Feature-Flags

Separating deployment from release is one of the best things you can do for your team’s sanity. Feature flags make this possible. The Core Idea 1 2 3 4 5 6 7 8 9 10 11 12 # Without flags: deploy = release def checkout(): process_payment() send_confirmation() # With flags: deploy != release def checkout(): process_payment() if feature_enabled("new_confirmation_email"): send_new_confirmation() # Deployed but not released else: send_confirmation() Code ships to production. Flag decides if users see it. ...

Deployment and release are different things. Deployment puts code on servers. Release makes features available to users. Feature flags separate these concerns. With feature flags, you can deploy daily but release weekly. Ship risky changes but only enable them for 1% of users. Roll back a broken feature in seconds without touching infrastructure. Basic Implementation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 class FeatureFlags: def __init__(self): self.flags = {} def is_enabled(self, flag_name: str, user_id: str = None) -> bool: flag = self.flags.get(flag_name) if not flag: return False # Global kill switch if not flag.get("enabled", False): return False # Check user allowlist if user_id and user_id in flag.get("allowed_users", []): return True # Check percentage rollout if user_id and flag.get("percentage", 0) > 0: # Consistent hashing: same user always gets same result hash_val = hash(f"{flag_name}:{user_id}") % 100 return hash_val < flag["percentage"] return flag.get("enabled", False) flags = FeatureFlags() flags.flags = { "new_checkout": { "enabled": True, "percentage": 10, # 10% of users "allowed_users": ["user_123"] # Plus specific users } } # Usage if flags.is_enabled("new_checkout", user_id=current_user.id): return new_checkout_flow() else: return old_checkout_flow() Configuration-Based Flags Store flags in config, not code: ...

Feature flags started as if (ENABLE_NEW_UI) { ... }. They’ve evolved into a deployment strategy that separates code deployment from feature release. Ship your code Tuesday. Release to 1% of users Wednesday. Roll back without deploying Thursday. Here’s how to implement feature flags that scale from simple toggles to sophisticated progressive delivery. The Basic Pattern At its core, a feature flag is a runtime conditional: 1 2 3 4 5 def get_recommendations(user_id: str) -> list: if feature_flags.is_enabled("new_recommendation_algo", user_id): return new_algorithm(user_id) else: return legacy_algorithm(user_id) The magic is in how is_enabled works — and how you manage the flag lifecycle. ...

Deploy on Friday. Release on Monday. That’s the power of feature flags. The traditional model couples deployment with release—code goes to production, users see it immediately. Feature flags break that coupling, letting you deploy dark code and control visibility separately from deployment. The Core Pattern A feature flag is a conditional that wraps functionality: 1 2 3 4 5 if (featureFlags.isEnabled('new-checkout-flow', { userId: user.id })) { return renderNewCheckout(); } else { return renderLegacyCheckout(); } Simple in concept. Transformative in practice. ...

There’s a subtle but powerful distinction in modern software delivery: deployment is not release. Deployment means your code is running in production. Release means your users can see it. Feature flags are the bridge between these two concepts—and mastering them changes how you think about shipping software. The Problem with Traditional Deployment In the old model, deploying code meant releasing features: 1 2 3 # Old way: deploy = release git push origin main # Boom, everyone sees the new feature immediately This creates pressure. You can’t deploy partially-complete work. You can’t test in production with real traffic. And if something breaks, your only option is another deploy to roll back. ...

Deploying code and releasing features don’t have to be the same thing. Feature flags let you ship code to production while controlling who sees it, when they see it, and how quickly you roll it out. This separation is transformative for both velocity and safety. Why Feature Flags? Traditional deployment: code goes live, everyone gets it immediately, and if something breaks, you redeploy. With feature flags: Deploy anytime — code exists in production but isn’t active Release gradually — 1% of users, then 10%, then 50%, then everyone Instant rollback — flip a switch, no deployment needed Test in production — real traffic, real conditions, controlled exposure A/B testing — compare variants with actual user behavior Basic Implementation Start simple. A feature flag is just a conditional: ...