Deployment Patterns Skill

Deployment Patterns

Production deployment workflows and CI/CD best practices.

When to Activate

Setting up CI/CD pipelines
Planning deployment strategy
Implementing health checks and readiness probes
Preparing for a production release
Configuring environment-specific settings

Deployment Strategies

Rolling (Default)

Replace instances gradually. Old and new run simultaneously.

Use when: Standard deployments, backward-compatible changes
Requires: Backward-compatible changes

Blue-Green

Two identical environments. Switch traffic atomically.

Use when: Critical services, zero-tolerance for issues
Benefit: Instant rollback (switch back)

Canary

Route small % of traffic to new version first.

Use when: High-traffic services, risky changes
Pattern: 5% → 50% → 100%

CI/CD Pipeline

# .github/workflows/ci.yml
name: CI/CD
on:
  push: { branches: [main] }
  pull_request: { branches: [main] }

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Setup language runtime
        # Use appropriate setup action for your language
      - name: Install dependencies
        run: <install-command>
      - name: Lint
        run: <lint-command>
      - name: Type check
        run: <typecheck-command>
      - name: Test with coverage
        run: <test-command>

  build:
    needs: test
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: docker/build-push-action@v5
        with:
          push: true
          tags: ghcr.io/${{ github.repository }}:${{ github.sha }}

  deploy:
    needs: build
    if: github.ref == 'refs/heads/main'
    environment: production
    runs-on: ubuntu-latest
    steps:
      - name: Deploy
        run: echo "Deploying ${{ github.sha }}"

Pipeline Stages

PR:   lint → type check → unit tests → integration tests → preview deploy
Main: lint → type check → tests → build image → staging → smoke tests → production

Health Checks

# Simple health endpoint
GET /health → { "status": "ok" }

# Detailed health (internal monitoring)
GET /health/detailed →
{
  "status": "ok" | "degraded",
  "version": "<app-version>",
  "uptime": <seconds>,
  "checks": {
    "database": { "status": "ok", "latency_ms": 2 },
    "cache":    { "status": "ok", "latency_ms": 1 }
  }
}
# Return 200 if healthy, 503 if degraded

Environment Configuration

# Validate all required config at startup — fail fast
# Use your language's validation library (Pydantic, Zod, viper, etc.)

Required variables:
  APP_ENV:      "development" | "staging" | "production"
  PORT:         integer, default 8080
  DATABASE_URL: valid connection string
  JWT_SECRET:   string, minimum 32 characters

Rules:

Validate at startup, crash immediately if invalid
Never hardcode secrets — use environment variables or secret managers
Different configs per environment (dev/staging/prod)

Rollback Strategy

kubectl rollout undo deployment/app      # Kubernetes
# Or redeploy the previous container image tag

Rules:

Always tag releases with git SHA or semantic version
Keep previous 3 versions deployable
Test rollback procedure before you need it

Production Readiness Checklist

Application

[ ] All tests pass (unit, integration, E2E)
[ ] No hardcoded secrets
[ ] Error handling covers edge cases
[ ] Structured logging (no PII)
[ ] Health check endpoint works

Infrastructure

[ ] Docker image reproducible (pinned versions)
[ ] Environment variables documented and validated
[ ] Resource limits set (CPU, memory)
[ ] SSL/TLS on all endpoints

Monitoring

[ ] Application metrics exported
[ ] Alerts for error rate spikes
[ ] Log aggregation set up
[ ] Uptime monitoring on health endpoint

Security

[ ] Dependencies scanned for CVEs
[ ] CORS configured restrictively
[ ] Rate limiting on public endpoints
[ ] Auth/authz verified
[ ] Security headers set

Operations

[ ] Rollback plan tested
[ ] Database migration tested against prod data
[ ] Runbook for common failures
[ ] On-call rotation defined

Agent Skills: Deployment Patterns

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