Kubernetes learning roadmap

This track is organized so you can build confidence in the right order: start with container and cluster basics, move through workloads and networking, then learn security, packaging, operations, and managed Kubernetes on AWS and Google Cloud.

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Kubernetes learning roadmap

This track is organized so you can build confidence in the right order: start with container and cluster basics, move through workloads and networking, then learn security, packaging, operations, and managed Kubernetes on AWS and Google Cloud.

Phase 1: Containers, cluster basics, and architecture

  • Start with Docker basics so Kubernetes manifests make sense in terms of images, containers, networking, and runtime behavior.
  • Start with what Kubernetes solves and how the cluster is structured.
  • Learn the control plane, worker nodes, the API server, scheduler, kubelet, kube-proxy, and etcd.
  • Learn namespaces, node selection, taints and tolerations, and pod affinity so scheduling decisions feel concrete.
  • Use the architecture diagram to connect concepts before moving into manifests.

Phase 2: Pods, deployments, and day-one workloads

  • Learn what a pod is and how Kubernetes runs one or more containers together.
  • Review readiness and liveness probes so you can model healthy application behavior.
  • Study deployments, rollout behavior, and practical workload manifests before moving into more advanced controllers.

Phase 3: Services, ingress, and cluster networking

  • Understand ClusterIP, NodePort, LoadBalancer, and headless services.
  • Move into ingress and gateway-style routing once service discovery makes sense.
  • Add network policy basics so service exposure and pod-to-pod communication are understood together.
  • Compare application-facing traffic patterns and the YAML used to express them.

Phase 4: Configuration, secrets, and access control

  • Learn ConfigMaps and Secrets so application configuration is separated from container images.
  • Study RBAC basics, roles, and users to understand how Kubernetes controls access to cluster resources.
  • Treat security and configuration as part of application design, not an afterthought.

Phase 5: Storage and stateful systems

  • Learn when ephemeral storage is not enough.
  • Use persistent volumes and claims to connect workloads to durable storage.
  • Continue into StatefulSets for databases such as MySQL and MongoDB.

Phase 6: Packaging, templating, and reuse

  • Learn Helm fundamentals and chart structure so you can package repeatable Kubernetes applications.
  • Compare raw manifests with Helm-based templating for multi-environment deployments.
  • Study Kustomize basics to understand overlays and environment-specific customization without rewriting YAML.

Phase 7: Operations, scaling, and best practices

  • Study rolling updates, horizontal scaling, and cluster autoscaling.
  • Review manifest examples that show how deployments evolve safely in production.
  • Review operational and platform best practices for security, observability, rollout safety, and resource management.
  • Treat the example YAML files as reference material you can adapt to your own cluster.

Phase 8: Managed Kubernetes platforms

  • Finish with AWS EKS so the core Kubernetes concepts map cleanly to a managed control plane.
  • Add Google Kubernetes Engine so you see how cluster provisioning and operations vary across cloud providers.
  • Use the recipes and troubleshooting examples as a bridge from theory to platform-specific practice.

How to use this track

  • Read section overview lessons before opening raw YAML manifests.
  • Use manifest lessons as working examples, not just reading material.
  • Add future topics by dropping new markdown or YAML files into the relevant section folder and updating this roadmap so the learning order stays intentional.