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Distributed Rate Limiter with Sliding Window Algorithm

redis distributed-systems rate-limiting concurrency
Prompt
Implement a distributed rate limiting system using Redis that supports a sliding window algorithm for managing concurrent API request rates. Design the solution to handle multiple service endpoints, with configurable per-second, per-minute, and per-hour rate limits. Include mechanisms for atomic increments, automatic window sliding, and graceful request rejection with appropriate HTTP status codes. Ensure the implementation is horizontally scalable and can handle high-concurrency scenarios.
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Python
Technology
Feb 28, 2026

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Tool
Ai Chat
Details
Category Pro
Purpose Coding
Platform Python
Industry Technology
Added Feb 28, 2026
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Use Cases
  • Managing API request limits for a cloud service.
  • Controlling user access in a multi-tenant application.
  • Balancing load across microservices in a distributed system.
Tips for Best Results
  • Set appropriate time windows based on expected traffic patterns.
  • Monitor performance to adjust limits dynamically.
  • Implement logging for better analysis of request patterns.

Frequently Asked Questions

What is a distributed rate limiter?
A system that controls the rate of requests across multiple servers.
How does the sliding window algorithm work?
It tracks requests over a specified time frame to manage traffic effectively.
What are the benefits of using this algorithm?
It provides smoother traffic management and reduces the risk of server overload.

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