Decouple Deployment from Release

Feature flags separate code deployment from feature release. Deploy code to production with the feature disabled, then enable it gradually — first for internal users, then a small percentage of users, then everyone. If problems arise, disable the flag instantly without rolling back code. At Nexis Limited, feature flags are a standard practice across all products, enabling safe and fast feature delivery.

Types of Feature Flags

Release Flags

Control the rollout of new features. Enable for internal testing, beta users, and then gradually for all users. Remove the flag once the feature is fully rolled out and stable. These are temporary by design.

Experiment Flags

Enable A/B testing by routing different user segments to different feature variants. Measure the impact of each variant on key metrics (conversion, engagement, retention) and roll out the winning variant. Remove after the experiment concludes.

Operational Flags

Control system behavior — enable maintenance mode, toggle between service providers, or disable resource-intensive features during high load. These may be long-lived.

Permission Flags

Control access to premium features based on subscription tier or user role. These are long-lived and often replace traditional role-based feature gating.

Progressive Rollout Strategies

  1. Internal users: Enable for the development team first. Catch obvious issues.
  2. Beta users: Enable for users who have opted into beta testing. Catch usability issues.
  3. Percentage rollout (1% → 5% → 25% → 50% → 100%): Gradually increase exposure, monitoring metrics at each stage.
  4. Geographic rollout: Enable in one region first, then expand globally.

Implementation Patterns

Client-Side Flags

Flag evaluation happens in the browser or mobile app. Suitable for UI changes, layout variations, and client-side feature toggling. Requires the flag configuration to be available on the client — use a feature flag SDK that handles caching and real-time updates.

Server-Side Flags

Flag evaluation happens on the server. Required for backend logic changes, API behavior changes, and security-sensitive features. The client never sees disabled features.

Flag Evaluation

Feature flag services (LaunchDarkly, Unleash, Flagsmith) provide SDKs that evaluate flags based on user context (user ID, email, subscription tier, geography). Evaluation should be fast (under 1ms) and cached locally to avoid network latency on every flag check.

Operational Best Practices

  • Clean up stale flags: Temporary flags (release, experiment) should be removed after rollout. Stale flags accumulate as technical debt.
  • Monitor flag impact: Track key metrics before and after flag changes to detect regressions.
  • Document flags: Each flag should have an owner, creation date, purpose, and expected retirement date.
  • Test both states: Integration tests should cover both flag-on and flag-off code paths.
  • Limit active flags: Too many active flags create combinatorial complexity. Aim for fewer than 20 active flags at any time.

Conclusion

Feature flags are one of the most impactful practices for shipping software safely. They decouple deployment from release, enable progressive rollouts, and provide instant rollback capability. Implement them thoughtfully, clean up stale flags regularly, and monitor the impact of every flag change.

Improving your deployment practices? Our team implements feature flag systems and progressive rollout strategies.