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.

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S9 · E6
Tuesday · 31 min
Observability Won't Save You, with Henrik Rexed
Kube Select takes one bold Kubernetes hypothesis and tests it with an expert. In the first episode, Salman Iqbal and Bart Farrell ask whether most organizations have an observability problem or a decision-making problem. Henrik Rexed, Senior Staff Engineer at Dynatrace, challenges the original claim. Teams can collect metrics, logs, and traces, but that telemetry needs system relationships, ownership, and deployment history to support a confident decision. In this episode: Why telemetry without context slows incident response How SLOs, ownership, and deployment events guide troubleshooting When more metrics increase cost without improving decisions How AI agents can investigate incidents without replacing human judgment Sponsor Kubernetes moves too fast to track everything. Learn Kubernetes Weekly filters out the noise to deliver one curated email with useful articles, tutorials, tools, jobs, events, and CFPs. Subscribe to Learn Kubernetes Weekly. More info Find all the links and info for this episode here: https://ku.bz/848pmBN5_ Interested in sponsoring an episode? Learn more.
S9 · E5
August 25 · 32 min
Why Kubernetes Needs to Learn GPUs, with Saiyam Pathak
Kube Signals starts where the keynote ends: with the trends that platform teams will have to operationalize next. In this special episode, Brian Teller speaks with Saiyam Pathak about his KubeCon India keynote and the shift from developer platforms to AI factories. They examine what GPU scarcity, shared accelerators, and AI workloads mean after the conference slides meet real infrastructure. In this interview: Why GPU infrastructure is becoming a platform-engineering concern How DRA, HAMI, MIG, and MPS change GPU allocation and utilization Where isolation, scheduling, and observability become harder for AI platforms Which cloud-native AI trends and projects platform engineers need to watch Sponsor This episode is sponsored by LearnKube. Download the free book, The Technical Guide to Kubernetes Rightsizing, to understand what Prometheus and Grafana cannot tell you about safely reducing requests and limits. More info Find all the links and info for this episode here: https://ku.bz/4QZDqrnf- Interested in sponsoring an episode? Learn more.
S9 · E4
August 19 · 36 min
GitOps at Enterprise Scale, with Elad Cohen
At enterprise scale, a deployment pipeline that runs Helm upgrades directly against Kubernetes hides drift, mixes configuration with CI logic, and makes the last pipeline run the source of truth. Elad Cohen explains how WSC Sports moved from Azure DevOps to GitHub Actions and redesigned delivery around Git and Argo CD. The resulting platform separates builds from deployments, keeps service configuration in values files, and continuously reconciles clusters. In this interview: Why CI should change Git instead of the cluster How ApplicationSets create main and shadow deployments from one values file How AppProjects scope permissions and route alerts by team Why reusable Helm contracts make customization compound across services Sponsor This episode is sponsored by LearnKube. Download the free book, The Technical Guide to Kubernetes Rightsizing, to understand what Prometheus and Grafana cannot tell you about safely reducing requests and limits. More info Find all the links and info for this episode here: https://ku.bz/wX5H5Mjwv Interested in sponsoring an episode? Learn more.
S9 · E3
August 10 · 45 min
Automating Pod Disruption Budgets with Kyverno, with Ahmad Asmar
Karpenter can reduce Kubernetes infrastructure costs, but aggressive node consolidation can also expose workloads that lack disruption safeguards. Ahmad Asmar explains how Zencity uses Kyverno to automatically generate Pod Disruption Budgets, while accounting for existing PDBs, percentage-based availability targets, single-replica workloads, and environment-specific policies. In this interview: How Karpenter consolidation changes the availability risks of cluster operations Why Kyverno's generated policies can provide safer defaults than manual enforcement How to handle duplicate PDBs, scaling workloads, and single-replica edge cases How aggregated ClusterRoles keep custom permissions separate from Helm-managed resources Sponsor This episode is sponsored by LearnKube. Download the free book, The Technical Guide to Kubernetes Rightsizing, to understand what Prometheus and Grafana cannot tell you about safely reducing requests and limits. More info Find all the links and info for this episode here: https://ku.bz/xrlPJg54D Interested in sponsoring an episode? Learn more.
S9 · E2
August 4 · 26 min
From KIAM to EKS Pod Identities, with Fabián Sellés Rosa
An unmaintained identity component can remain invisible until a routine Kubernetes upgrade turns it into an incident. Fabián Sellés Rosa, Platform Engineer and Runtime Tech Lead at Adevinta, explains how his team moved from KIAM to EKS Pod Identities without discarding the security boundaries and application interface that their internal platform depended on. In this interview: Why KIAM became urgent to replace after years of stable operation How Crossplane, a custom controller, and KRO with ACK compared against the team's criteria Why managed EKS Capabilities reduced toil but introduced observability and rollout trade-offs How Kyverno preserved namespace-level authorization for IAM roles Sponsor This episode is sponsored by LearnKube. Download the free book, The Technical Guide to Kubernetes Rightsizing, to understand what Prometheus and Grafana cannot tell you about safely reducing requests and limits. More info Find all the links and info for this episode here: https://ku.bz/R_06hwnCn Interested in sponsoring an episode? Learn more.
S9 · E1
July 28 · 47 min
1 Million Tokens Per Second on Kubernetes, with Federico Iezzi
GPU inference throughput depends on more than accelerator generation or count. Memory bandwidth, model parallelism, cache configuration, and the load generator itself all influence measured throughput. Federico Iezzi, Customer Engineer at Google Cloud, explains how his team achieved 1 million output tokens per second using Qwen 3.5 27B, vLLM, GKE Autopilot, and NVIDIA B200 GPUs. The discussion covers: Why memory bandwidth limits decode performance How Federico chose between tensor and data parallelism What changed after enabling multi-token prediction and reducing the KV cache footprint with FP8 quantization. Sponsor This episode is sponsored by LearnKube. Download the free book, The Technical Guide to Kubernetes Rightsizing, to understand what Prometheus and Grafana cannot tell you about safely reducing requests and limits. More info Find all the links and info for this episode here: https://ku.bz/1xD9Md0mb Interested in sponsoring an episode? Learn more.
S8 · E17
May 19 · 21 min
The Hidden Cost of Slow Autoscaling, with John Ford
Forced platform migrations are usually treated as something to survive. At Scout24, a mandatory OS migration became an opportunity to rethink Kubernetes autoscaling, node provisioning, and infrastructure efficiency. John Ford explains how Scout24 moved its EKS-based Infinity platform from a polling autoscaler and over-provisioned capacity to Karpenter and Bottlerocket. The result was faster node startup, a safer migration path, and about a 30% infrastructure reduction without major downtime. In this interview: Why two-minute node provisioning forced a 25% capacity buffer How Karpenter made the Bottlerocket migration safer What broke around EC2 metadata, AWS SDKs, and cgroups How the new foundation enables Spot, ARM, and GPU workloads 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/DdmVC2_7v Interested in sponsoring an episode? Learn more.
S8 · E16
May 12 · 36 min
The Namespaces Scaling Trap, with Brian Stack
Most teams scale Kubernetes by thinking about pods and nodes. At Render, Brian Stack ran into a different dimension: hundreds of thousands of namespaces per cluster, multiplied across DaemonSets that list-watch every namespace. Brian explains how Render traced the issue through Calico and Vector, worked with upstream maintainers, and turned memory profiling into operational wins: lower node costs, lighter API-server load, and faster rollouts. In this interview: Why namespaces can become a hidden scaling bottleneck How DaemonSets multiply memory and control-plane pressure How profiling, staging clusters, and upstream collaboration freed 7 TiB Why pushing from an 80% fix to a complete fix can make teams faster 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/0mrvCsXrV Interested in sponsoring an episode? Learn more.
S8 · E15
May 5 · 38 min
AI Agents Running Kubernetes, with Mike Solomon
What happens when an AI agent stops generating Kubernetes YAML and starts operating the cluster directly? Mike Solomon, software engineer at AIATELLA, explains how his team moved from a sprawling Helm setup to Markdown-driven infrastructure specs that Claude Code can execute, test, and refine. You will learn Why Helm became hard to maintain for a fast-moving medical infrastructure repo How Claude debugged Argo, TLS conflicts, kubectl patches, and private registry credentials How runbooks plus agent memory files capture failures so deployments become reproducible. It is a practical look at where Kubernetes automation may be heading: less hand-written YAML, more precise intent, and a sharper definition of when the human must stay in the loop. 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/y70mLvWNs Interested in sponsoring an episode? Learn more.
S8 · E14
April 28 · 35 min
SaaS with Kubernetes Operators and Garbage Collection, with Alexander Held
A single Kubernetes CRD for every service request turns small changes into full-platform reconciliations. Alexander Held, former platform engineer at Mercedes-Benz Tech Innovation, describes a production refactor from a 2,000-line CRD to purpose-built resources and controllers. He shows how teams can model business workflows as Kubernetes APIs and then use owner references, finalizers, and events to keep platform operations predictable. You will learn: Why monolithic CRDs create performance and troubleshooting problems How controllers turn database provisioning and backups into reconciliation loops How finalizers clean up external resources such as S3 backups Why Kubernetes events make platform workflows easier to debug 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/TGy4Qn7Qs Interested in sponsoring an episode? Learn more.
S8 · E13
April 21 · 1 hr 29 min
What Hip-Hop Can Teach Us About Kubernetes, with Kelsey Hightower, Eric Abercrombie, and Julius Payne II
Kelsey Hightower, Eric Abercrombie, and Julius Payne II reflect on life after achievement, entering the Kubernetes world for the first time, and how music, creativity, and lived experience shape the way they think about technology. In this interview: Why fundamentals, patience, and repetition still matter more than shortcuts How Kubernetes, community, and confidence intersect for people entering cloud-native work What hip-hop, production, and storytelling can teach us about ownership, authenticity, and finding your voice 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/czrCCXSLt Interested in sponsoring an episode? Learn more.
S8 · E12
April 7 · 30 min
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.
S8 · E11
March 31 · 28 min
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.
S8 · E10
March 24 · 45 min
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.
S8 · E9
March 17 · 20 min
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.
S8 · E8
March 10 · 25 min
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.
S8 · E7
March 3 · 1 hr 1 min
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.
S8 · E6
February 24 · 38 min
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.
S8 · E5
February 17 · 21 min
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.
S8 · E4
February 10 · 27 min
Kubernetes is not just for Black Friday, with Thibault Martin
You self-host services at home, but upgrades break things, rollbacks require SSH-ing in to kill containers manually, and there's no safety net if your hardware fails. Thibault Martin, Director of Program Development at the Matrix Foundation, walked this exact path — from Docker Compose to Podman with Ansible to Kubernetes on a single server — and explains why each transition happened and what it solved. In this interview: Why Ansible's declarative promise fell short with the Podman collection, forcing sequential imperative steps instead of desired-state definitions How community Helm charts replace the need to write and maintain every manifest yourself Why GitOps isn't just a deployment workflow — it's a disaster recovery strategy when your infrastructure lives in your living room How k3s removes the barrier to entry by bundling opinionated defaults so you can skip choosing CNI plugins and storage providers Kubernetes doesn't have to be enterprise-scale — with the right distribution and community tooling, it can be a practical, low-overhead choice for anyone who cares about their data. 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/Xk5S7VqXz Interested in sponsoring an episode? Learn more.

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