Learn from production

• Taming the Storm: Building Groww’s Internal Chaos Engineering Platform

  Groww Engineering Team

  This case study explains how Groww built an internal chaos engineering platform on Kubernetes to run controlled failure drills like network faults, dependency outages, and traffic replay before real incidents hit production.

• Investigating and fixing "stoppodsandbox from runtime service failed" kubelet errors

  In this blog post, the author tracks down persistent sandbox-cleanup errors in a Kubernetes cluster, finds that zero-length CNI cache files cause the problem, and shows how manually deleting those files cleared the error.

• Migrating legacy PHP monolith apps on Drupal 8 to Kubernetes

  Alexey Demyanov

  This case study shows how Palark migrated high-traffic Drupal 8 monoliths to Kubernetes to improve resilience, autoscaling, deployment automation, and DDoS handling while reducing infrastructure waste.

• How we found 7 TiB of memory just sitting around

  This blog post tells how the Render team:

  • tracked down Kubernetes memory waste caused by many daemonset namespace watches,
  • fixed config issues,
  • and freed over 7 TiB of memory across clusters by reducing unnecessary listwatch overhead.

More case studies →

Matching jobs

1. • Machine Learning Engineer with Nebius

   • Salary: $208K to $261K a year

   • Location: remote from

   • Tech stack: Kubernetes, AWS, Azure, GCP, Docker, Python, Shell

2. • Software Engineer with NISC

   • Salary: $40 to $297K a year

   • Location: based in the office (and remote from home) in Cedar Rapids, IA; Lake Saint Louis, MO; Mandan, ND, USA

   • Tech stack: Kubernetes, AWS, Docker, Java, Scala, SQL, Typescript, DynamoDB, Cassandra, Kafka

3. • Software Engineer with NinjaTrader

   • Salary: $195K to $220K a year

   • Location: based in the office in Chicago, IL, USA

   • Tech stack: Kubernetes, Docker, Scala, Redis, RabbitMQ, Kafka, GitHub Actions, Jenkins

4. • Software Engineer with Nubank

   • Salary: $168K to $210K a year

   • Location: based in the office (and remote from home) in Toronto, CA

   • Tech stack: Kubernetes, AWS, Clojure, DynamoDB, Kafka, Prometheus

5. • Solution Architect with New Relic

   • Salary: $47.97K to $247.5K a year

   • Location: remote from

   • Tech stack: Kubernetes, AWS, Azure, GCP, Docker, Go, Python, Shell, Terraform, GitHub Actions

Discover more Kubernetes jobs on Kube Careers →

Build something

• The Hybrid Cloud Platform Illusion: Why Your On-Prem and Cloud Are Still Strangers

  Shubham Katara

  This tutorial shows how to connect on-prem Kubernetes workloads to Google Cloud without service account keys using Workload Identity Federation, OIDC, Terraform, Kyverno, and IAM attribute conditions.

• Local Log Monitoring: Bridging the Observability Gap in AWS EKS with Stern, Fluent Bit, and Elasticsearch

  M Sandy H

  This tutorial teaches how to build a local observability stack for AWS EKS logs using Stern for multi-pod tailing, Fluent Bit for log processing with multiline parsing, and Elasticsearch with Kibana for searchable visualization via Docker Compose.

• GitOps-Driven Model Serving on Red Hat OpenShift AI with OpenShift GitOps (Argo CD) on IBM Fusion HCI

  Harichandana Kotha

  This tutorial shows how to serve open source LLMs on Red Hat OpenShift AI with KServe, vLLM, Argo CD, and IBM Fusion using a fully declarative GitOps workflow.

• Building a Production-Grade Private EKS Cluster with OpenVPN, Prometheus & Grafana

  Asmaa Elalfy

  This tutorial shows how to build a private EKS cluster with zero public API exposure using Terraform.

  It also covers self-hosted OpenVPN as a VPN gateway, NAT masquerade iptables setup, kube-prometheus-stack via internal load balancer, and Route 53.

More tutorials →

Call for Papers closing soon

1. 5

   days

   AI Engineering Summit

   The Call For Paper is open until 14 July 2026 at GMT-4. More info →

   • Location: Berlin, DE

   • In-person conference organized by AI Engineering Summit.

   • The conference starts on the 20 November 2026.

   • Apply here

2. 5

   days

   Kubernetes Community Days Gujarat 2026

   The Call For Paper is open until 14 July 2026 at GMT-4. More info →

   • Location: Ahmedabad, IN

   • In-person conference organized by KCD Gujarat.

   • The conference starts on the 19 September 2026.

   • Apply here

3. 6

   days

   Kubernetes Community Days Suisse Romande 2026

   The Call For Paper is open until 15 July 2026 at GMT-4. More info →

   • Location: Geneva, CH

   • In-person conference organized by KCD Suisse Romande.

   • The conference starts on the 10 December 2026.

   • Apply here

4. 6

   days

   Great International AI Native Summit

   The Call For Paper is open until 15 July 2026 at GMT-4. More info →

   • Location: Bangalore, IN

   • In-person conference organized by Saltmarch.

   • The conference starts on the 10 December 2026.

   • Apply here

5. 7

   days

   Kubernetes Community Days Porto 2026

   The Call For Paper is open until 16 July 2026 at GMT-4. More info →

   • Location: Porto, PT

   • In-person conference organized by KCD Porto.

   • The conference starts on the 20 November 2026.

   • Apply here

6. 8

   days

   Subsurface 2026 — The Open Data and AI Conference

   The Call For Paper is open until 17 July 2026 at GMT-4. More info →

   • This is a virtual event

   • Online conference organized by Dremio.

   • The conference starts on the 2 October 2026.

   • Apply here

7. 8

   days

   Devopsdays Cairo

   The Call For Paper is open until 17 July 2026 at GMT-4. More info →

   • Location: Cairo, EG

   • In-person conference organized by Devopsdays.

   • The conference starts on the 26 September 2026.

   • Apply here

More articles

• What Does 4.4% GPU Utilization Actually Mean?

  Federico Iezzi

  This article explains why low GPU utilization during LLM inference can be normal by breaking down prefill, decode, memory bandwidth limits, batching, and GKE B200 benchmark numbers.

• GKE Gateway API for Production Traffic Management Guide

  Amit Malhotra

  This article explains why GKE Gateway API is cleaner than Ingress for production traffic, covering role separation, HTTPRoute traffic splitting, Certificate Manager, NEGs, and migration trade-offs.

• Evicting MCP tool calls from your Kubernetes cluster

  Misha Mekhanov

  This article explains how to optimize AI agents for Kubernetes diagnostics by shifting from sequential Model Context Protocol tool calls to code execution mode, reducing token usage by up to 90%.

• Building self-evolving AI systems: exploring the architecture

  Pavel Buchnev

  This article teaches how to build self-evolving AI systems using Kubernetes, Temporal workflows, and automated deployment pipelines, enabling AI agents to detect errors, fix code, and redeploy services without manual intervention.

Even more articles →