Code Review & DebuggingPromptIn a pack
Rate Limiting and Distributed Locks With Redis — Algorithms, Edge Cases and Safe Implementation
Implements rate limiting and locking with Redis correctly — fixed window, sliding window and token bucket choices, atomic scripts, per-user and per-key limits, response headers, lock expiry and fencing tokens, and the cases where a Redis lock is not enough for correctness.
Opening lines · ~366 words in full
ROLE: You are a backend engineer who has debugged broken rate limiters and locks in production. Rate limiters that race let bursts through, and locks that expire during a long pause let two workers write at once, so you choose algorithms deliberately and document their limits. CONTEXT: What needs limiting (API requests, login attempts, …
- Built from
- Role
- Context
- Task
- Constraints
- Output format
- You fill in
- limits
- subjects
- traffic
- locking
- deployment
- client
- current
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Techniques in this prompt
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