1. Write Dockerfile
2. Build and test locally
3. Push to registry
4. Update K8s manifests
5. Apply to cluster
6. Verify deployment
7. Monitor logs/metrics

1. Create feature branch
2. Write Terraform code
3. Run `terraform plan`
4. Review plan output
5. Create PR
6. Apply after approval
7. Verify resources

# GitHub Actions example
name: Deploy
on:
  push:
    branches: [main]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Build and push
        run: |
          docker build -t app:${{ github.sha }} .
          docker push registry/app:${{ github.sha }}

  deploy:
    needs: build
    runs-on: ubuntu-latest
    steps:
      - name: Deploy to K8s
        run: |
          kubectl set image deployment/app \
            app=registry/app:${{ github.sha }}

# Build image
docker build -t app:latest .

# Run container
docker run -d -p 8080:80 app:latest

# View logs
docker logs -f container_id

# Compose up
docker compose up -d

# Clean up
docker system prune -af

# Apply manifests
kubectl apply -f deployment.yaml

# Get resources
kubectl get pods,svc,deploy

# View logs
kubectl logs -f pod/app-xxx

# Port forward
kubectl port-forward svc/app 8080:80

# Scale
kubectl scale deploy/app --replicas=3

# Initialize
terraform init

# Plan
terraform plan -out=tfplan

# Apply
terraform apply tfplan

# Destroy
terraform destroy

# State list
terraform state list

# Configure
aws configure

# S3
aws s3 sync ./dist s3://bucket/

# ECR login
aws ecr get-login-password | docker login --username AWS --password-stdin xxx.ecr.region.amazonaws.com

# Lambda invoke
aws lambda invoke --function-name func output.json

# Prometheus alert example
groups:
  - name: app
    rules:
      - alert: HighErrorRate
        expr: |
          rate(http_requests_total{status=~"5.."}[5m])
          / rate(http_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: High error rate detected