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Scalable Rate Limiter with Distributed Token Bucket Algorithm

distributed systems rate limiting microservices redis
Prompt
Design a distributed rate limiter using Redis as a backend that implements a token bucket algorithm for microservices. The solution must support per-service configurable rate limits, handle concurrent requests efficiently, and provide atomic token consumption with less than 10ms latency. Include metrics tracking, distributed synchronization, and a fallback mechanism for Redis connection failures.
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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
  • Manage API traffic for high-demand applications.
  • Prevent service overload during peak usage times.
  • Ensure fair resource distribution among users.
Tips for Best Results
  • Monitor traffic patterns to adjust limits effectively.
  • Test the system under load to ensure reliability.
  • Document your rate limiting strategy for transparency.

Frequently Asked Questions

What is a Scalable Rate Limiter with Distributed Token Bucket Algorithm?
It's a system for managing API request rates across distributed systems.
How does it enhance API performance?
By controlling traffic, it prevents overload and maintains responsiveness.
Is it easy to implement?
Yes, it can be integrated into existing API infrastructures.

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