Kubernetes for Developers: The Concepts You Must Know to Deploy and Debug in K8s

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-api
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-api
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxUnavailable: 1   # At most 1 pod down during update
      maxSurge: 1         # At most 1 extra pod during update
  template:
    metadata:
      labels:
        app: my-api
    spec:
      containers:
        - name: api
          image: my-registry/my-api:v1.2.3  # Always pin exact version
          ports:
            - containerPort: 3000
          env:
            - name: NODE_ENV
              value: production
            - name: DATABASE_URL
              valueFrom:
                secretKeyRef:       # From Secret, not hardcoded
                  name: db-secret
                  key: url
          resources:
            requests:               # Minimum guaranteed
              cpu: "100m"           # 0.1 CPU core
              memory: "128Mi"
            limits:                 # Maximum allowed
              cpu: "500m"           # 0.5 CPU core
              memory: "512Mi"       # Pod killed if exceeded!
          livenessProbe:            # Restart if unhealthy
            httpGet:
              path: /health
              port: 3000
            initialDelaySeconds: 15
            periodSeconds: 20
          readinessProbe:           # Remove from load balancer if not ready
            httpGet:
              path: /ready
              port: 3000
            initialDelaySeconds: 5
            periodSeconds: 10

# The debugging workflow for any K8s issue

# Step 1: What's wrong?
kubectl get pods                                # List pods and their status
kubectl get pods -l app=my-api                  # Filter by label

# Step 2: Why is it failing?
kubectl describe pod my-api-abc123             # Events, conditions, resource issues
# Look for:
# - "OOMKilled" = pod exceeded memory limit
# - "CrashLoopBackOff" = container keeps crashing
# - "ImagePullBackOff" = can't pull image
# - "Pending" = no node has enough resources

# Step 3: What did the app log?
kubectl logs my-api-abc123                     # Current container logs
kubectl logs my-api-abc123 --previous         # Previous container logs (after crash)
kubectl logs -l app=my-api --since=1h         # All pods, last 1 hour
kubectl logs -f my-api-abc123                 # Follow live

# Step 4: Get a shell in the container
kubectl exec -it my-api-abc123 -- /bin/sh    # Interactive shell
kubectl exec my-api-abc123 -- env            # Check environment variables
kubectl exec my-api-abc123 -- curl localhost:3000/health  # Test endpoint from inside

# Step 5: Check resource usage
kubectl top pods                              # CPU and memory per pod
kubectl top nodes                            # Node resource usage

---
apiVersion: v1
kind: Service
metadata:
  name: my-api-svc
spec:
  selector:
    app: my-api           # Routes to pods with this label
  ports:
    - port: 80            # Service port
      targetPort: 3000    # Container port
  type: ClusterIP         # Internal only (use LoadBalancer for external)

---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: my-api-ingress
  annotations:
    nginx.ingress.kubernetes.io/rate-limit: "100"
spec:
  rules:
    - host: api.myapp.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: my-api-svc
                port:
                  number: 80