Orchestrate containerised workloads at scale: Kubernetes architecture, imperative vs declarative workflows, Pods, Deployments, and Services.
Introduction to Kubernetes
What Kubernetes is, where it came from, who uses it, and how to spin up a local cluster and start using kubectl.
Why Kubernetes?
The production problems that Docker alone can't solve — scaling, crashes, server failures, deployments — and how Kubernetes solves each one.
Container Orchestration
How deployment evolved from bare servers to VMs to containers, and why managing containers at scale demands an orchestrator.
Kubernetes Architecture
The anatomy of a Kubernetes cluster — control plane, worker nodes, and how a kubectl command becomes a running Pod.
Kubernetes Components
What each control plane and node component actually does — API Server, etcd, Scheduler, Controller Manager, kubelet, kube-proxy, and the container runtime.
Imperative vs Declarative
Compare imperative kubectl commands with declarative YAML manifests and understand why production workflows standardize on the latter.
Pod YAML
Understand why Kubernetes wraps containers in Pods, then build a Pod manifest field by field and manage its full lifecycle with kubectl.
Labels & Selectors
Tag Kubernetes objects with labels and query them with selectors — the mechanism that wires Deployments, ReplicaSets, and Services together.
ReplicaSet
Keep a fixed number of identical Pods running at all times with ReplicaSets and the desired-state reconciliation loop.
Deployment
Manage applications with Deployments — rolling updates, rollbacks, scaling, health checks, and configuration with ConfigMaps and Secrets.
Service
Give a set of pods one stable IP and DNS name with a Kubernetes Service, and understand how selectors, endpoints, and load balancing work.
Types of Service
Compare the four Kubernetes Service types — ClusterIP, NodePort, LoadBalancer, and ExternalName — and learn when to use each, from local Kind clusters to production architectures.