Docker & Kubernetes

Understand processes, namespaces, cgroups, and how Linux isolates workloads — the building blocks containers rely on.

Learn what containers are, how they differ from VMs, and why they became the standard unit of deployment.

Understand how images are built from layers, how layer caching works, and what a container registry stores.

You understand the theory behind containers and can explain how they work at the OS level.

Learn Dockerfile syntax, instruction ordering for cache efficiency, and best practices for small, secure images.

Master docker build, run, exec, logs, stop, and rm — the day-to-day commands for working with containers.

Persist data outside the container filesystem using volumes and bind mounts for development and production.

Understand bridge, host, and overlay networks and how containers communicate with each other and the outside world.

Use multi-stage Dockerfiles to separate build-time dependencies from runtime, producing minimal production images.

Define and run multi-container applications with a single YAML file, managing services, networks, and volumes together.

Scan images for vulnerabilities, use minimal base images, and follow least-privilege principles in containers.

You can containerize any application, compose multi-service stacks, and follow production best practices.

Understand the problems that arise when running containers at scale — scheduling, healing, scaling, and service discovery.

Learn the control plane components (API server, etcd, scheduler, controller manager) and node components (kubelet, kube-proxy).

Explore Docker's built-in orchestrator as a simpler alternative to Kubernetes for smaller deployments.

You understand why orchestrators exist and how Kubernetes is architected.

Understand the Pod as the smallest deployable unit — why it exists, multi-container patterns, and pod lifecycle.

Manage stateless applications declaratively with rolling updates, rollbacks, and desired-state reconciliation.

Expose pods via ClusterIP, NodePort, and LoadBalancer services to enable stable networking within and outside the cluster.

Inject configuration and sensitive data into pods without baking them into images.

Organize cluster resources with namespaces and control access with role-based authorization.

Become fluent with kubectl for inspecting, debugging, and managing cluster resources from the command line.

You can deploy, expose, configure, and manage stateless workloads on a Kubernetes cluster.

Route external HTTP/HTTPS traffic to services using rules, TLS termination, and path-based routing.

Provision and attach durable storage to pods using PVs, PVCs, and StorageClasses.

Run stateful workloads (databases, message queues) with stable network identities and ordered deployment.

Define firewall rules at the pod level to control ingress and egress traffic within the cluster.

You can handle ingress routing, persistent storage, and stateful workloads in Kubernetes.

Package, version, and deploy complex applications using Helm templates and values files.

Automatically scale workloads based on CPU, memory, or custom metrics to handle variable load.

Run one-off and scheduled batch workloads with completion guarantees and retry policies.

Set up Prometheus metrics, Grafana dashboards, and log aggregation to observe cluster and application health.

Integrate container builds and Kubernetes deployments into automated pipelines using GitOps or push-based strategies.

Add observability, traffic management, and mutual TLS between services without changing application code.

You can operate production-grade Kubernetes with scaling, monitoring, packaging, and CI/CD.