shift-right-testing

When to Use

• Progressive feature rollouts
• Production reliability validation
• Performance monitoring at scale
• Learning from real user behavior

Shift-Right Techniques

| Technique | Purpose | When |

|-----------|---------|------|

| Feature Flags | Controlled rollout | Every feature |

| Canary | Compare new vs old | Every deployment |

| Synthetic Monitoring | Proactive detection | 24/7 |

| RUM | Real user metrics | Always on |

| Chaos Engineering | Resilience validation | Regularly |

| A/B Testing | User behavior validation | Feature decisions |

Progressive Rollout Pattern

```

1% → 10% → 25% → 50% → 100%

↓ ↓ ↓ ↓

Check Check Check Monitor

```

Key Metrics to Monitor

| Metric | SLO Target | Alert Threshold |

|--------|------------|-----------------|

| Error rate | < 0.1% | > 1% |

| p95 latency | < 200ms | > 500ms |

| Availability | 99.9% | < 99.5% |

| Apdex | > 0.95 | < 0.8 |

---

```javascript

// Progressive rollout with LaunchDarkly/Unleash pattern

const newCheckout = featureFlags.isEnabled('new-checkout', {

userId: user.id,

percentage: 10, // 10% of users

allowlist: ['beta-testers']

});

if (newCheckout) {

return ;

} else {

return ;

}

// Instant rollback on issues

await featureFlags.disable('new-checkout');

```

---

```yaml

# Flagger canary config

apiVersion: flagger.app/v1beta1

kind: Canary

spec:

targetRef:

apiVersion: apps/v1

kind: Deployment

name: checkout-service

progressDeadlineSeconds: 60

analysis:

interval: 1m

threshold: 5 # Max failed checks

maxWeight: 50 # Max traffic to canary

stepWeight: 10 # Increment per interval

metrics:

- name: request-success-rate

threshold: 99

- name: request-duration

threshold: 500

```

---

```javascript

// Continuous production validation

await Task("Synthetic Tests", {

endpoints: [

{ path: '/health', expected: 200, interval: '30s' },

{ path: '/api/products', expected: 200, interval: '1m' },

{ path: '/checkout', flow: 'full-purchase', interval: '5m' }

],

locations: ['us-east', 'eu-west', 'ap-south'],

alertOn: {

statusCode: '!= 200',

latency: '> 500ms',

contentMismatch: true

}

}, "qe-production-intelligence");

```

---

```typescript

// Controlled failure injection

await Task("Chaos Experiment", {

hypothesis: 'System handles database latency gracefully',

steadyState: {

metric: 'error_rate',

expected: '< 0.1%'

},

experiment: {

type: 'network-latency',

target: 'database',

delay: '500ms',

duration: '5m'

},

rollback: {

automatic: true,

trigger: 'error_rate > 5%'

}

}, "qe-chaos-engineer");

```

---

```typescript

// Convert production incidents to regression tests

await Task("Incident Replay", {

incident: {

id: 'INC-2024-001',

type: 'performance-degradation',

conditions: { concurrent_users: 500, cart_items: 10 }

},

generateTests: true,

addToRegression: true

}, "qe-production-intelligence");

// Output: New test added to prevent recurrence

```

---

Memory Namespace

```

aqe/shift-right/

├── canary-results/* - Canary deployment metrics

├── synthetic-tests/* - Monitoring configurations

├── chaos-experiments/* - Experiment results

├── production-insights/* - Issues → test conversions

└── rum-analysis/* - Real user data patterns

```

Fleet Coordination

```typescript

const shiftRightFleet = await FleetManager.coordinate({

strategy: 'shift-right-testing',

agents: [

'qe-production-intelligence', // RUM, incident replay

'qe-chaos-engineer', // Resilience testing

'qe-performance-tester', // Synthetic monitoring

'qe-quality-analyzer' // Metrics analysis

],

topology: 'mesh'

});

```

---

• [shift-left-testing](../shift-left-testing/) - Pre-production testing
• [chaos-engineering-resilience](../chaos-engineering-resilience/) - Failure injection deep dive
• [performance-testing](../performance-testing/) - Load testing
• [agentic-quality-engineering](../agentic-quality-engineering/) - Agent coordination

---

Production is the ultimate test environment. Feature flags enable instant rollback. Canary catches issues before 100% rollout. Synthetic monitoring detects problems before users. Chaos engineering builds resilience. RUM shows real user experience.

With Agents: Agents monitor production, replay incidents as tests, run chaos experiments, and convert production insights to pre-production tests. Use agents to maintain continuous production quality.