Deployment Strategies

Deployment Strategies

Purpose

Master production deployment strategies:

• Zero-downtime deployments
• Risk mitigation
• Rollback procedures
• Progressive delivery
• Infrastructure patterns

When to Use

Invoke this skill when:

• Planning production deployments
• Designing deployment pipelines
• Troubleshooting failed deploys
• Implementing new deployment strategy
• Reducing deployment risk

Deployment Strategies

1. Blue-Green Deployment

Concept: Two identical environments (Blue=current, Green=new)

┌─────────────┐
│  Load       │
│  Balancer   │
└──────┬──────┘
       │
       ├─────────────┐
       │             │
  ┌────▼───┐    ┌───▼────┐
  │ Blue   │    │ Green  │
  │ (v1.0) │    │ (v2.0) │
  │ LIVE   │    │ IDLE   │
  └────────┘    └────────┘

After testing Green:
Switch traffic → Green becomes LIVE

If issues:
Switch back → Instant rollback

Implementation:

// Example using AWS ELB
async function blueGreenDeploy(version: string): Promise<void> {
  // 1. Deploy to green environment
  await deployToEnvironment('green', version);

  // 2. Run smoke tests on green
  const testsPass = await runSmokeTests('green');
  if (!testsPass) {
    throw new Error('Green environment failed tests');
  }

  // 3. Gradually shift traffic
  await shiftTraffic('blue', 'green', {
    steps: [10, 25, 50, 100],
    intervalMinutes: 5,
  });

  // 4. Monitor for errors
  const errors = await monitorErrors('green', { duration: '10m' });
  if (errors > THRESHOLD) {
    await rollback('blue');
    throw new Error('Rollback triggered due to errors');
  }

  // 5. Decommission blue
  await decommission('blue');
}

Pros: ✅ Instant rollback, ✅ Zero downtime, ✅ Full testing before switch Cons: ❌ 2x infrastructure cost, ❌ Database migrations tricky

2. Canary Deployment

Concept: Gradually roll out to small percentage of users

Phase 1: 5% traffic → v2.0
         95% traffic → v1.0

Phase 2: 25% traffic → v2.0
         75% traffic → v1.0

Phase 3: 50% traffic → v2.0
         50% traffic → v1.0

Phase 4: 100% traffic → v2.0

Implementation:

interface CanaryConfig {
  stages: number[];           // [5, 25, 50, 100]
  stageDuration: string;      // '30m'
  successCriteria: {
    errorRate: number;        // <1%
    latencyP95: number;       // <500ms
    cpuUsage: number;         // <70%
  };
}

async function canaryDeploy(version: string, config: CanaryConfig): Promise<void> {
  for (const percentage of config.stages) {
    console.log(`Canary: Routing ${percentage}% to ${version}`);

    await routeTraffic(version, percentage);
    await sleep(config.stageDuration);

    const metrics = await collectMetrics(version, config.stageDuration);

    if (!meetsSuccessCriteria(metrics, config.successCriteria)) {
      await rollback(version);
      throw new Error(`Canary failed at ${percentage}%: ${metrics}`);
    }
  }

  console.log('Canary successful - deployed to 100%');
}

function meetsSuccessCriteria(metrics: Metrics, criteria: SuccessCriteria): boolean {
  return (
    metrics.errorRate < criteria.errorRate &&
    metrics.latencyP95 < criteria.latencyP95 &&
    metrics.cpuUsage < criteria.cpuUsage
  );
}

Pros: ✅ Low risk, ✅ Real user feedback, ✅ Gradual rollout Cons: ❌ Slower deployment, ❌ Complex routing, ❌ Inconsistent UX

3. Rolling Update

Concept: Update instances one-by-one or in batches

Initial State:
[v1.0] [v1.0] [v1.0] [v1.0] [v1.0]

Step 1: Update first instance
[v2.0] [v1.0] [v1.0] [v1.0] [v1.0]

Step 2: Update second instance
[v2.0] [v2.0] [v1.0] [v1.0] [v1.0]

Step 3: Update third instance
[v2.0] [v2.0] [v2.0] [v1.0] [v1.0]

...continue until all updated

Kubernetes Implementation:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
spec:
  replicas: 5
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1        # Max extra pods during update
      maxUnavailable: 1  # Max unavailable pods
  template:
    spec:
      containers:
      - name: app
        image: my-app:2.0
        readinessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 10
          periodSeconds: 5

Pros: ✅ Simple, ✅ No extra infrastructure, ✅ Gradual Cons: ❌ Slow rollback, ❌ Mixed versions during deploy

4. Feature Flags (Dark Launch)

Concept: Deploy code but control feature activation

// Deploy new code but keep feature off
class PaymentService {
  async processPayment(amount: number): Promise<void> {
    if (featureFlags.isEnabled('new-payment-provider')) {
      // New code path
      return this.newPaymentProvider.process(amount);
    } else {
      // Old code path (still running)
      return this.oldPaymentProvider.process(amount);
    }
  }
}

// Gradually enable for users
featureFlags.enableFor('new-payment-provider', {
  percentage: 10,           // 10% of users
  userIds: [123, 456],     // Specific test users
  countries: ['US', 'CA'], // Specific countries
});

Progressive Rollout:

// Week 1: Internal testing
await featureFlags.enable('new-feature', { internal: true });

// Week 2: Beta users
await featureFlags.enable('new-feature', { beta: true });

// Week 3: 5% of production
await featureFlags.enable('new-feature', { percentage: 5 });

// Week 4: 25% of production
await featureFlags.enable('new-feature', { percentage: 25 });

// Week 5: 100%
await featureFlags.enable('new-feature', { percentage: 100 });

// Remove flag after stability
await featureFlags.remove('new-feature');

Pros: ✅ Instant rollback, ✅ A/B testing, ✅ Gradual rollout Cons: ❌ Code complexity, ❌ Technical debt if not cleaned up

5. A/B Testing Deployment

Concept: Run multiple versions for comparison

interface ABTest {
  name: string;
  variants: {
    control: string;    // Current version
    treatment: string;  // New version
  };
  traffic: {
    control: number;    // 50%
    treatment: number;  // 50%
  };
  metrics: string[];    // ['conversion', 'engagement']
  duration: string;     // '7days'
}

async function deployABTest(test: ABTest): Promise<void> {
  // Deploy both versions
  await deploy(test.variants.control);
  await deploy(test.variants.treatment);

  // Route traffic
  await routeTraffic({
    [test.variants.control]: test.traffic.control,
    [test.variants.treatment]: test.traffic.treatment,
  });

  // Collect data
  const results = await collectMetrics(test.metrics, test.duration);

  // Analyze and decide winner
  const winner = analyzeResults(results);
  console.log(`Winner: ${winner}`);

  // Deploy winner to 100%
  await deploy(winner, { percentage: 100 });
}

Zero-Downtime Patterns

Health Checks

// Readiness check (ready to receive traffic?)
app.get('/health/ready', (req, res) => {
  const checks = [
    database.isConnected(),
    cache.isConnected(),
    // Other dependencies
  ];

  const ready = checks.every(check => check);
  res.status(ready ? 200 : 503).json({ ready, checks });
});

// Liveness check (is app alive?)
app.get('/health/live', (req, res) => {
  res.status(200).json({ alive: true });
});

Graceful Shutdown

let isShuttingDown = false;

// Stop accepting new requests
process.on('SIGTERM', async () => {
  console.log('SIGTERM received, starting graceful shutdown');
  isShuttingDown = true;

  // Stop accepting new connections
  server.close(() => {
    console.log('Server closed, no new connections');
  });

  // Wait for existing requests to complete (with timeout)
  await waitForCompletion({ timeout: 30000 });

  // Close database connections
  await database.close();

  // Exit
  process.exit(0);
});

// Reject new requests during shutdown
app.use((req, res, next) => {
  if (isShuttingDown) {
    res.status(503).send('Server is shutting down');
  } else {
    next();
  }
});

Database Migrations

Backward-Compatible Pattern:

Phase 1: Add new column (nullable)
Phase 2: Deploy code that writes to both old and new
Phase 3: Backfill data
Phase 4: Deploy code that reads from new
Phase 5: Remove old column

Never do destructive changes in same deploy as code!

Rollback Strategies

Automatic Rollback Triggers

interface RollbackCriteria {
  errorRate: number;        // >5% errors
  latency: number;          // >2000ms p95
  availability: number;     // <99%
  customMetric?: () => boolean;
}

async function deployWithAutoRollback(
  version: string,
  criteria: RollbackCriteria
): Promise<void> {
  const previousVersion = await getCurrentVersion();

  try {
    await deploy(version);

    // Monitor for 10 minutes
    const metrics = await monitorDeployment(version, '10m');

    if (shouldRollback(metrics, criteria)) {
      throw new Error('Metrics exceeded thresholds');
    }
  } catch (error) {
    console.error('Deployment failed, rolling back:', error);
    await deploy(previousVersion);
    throw error;
  }
}

function shouldRollback(metrics: Metrics, criteria: RollbackCriteria): boolean {
  return (
    metrics.errorRate > criteria.errorRate ||
    metrics.latencyP95 > criteria.latency ||
    metrics.availability < criteria.availability ||
    criteria.customMetric?.()
  );
}

Deployment Checklist

Pre-Deployment

- [ ] Code reviewed and approved
- [ ] Tests passing (unit, integration, E2E)
- [ ] Database migrations tested
- [ ] Rollback plan documented
- [ ] Stakeholders notified
- [ ] Feature flags configured
- [ ] Monitoring/alerts set up
- [ ] Load testing completed (if major change)
- [ ] Security scan passed
- [ ] Deployment window scheduled

During Deployment

- [ ] Announcement sent to team
- [ ] Deployment started (timestamp)
- [ ] Health checks passing
- [ ] Metrics monitored
- [ ] Error rates normal
- [ ] Logs reviewed
- [ ] User reports monitored
- [ ] No rollback needed

Post-Deployment

- [ ] Smoke tests passed
- [ ] Metrics stable for 30 minutes
- [ ] No unusual errors
- [ ] Performance acceptable
- [ ] Documentation updated
- [ ] Deployment announcement (success)
- [ ] Post-mortem (if issues)
- [ ] Remove old infrastructure (if blue-green)

Related Skills

• incident-response: For handling deployment issues
• monitoring-setup: For deployment metrics
• database-migrations: For schema changes
• feature-flags: For progressive rollout

Converted and distributed by TomeVault — claim your Tome and manage your conversions.