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Distributed Rate Limiter with Sliding Window Algorithm

distributed systems redis rate limiting concurrency
Prompt
Design a distributed rate limiting system using Redis that implements a sliding window algorithm for handling concurrent API requests. Create a solution that can track request rates per user/service with configurable time windows (1s, 1m, 1h), supports horizontal scaling, and provides atomic rate limit checks. Include mechanisms for tracking current request load, preventing race conditions, and gracefully handling rate limit exceeded scenarios with proper error responses.
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TypeScript
Technology
Feb 28, 2026

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Tool
Ai Chat
Details
Category Pro
Purpose Coding
Platform TypeScript
Industry Technology
Added Feb 28, 2026
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Use Cases
  • Managing API request rates in web applications.
  • Preventing server overload during peak usage times.
  • Ensuring fair access to resources among users.
Tips for Best Results
  • Adjust window size based on traffic patterns.
  • Monitor system performance for optimization.
  • Implement logging to track request rates effectively.

Frequently Asked Questions

What is a distributed rate limiter with a sliding window algorithm?
It's a system that controls the rate of requests across distributed systems using a sliding window.
How does this algorithm improve system performance?
By preventing overload and ensuring fair resource allocation among users.
Is it suitable for high-traffic applications?
Yes, it effectively manages request rates in high-demand environments.

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