Learn from production

• We’re a 3-person tech team running production Kubernetes — So we built an AI SRE

  Leo Blondel

  This case study shows how a 3-person team built a Claude-based AI SRE that triages SigNoz alerts, checks Kubernetes, GitLab, logs, traces, and Slack, then ignores noise, escalates, or runs safe fixes.

• How We Set Up One Private Container Registry for 6 AKS Clusters Across 3 Regions and What Broke Along the Way

  Alex

  This case study explains how one private container registry was shared across six AKS clusters in three regions.

  It covers ACR geo-replication, image pull reliability, network access, permissions, and operational breakages.

• Our Kubernetes operator didn't scale, so we rebuilt it

  Infisical's case study explains why its Kubernetes operator hit memory and authentication scaling limits and how a reference-based CRD design fixed secret sync.

• 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.

More case studies →

Matching jobs

1. • DevOps Engineer with Mark43

   • Salary: $155K to $170K a year

   • Location: remote from

   • Tech stack: Kubernetes, Docker, Terraform

2. • DevOps Engineer with RobCo

   • Salary: US$70.74K to US$440K a year

   • Location: based in the office in Munich, DE

   • Tech stack: Kubernetes, AWS, Go, Python, Terraform, Datadog, Grafana, Prometheus

3. • Site Reliability Engineer with MyFitnessPal

   • Salary: $120K to $165K a year

   • Location: remote from

   • Tech stack: Kubernetes, AWS, Docker, Go, Python, Typescript, Terraform, GitHub Actions, Datadog

4. • AI Enterprise Technical Program Manager with Redhorse Corporation

   • Salary: $37 to $485.65K a year

   • Location: based in the office in Arlington, VA, USA

   • Tech stack: Kubernetes, AWS, Azure, Docker, Spark

5. • Commercial Account Executive with Vantage

   • Salary: $100K to $200K a year

   • Location: remote from

   • Tech stack: Kubernetes, AWS, CircleCI, Datadog

Discover more Kubernetes jobs on Kube Careers →

Build something

• Docker Image Signing and Verification

  Lakhan Solanki

  This tutorial explains how to sign and verify Docker images in Amazon ECR using Cosign and AWS KMS.

  It also shows how trusted image enforcement can fit into EKS and Kyverno-based supply chain security.

• Multi-Agent A2A with the Agent Development Kit(ADK), Amazon EKS, and Gemini CLI

  xbill

  This tutorial shows how to deploy a 5-agent ADK system on Amazon EKS and test Agent-to-Agent workflows with Gemini CLI.

• Health Checks in ASP.NET Core: Beyond the Basic /health Endpoint

  Adrián Bailador

  This tutorial shows how to design ASP.NET Core health checks for Kubernetes using separate liveness, readiness, and startup probes.

• Deploy production generative AI at the edge using Amazon EKS Hybrid Nodes with NVIDIA DGX

  Sheng Chen is a Sr. Specialist Solutions Architect at AWS Australia, bringing over 20 years of experience in IT infrastructure, cloud architecture, and multi-cloud networking. In his current role, Sheng helps customers accelerate cloud migrations and infrastructure modernization by leveraging cloud-native technologies. He specializes in Amazon EKS, AWS hybrid cloud services, platform engineering and AI infrastructure.

  This tutorial shows how to run production generative AI at the edge by attaching on-prem NVIDIA DGX systems to an Amazon EKS control plane with hybrid nodes, GPU Operator, and NVIDIA NIM.

More tutorials →

More articles

• We Blamed CoreDNS for Weeks. The Real Culprit Was a Default We Never Questioned

  Akash Warkhade

  This article explains how Kubernetes pod DNS failures can come from the default ndots:5 setting and a Linux conntrack issue, and shows how ndots:2 plus single-request-reopen can reduce DNS noise and fix intermittent resolution errors.

• Building an ML Platform on Kubernetes: What Nobody Tells You About Running GPU Workloads in Production

  Sri Ramanjaneyulu Lingala

  This article explains how to build an ML platform on AKS with GPU node pools, Argo Workflows, MLflow, KServe, GitOps, security controls, and practical lessons around GPU cost, scheduling, and serving.

• Building an AI Agent That Runs Your SRE Operations — What I Learned, What Works, and How You Can Do It Too

  Ganesh Gurudu

  This article explains how to design an AI agent for SRE operations that reads alerts, logs, Kubernetes data, runbooks, deployments, and observability signals to diagnose incidents and propose safe actions.

• Why your ONNX process holds onto gigabytes of memory after inference and what to do about it

  Rakesh Raushan

  This article explains why ONNX Runtime can keep gigabytes of memory after inference.

  It shows how allocator behavior, session reuse, and runtime tuning affect memory usage, latency, and containerized workloads.

Even more articles →