B0387: Feature Flag Governance Framework
A decision-ready template derived from the framework.
Name variants
- English
- B0387: Feature Flag Governance Framework
- Katakana
- フラグ・ガバナンスフレームワーク
- Kanji
- 機能
Quality / Updated / Source / COI
- Quality
- Reviewed
- Updated
- Source
- Citations & Trust
- COI
- none
Context
Context: when teams interpret release frequency, defect escape rate, rollback time and testing capacity, observability coverage, risk tolerance differently, decisions about feature flag governance framework become slow and inconsistent. Without a shared frame, the velocity versus stability tradeoff stays implicit and accountability erodes. A concise decision record is required so future reviews can challenge assumptions without restarting the debate.
Options
- Option A: Maintain the current approach to minimize disruption while accepting limited improvement in release frequency and defect escape rate.
- Option B: Pilot changes in phases, validate against testing capacity, observability coverage, risk tolerance, and scale once the velocity versus stability criteria hold.
- Option C: Redesign the approach end to end to pursue larger gains with higher execution risk and change cost.
Decision
Decision: Choose Option B. Validate assumptions for testing capacity, observability coverage, risk tolerance, confirm release frequency, defect escape rate, rollback time baselines, and proceed only if the velocity versus stability balance remains acceptable. Document thresholds, owners, constraints, and review dates so accountability stays clear.
Rationale
Rationale: Option B balances the velocity versus stability tradeoff while preserving flexibility. It tests whether release frequency, defect escape rate, rollback time respond as expected to testing capacity, observability coverage, risk tolerance before committing to a full rollout, reducing the risk of locking in a costly path based on weak evidence. The phased approach also strengthens governance by keeping decision criteria explicit and reviewable.
Risks
- Delayed data refresh can mask shifts in release frequency, defect escape rate, rollback time and cause late responses to emerging risks.
- Execution slippage can erode confidence and widen velocity versus stability costs before corrective action is taken.
Next
Next: Assign owners for release frequency, defect escape rate, rollback time and testing capacity, observability coverage, risk tolerance, finalize baseline values, and publish trigger thresholds. Schedule the first review checkpoint, define escalation paths, and document stop conditions so the decision can be revisited quickly.