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Kubernetes

Kubernetes lets you describe the state your containerized workloads should be in — how many replicas, what image, what storage, what network access — and continuously reconciles the real cluster toward that state, forever, without you running a command every time something drifts. This is a hands-on guide to using it well: understanding the architecture underneath a kubectl apply, writing production-grade workloads, securing and observing a cluster, debugging what breaks, and operating OpenShift where that's the platform in front of you.

It's built to work two ways: read it start to finish as a course, or jump straight to the one page that answers what you need right now.

Start Here, Based on Where You Are

You are... Start at
New to Kubernetes entirely Getting Started
Comfortable with the basics, want the daily-driver objects Core Concepts
Running real workloads, want to tune rollouts and scheduling Workloads & Scheduling
Exposing services, debugging traffic Networking
Working with stateful apps and volumes Storage
Managing app config, Secrets, or packaging with Helm/Kustomize Configuration & Packaging
Locking down a cluster Security
Wiring up probes, logs, and metrics Observability & Health
Running the control plane yourself Cluster Administration
Building a deployment pipeline or adopting GitOps CI/CD & GitOps
Running Kubernetes in production at scale Production Engineering
Working on Red Hat OpenShift specifically OpenShift
Learning by doing, on a local cluster Labs
Wanting full worked examples, failure paths included Case Studies
Something's broken right now Troubleshooting
Prepping for a Kubernetes or DevOps interview Interview Preparation
Already know Kubernetes, need a fast lookup Quick Reference

The Learning Path

flowchart TD
    A[Getting Started] --> B[Core Concepts]
    B --> C[Workloads & Scheduling /\nNetworking / Storage]
    C --> D[Configuration & Packaging /\nSecurity / Observability]
    D --> E[Cluster Administration /\nCI/CD & GitOps]
    E --> F[Production Engineering /\nOpenShift]
    F --> G[Labs & Case Studies]
    G --> H[Interview Preparation]

Learn by Building

Each project uses only what the previous ones already taught you. Skip ahead if you're already past a stage.

  1. Deploy and expose your first app — Your First Deployment
  2. Roll out a change with zero dropped requests — Deployment Strategies, Case Study: Rolling Deployment With Zero Downtime
  3. Route real traffic in with TLS — Ingress and Ingress Controllers
  4. Give a database stable storage — StatefulSets, StatefulSet Storage Patterns
  5. Package it as a Helm chart — Helm Fundamentals and Writing Charts
  6. Isolate a new team in its own namespace — Case Study: Multi-Tenant Namespace Setup
  7. Lock down access with least privilege — RBAC
  8. Scale it automatically under load — Autoscaling, Case Study: Autoscaling Under Load
  9. Adopt GitOps instead of pushing kubectl apply by hand — GitOps With ArgoCD and Flux
  10. Practice debugging a real incident — Case Study: Debugging a CrashLoopBackOff Incident
  11. Run the production readiness checklist against it — Production Readiness Checklist

Every Section

  • Getting Started — history and origins, what Kubernetes actually is, control-plane architecture, installing kubectl, your first deployment
  • Core Concepts — Pods, ReplicaSets and Deployments, Services, namespaces, labels and selectors, Jobs and CronJobs
  • Workloads & Scheduling — deployment strategies, StatefulSets, DaemonSets, affinity and taints, requests/limits, autoscaling
  • Networking — the cluster networking model, Services in depth, Ingress, NetworkPolicy, DNS, CNI plugins
  • Storage — volumes, PersistentVolumes and Claims, StorageClasses and dynamic provisioning, StatefulSet storage
  • Configuration & Packaging — ConfigMaps and Secrets in depth, config injection, Helm, Kustomize, external secret stores
  • Security — authentication and authorization, RBAC, service accounts, Pod Security Admission, supply chain, encryption at rest
  • Observability & Health — probes, logging architecture, metrics-server, events and debugging
  • Cluster Administration — kubeadm, etcd, node management, upgrades, backup and restore, multi-tenancy
  • CI/CD & GitOps — pipelines for Kubernetes, kubectl scripting, progressive delivery, ArgoCD and Flux
  • Production Engineering — capacity planning, cost optimization, multi-cluster design, disaster recovery, readiness review
  • OpenShift — what OpenShift adds, the oc CLI and Projects, Routes, Source-to-Image, Operators
  • Labs — minikube, kind, Docker Desktop, Podman, and guided hands-on scenarios
  • Case Studies — full worked deployments, including the failure paths
  • Troubleshooting — a symptom-first debugging methodology, not just a list of errors
  • Interview Preparation — by subject and by level, tied back to the concepts
  • Quick Reference — cheat sheets, no prose

Further Reading