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Cover image for How to Implement API Rate Limiting in .NET
Shreyans Padmani
Shreyans Padmani

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How to Implement API Rate Limiting in .NET

As developers, we often build APIs that many users or systems can access. But what if too many requests come in at once , either by mistake or because someone is trying to overload the system? That’s when Rate Limiting becomes very useful.

In this article, we’ll learn how to add rate limiting to your .NET APIs to protect your backend, make sure every user gets a fair share, and keep your system running smoothly.

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What is Rate Limiting?

Rate limiting is a technique to control the number of requests a client can make to your API in a given time frame. It helps:

  • Prevent abuse or DDoS attacks
  • Maintain server performance
  • Enforce fair usage policies

Fixed Window Rate Limiting

How it works: Divides time into fixed intervals (windows) and allows a set number of requests per window.

Key characteristics:

  • Simple implementation with clear boundaries.
  • Can lead to request bursts at window edges.
  • Minimal memory requirements.

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Sliding Window Rate Limiting

How it works: Tracks requests over a rolling period, providing smoother limiting than fixed windows.

Key Points:

  • Reduces boundary bursts by using overlapping windows.
  • More accurate rate enforcement.
  • Slightly higher memory usage.

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Concurrency Rate Limiting

How it works: Limits the number of simultaneous requests rather than requests per period.

Key Ponits:

Protects against resource exhaustion
Ideal for CPU/memory-intensive operations
Doesn’t limit total request volume over time

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Token Bucket Rate Limiting

How it works: Uses a token-based system where tokens are replenished at a fixed rate.

Key Points:

  • Allows for controlled bursts
  • Maintains a long-term average rate
  • More complex configuration

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Choosing the Right Algorithm

Fixed Window: Best for simple scenarios where occasional bursts are acceptable
Sliding Window: Ideal when you need more precise control without bursts
Concurrency: Perfect for protecting resources with limited parallel capacity
Token Bucket: Excellent when you need to allow controlled bursts while maintaining an average rate

Conclusion

All implementations support queueing with configurable queue limits and processing order (oldest or newest first). The .NET implementation also provides automatic replenishment for token buckets and easy integration with middleware.

Top comments (1)

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michael_liang_0208 profile image
Michael Liang

Great