How would you rate limit an API without breaking legitimate users?

Apply rate limits and abuse throttles to APIs

Explains rate-limit identity, endpoint cost, login and suggestion throttles, Redis counters, user experience, and observability.

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I would identify callers by the best available stable signal: user id, API key, tenant, IP address, device id, or a combination. Then I would set limits by endpoint cost and risk. Login, password reset, suggestions, imports, and expensive searches may need different limits. When a limit is hit, the API returns 429 with a clear retry behavior.

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Caller identity, endpoint cost, fixed or sliding windows, login abuse, distributed counters, 429 responses, and metrics.

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Rate limiting is both reliability and security. A useful design protects expensive and abusive paths without randomly punishing normal clients.
I would identify callers by the best available stable signal: user id, API key, tenant, IP address, device id, or a combination. Then I would set limits by endpoint cost and risk. Login, password reset, suggestions, imports, and expensive searches may need different limits. When a limit is hit, the API returns 429 with a clear retry behavior.
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I would roll limits out with observation first where possible. For distributed APIs, counters can live in Redis or another shared store so all instances enforce the same policy. I would avoid only IP-based limits for authenticated users because shared networks can create false positives. I would also protect high-risk endpoints with stricter identity-specific throttles and safe failure behavior.

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Using one global limit for every endpoint.
Rate limiting only by IP for authenticated users.
Returning vague errors without retry information.
No metrics for false positives or attack patterns.

How would you rate limit an API without breaking legitimate users?

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