdoX3DeBPF for Kubernetes monitoring and the Pixie project: https://www.youtube.com/watch?v=NYDBj5ctKaw&list=PLd57eY2edRXz4djMETYTm-2p8WGTdoX3D&index=52Dotan Horovits============Twitter: @horovitsLinkedIn: www.linkedin.com/in/horovitsMastodon: @horovits@fosstodonBlueSky: @horovits.bsky.socialMario Macías===========LinkedIn: https://www.linkedin.com/in/mariomac/Mastodon: https://masto.es/@maciasSocials:BlueSky: ⁠https://bsky.app/profile/openobservability.bsky.social⁠Twitter: ⁠⁠https://twitter.com/OpenObserv⁠⁠LinkedIn: ⁠https://www.linkedin.com/company/openobservability/⁠YouTube:⁠ ⁠https://www.youtube.com/@openobservabilitytalks⁠⁠OpenObservability Talks episodes are released monthly, on the last Thursday of each month and are available for listening on your favorite podcast app and on YouTube.

Monzy Merza (@monzymerza, CEO/Founder @Crogl) talks about build a next-generation Enterprise SOC by leveraging AI to stay ahead of Cybersecurity threats.SHOW: 969SHOW TRANSCRIPT: The Cloudcast #969 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:Crogl websiteTechCrunch articleForbes ArticleIntellyx ArticleLast WatchDog ArticleTopic 1 - Welcome to the show, Monzy. Give everyone a brief introduction and tell us about your unique journey from government research to Splunk to Databricks to founding Crogl.Topic 2 - Let's start with the current state of cybersecurity and AI. We're seeing headlines about AI being the top cybersecurity concern for 2025, even overtaking ransomware. From your perspective, what's driving this shift and why should organizations be paying attention to the intersection of cybersecurity and AI?Topic 3 - You've described Crogl as an "Iron Man suit" for security analysts. That's a compelling metaphor. Can you break down what you mean by that and how your approach differs from the traditional "reduce alerts" mentality that most vendors have been pushing?Topic 4 - Let's talk about your "knowledge engine" and what you call an “AI for the Enterprise SOC”. You're using compound AI systems with LLMs, smaller models, and knowledge graphs. This sounds quite different from vendors who are just "bolting on" LLMs to existing tools. Walk us through this architectural decision and why it matters.Topic 5 - The cybersecurity industry is experiencing massive alert fatigue - 4,500 alerts per day, with analysts only able to investigate 8-25 of them. Your philosophy is "every alert should be analyzed" rather than filtering them out. That seems counterintuitive to what the market has been doing. How does your autonomous investigation approach actually work in practice?Topic 6 - Where do you see this evolution heading, and what are the implications for SOC teams and security practitioners? Are we heading toward fully autonomous SOCs?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodI

In this episode of the Ardan Labs Podcast, Bill Kennedy talks with Zack Holland, CEO & Founder of Averi AI, about his journey from early life in Ecuador's Amazon rainforest to building an AI-powered marketing platform. Zack shares lessons from early business ventures, the challenges of running startups, and the evolution of his entrepreneurial mindset. They explore how Averi AI helps marketers become more creative and efficient, the importance of data security and trust in AI, and what it takes to innovate in a rapidly evolving digital landscape.00:00 Introduction02:54 Marketing and AI Evolution05:58 Changing Digital Landscape09:04 Early Life and Influences12:02 From Ecuador to Utah18:00 First Business in High School29:53 LLMs and Entrepreneurship39:44 Lessons from Failure43:46 Starting a Marketing Agency56:19 Founding Avery AI01:08:10 Trust and Data Security01:13:14 Marketing and AI Adoption01:17:58 AI Challenges and Opportunities01:26:00 Contact Info Connect with Zack: Linkedin: https://www.linkedin.com/in/zackhollandX: https://x.com/zack_hollandMentioned in this Episode:Averi AI: https://www.averi.ai/Want more from Ardan Labs? You can learn Go, Kubernetes, Docker & more through our video training, live events, or through our blog!Online Courses : https://ardanlabs.com/education/ Live Events : https://www.ardanlabs.com/live-training-events/ Blog : https://www.ardanlabs.com/blog Github : https://github.com/ardanlabs

Welcome to episode 327 of The Cloud Pod, where the forecast is always cloudy! Justin, Matt, and Ryan are here to bring you all the latest news (and a few rants) in the worlds of Cloud and AI. I'm sure all our readers are aware of the AWS outage last week, as it was in all the news everywhere. But we've also got some new AI models (including Sora in case you're low on really crappy videos the youths might like), plus EKS, Kubernetes, Vertex AI, and more. Let's get started!  Titles we almost went with this week Oracle and Azure Walk Into a Cloud Bar: Nobody Gets ETL’d When DNS Goes Down, So Does Your Monday: AWS Takes Half the Internet on a Coffee Break 404 Cloud Not Found: AWS Proves Even the Internet’s Phone Book Can Get Lost DNS: Definitely Not Staffed – How AWS Lost Its Way When It Lost Its People When Larry Met Satya: A Cloud Love Story Azure Finally Answers ‘Dude, Where’s My Data?’ with Storage Discovery Breaking: Microsoft Discovers AI Training Uses More Power Than a Small Country 404 Engineers Not Found – AWS Learns the Hard Way That People Are Its Most Critical Infrastructure Azure Storage Discovery: Finding Your Data Needles in the Cloud Haystack EKS Auto Mode: Because Even Your Clusters Deserve Cruise Control Azure Gets Reel: Microsoft Adds Video Generation to AI Foundry The Great Token Heist: Vertex AI Steals 90% Off Your Gemini Bills Cache Me If You Can: Vertex AI’s Token-Saving Feature IaC Just Got a Manager – And It’s Not Your Boss  From Musk to Microsoft: Grok 4 Makes the Great Cloud Migration No Harness.. You are not going to make IACM happen Microsoft Drafts a Solution to Container Creation Chaos PowerShell to the People: Azure Simplifies the Great Gateway Migration IP There Yet? Azure’s Scripts Keep Your Address While You Upgrade Follow Up 00:53 Glacier Deprecation Email Standalone Amazon Glacier service (vault-based with separate APIs) will stop accepting new customers as of December 15, 2025.  S3 Glacier storage classes (Instant Retrieval, Flexible Retrieval, Deep Archive) are completely unaffected and continue normally Existing Glacier customers can keep using it forever – no forced migration required.  AWS is essentially consolidating around S3 as the unified storage platform, rather than maintaining two separate archival services. The standalone service will enter maintenance mode, meaning there will be no new features, but the service will remain operational. Migration to S3 Glacier is optional but recommended for better integration, lower costs, and more features. (Justin assures us it is actually slightly cheaper, so there's that.)  General News  02:24

Python in 2025 is different. Threads really are about to run in parallel, installs finish before your coffee cools, and containers are the default. In this episode, we count down 38 things to learn this year: free-threaded CPython, uv for packaging, Docker and Compose, Kubernetes with Tilt, DuckDB and Arrow, PyScript at the edge, plus MCP for sane AI workflows. Expect practical wins and migration paths. No buzzword bingo, just what pays off in real apps. Join me along with Peter Wang and Calvin Hendrix-Parker for a fun, fast-moving conversation. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Calvin Hendryx-Parker: github.com/calvinhp Peter on BSky: @wang.social Free-Threaded Wheels: hugovk.github.io Tilt: tilt.dev The Five Demons of Python Packaging That Fuel Our ...: youtube.com Talos Linux: talos.dev Docker: Accelerated Container Application Development: docker.com Scaf - Six Feet Up: sixfeetup.com BeeWare: beeware.org PyScript: pyscript.net Cursor: The best way to code with AI: cursor.com Cline - AI Coding, Open Source and Uncompromised: cline.bot Watch this episode on YouTube: youtube.com Episode #524 deep-dive: talkpython.fm/524 Episode transcripts: talkpython.fm Theme Song: Developer Rap

What happens when the biggest technology trend is built on economics that don't make any sense when viewed end-to-end? Eventually, some aspect has to change, but which one? SHOW: 968SHOW TRANSCRIPT: The Cloudcast #968 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSORS:[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.SHOW NOTES:Tokens are getting more expensiveNvidia Earnings, Moats and China, Nvidia vs. the AI LabsOracle Assures Investors on AI Cloud Margins as It Struggles to Profit From Older Nvidia ChipsWHERE ARE THE BIGGEST AI RISKS?Jensen Huang (NVIDIA CEO) is convinced that the future will be built on always having the most advanced GPUs and Frontier Models. Oracle is telling investors that they will significantly increase profit margins between now and 2028-30, although they have low margins now and they don't make high margins on older chipsThe economics of AI (reasoning models, high#s of AI tokens) is in contrast to the established SaaS business model.Right now everything AI-associated has a high valuation, but these forces are working against each other. Which one is going to give first? FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

Aspire has been around for almost two years. How do you use it effectively? Carl and Richard talk to Chris Klug about his experience with .NET Aspire. Chris discusses thinking cloud natively, whether you are going to the cloud or not - it's not just a place, but also an architecture. The conversation digs into the role of containers and Kubernetes, deployment strategies, telemetry, security, testing, and more. You can use as much or as little Aspire as you wish!

Michael Reid went from studying aerospace engineering to becoming CEO at Megaport, a global network-as-a-service platform. How did he get there, and what can we learn from his journey? We walk his career path, including a pivotal role scaling ThousandEyes from 74 million to over 2.4x ARR post-acquisition, and how those experiences shaped his approach to... Read more »

Animesh Koratana - CEO and Founder of PlayerZero discusses how agentic AI is transforming software quality assurance through predictive code simulation, and how teams can shift from reactive debugging to proactive problem prevention in the era of AI-generated code.SHOW: 967SHOW TRANSCRIPT: The Cloudcast #967 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS"SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:PlayerZero websiteTopic 1 - Welcome to the show Animesh. Tell us about your background and your involvement in.Topic 2 - Let's start with the core problem you're solving. What is "predictive software quality" and why is this becoming critical now, especially in the era of AI-generated code?Topic 3 - How does agentic code simulation work, and what makes it different from traditional testing approaches?Topic 4 - This feels like it democratizes software quality beyond just engineering teams. How does PlayerZero work across different roles - developers, QA, product managers, and support teams?Topic 5 - Integration and workflow - how does PlayerZero fit into existing CI/CD pipelines and development workflows? What does the implementation look likeTopic 6 - Let's talk about scale and complexity. How does PlayerZero handle large, distributed systems with microservices, databases, and complex architecturesTopic 7 - If someone out there is interested and wants to get started, what is the best place to started?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod