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How can rate limiting be implemented in ASP.NET Core APIs to protect backend services from excessive traffic?

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How can ASP.NET Core rate limiting protect APIs from excessive requests, accidental traffic spikes, abuse, and resource exhaustion? Explore fixed-window, sliding-window, token-bucket, and concurrency-based limiting, along with endpoint-specific policies and appropriate HTTP responses such as 429 Too Many Requests. Learn how rate limits should be designed alongside authentication, authorization, caching, logging, monitoring, and distributed deployments. The objective is to build APIs that remain secure, predictable, and resilient under high traffic.
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Answers

ASP.NET Core provides built-in rate-limiting capabilities that can protect APIs from excessive traffic and help maintain predictable application performance.

The main approaches include:

  • Fixed Window – limits requests within a defined time period.
  • Sliding Window – provides smoother request control across time segments.
  • Token Bucket – allows controlled bursts while maintaining an overall rate.
  • Concurrency Limiting – restricts how many expensive requests execute simultaneously.

Don't use one identical limit for every endpoint.

For example:

GET /products may tolerate higher traffic, while:

POST /generate-report

may require much stricter limits because it consumes more CPU and database resources.

In enterprise APIs, consider partitioning limits by user, tenant, API client or another meaningful identity, rather than relying only on IP address.

Also monitor rejected requests and make clients handle throttling appropriately.

A good architecture is:

Client → Gateway/WAF → ASP.NET Core Rate Limiter → API → Database

Interview tip: Don't just explain the four algorithms. Explain why you would select a particular algorithm for a particular business scenario.

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