KubeFM

KubeFM

Discover all the great things happening in the world of Kubernetes, learn (controversial) opinions from the experts and explore the successes (and failures) of running Kubernetes at scale.

  1. HÁ 3 DIAS

    Intelligent Kubernetes Load Balancing, with Rohit Agrawal

    You're running gRPC services in Kubernetes, load balancing looks fine on the dashboard — but some pods are burning at 80% CPU while others sit idle, and adding more replicas only partially helps. Rohit Agrawal, a Staff Software Engineer on the traffic platform team at Databricks, explains why this happens and how his team replaced Kubernetes's default networking with a proxy-less, client-side load-balancing system built on the xDS protocol. In this episode: Why KubeProxy's Layer 4 routing breaks down under high-throughput gRPC: it picks a backend once per TCP connection, not per request How Databricks built an Endpoint Discovery Service (EDS) that watches Kubernetes directly and streams real-time pod metadata to every client How zone-aware spillover cut cross-availability-zone costs without sacrificing availability Why CPU-based routing failed (monitoring lag creates oscillation) and what signals to use instead The system has been running in production for three years across hundreds of services, handling millions of requests. Sponsor This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training. More info Find all the links and info for this episode here: https://ku.bz/y803JMhBk Interested in sponsoring an episode? Learn more.

    30 min

  2. 31 DE MAR.

    That Time I Found a Service Account Token in my Log Files, with Vincent von Büren

    You're integrating HashiCorp Vault into your Kubernetes cluster and adding a temporary debug log line to check whether the ServiceAccount token is being passed correctly. Three months later, that log line is still in production — and the token it prints has a 1-year expiry with no audience restrictions. Vincent von Büren, a platform engineer at ipt in Switzerland, lived through exactly this incident. In this episode, he breaks down why default Kubernetes ServiceAccount tokens are a quiet security risk hiding in plain sight. You will learn: What's actually inside a Kubernetes ServiceAccount JWT (issuer, subject, audience, and expiry) Why tokens with no audience scoping enable replay attacks across internal and external systems How Vault's Kubernetes auth method and JWT auth method compare, and when to choose each What projected tokens are, why they dramatically reduce blast radius, and what's holding teams back from using them Practical steps for auditing which pods actually need API access and disabling auto-mounting everywhere else Sponsor This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training. More info Find all the links and info for this episode here: https://ku.bz/LTnB_Ntbc Interested in sponsoring an episode? Learn more.

    29 min

  3. 24 DE MAR.

    GPU Containers as a Service, with Landon Clipp

    Running GPU workloads on Kubernetes sounds straightforward until you need to isolate multiple tenants on the same server. The moment you virtualize GPUs for security, you lose access to NVIDIA kernel drivers — and almost every tool in the ecosystem assumes those drivers exist. Landon Clipp built a GPU-based Containers as a Service platform from scratch, solving each isolation layer — from kernel separation with Kata Containers + QEMU to NVLink fabric partitioning to network policies with Cilium/eBPF — and shares exactly what broke along the way. In this interview: Why standard NVIDIA tooling (GPU Operator) fails in multi-tenant setups, and how to use CDI with PCI topology scanning to make GPUs visible to Kubernetes without kernel drivers How to partition the NVLink fabric between tenants using a trusted service VM running Fabric Manager, and why the physical PCIe wiring differs between Supermicro HGX and NVIDIA DGX systems Why gVisor doesn't work for GPU workloads — NVIDIA's unstable ioctl ABI means Google has to update gVisor for every driver release, and they only support a handful of GPUs What caused 8-GPU VMs to take 30+ minutes to boot, and the specific fixes (IOMMUFD, cold plugging, kernel upgrades) that brought it down to minutes How Cilium network policies enforce tenant isolation at the Kubernetes identity level instead of fragile IP-based rules Where Containers as a Service fits best: inference workloads where AI teams want to ship an OCI image without managing infrastructure or signing multi-million dollar cluster contracts. Sponsor This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training. More info Find all the links and info for this episode here: https://ku.bz/jjK_yJTDz Interested in sponsoring an episode? Learn more.

  4. 17 DE MAR.

    How We Cut Build Debugging Time by 75% with AI, with Ron Matsliah

    Build failures in Kubernetes CI/CD pipelines are a silent productivity killer. Developers spend 45+ minutes scrolling through cryptic logs, often just hitting rerun and hoping for the best. Ron Matsliah, DevOps engineer at Next Insurance, built an AI-powered assistant that cut build debugging time by 75% — not as a dashboard, but delivered directly in Slack where developers already work. In this episode: Why combining deterministic rules with AI produces better results than letting an LLM guess alone How correlating Kubernetes events with build logs catches spot instance terminations that produce misleading errors Why integrating into existing workflows and building feedback loops from day one drove adoption The prompt engineering lessons learned from testing with real production data instead of synthetic examples The takeaway: simple rules plus rich context consistently outperform complex AI queries on their own. Sponsor This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training. More info Find all the links and info for this episode here: https://ku.bz/PDdYfC00w Interested in sponsoring an episode? Learn more.

    21 min

  5. 10 DE MAR.

    Migrating Kubernetes Off Big Cloud, with Fernando Duran

    Managed Kubernetes on a major cloud provider can cost hundreds or even thousands of dollars a month — and much of that spending hides behind defaults, minimum resource ratios, and auxiliary services you didn't ask for. Fernando Duran, founder of SadServers, shares how his GKE Autopilot proof of concept ran close to $1,000/month on a fraction of the CPU of the actual workload and how he cut that to roughly $30/month by moving to Hetzner with Edka as a managed control plane. In this interview: Why Kubernetes hasn't delivered on its original promise of cost savings through bin packing — and what it actually provides instead A real cost comparison: $1,000/month on GKE vs. $30/month on Hetzner with Edka for the same nominal capacity What you need to bring with you (observability, logging, dashboards) when leaving a fully managed cloud provider The decision comes down to how tightly coupled you are to cloud-specific services and whether your team can spare the cycles to manage the gaps. Sponsor This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training. More info Find all the links and info for this episode here: https://ku.bz/6nSDbz9m4 Interested in sponsoring an episode? Learn more.

    25 min

  6. 3 DE MAR.

    Migrating to Karpenter: Fun Stories, with Adhi Sutandi

    Running multiple Kubernetes clusters on AWS with the cluster autoscaler? Every four months, you face the same grind: upgrading Kubernetes versions, recreating auto scaling groups, and hoping instance type changes stick. Adhi Sutandi, DevOps Engineer at Beekeeper by LumApps, shares how his team migrated from the cluster autoscaler to Karpenter across eight EKS clusters — and the hard lessons they learned along the way. In this episode: Why AWS auto scaling groups are immutable and how that creates upgrade bottlenecks at scale How the latest AMI tag accidentally turned less critical clusters into chaos engineering environments, dropping SLOs before anyone realized Karpenter was the cause Why pre-stop sleep hooks solved pod restartability problems that Quarkus's built-in graceful shutdown couldn't The case for pod disruption budgets over Karpenter annotations when protecting critical workloads during node rotations How Karpenter's implicit 10% disruption budget caught the team off guard — and the explicit configuration that fixed it Sponsor This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training. More info Find all the links and info for this episode here: https://ku.bz/XyVfsSQPr Interested in sponsoring an episode? Learn more.

    1h 2min

  7. 24 DE FEV.

    From ECS to Kubernetes: A Real Migration Story, with Radosław Miernik

    Migrating from ECS to Kubernetes sounds straightforward — until you hit spot capacity failures, firewall rules silently dropping traffic, and memory metrics that lie to your autoscaler. Radosław Miernik, Head of Engineering at aleno, walks through a real production migration: what broke, what they missed, and the fixes that made it work. In this interview: Running Flux and Argo CD together — Flux for the infra team, Argo CD's UI for developers who don't want to touch YAML How the wrong memory metric caused OOM errors, and why switching to jemalloc cut memory usage by 20% Splitting WebSocket and API containers into separate deployments with independent autoscaling Four months of migration, over 100 configuration changes in the first month, and a concrete breakdown of what platform work looks like when you can't afford downtime. Sponsor This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training. More info Find all the links and info for this episode here: https://ku.bz/x6wFMhVsx Interested in sponsoring an episode? Learn more.

    38 min

  8. 17 DE FEV.

    Faster EKS Node and Pod Startup, with Jan Ludvik

    Kubernetes nodes on EKS can take over a minute to become ready, and pods often wait even longer — but most teams never look into why. Jan Ludvik, Senior Staff Reliability Engineer at Outreach, shares how he cut node startup from 65 to 45 seconds and reduced P90 pod startup by 30 seconds across ~1,000 nodes — by tackling overlooked defaults and EBS bottlenecks. In this episode: Why Kubelet's serial image pull default quietly blocks pod startup, and how parallel pulls fix it How EBS lazy loading can silently negate image caching in AMIs — and the critical path workaround A Lambda-based automation that temporarily boosts EBS throughput during startup, then reverts to save cost The kubelet metrics and logs that expose pod and node startup latenc,y most teams never monitor Every second saved translates to faster scaling, lower AWS bills, and better end-user experience. Sponsor This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training. More info Find all the links and info for this episode here: https://ku.bz/B7TzKXyxf Interested in sponsoring an episode? Learn more.

    22 min
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Sobre

Discover all the great things happening in the world of Kubernetes, learn (controversial) opinions from the experts and explore the successes (and failures) of running Kubernetes at scale.

Informações

  • Criado por
    KubeFM
  • Anos de atividade
    2023 - 2026
  • Episódios
    95
  • Classificação
    Livre
  • Copyright
    © 2023-2026 KubeFM
  • Site do podcast
    KubeFM

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