Feature Flags
A software development technique allowing teams to enable or disable features for specific users without deploying new code, used for gradual rollouts and A/B testing.
Definition
Feature flags (also called feature toggles) let teams enable or disable functionality without deploying new code. They decouple deployment from release, allowing gradual rollouts, A/B tests, and quick rollbacks.
How Feature Flags Work
if (featureFlag.isEnabled("new-checkout")) {
showNewCheckout()
} else {
showOldCheckout()
}The flag state is controlled externally, so behavior changes without code changes.
Feature Flag Use Cases
Gradual Rollouts
Release to 10% of users, then 50%, then 100%. Monitor for issues at each stage.
Beta Testing
Enable features for specific users or companies before general release.
Kill Switches
Quickly disable problematic features without deploying a fix.
A/B Testing
Show different variants to different users and measure which performs better.
Entitlements
Enable premium features for paying customers only.
Feature Flag Types
| Type | Purpose |
|---|---|
| Release flags | Control feature rollout |
| Experiment flags | A/B testing variants |
| Ops flags | System behavior toggles |
| Permission flags | User entitlements |
Tools for Feature Flags
Platforms that provide feature flag management:
- PostHog - Feature flags with analytics integration
- LaunchDarkly - Enterprise feature management
- Split - Feature delivery with data platform
- Flagsmith - Open-source option
Frequently Asked Questions
Should I build my own feature flag system?
For simple on/off flags, a basic implementation works. For percentage rollouts, targeting rules, and analytics integration, purpose-built tools save significant development time.
How do I manage flag lifecycle?
Remove flags after features are fully rolled out. Stale flags add code complexity. Most teams review flags quarterly and remove those no longer needed.
Can feature flags slow down my application?
Well-implemented flags add minimal latency (1-5ms). Most tools support local evaluation or caching. Test performance impact with your specific implementation.