MEDIUMInfrastructuresenior engineer
Design a Rate Limiter
Design a distributed rate limiting system to protect APIs from abuse and ensure fair usage.
Estimated Time: 30 minutes
GoogleAmazonStripe
#rate-limiting#api#redis#distributed-systems
Solution Overview
Token bucket refills at constant rate with burst allowance. Sliding window tracks requests in time windows. Distributed rate limiting uses Redis for shared counters. Allows graceful degradation under overload.
Architecture Pattern
Token bucket and sliding window rate limiting algorithms
Key Concepts
Token BucketSliding WindowDistributed CountersQuota ManagementThrottling
Used By Companies
StripeGitHubTwilio
Solution Overview
Token bucket refills at constant rate with burst allowance. Sliding window tracks requests in time windows. Distributed rate limiting uses Redis for shared counters. Allows graceful degradation under overload.
Hints to Get Started
1
Compare token bucket vs sliding window
2
How do you handle distributed state?
3
Consider race conditions
Companies
- •Stripe
- •GitHub
- •Twilio
Key Concepts
- •Token Bucket
- •Sliding Window
- •Distributed Counters
- •Quota Management
- •Throttling
Implementation Url
https://github.com/codecrafters-io/build-your-own-x