Harness Feature Flags

Feature flag lifecycle management involves defining, enabling, disabling, and retiring flags with documented ownership and timelines. You can catalog and govern feature flags across codebases to maintain clear ownership and automated hygiene rules.

Gradual rollout governance is implemented using percentage rollouts, segment targeting, and kill switches to minimize blast radius. This approach allows you to incrementally increase exposure while maintaining a safety net to instantly revert if issues arise.

A/B testing infrastructure is designed to run experiments with consistent user assignment and outcome tracking. This ensures users remain in their assigned test groups across sessions, providing accurate measurement of the experiment's impact.

Feature flag hygiene is enforced by applying default values, strict naming conventions, and automatic cleanup processes. This governance prevents flag accumulation and ensures flags are retired with documented timelines once their lifecycle ends.

Yes, segment targeting is a core component of gradual rollout governance. You can roll out features to a specific user segment, such as exposing a new search algorithm to 5% of users, measuring the impact, and safely scaling exposure.

Release governance for feature flags reduces risk during releases by centralizing control. It enables safe experiments, controlled rollouts, and clear ownership with automated hygiene rules, preventing untracked flags from causing deployment issues.