Progressive Delivery: Scenario-Based Questions

Progressive rollouts gradually expose new features to increasing segments of users, allowing early detection of bugs, performance issues, or unintended behaviors. Feature flag platforms offer fine-grained control over rollouts.

🚀 What Is Progressive Delivery?

• Gradually increase traffic to new code paths via feature flags.
• Monitor metrics and error rates before full rollout.
• Roll back or pause immediately if degradation is detected.

⚙️ Implementation Steps

• Integrate a feature flag SDK (e.g., LaunchDarkly, Unleash, Flipt, Split.io) into your codebase.
• Wrap new functionality with conditional checks:

  
  if (featureFlags.newBilling) {
    enableNewBillingFlow();
  } else {
    useLegacyFlow();
  }
              

• Create rollout rules by user ID, region, team, or random cohort (e.g., 5% traffic initially).

📊 Monitoring & Safety Nets

• Define alerting thresholds (e.g., error rates, latency, drop-off).
• Instrument flags with metrics and observability tags.
• Correlate flag toggles with dashboards and logs for traceability.
• Use kill switches to instantly disable features in case of incident.

✅ Best Practices

• Tag flags with owner, expiration, environment scope, and type (release/test/ops).
• Document rollout plans and approval gates for staged traffic increases.
• Clean up stale flags regularly — maintain flag hygiene.

🚫 Common Pitfalls

• Forgetting to implement a fallback — user stuck with broken experience.
• Blindly rolling out to 100% without monitoring results at lower stages.
• Embedding flag values in front-end code without access controls.

📌 Real-World Insight

Progressive delivery enables confident, reversible, and low-risk deployments. Teams that combine feature flags with observability and ownership scale faster without compromising stability.