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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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
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
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
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 obser
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 F
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
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
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 wher
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
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 Kube
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 Da
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
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 (
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 prod
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
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 int
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 an
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 automatio
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 re
Your database backup strategy shouldn't be the thing that takes your production systems down. Ziv Yatzik manages 600+ Postgres clusters in a closed network environment with no public cloud. After existing backup solutions proved unreliable — causing downtime when disks filled up — his team built a new architecture using pgBackRest, Argo CD, and Kubernetes CronJobs. In this episode: Why storing WAL files on shared NAS storage prevents backup failures from cascading into database outages How GitOps with Argo CD lets them manage backups for hundreds of clusters by adding a single YAML file The An
Most developers assume Kubernetes requires an enterprise budget. Varnit Goyal proves otherwise — he built a full three-node Kubernetes cluster for $2.16/month using Rackspace Spot Instances. The trick: pick non-default instance types, distribute nodes across low-demand regions, and let Kubernetes handle rescheduling when nodes get preempted. For service exposure, he replaced the $10/month load balancer with Tailscale Funnel — free. In this episode: How Spot Instance bidding works and which strategies keep costs and preemption low Using Tailscale Kubernetes operator as a free alternative to tra
Dilshan Wijesooriya, Senior Cloud Engineer, discusses a real incident where migrating EKS nodes to AL2023 caused the cluster autoscaler to lose AWS permissions silently. You will learn: Why AL2023 blocks pod access to instance metadata by default, breaking components that relied on node IAM roles (like cluster autoscaler, external-DNS, and AWS Load Balancer Controller) How to implement IRSA correctly by configuring IAM roles, Kubernetes service accounts, and OIDC trust relationships, and why both AWS IAM and Kubernetes RBAC must be configured independently The recommended migration strategy: m
Fabián Sellés Rosa, Tech Lead of the Runtime team at Adevinta, walks through a real engineering investigation that started with a simple request: allowing tenants to use third-party Kafka services. What seemed straightforward turned into a complex DNS resolution problem that required testing seven different approaches before a working solution was found. You will learn: Why Kafka's multi-step DNS resolution creates unique challenges in multi-tenant environments, where bootstrap servers and dynamic broker lists complicate standard DNS approaches The iterative debugging process from Route 53 spl
Amos Wenger walks through his production incident where adding a home computer as a Kubernetes node caused TLS certificate renewals to fail. The discussion covers debugging techniques using tools like netshoot and K9s, and explores the unexpected interactions between Kubernetes overlay networks and consumer routers. You will learn: How Kubernetes networking assumptions break when mixing cloud VMs with nodes behind consumer routers, and why cert-manager challenges fail in NAT environments The differences between CNI plugins like Flannel and Calico, particularly how they handle IPv6 translation
Tanat Lokejaroenlarb shares the complete journey of replacing EKS Managed Node Groups and Cluster Autoscaler with AWS Karpenter. He explains how this migration transformed their Kubernetes operations, from eliminating brittle upgrade processes to achieving significant cost savings of €30,000 per month through automated instance selection and AMD adoption. You will learn: How to decouple control plane and data plane upgrades using Karpenter's asynchronous node rollout capabilities Cost optimization strategies including flexible instance selection, automated AMD migration, and the trade-offs bet
