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Scalable Rate Limiter for Distributed API Endpoints

microservices distributed systems performance concurrency
Prompt
Design a thread-safe rate limiting decorator for Python microservices that can track request frequency across multiple server instances using Redis as a centralized counter. Implement sliding window rate limiting with configurable thresholds (requests per minute/second). The solution should handle concurrent access, prevent race conditions, and provide granular tracking per API endpoint and client IP address.
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Python
General
Mar 2, 2026

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Tool
Ai Chat
Details
Category Pro
Purpose Coding
Platform Python
Industry General
Added Mar 2, 2026
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Use Cases
  • Manage API traffic for a high-traffic web application.
  • Prevent abuse in a public API by limiting request rates.
  • Ensure fair usage among users in a multi-tenant environment.
Tips for Best Results
  • Set appropriate limits based on user roles and needs.
  • Monitor usage patterns to adjust rate limits dynamically.
  • Implement logging to track and analyze rate limit violations.

Frequently Asked Questions

What is a scalable rate limiter?
A scalable rate limiter controls the number of requests to APIs, ensuring fair usage.
How does it work for distributed endpoints?
It synchronizes request limits across multiple servers to maintain consistent performance.
Why is rate limiting important?
It prevents abuse and overload, ensuring service reliability and availability.

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