Feature flag best practices for production

Feature flags are powerful. They are also easy to misuse. A codebase with 200 stale flags and nested conditionals is worse than one with no flags at all.

Here are the practices we follow internally and recommend to teams using Flagify.

Name flags with intent

A flag name should tell you what it does without reading the code.

Bad	Good
flag-123	new-checkout-flow
test	search-v2-rollout
feature_a	pro-plan-csv-export

Use lowercase with hyphens. Include the feature or context. Avoid abbreviations that only one person understands.

Define a lifecycle

Every flag should have a planned end state:

1. Temporary — ship a feature, roll it out to 100%, remove the flag. Target lifecycle: 2–4 weeks.
2. Kill switch — stays in the codebase as a safety mechanism. Clearly marked, never removed.
3. Entitlement — gates access by plan or role. Lives as long as the business rule exists.

The most common mistake is treating every flag as permanent. Temporary flags that are never cleaned up become technical debt.

Clean up aggressively

Set a rule: when a temporary flag reaches 100% rollout and has been stable for one sprint, remove it. Not “someday.” Next sprint.

In Flagify, you can see evaluation counts per flag. If a flag is always returning the same value for everyone, it is a candidate for cleanup.

Keep nesting shallow

// Bad: nested flags create exponential complexity
if (await flagify.isEnabled('new-checkout')) {
  if (await flagify.isEnabled('checkout-upsell')) {
    if (await flagify.isEnabled('upsell-v2')) {
      // Which combination are we testing?
    }
  }
}

// Good: one flag per decision point
const checkoutVariant = await flagify.getVariant('checkout-experience');
renderCheckout(checkoutVariant);

Nested flags create combinatorial explosions. If you have 3 nested boolean flags, that is 8 possible states. Use multivariate flags instead.

Use fallbacks defensively

Always provide a fallback value. The SDK should never be a single point of failure.

// If the service is down, the app still works
const showBanner = await flagify.isEnabled('promo-banner', user, false);

Flagify evaluates flags locally from cached rules, so outages are rare. But the fallback is your safety net for cold starts and edge cases.

Separate concerns

Do not use a single flag for multiple purposes. If “new dashboard” also changes the API response format, those are two flags — one for UI, one for API. They may roll out at different speeds.

Monitor what matters

Pair feature flags with metrics. When you roll out a new search engine to 25% of users, track:

• Latency (is it faster or slower?)
• Error rate (is it more or less stable?)
• Engagement (are users finding what they need?)

Flagify tells you which variant a user is in. Your analytics tool tells you whether that variant is working. Use both.

Summary

Practice	Why
Name with intent	Readability across the team
Define lifecycle	Prevents flag sprawl
Clean up aggressively	Reduces technical debt
Avoid nesting	Limits complexity
Use fallbacks	Prevents outages
Separate concerns	Independent rollouts
Monitor metrics	Data-driven decisions

Feature flags are infrastructure. Treat them with the same discipline as your database migrations or CI pipeline.