Behavioral & System Design API Design Rate Limiting Throttling

API Rate Limiting and Throttling Strategies

Mind Map Summary

  • Topic: API Rate Limiting and Throttling
  • Core Concepts:
    • Rate Limiting: The process of controlling the rate of traffic sent or received by a network interface.
    • Throttling: The process of controlling the usage of an API by limiting the number of requests that a user can make in a given period of time.
  • Algorithms:
    • Token Bucket: A simple algorithm where a bucket contains a number of tokens. Each request consumes a token. If the bucket is empty, the request is rejected.
    • Leaky Bucket: An algorithm where requests are added to a queue. If the queue is full, new requests are rejected. Requests are processed from the queue at a fixed rate.
  • Implementation Points:
    • API Gateway: A common place to implement rate limiting, as it is the single entry point for all API requests.
    • Middleware: Rate limiting can also be implemented in middleware in the application itself.

Practice Exercise

Design a rate-limiting strategy for a multi-tenant API. How would you handle different rate limits for different subscription tiers (e.g., Free vs. Pro)? Whiteboard the components involved.

Answer

Rate-Limiting Strategy:

  • Algorithm: We will use the Token Bucket algorithm, as it is simple to implement and effective for this use case.
  • Storage: We will use a distributed cache like Redis to store the token buckets for each user.
  • Implementation: We will implement the rate limiting in middleware in our API gateway.

Components:

  • API Gateway: The single entry point for all API requests.
  • Rate Limiting Middleware: Middleware in the API gateway that implements the rate limiting logic.
  • Redis: A distributed cache that stores the token buckets for each user.
  • Subscription Service: A service that manages user subscriptions and their corresponding rate limits.

Workflow:

  1. A user makes a request to the API gateway.
  2. The rate limiting middleware intercepts the request.
  3. The middleware retrieves the user’s subscription tier from the subscription service.
  4. The middleware retrieves the user’s token bucket from Redis.
  5. If the token bucket has enough tokens, the request is allowed to proceed. The middleware decrements the number of tokens in the bucket.
  6. If the token bucket does not have enough tokens, the request is rejected with a 429 Too Many Requests error.