Topic
Implementing feature flags
Choosing a vendor or building in-house is only half the work. The engineering details — where rules execute, how fresh they are, and what happens on failure — determine whether flags feel reliable or flaky.
Where evaluation runs
Server-side evaluation keeps targeting rules and sensitive attributes closer to systems you control. Client-side evaluation can be right for UX experiments or offline-capable apps, but implies a threat model where curious users may inspect what the client knows.
Freshness and propagation
Rules change more often than binaries. Decide how quickly a policy update must reach running processes: pull intervals, streaming connections, edge caches, and mobile app constraints all matter. Slow propagation is not always wrong — but it should be a conscious choice.
Failure behaviour
Defaults and circuit breaking
When the flag service is unreachable, what variant should code assume? Document defaults per flag class: a kill switch might default to “off” while an internal-only experiment might default to “control.” Emit metrics when evaluation falls back so silent drift is visible.
Consistency across layers
A user should not see contradictory outcomes between API and UI when both consult flags for the same decision. Align identifiers, bucketing inputs, and cache boundaries — especially when anonymous and authenticated contexts merge.
Configuration as operational data
Treat flag definitions like production data: access control, change history, approvals where needed, and runbooks for emergency toggles. Small teams can keep this lightweight; regulated environments often cannot.
For SDK entry points and standards, see Libraries and links. For economics and staffing trade-offs, see build vs buy.