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Practice · High Level Design · Storage and Infrastructure

Design a Distributed Rate Limiter

IntermediateToken bucketSliding windowRedisMany servers⏱ 2 h

Protecting an API from floods: token bucket vs sliding window, keeping counts in Redis, and limiting fairly when requests hit many servers at once.

Read first:API Design, API Gateway and Rate LimitingCaching and CDN

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The full solution is on its way. Here is its outline, so you can try designing it yourself first.

  1. 01Problem introduction
  2. 02Problem statement
  3. 03Requirements
  4. 04Capacity estimation
  5. 05API design
  6. 06Database design
  7. 07Architecture
  8. 08Request lifecycle
  9. 09Component deep dive
  10. 10Scaling, 100 to 10M users
  11. 11Failure scenarios
  12. 12Reliability and observability
  13. 13Security
  14. 14Trade-offs
  15. 15Final architecture
  16. 16Interview discussion

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