Feature flags solve real problems. They let you deploy code that isn’t ready for all users, roll out changes gradually to catch problems early, quickly disable features without deployments, and run experiments on subsets of traffic. Teams that use them well ship faster with more confidence.
But feature flags also create problems. Code becomes harder to understand with conditional logic everywhere. Old flags accumulate because nobody remembers to remove them. Testing becomes complex when features have multiple states. Flags interact in unexpected ways.
The difference between feature flags as a superpower and feature flags as a nightmare is how disciplined you are about managing them.
What Feature Flags Are For
Feature flags serve different purposes, and the purpose affects how you should manage them.
Release flags control whether a feature is available. They let you deploy code to production before it’s ready for users, then enable it when it’s complete. This separates deployment from release—you can deploy continuously while releasing on your own schedule.
Experiment flags enable A/B testing. Different users see different variations, and you measure which performs better. These flags need statistical rigor around user assignment and metric tracking.
Operational flags let you change system behavior without deploying. Kill switches that disable expensive features during traffic spikes, circuit breakers that fall back to cached data when services are slow, configuration that adjusts rate limits or timeouts.
Permission flags control access based on user attributes. Beta features available to select customers, premium features for paying users, internal tools available only to employees.
Each type has different lifecycle expectations. Release flags should be short-lived—enable the feature, confirm it works, remove the flag. Experiment flags run until you have statistical significance, then one variation wins and the flag goes away. Operational flags might be permanent infrastructure. Permission flags are tied to your authorization model and might live forever.
Treating all flags the same leads to problems. Release flags that stick around become confusing. Operational flags that get removed at the wrong time cause outages. Knowing the purpose of each flag guides how you manage it.
The Lifecycle Problem
Feature flags should be temporary. The code that checks whether to show the new checkout flow should eventually just show the new checkout flow, without the conditional. The flag exists during the transition; once the transition is complete, the flag should be removed.
But removal takes effort that nobody prioritizes. The feature is launched, it’s working, and there are other things to do. The flag stays in the code, still being checked thousands of times per request, adding complexity that no longer serves any purpose.
Over time, these orphan flags accumulate. New developers don’t know which flags are active and which are remnants. Testing combinations of flag states becomes exponentially complex. The flag service becomes a source of latency and a potential failure point for checks that no longer matter.
Managing this requires explicit lifecycle practices:
Set expiration expectations when creating flags. Release flags should have owners and expected removal dates from the start. If the flag is still around three months after launch, something went wrong.
Track flag status. Maintain a registry of all flags with their purpose, owner, creation date, and expected lifecycle. Review it regularly. Flags without owners, flags past their expected lifetime, and flags that nobody can explain are candidates for cleanup.
Make removal easy. If removing a flag requires coordinated changes across multiple services, hunting down all the places it’s checked, and extensive testing, removal won’t happen. Invest in tooling that identifies flag references and makes cleanup straightforward.
Celebrate cleanup. If shipping features gets recognition but removing flags doesn’t, flags will accumulate. Track flag cleanup as a metric. Include flag removal in definition of done for features.
Testing Complexity
Every feature flag doubles the configuration space. One flag means two states. Two flags mean four. Ten flags mean 1,024 possible combinations. You can’t test them all.
In practice, most combinations don’t matter—most flags are independent, and their interaction is just “both on” or “both off” or one of each. But some combinations do interact, and those interactions cause bugs that are hard to reproduce.
Manage testing complexity by:
Minimizing active flags. Fewer concurrent flags means fewer combinations. Aggressive flag cleanup isn’t just about code cleanliness; it’s about testability.
Testing flag transitions, not just states. The moment of flipping a flag often causes problems: cached data inconsistent with new behavior, database migrations not yet complete, users mid-session seeing abrupt changes. Test the transition path, not just the before and after states.
Defaulting to the final state in tests. Most tests should run with flags in their final expected state—the feature on if it will be on. Test the flag-off behavior intentionally and specifically, but don’t make every test run every combination.
Monitoring flag-specific metrics. When rolling out a flagged feature, track metrics segmented by flag state. If the flag-on cohort shows errors or performance problems, you’ll see it clearly.
Operational Flags Are Different
Some flags aren’t temporary—they’re operational controls that you expect to use forever. Kill switches for expensive features, circuit breakers for degraded dependencies, configuration for performance tuning.
These flags need different treatment:
Document their purpose and usage. Runbooks should explain when to flip operational flags, what the impact is, and how to verify the change worked.
Monitor flag state. If a kill switch is flipped, alerting should notice. If a circuit breaker opens automatically, dashboards should show it. Operational flags that change without visibility cause confusion.
Test that they work. Kill switches that have never been used might not work when you need them. Periodically exercise operational flags to verify they have the expected effect.
Keep them separate. Operational flags shouldn’t be mixed with release flags in the same system if that system is optimized for short-lived release flags. The lifecycle and importance are different; the management should be too.
Flag Evaluation Performance
Checking a flag once per request is cheap. Checking dozens of flags, each requiring a remote service call, for every request becomes a performance problem and a reliability risk.
Batch flag evaluation. Instead of checking each flag independently, fetch all relevant flags at once at the start of request handling. Pass the flag values through the request context rather than re-fetching.
Cache aggressively. Flag values change rarely; latency matters constantly. Cache flag values with appropriate TTL. Accept that changes take time to propagate in exchange for consistent, fast evaluation.
Have fallbacks. If the flag service is unavailable, what happens? Requests that can’t evaluate flags will fail unless you have fallback behavior. Default to safe values (often the old behavior) when flag evaluation fails.
Make the flag service reliable. If feature flags gate critical functionality, the flag service is critical infrastructure. It needs the same reliability investment as your database or payment processing.
Making It Work
Feature flags are a tool. Like any tool, they can be used well or poorly. The difference is discipline: clear purpose for each flag, lifecycle expectations enforced, testing practices that account for flag complexity, and operational rigor for flags that aren’t temporary.
Start with fewer flags and manage them well. Teams that scatter flags throughout their codebase because they’re easy to add quickly lose control. Teams that treat each flag as a deliberate decision with ongoing management requirements get the benefits without the chaos.
The goal is safe, fast deployment with the ability to control feature exposure. Feature flags enable that goal—but only if they’re managed as a capability that requires investment, not as a free feature with no ongoing cost.