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Distributed Rate Limiter with Sliding Window Algorithm

redis distributed-systems rate-limiting concurrency
Prompt
Design a distributed rate limiting system using Redis that implements a sliding window algorithm for preventing API abuse. The system should track request rates per user/IP, support configurable time windows (1s, 1m, 1h), and handle concurrent requests with atomic operations. Include mechanism for returning precise rate limit headers, tracking remaining requests, and implementing exponential backoff for clients exceeding limits.
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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 traffic for a high-traffic web application.
  • Preventing abuse in online gaming platforms.
Tips for Best Results
  • Adjust time windows based on traffic patterns.
  • Monitor performance to fine-tune rate limits.
  • Implement fallback mechanisms for high traffic.

Frequently Asked Questions

What is a distributed rate limiter?
A distributed rate limiter controls the number of requests across multiple servers.
How does the sliding window algorithm work?
It tracks request counts in fixed time intervals to manage traffic effectively.
What are the benefits of using this algorithm?
It provides better control over request rates and improves system stability.

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