Intro

# ===== The model =====
# You describe DESIRED state in YAML (Deployment, Service, etc).
# The control plane reconciles ACTUAL state to match.
# Pod dies -> controller replaces. Node dies -> pods reschedule.

# ===== Core objects =====
# Pod            smallest deployable unit (usually one container)
# Deployment     manages identical Pods (replicas, rolling updates)
# Service        stable network endpoint in front of pods
# Ingress        HTTP/HTTPS routing into the cluster
# ConfigMap      non-secret config
# Secret         sensitive config
# Namespace      logical grouping
# Job / CronJob  one-shot / scheduled tasks
# StatefulSet    pods with stable identity + persistent volumes
# DaemonSet      one pod per node (log shippers, agents)

# ===== Tiny example =====
apiVersion: apps/v1
kind: Deployment
metadata: { name: shop }
spec:
  replicas: 3
  selector: { matchLabels: { app: shop } }
  template:
    metadata: { labels: { app: shop } }
    spec:
      containers:
        - name: shop
          image: ghcr.io/me/shop:v1
          ports: [{ containerPort: 3000 }]
          readinessProbe: { httpGet: { path: /healthz, port: 3000 } }
---
apiVersion: v1
kind: Service
metadata: { name: shop }
spec:
  selector: { app: shop }
  ports: [{ port: 80, targetPort: 3000 }]

# Apply:
kubectl apply -f shop.yaml
kubectl get pods,svc -l app=shop

# ===== Daily commands =====
kubectl get pods -A
kubectl logs -f <pod>
kubectl describe pod <pod>
kubectl exec -it <pod> -- sh
kubectl rollout status deploy/shop
kubectl port-forward svc/shop 8080:80

# ===== Where K8s lives =====
# Managed:    EKS (AWS), GKE (Google), AKS (Azure), DOKS, Linode LKE
# Self-host:  kubeadm, kops, k3s, rke2
# Local dev:  kind, k3d, minikube, Docker Desktop

# ===== When K8s wins =====
# - 5+ services that need to talk
# - Multi-team or multi-tenant platforms
# - Rolling deploys + autoscaling + self-healing
# - Hybrid / multi-cloud portability

# ===== When K8s hurts =====
# - One container, one box, one user (use a PaaS)
# - Tiny team without ops capacity
# - GPU / specialised hardware (manageable but extra)

# ===== Patterns to internalise =====
# - Declarative everything; YAML in git; apply via CI
# - Probes (liveness, readiness, startup) on every container
# - Requests + limits on every container
# - Namespaces per environment; RBAC by namespace

# ===== Pitfalls =====
# - 'latest' image tags -> non-deterministic deploys
# - No resource limits -> noisy neighbour crashes others
# - Secrets in plain ConfigMaps
# - kubectl apply by hand on prod -> drift from git source of truth

# Kubernetes (K8s) orchestrates containers.
# Schedules, scales, heals, networks them.