Systems break down under tremendous load, and we need to ensure that it doesn’t happen
Key Objectives
A well-constructed rate limiter should achieve the following goals:
- Limit Requests: Control the number of incoming requests within a specified timeframe.
- Granular Configuration: Empower developers with the flexibility to configure thresholds at a granular level. Minimal Overhead: Ensure that the rate limiter implementation does not introduce significant additional overhead.
Understanding the Rate Limiter
The rate limiter functions as the initial defense mechanism for incoming requests. It follows a straightforward process:
- The Rate limiter is the first line of defense
- Any incoming request is first consulted against the rate limiter
- If we are under limits, let the request pass-through
- Otherwise, reject the request with Error 429 (Too many requests)
Implementation as a Library
Rather than conceiving the rate limiter as a standalone service, we propose implementing it as a library. This approach centralizes the business logic within a dedicated library, providing a cleaner and more modular solution.
By encapsulating the rate limiter within a library, developers gain a seamless way to integrate this crucial functionality into their applications.
Scaling the Redis Database
When considering the scalability of the underlying database, such as Redis, two primary approaches can be explored:
- Vertical Scaling: Enhance the performance of the existing database server by upgrading its resources.
- Sharding: Distribute the database load by adding shards, enabling horizontal scaling. By strategically implementing these scaling strategies, the rate limiter can efficiently manage increasing workloads while maintaining optimal performance.