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Recent episodes
The Hidden Kubernetes Tax Costing Teams $43,800 a Year
Mar 30, 2026
18m 22s
Your Kubernetes Stack Is Why AI Isn’t Shipping
Mar 27, 2026
18m 56s
AI Agents in Kubernetes Need Standards — Before Everything Breaks
Mar 26, 2026
19m 09s
AI Agents Are About to Break Kubernetes — Unless We Standardize Now
Mar 25, 2026
19m 42s
How to Monitor LLMs in Production Before They Drain Your Budget
Mar 24, 2026
20m 19s
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 3/30/26 | The Hidden Kubernetes Tax Costing Teams $43,800 a Year✨ | Kubernetes costsvirtual clusters+4 | — | Azure Copilot Migration AgentKubescape 4.0+2 | — | Kuberneteshidden costs+5 | — | 18m 22s | |
| 3/27/26 | Your Kubernetes Stack Is Why AI Isn’t Shipping | **Why do 87% of AI models never reach production? It's not the AI - it's the infrastructure underneath.** In this deep dive episode of Platform Engineering Playbook, we tackle the critical challenge of building cloud-native platforms that can actually support AI workloads at scale. While everyone's talking about model performance, the real bottleneck is happening at the infrastructure layer. **What You'll Learn:**• Why traditional Kubernetes setups fail with AI workloads• How to architect platforms for GPU-intensive applications• Real-world strategies from teams successfully running AI in production• Practical steps to prepare your platform for the AI transformation **Episode Breakdown:**00:00 Cold Open: The AI production problem02:30 Today's platform engineering news roundup08:45 Deep Dive Act 1: AI workloads are breaking Kubernetes18:20 Deep Dive Act 2: How successful teams handle AI infrastructure **Today's News:**• CNCF adds 21 new silver members focused on AI infrastructure• Critical Grafana security vulnerabilities (CVE-2026-27876 & CVE-2026-27880)• GitHub Actions 2026 security roadmap• AWS launches new AI development tools• Aurora PostgreSQL joins AWS Free Tier Perfect for platform engineers, SREs, and infrastructure teams navigating the AI infrastructure challenge. **Sources & References:**- https://www.cncf.io/blog/2026/03/26/the-platform-under-the-model-how-cloud-native-powers-ai-engineering-in-production/- https://www.cncf.io/announcements/2026/03/25/cncf-welcomes-21-new-silver-members-as-global-demand-surges-for-observability-ai-and-secure-cloud-native-infrastructure/- https://grafana.com/blog/grafana-security-release-critical-and-high-severity-security-fixes-for-cve-2026-27876-and-cve-2026-27880/- https://github.blog/news-insights/product-news/whats-coming-to-our-github-actions-2026-security-roadmap/- https://aws.amazon.com/about-aws/whats-new/2026/03/agent-plugin-aws-serverless/- https://aws.amazon.com/about-aws/whats-new/2026/03/amazon-aurora-postgresql-aws-free-tier/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 56s | ||||||
| 3/26/26 | AI Agents in Kubernetes Need Standards — Before Everything Breaks | **What happens when AI agents in your Kubernetes cluster start making their own scaling decisions without proper guardrails?** In this episode of Platform Engineering Playbook, we dive deep into the emerging world of cloud native agentic standards and why they're becoming mission-critical for modern infrastructure. As AI agents become more autonomous in managing our clusters, the need for standardized communication protocols has never been more urgent. **What You'll Learn:**• How cloud native agentic standards are reshaping Kubernetes operations• Real-world scenarios where unsupervised AI agents can wreak havoc on your infrastructure• Practical strategies for implementing these standards in existing systems• Latest CNCF developments including 21 new silver members and expanded AI inference capabilities• Istio's new AI-era features and AWS Load Balancer Controller GA release **Episode Chapters:**0:00 - Cold Open: The AI Agent Standardization Crisis2:15 - Industry News Roundup8:30 - Deep Dive: Cloud Native Agentic Standards15:45 - The Problem: When AI Agents Go Rogue Whether you're already running AI workloads on Kubernetes or planning your first implementation, this episode provides the frameworks and insights you need to avoid costly mistakes while building resilient, agent-aware infrastructure. **Sources & References:**- Cloud native agentic standards: https://www.cncf.io/blog/2026/03/23/cloud-native-agentic-standards/- CNCF Celebrates Innovators: https://www.cncf.io/announcements/2026/03/25/cncf-celebrates-innovators-advancing-cloud-native-at-kubecon-cloudnativecon-europe/- CNCF AI Inference Expansion: https://cloudnativenow.com/features/cncf-expands-efforts-to-run-ai-inference-workloads-on-kubernetes-clusters/- Istio AI Era Features: https://www.cncf.io/announcements/2026/03/25/istio-brings-future-ready-service-mesh-to-the-ai-era-with-new-ambient-multicluster-gateway-api-inference-extension-and-more/- CNCF New Silver Members: https://www.cncf.io/announcements/2026/03/25/cncf-welcomes-21-new-silver-members-as-global-demand-surges-for-observability-ai-and-secure-cloud-native-infrastructure/- AWS Gateway API GA: https://www.infoq.com/news/2026/03/aws-gateway-api-ga/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 19m 09s | ||||||
| 3/25/26 | AI Agents Are About to Break Kubernetes — Unless We Standardize Now | What happens when hundreds of AI agents start running in your Kubernetes cluster but can't communicate with each other? By 2026, this isn't a hypothetical problem—it's the reality platform engineers are facing right now. In this episode of Platform Engineering Playbook, we dive deep into the CNCF's new cloud-native agentic standards and what they mean for your infrastructure. We'll break down why these standards exist, how they solve critical interoperability challenges, and most importantly—what you need to implement today to stay ahead. **What You'll Learn:**• How to prepare your platform for the AI agent explosion• CNCF's new agentic workflow validation requirements• Why IBM, Red Hat, and Google just donated their LLM inference blueprint• The latest enterprise networking developments with multi-cloud SD-WAN• How the cloud-native community reached 19.9 million developers **Episode Timestamps:**0:00 Cold Open - The AI Agent Problem2:30 Platform Engineering News Roundup8:15 Deep Dive: Cloud Native Agentic Standards15:45 Analysis: What These Standards Actually Mean Whether you're managing existing Kubernetes workloads or planning your AI strategy, this episode gives you the practical insights to build resilient, future-ready platforms. **Sources & References:**• CNCF Cloud Native Agentic Standards: https://www.cncf.io/blog/2026/03/23/cloud-native-agentic-standards/• Colt Multi-Cloud SD-WAN Launch: https://totaltele.com/colt-targets-enterprise-digital-transformation-with-multi-cloud-sd-wan-launch/• CNCF Developer Community Report: https://cloudnativenow.com/kubecon-cloudnativecon-europe-2026/cncf-and-slashdata-report-finds-cloud-native-developer-community-has-reached-19-9-million/• Kubernetes LLM Inference Blueprint: https://thenewstack.io/llm-d-cncf-kubernetes-inference/• CNCF AI Platform Certifications: https://cloudnativenow.com/kubecon-cloudnativecon-europe-2026/cncf-nearly-doubles-certified-kubernetes-ai-platforms-adds-agentic-workflow-validation/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 19m 42s | ||||||
| 3/24/26 | How to Monitor LLMs in Production Before They Drain Your Budget | **Are you burning through your LLM budget with zero visibility into why?** You're not alone - 73% of production deployments are facing this exact problem right now. In today's Platform Engineering Playbook, we tackle the monitoring crisis plaguing AI infrastructure and break down five game-changing developments reshaping how we deploy and secure production systems. **🎯 What You'll Learn:**• How to implement proper LLM observability using Grafana Cloud, OpenLIT, and OpenTelemetry• Step-by-step rollout strategies that won't break your production environment• Why Teleport's new Beams could revolutionize AI agent security in your infrastructure **📺 Chapters:**0:00 - Cold Open: The LLM Budget Crisis2:15 - Today's Platform Engineering News8:30 - Deep Dive: LLM Monitoring in Production15:45 - Implementation Walkthrough **🔥 This Week's News:**• Teleport Beams: Trusted runtimes for AI agents• Metal3 joins CNCF incubation at KubeCon Europe 2026• Cloudflare's Gen 13 servers deliver 2x edge compute performance• New AI-compatible certification frameworks• Pi-Hole deployment strategies for network-wide ad blocking Perfect for platform engineers, DevOps teams, and infrastructure leaders dealing with AI workloads in production. **Sources & References:**• https://grafana.com/blog/ai-observability-llms-in-production/• https://cloudnativenow.com/kubecon-cloudnativecon-europe-2026/teleport-launches-beams-to-provide-trusted-runtimes-for-ai-agents-in-production-infrastructure/• https://www.cncf.io/blog/2026/03/23/metal3-at-kubecon-cloudnativecon-europe-2026-meet-the-cncfs-freshly-incubated-bare-metal-project/• https://blog.cloudflare.com/gen13-launch/• https://letsdatascience.com/news/made-in-usa-introduces-ai-compatible-certification-framework-b0b018ac• https://thenewstack.io/pihole-docker-network-adblocking/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 20m 19s | ||||||
| 3/23/26 | Helm Security Is Broken. WebAssembly Fixes It. | **What if 94% of Helm chart vulnerabilities could be prevented with one unexpected technology?** Today's Platform Engineering Playbook dives deep into the surprising intersection of WebAssembly and Kubernetes security, plus breaking news that every platform engineer needs to know. **What You'll Learn:**• How WebAssembly is revolutionizing Helm chart security (spoiler: it's not replacing Kubernetes)• Why Trivy is under attack again and what it means for your CI/CD pipelines• Critical findings from a security audit of 22,511 AI coding skills• Whether AI will evolve code or make it extinct• GrapheneOS's bold stance against age verification laws **Episode Breakdown:**0:00 - Cold Open: The 94% Helm vulnerability stat that will shock you2:30 - Today's platform engineering headlines5:15 - Deep Dive: WebAssembly + Kubernetes security analysis15:45 - Practical implementation strategies for platform teams Perfect for platform engineers, DevOps professionals, and anyone building resilient cloud-native infrastructure. Get the technical depth you need with practical insights you can implement immediately. **Sources & References:**• WebAssembly & Helm Security: https://thenewstack.io/helm-webassembly-kubernetes-security/• Trivy Attack Analysis: https://socket.dev/blog/trivy-under-attack-again-github-actions-compromise• AI Coding Skills Audit: https://thenewstack.io/ai-agent-skills-security/• AI Programming Future: https://thenewstack.io/ai-programming-languages-future/• GrapheneOS News: https://www.tomshardware.com/software/operating-systems/grapheneos-refuses-to-comply-with-age-verification-laws #PlatformEngineering #DevOps #CloudNative #Kubernetes | 14m 37s | ||||||
| 3/20/26 | The Kubernetes AI Pattern That Cuts GPU Costs | **87% of AI workloads are sitting idle on GPUs right now** - yet companies keep buying more hardware. What if the problem isn't capacity, but how we're running AI on Kubernetes? In today's Platform Engineering Playbook, we tackle the massive inefficiencies plaguing AI infrastructure at scale. You'll discover why traditional Kubernetes patterns break down with AI workloads, what's actually happening under the hood when you try to serve ML models in production, and concrete strategies to fix GPU utilization without throwing more money at the problem. **What You'll Learn:**• Why current Kubernetes-native AI patterns are failing at scale• The hidden bottlenecks destroying your GPU efficiency • Runtime security developments from Grafana Labs and Miggo• Amazon ECR's new pull-through cache support for Chainguard• How to evolve from Kubernetes Gatekeeper to full-stack governance with OPA **Timestamps:**0:00 Cold Open - The AI Infrastructure Crisis2:15 Today's Platform Engineering News8:30 Deep Dive: Kubernetes + AI at Scale15:45 Under the Hood Analysis22:10 Actionable Takeaways Whether you're scaling AI workloads or just trying to understand why your GPU bills keep growing while performance stays flat, this episode gives you the platform engineering perspective you need. **Sources & References:**• Building Kubernetes-native AI infrastructure: https://thenewstack.io/kubernetes-native-ai-infrastructure/• Grafana Cloud and Miggo runtime protection: https://grafana.com/blog/grafana-cloud-and-miggo-for-runtime-protection/• Amazon ECR Chainguard support: https://aws.amazon.com/about-aws/whats-new/2026/03/amazon-ecr-pull-through-cache-chainguard/• AWS Cloud 20 years retrospective: https://aws.amazon.com/blogs/aws/20-years-in-the-aws-cloud-how-time-flies/• LLM Compressor v0.10: https://developers.redhat.com/articles/2026/03/18/llm-compressor-010-faster-compression-distributed-gptq• Kubernetes Gatekeeper to OPA governance: https://www.pulumi.com/blog/kubernetes-gatekeeper-full-stack-governance-opa/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 23m 11s | ||||||
| 3/19/26 | You’re Monitoring the Wrong Kubernetes Metrics | **Are 73% of Kubernetes clusters really flying blind?** According to recent industry reports, most K8s deployments are drowning in meaningless metrics while missing the signals that actually matter for performance and cost optimization. In today's Platform Engineering Playbook, we tackle the Kubernetes observability crisis head-on. You'll discover why traditional monitoring approaches are failing platform teams and learn actionable strategies to build metrics that drive real business value. **What You'll Learn:**• Why most K8s metrics collection strategies are fundamentally broken• How to identify and implement performance indicators that actually matter• Practical frameworks for establishing effective observability in your clusters• Real-world approaches to turning metrics into cost savings and performance gains **Episode Breakdown:**00:00 - Cold Open: The K8s Observability Crisis02:30 - Industry News Roundup08:45 - Deep Dive: Fixing Kubernetes Metrics (Part 1) **Today's News:** Container security innovations from Chainguard, Grafana's new cost optimization tools, custom metrics scaling strategies, and the latest observability trends including AI integration challenges. Perfect for platform engineers, DevOps teams, and engineering leaders looking to move beyond vanity metrics to actionable observability. **Sources & References:**- CNCF Kubernetes Metrics Best Practices: https://www.cncf.io/blog/2026/03/18/understanding-kubernetes-metrics-best-practices-for-effective-monitoring/- Grafana Cost Optimization Guide: https://grafana.com/blog/from-signals-to-savings-optimizing-cloud-costs-with-grafana-assistant-and-mcp-servers/- Chainguard Container Security Analysis: https://thenewstack.io/chainguard-os-packages-containers/- Datadog Custom Metrics Scaling: https://www.datadoghq.com/blog/autoscaling-custom-metrics/- Grafana Observability Standards Report: https://grafana.com/blog/observability-survey-OSS-open-standards-2026/- AI in Observability Survey: https://grafana.com/blog/observability-survey-AI-2026/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 27s | ||||||
| 3/18/26 | The AI Security Hole Your Red Team Is Missing | **87% of enterprise AI deployments have a critical security vulnerability that red teams aren't even testing for.** Are you one of them? In today's Platform Engineering Playbook, we expose the massive security hole plaguing enterprise AI systems and dive deep into prompt injection attacks that are slipping past traditional security measures. Plus, we cover the latest platform engineering news that's reshaping how enterprises build and deploy. **What You'll Learn:**• The hidden AI security vulnerability affecting 9 out of 10 enterprise deployments• Step-by-step breakdown of how prompt injection attacks work in production• Actionable security strategies for platform engineers deploying AI agents• Microsoft's aggressive PostgreSQL push and what it means for your data strategy• Cloudflare's evolution from legacy architecture to modern SASE solutions **Timestamps:**0:00 Cold Open - The 87% Problem1:30 Introduction3:00 Deep Dive: The AI Security Crisis8:45 How Prompt Injection Attacks Actually Work15:20 Platform Engineer Action Items Whether you're currently deploying AI systems or planning your enterprise AI strategy, this episode delivers the security insights and platform engineering intelligence you need to stay ahead of emerging threats. **Sources & References:**• AI Security Research: https://thenewstack.io/red-teaming-enterprise-ai-agents/• PostgreSQL on Azure: https://azure.microsoft.com/en-us/blog/from-legacy-to-leadership-how-postgresql-on-azure-powers-enterprise-agility-and-innovation/• Cloudflare SASE Evolution: https://blog.cloudflare.com/legacy-to-agile-sase/• AI Tooling Survey: https://newsletter.pragmaticengineer.com/i/189777574/2-most-used-ai-tools• Azure DevOps MCP Server: https://devblogs.microsoft.com/devops/azure-devops-remote-mcp-server-public-preview/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 56s | ||||||
| 3/17/26 | Your Kubernetes Monitoring Is Blind to AI Attacks | **Is your Kubernetes cluster blind to AI model poisoning attacks?** 73% of companies running AI workloads can't detect when their models are compromised - and traditional monitoring tools are completely useless against these threats. In today's Platform Engineering Playbook, we dive deep into why AI workloads are breaking traditional Kubernetes observability strategies and what platform teams need to do about it. Plus, we cover the latest developments shaking up the cloud native ecosystem. **What You'll Learn:**✅ Why traditional Kubernetes monitoring fails with AI workloads✅ How to detect AI model poisoning in production environments✅ Critical AWS security vulnerabilities affecting managed services✅ New authentication strategies for Kubernetes registry mirrors✅ Latest developments from the cloud native community **Timestamps:**0:00 Cold Open - The AI observability crisis1:30 Today's Platform Engineering News8:45 Deep Dive: AI Workloads vs Traditional Monitoring15:20 The Real-World Impact on Autoscaling Whether you're running AI workloads today or planning for tomorrow, this episode gives you the strategies and tools to maintain visibility and security in your Kubernetes environments. **Sources & References:**- Why AI workloads are breaking traditional Kubernetes observability strategies: https://thenewstack.io/ai-kubernetes-observability-practices/- AWS Launches Managed Openclaw on Lightsail Amid Critical Security Vulnerabilities: https://www.infoq.com/news/2026/03/aws-lightsail-openclaw-security/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global- LLM Architecture Gallery: https://sebastianraschka.com/llm-architecture-gallery/- Cursor built a fleet of security agents to solve a familiar frustration: https://thenewstack.io/cursor-open-sources-security-agents/- Registry Mirror Authentication with Kubernetes Secrets: https://www.cncf.io/blog/2026/03/16/registry-mirror-authentication-with-kubernetes-secrets-2/- KubeCon + CloudNativeCon Europe 2026 Co-located Event Deep Dive: Open Sovereign Cloud Day: https://www.cncf.io/blog/2026/03/16/kubecon-cloudnativecon-europe-2026-co-located-event-deep-dive-open-sovereign-cloud-day/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 17m 35s | ||||||
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| 3/16/26 | The 6 Types of AI Cloud Infrastructure | **87% of AI companies are burning cash on the wrong cloud infrastructure - and they have no idea.** In this episode of Platform Engineering Playbook, we expose the costly mistakes plaguing AI infrastructure and reveal the framework that's helping platform teams save millions while scaling smarter. **What You'll Learn:**• The 6 categories of AI cloud infrastructure that matter in 2026• How to transform inference from dedicated resources into efficient multi-tenant services• A battle-tested evaluation framework from dozens of real-world AI platform implementations• Critical security vulnerabilities in AWS's new Managed OpenClaw service that could impact your infrastructure **Episode Breakdown:**00:00 Cold Open - The 87% cash burn crisis02:30 Today's Platform Engineering News08:15 Deep Dive: AI Cloud Infrastructure Fundamentals **Breaking News Covered:**- AWS Lightsail OpenClaw security situation- New LLM Architecture Gallery release- MCP production roadmap updates- Linux's game-changing performance breakthrough Whether you're architecting AI platforms or optimizing existing infrastructure, this episode delivers actionable insights to help you avoid the expensive mistakes that are crushing 87% of AI companies. **Sources & References:**- AI Cloud Taxonomy 2026: https://thenewstack.io/ai-cloud-taxonomy-2026/- AWS Lightsail OpenClaw Security: https://www.infoq.com/news/2026/03/aws-lightsail-openclaw-security/- LLM Architecture Gallery: https://sebastianraschka.com/blog/2026/llm-architecture-gallery.html- MCP Production Roadmap: https://thenewstack.io/model-context-protocol-roadmap-2026/- Linux Performance Feature: https://www.iowaparkleader.com/linux-finally-catches-up-to-windows-with-a-game-changing-performance-feature/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 08s | ||||||
| 3/13/26 | Why AI Code Is Killing Your Monitoring Budget | **Is your monitoring bill about to explode? AI-generated code is creating 10x more observability data than human-written code.** In this deep dive episode of Platform Engineering Playbook, we unpack the hidden observability crisis that's quietly hitting DevOps teams everywhere. While AI accelerates development, it's also flooding your monitoring systems with unprecedented amounts of telemetry data. **What You'll Learn:**✅ Why AI-generated code produces exponentially more observability data✅ How to manage exploding monitoring costs without losing visibility✅ Practical strategies for optimizing telemetry in AI-heavy environments✅ Real-world approaches to selective instrumentation and data sampling **Episode Breakdown:**0:00 - Cold Open: The 10x observability data problem2:15 - Industry news roundup8:30 - Deep Dive Act 1: Understanding the AI observability explosion18:45 - Deep Dive Act 2: Technical analysis and root causes **Today's News Coverage:**• CNCF's new etcd debugging improvements for Kubernetes• Uber's MySQL consensus architecture breakthrough• Cloudflare's Account Abuse Protection launch• GitLab Container Virtual Registry updates Perfect for platform engineers, DevOps leads, and SREs dealing with modern observability challenges in AI-driven development environments. **Sources & References:**- https://devops.com/ai-is-forcing-devops-teams-to-rethink-observability-data-management/- https://www.cncf.io/blog/2026/03/12/making-etcd-incidents-easier-to-debug-in-production-kubernetes/- https://www.infoq.com/news/2026/03/uber-mysql-uptime-consensus/- https://blog.cloudflare.com/account-abuse-protection/- https://about.gitlab.com/blog/using-gitlab-container-virtual-registry-with-docker-hardened-images/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 21m 53s | ||||||
| 3/12/26 | How Karpenter Fixes Kubernetes Autoscaling | **Are you throwing money away on Kubernetes compute costs?** 87% of clusters waste up to half their resources on idle nodes - but there's a solution that's changing everything. In today's Platform Engineering Playbook, we dive deep into **Karpenter**, the game-changing autoscaler that's revolutionizing how teams think about Kubernetes resource management. You'll discover why traditional cluster autoscaling falls short and how Karpenter's architecture solves real-world scaling challenges. **What You'll Learn:**✅ Why 87% of K8s clusters are bleeding money on unused compute✅ Karpenter's under-the-hood architecture and decision-making process ✅ Practical evaluation framework for adopting Karpenter in your platform✅ Latest platform engineering news from Microsoft Azure AI agents, KubeCon India 2026, and more **Timestamps:**0:00 - Cold Open: The Kubernetes Cost Crisis2:15 - Today's Platform Engineering News8:30 - Deep Dive: Karpenter vs Traditional Autoscaling Perfect for platform engineers, DevOps teams, and cloud architects looking to optimize their Kubernetes infrastructure costs and performance. **Sources & References:**- Understanding Karpenter architecture: https://www.datadoghq.com/blog/karpenter-architecture/- Microsoft Azure Skills Plugin: https://devops.com/microsoft-azure-skills-plugin-gives-ai-coding-agents-a-playbook-for-cloud-deployment/- KubeCon India 2026 Schedule: https://www.cncf.io/announcements/2026/03/10/cncf-unveils-kubecon-cloudnativecon-india-2026-schedule/- Cloudflare Security Insights: https://blog.cloudflare.com/attack-surface-intelligence/- Monitor Karpenter with Datadog: https://www.datadoghq.com/blog/monitor-karpenter-datadog/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 29s | ||||||
| 3/11/26 | AI Is Not the Problem — Your Infrastructure Is | **Why do 70% of AI projects crash and burn before they ever see production?** Spoiler alert: it's not the AI that's broken. In today's Platform Engineering Playbook, we're diving deep into the AI infrastructure crisis that's keeping CTOs awake at night. While everyone's racing to deploy the latest AI models, most organizations are discovering their legacy systems simply can't handle the load. **What You'll Learn:**• The real reason AI projects fail (hint: it's your infrastructure)• How to build a unified data fabric that actually works• Which legacy systems are sabotaging your AI ambitions• Practical strategies for modernizing without breaking everything **Episode Breakdown:**00:00 - Cold Open: The 70% AI failure rate02:15 - Platform Engineering News Roundup08:30 - Deep Dive: The AI Infrastructure Disconnect15:45 - Building Unified Data Fabrics **Today's News:** Cloudflare & Mastercard's new security partnership, Amazon's R8g instance expansion, Pulumi's Google Sign-In support, Amazon vs. Perplexity AI legal battle, and Together AI's GPU cluster improvements. Perfect for platform engineers, DevOps teams, and technical leaders navigating the AI transformation. **Sources & References:**- AI Infrastructure Crisis Roadmap: https://thenewstack.io/ai-infrastructure-crisis-roadmap/- Cloudflare & Mastercard Security Partnership: https://blog.cloudflare.com/attack-surface-intelligence/- Amazon EC2 R8g Regional Expansion: https://aws.amazon.com/about-aws/whats-new/2026/03/amazon-ec2-r8g-instances-additional-regions/- Pulumi Google Sign-In: https://www.pulumi.com/blog/pulumi-cloud-now-supports-google-sign-in/- Amazon vs. Perplexity Legal Update: https://www.businessoffashion.com/news/technology/amazon-wins-court-order-blocking-perplexity-ai-shopping-bots/- Together AI GPU Clusters: https://www.together.ai/blog/new-in-together-gpu-clusters-autoscaling-observability-self-healing #PlatformEngineering #DevOps #CloudNative #Kubernetes | 19m 03s | ||||||
| 3/10/26 | Why Kubernetes Doesn’t Scale Without an IDP | **Why do 97% of companies using Kubernetes never scale beyond their original expert team?** It's not a skills problem - it's an architecture problem that Internal Developer Platforms (IDPs) are uniquely positioned to solve. In today's episode of Platform Engineering Playbook, we dive deep into the Kubernetes scaling crisis and explore how IDPs can democratize container orchestration across your entire engineering organization. Plus, we cover the latest platform engineering news that's shaping the industry. **What You'll Learn:**• The real reason most Kubernetes deployments stay trapped in expert-only silos• How IDPs solve the complexity problem without dumbing down capabilities • Tactical frameworks for deciding if your organization actually needs an IDP• Breaking news: Pulumi's expanded VCS support, Netflix's massive PostgreSQL migration, and Apono's game-changing Grafana integration **Timestamps:**0:00 - Cold Open: The 97% Problem2:15 - Industry News Roundup8:30 - Deep Dive: The Kubernetes Scaling Crisis15:45 - How IDPs Bridge the Expert Gap Whether you're a platform engineer, DevOps lead, or engineering manager struggling with Kubernetes adoption, this episode gives you concrete strategies to scale your platform beyond the experts who built it. **Sources & References:**• Why IDPs are the Only Way to Scale Kubernetes Beyond Experts: https://cloudnativenow.com/social-facebook/why-idps-are-the-only-way-to-scale-kubernetes-beyond-experts/• Expanded Version Control Support in Pulumi Cloud: https://www.pulumi.com/blog/expanded-version-control-support/• Apono integration for Grafana: https://grafana.com/blog/apono-integration-for-grafana-enabling-just-in-time-access-for-data-sources/• Netflix Automates RDS PostgreSQL to Aurora PostgreSQL Migration: https://www.infoq.com/news/2026/03/netflix-automates-rds-aurora/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 17m 23s | ||||||
| 3/9/26 | The AWS Cost That Doesn’t Show Up in Cost Explorer | **What if your AWS bill has a hidden line item costing you thousands that doesn't even show up in Cost Explorer?** Today on Platform Engineering Playbook, we expose the sneaky cloud costs that are bleeding your budget dry and dive deep into the AWS Well-Architected Framework's six pillars to help you architect cost-efficient, secure platforms. **What You'll Learn:**✅ How to identify and eliminate hidden AWS costs using the Well-Architected Framework✅ Practical steps platform engineers can take TODAY to optimize cloud spending✅ Real-world analysis of cost optimization strategies that actually work **Episode Breakdown:**🎯 Cold Open: The hidden AWS cost crisis📊 Deep Dive Act 1: Setting up the hidden cost problem🔍 Deep Dive Act 2: AWS Well-Architected Framework analysis with expert insights⚡ Deep Dive Act 3: Actionable takeaways for platform engineers📰 Industry News: NanoClaw's containerized AI agents, OpenLens alternatives, incident management at Port, DevOps job opportunities, and GitHub Codespaces incidents Whether you're managing multi-million dollar cloud infrastructures or optimizing costs for growing startups, this episode delivers the framework and tactics you need to stop hidden costs from destroying your budget. **Sources & References:**- AWS Well-Architected Framework Hidden Costs: https://aws.amazon.com/blogs/architecture/the-hidden-price-tag-uncovering-hidden-costs-in-cloud-architectures-with-the-aws-well-architected-framework/- NanoClaw Containerized AI Agents: https://thenewstack.io/nanoclaw-containerized-ai-agents/- OpenLens Alternatives Guide: https://feeds.dzone.com/link/23568/17293987/best-openlens-alternatives-for-kubernetes-visibility- Port Incident Management: https://www.port.io/blog/how-ai-would-have-handled-a-real-incident-at-port- DevOps Job Opportunities: https://devops.com/five-great-devops-job-opportunities-179/- GitHub Codespaces Incident: https://www.githubstatus.com/incidents/tp8m3544w2g8 #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 51s | ||||||
| 3/6/26 | 87% of Ansible Playbooks Are Broken (AI Just Proved It) | **87% of production Ansible playbooks have critical flaws - but AI just revealed how to fix them.** Today's Platform Engineering Playbook dives deep into how AI is revolutionizing infrastructure automation and Ansible development. We'll explore groundbreaking research showing most production playbooks lack proper error handling, and how collaborative AI approaches are changing the game for platform engineers. **What You'll Learn:**• Why most Ansible deployments are more fragile than you think• How to leverage AI to identify and fix critical infrastructure code issues• Real-world case studies of AI-assisted Ansible improvement• Latest developments in route optimization algorithms (RADAR)• Pulumi's massive 20x performance improvements now in GA• AWS Lambda's new Kiro power for durable functions **Timestamps:**0:00 Cold Open - The Ansible Crisis2:15 Today's Platform Engineering News8:30 Deep Dive: AI + Ansible Collaboration Whether you're managing infrastructure at scale or just starting your platform engineering journey, this episode delivers actionable insights you can implement immediately. Learn how top engineering teams are using AI not to replace their expertise, but to amplify it. **Sources & References:**• How to collaborate with AI to improve your Ansible skills: https://developers.redhat.com/articles/2026/03/04/how-collaborate-ai-improve-your-ansible-skills• RADAR: Learning to Route with Asymmetry-aware DistAnce Representations: https://arxiv.org/abs/2603.03388• Now GA: Up to 20x Faster Pulumi Operations for Everyone: https://www.pulumi.com/blog/journaling-ga/• Accelerate Lambda durable functions development with new Kiro power: https://aws.amazon.com/about-aws/whats-new/2026/03/lambda-durable-kiro-power/• How we would have managed a recent incident at Port with an incident agent: https://www.port.io/blog/how-we-would-have-managed-a-recent-incident-at-port-with-an-incident-agent• Scaling AI opportunity across the globe: Learnings from GitHub and Andela: https://github.blog/developer-skills/career-growth/scaling-ai-opportunity-across-the-globe-learnings-from-github-and-andela/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 14m 49s | ||||||
| 3/5/26 | GrafanaCON 2026: The Agenda That Signals the Future of Observability | **GrafanaCON 2026 just dropped their agenda, and every attendee will build an AI agent from scratch on day one. What does this tell us about the future of platform engineering?** In today's Platform Engineering Playbook, we dissect the GrafanaCON 2026 agenda to uncover what it reveals about emerging trends in observability and platform tooling. We analyze why hands-on AI workshops are becoming conference staples and what this means for platform teams in 2026. **What You'll Learn:**• How GrafanaCON's AI-first approach signals industry shifts• Strategic insights for platform teams from the conference agenda• Hidden cloud costs exposed by AWS's Well-Architected Framework• Release platform migration strategies that actually work• Why traditional ITOps fails with AI incident management **Timestamps:**00:00 Cold Open - GrafanaCON's AI Agent Challenge02:15 Today's Platform Engineering News08:30 Deep Dive: GrafanaCON 2026 Agenda Analysis Whether you're planning conference attendance or building your 2026 platform strategy, this episode breaks down the signals that matter for platform engineering leaders. **Sources & References:**• GrafanaCON 2026 agenda: https://grafana.com/blog/grafanacon-2026-agenda/• AWS Hidden Cloud Costs: https://aws.amazon.com/blogs/architecture/the-hidden-price-tag-uncovering-hidden-costs-in-cloud-architectures-with-the-aws-well-architected-framework/• Release Platform Migration Strategy: https://launchdarkly.com/blog/release-platform-migration/• Datadog Synthetic Monitoring: https://www.datadoghq.com/blog/simplifying-troubleshooting-with-synthetic-monitoring/• AI Incident Management Evolution: https://thenewstack.io/ai-incident-management-evolution/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 25s | ||||||
| 3/4/26 | Can AI Run Your Production Systems? | What if your observability stack could debug and fix production issues while you sleep? That future might be closer than you think. In today's Platform Engineering Playbook, we explore the cutting edge of agentic AI in observability systems and break down the biggest platform engineering news shaping March 2026. **🎯 WHAT YOU'LL LEARN:**• How self-healing observability stacks are revolutionizing platform operations• Whether AI agents can truly handle your system's edge cases• Practical evaluation criteria for agentic observability tools• Critical security updates from Datadog's OCI protection expansion• Confluent's game-changing Kafka platform updates with A2A support **⏰ TIMESTAMPS:**0:00 Cold Open - The Future of Self-Debugging Systems1:30 Today's Platform Engineering Headlines8:45 Deep Dive: Agentic Observability - The Setup15:20 Can AI Handle Your Edge Cases? - The Analysis **💡 WHY LISTEN:**Get actionable insights on emerging platform technologies, real-world implementation strategies, and stay ahead of industry trends that will impact your infrastructure decisions. Perfect for platform engineers, SREs, and DevOps professionals navigating the evolving landscape of autonomous systems. **Sources & References:**• https://grafana.com/blog/the-rise-of-agentic-ai-in-production-can-observability-systems-run-themselves/• https://www.datadoghq.com/blog/cloud-security-oci/• https://thenewstack.io/confluent-kafka-a2a-agents/• https://npmx.dev/blog/alpha-release• https://blog.cloudflare.com/bootstrap-mtc/• https://www.bbc.com/news/articles/cgk28nj0lrjo #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 17s | ||||||
| 3/3/26 | Claude Went Down. The API Didn’t. Here’s Why. | What happens when a major AI platform goes dark while secretly pursuing billion-dollar government contracts? Claude's massive outage reveals critical lessons about platform engineering resilience that every infrastructure team needs to understand. In today's Platform Engineering Playbook, we dissect Anthropic's Claude outage and uncover the hidden platform engineering challenges of serving classified government workloads. You'll discover why traditional cloud architectures fail when security requirements demand air-gapped infrastructure, and learn a practical framework for building "architectural resilience" into your own platforms. **What You'll Learn:**• How to architect platforms for multiple security classifications• The real cost of government compliance on platform design• Pulumi's game-changing self-hosted Insights for infrastructure visibility• AWS Lambda runtime automation strategies that actually work• Why Cloudflare's markdown support signals a major shift in web architecture **Timestamps:**0:00 - Cold Open: Claude's Billion-Dollar Secret2:15 - Today's Platform Engineering News8:30 - Deep Dive: The Hidden Cost of Classified Computing15:45 - Framework: Building Architectural Resilience Whether you're scaling startup infrastructure or designing enterprise platforms, this episode delivers actionable insights you can implement immediately. **Sources & References:**- Anthropic's Claude outage: https://techcrunch.com/2026/03/02/anthropics-claude-reports-widespread-outage/- Pulumi self-hosted Insights: https://www.pulumi.com/blog/self-hosted-insights/- AWS Lambda runtime automation: https://aws.amazon.com/blogs/devops/automate-aws-lambda-runtime-upgrades-with-aws-transform-custom/- Ansible AWS updates: https://developers.redhat.com/articles/2026/03/02/whats-new-ansible-certified-content-collection-aws- Cloudflare markdown evolution: https://thenewstack.io/intent-engineering-ai-agents/- Kubernetes DevOps patterns: https://feeds.dzone.com/link/23568/17287898/kubernetes-for-devops-engineers-mastering-modern #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 49s | ||||||
| 3/2/26 | Backstage Is Becoming the Control Plane for Engineering | **What if Spotify's secret weapon for managing 2,800 microservices could transform your entire platform engineering strategy?** Today's Platform Engineering Playbook dives deep into the Backstage revolution that's quietly reshaping how engineering teams operate at scale. We break down what a production-grade Backstage implementation actually looks like in 2026, complete with real-world examples and concrete takeaways for your team. **What You'll Learn:**• How Spotify's internal developer portal handles massive microservice complexity• Production-grade Backstage implementation strategies and best practices• Critical MySQL 9.6 changes affecting foreign key constraints and cascade handling• Bootc and OSTree's role in modernizing Linux system deployment• The latest developments in AI company military partnerships **Episode Timestamps:**0:00 - Cold Open: Spotify's Backstage Breakthrough2:15 - Platform Engineering News Roundup8:30 - Deep Dive Act 1: The Backstage Setup Revolution Whether you're considering Backstage adoption or optimizing your current platform engineering stack, this episode delivers the tactical insights you need to level up your developer experience. **Sources & References:**• KubeCon + CloudNativeCon Europe 2026 BackstageCon: https://www.cncf.io/blog/2026/02/27/kubecon-cloudnativecon-europe-2026-co-located-event-deep-dive-backstagecon/• MySQL 9.6 Foreign Key Changes: https://www.infoq.com/news/2026/02/mysql-foreign-keys/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global• Bootc and OSTree Guide: https://a-cup-of.coffee/blog/ostree-bootc/• AI Military Partnerships Update: https://www.businessinsider.com/anthropic-deal-pentagon-openai-sam-altman-dario-amodei-pete-hegseth-2026-2 #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 22s | ||||||
| 2/27/26 | The End of ingress-nginx: Kubernetes Migration Guide Before 2026 | **70% of Kubernetes clusters will go dark in March 2026 when ingress-nginx support officially ends. Are you ready?** Today's Platform Engineering Playbook dives deep into the massive ingress-nginx migration that's about to impact millions of Kubernetes workloads. We'll break down your migration options, timeline, and practical steps to avoid the chaos. **What You'll Learn:**✅ Why ingress-nginx is ending support and what it means for your clusters✅ Complete migration strategies from early adopter teams✅ Step-by-step playbook for platform engineering teams✅ Alternative ingress controllers and their trade-offs **Episode Chapters:**0:00 Cold Open - The ingress-nginx crisis2:30 Welcome & Today's Platform Engineering News5:15 Deep Dive: The ingress-nginx EOL situation12:45 Migration analysis and real-world experiences **Plus:** Pulumi's distributed work scheduling system architecture, observability platform migration strategies with Prometheus and OpenTelemetry, Kubernetes AI inference updates, and SRE database connectivity troubleshooting frameworks. Perfect for platform engineers, DevOps teams, and anyone managing Kubernetes infrastructure at scale. **Sources & References:**- The End of kubernetes/ingress-nginx: Your March 2026 Migration Playbook: https://medium.com/@housemd/kubernetes-ingress-nginx-eol-march-2026-the-complete-migration-guide-to-replace-ingress-nginx-e8f6e118fb5f- How We Built a Distributed Work Scheduling System for Pulumi Cloud: https://www.pulumi.com/blog/how-we-built-a-distributed-work-scheduling-system-for-pulumi-cloud/- Observability platform migration guide: Prometheus, OpenTelemetry, and Fluent Bit: https://thenewstack.io/observability-platform-migration-guide/- Kubernetes WG Serving concludes following successful advancement of AI inference support: https://www.cncf.io/blog/2026/02/26/kubernetes-wg-serving-concludes-following-successful-advancement-of-ai-inference-support/- A Unified Framework for SRE to Troubleshoot Database Connectivity in Kubernetes Cloud Applications: https://feeds.dzone.com/link/23568/17283905/sre-database-connectivity-troubleshooting-kubernetes #PlatformEngineering #DevOps #CloudNative #Kubernetes | 20m 14s | ||||||
| 2/26/26 | Claude Code Remote Control Changes Developer Workflows | **What if 87% of developer productivity loss just became a thing of the past?** Anthropic's Claude Computer Use capability is reshaping how platform engineers think about developer workflows, and today we're breaking down exactly what this means for your platform strategy. **In this episode:**• **Deep dive into Claude's Computer Use** - How remote control capabilities are eliminating context switching between development environments• **Technical analysis** - Session management, security implications, and integration patterns for platform teams• **Practical evaluation framework** - Should your platform team adopt Claude Code? We'll give you the decision matrix• **Platform engineering news roundup** - Self-service observability with OpenTelemetry, hidden costs of "automated" infrastructure, and real-world IT scaling challenges **Timestamps:**0:00 - Cold Open: The Context Switching Crisis2:15 - Today's Platform Engineering Headlines 8:30 - Deep Dive: Claude Computer Use Breakdown Whether you're architecting developer platforms or evaluating AI tooling for your engineering org, this episode delivers actionable insights you can implement immediately. **Sources & References:**• Claude Code Remote Control: https://code.claude.com/docs/en/remote-control• Self-service observability guide: https://platformengineering.org/blog/self-service-observability• Infrastructure hidden costs analysis: https://thenewstack.io/automated-infrastructure-hidden-costs/• IT scaling discussion: https://www.reddit.com/r/sysadmin/comments/1redz97/2man_it_team_solo_admin_for_300_users_no_raise/• Data sovereignty policy update: https://techcrunch.com/2026/02/25/us-tells-diplomats-to-lobby-against-foreign-data-sovereignty-laws/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 18m 50s | ||||||
| 2/25/26 | Databricks Lakebase vs Postgres: The AI Database Shift | **Is PostgreSQL really obsolete for AI workloads?** Databricks just dropped Lakebase and it's shaking up everything we thought we knew about database architecture for machine learning pipelines. In today's Platform Engineering Playbook, we're diving deep into Databricks' game-changing announcement and what it means for your data infrastructure strategy. Plus, we're covering the week's biggest platform engineering news that's reshaping how we build scalable systems. **What You'll Learn:**• Why Databricks believes traditional PostgreSQL falls short for AI workloads• Technical breakdown of Lakebase architecture and its key innovations• Practical decision framework: when to adopt Lakebase vs. stick with existing solutions• AWS expands Elemental Media Services to Malaysia• Elastic Cloud Serverless doubles Azure region availability• Hybrid Kubernetes strategies for enterprise-scale deployments• OpenTelemetry's 2025 achievements and 2026 roadmap **Timestamps:**0:00 Cold Open - PostgreSQL vs AI Reality Check2:15 Databricks Lakebase Deep Dive15:30 Platform Engineering News Roundup Whether you're architecting data platforms, evaluating database solutions for ML workloads, or staying current with cloud-native trends, this episode delivers actionable insights you can implement immediately. **Sources & References:**• https://www.infoq.com/news/2026/02/databricks-lakebase-postgresql/• https://aws.amazon.com/about-aws/whats-new/2026/02/elemental-Malaysia/• https://www.elastic.co/blog/elastic-cloud-now-available-azure-virginia-singapore-spain-frankfurt• https://aws.amazon.com/blogs/containers/running-containerized-hybrid-nodes-with-amazon-elastic-kubernetes-service/• https://cloudnativenow.com/contributed-content/hybrid-cloud-at-enterprise-scale-private-kubernetes-for-portability-and-control/• https://opentelemetry.io/blog/2026/2025-year-in-review/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 19m 29s | ||||||
| 2/24/26 | How to Secure AI Agents with MCP, OPA & Ephemeral Runners | **Your AI agents have root access to your infrastructure right now - and you don't even know it.** What happens when we give AI agents the keys to our entire platform? In today's Platform Engineering Playbook, we dive deep into the hidden security risks of AI infrastructure automation and explore practical solutions for implementing least-privilege access controls. **What You'll Learn:**• How to secure AI agents with least-privilege gateway patterns using MCP and OPA• Databricks' new Lakebase PostgreSQL database designed specifically for AI workloads• Uber's Uforwarder: A scalable Kafka consumer proxy revolutionizing event-driven microservices• Why Kubernetes 1.35 signals the future of AI orchestration• Latest AWS updates including Claude Sonnet 4.6 in Bedrock and new agent plugins **Timestamps:**0:00 - Cold Open: The AI Security Wake-Up Call2:15 - Platform Engineering News Roundup8:30 - Deep Dive: Securing AI Infrastructure Access15:45 - Real-World Implementation Strategies Perfect for platform engineers, DevOps professionals, and infrastructure teams navigating the intersection of AI and cloud-native technologies. Get actionable insights to secure your AI-driven infrastructure before it's too late. **Sources & References:**- Building a Least-Privilege AI Agent Gateway: https://www.infoq.com/articles/building-ai-agent-gateway-mcp/- Databricks Lakebase PostgreSQL: https://www.infoq.com/news/2026/02/databricks-lakebase-postgresql/- KubeCon SecurityCon Deep Dive: https://www.cncf.io/blog/2026/02/23/kubecon-cloudnativecon-europe-2026-co-located-event-deep-dive-open-source-securitycon/- Uber's Uforwarder: https://www.infoq.com/news/2026/02/uber-uforwarder-kafka-push-proxy/- AWS Weekly Roundup: https://aws.amazon.com/blogs/aws/aws-weekly-roundup-claude-sonnet-4-6-in-amazon-bedrock-kiro-in-govcloud-regions-new-agent-plugins-and-more-february-23-2026/- Kubernetes 1.35 AI Signals: https://www.cncf.io/blog/2026/02/23/kubernetes-as-ais-operating-system-1-35-release-signals/ #PlatformEngineering #DevOps #CloudNative #Kubernetes | 19m 55s | ||||||
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