Kubernetes Deployment

Kubernetes Deployment Patterns

When to Use This Skill

• Deploying applications to Kubernetes
• Implementing microservices on k8s
• Setting up autoscaling and load balancing
• Managing Kubernetes configurations
• Production k8s best practices

Target Agents

• devops-engineer - Primary user
• cloud-architect - K8s architecture
• backend-developer - Application deployment

Core Patterns

1. Deployment Configuration

apiVersion: apps/v1
kind: Deployment
metadata:
  name: web-app
  labels:
    app: web-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: web-app
  template:
    metadata:
      labels:
        app: web-app
    spec:
      containers:
      - name: web-app
        image: myregistry.com/web-app:v1.0.0
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "256Mi"
            cpu: "250m"
          limits:
            memory: "512Mi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 5
        env:
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef:
              name: app-secrets
              key: database-url

2. Service Configuration

apiVersion: v1
kind: Service
metadata:
  name: web-app-service
spec:
  selector:
    app: web-app
  ports:
  - protocol: TCP
    port: 80
    targetPort: 8080
  type: LoadBalancer
---
apiVersion: v1
kind: Service
metadata:
  name: web-app-internal
spec:
  selector:
    app: web-app
  ports:
  - protocol: TCP
    port: 8080
  type: ClusterIP

3. Horizontal Pod Autoscaler

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: web-app-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: web-app
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80

4. ConfigMap and Secrets

apiVersion: v1
kind: ConfigMap
metadata:
  name: app-config
data:
  app.properties: |
    server.port=8080
    logging.level=INFO
---
apiVersion: v1
kind: Secret
metadata:
  name: app-secrets
type: Opaque
data:
  database-url: <base64-encoded-value>
  api-key: <base64-encoded-value>

5. Ingress Configuration

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: web-app-ingress
  annotations:
    kubernetes.io/ingress.class: nginx
    cert-manager.io/cluster-issuer: letsencrypt-prod
spec:
  tls:
  - hosts:
    - example.com
    secretName: example-com-tls
  rules:
  - host: example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: web-app-service
            port:
              number: 80

Best Practices

1. Use resource limits and requests
2. Implement health checks (liveness/readiness)
3. Use ConfigMaps for configuration
4. Store secrets in Secrets resources
5. Implement HPA for autoscaling
6. Use namespaces for isolation
7. Implement RBAC for security
8. Use StatefulSets for stateful apps
9. Implement PodDisruptionBudgets
10. Monitor with Prometheus/Grafana