Design a Rate Limiter

Rate Limiter System Design:

1. High-Level Design:

   • Token Bucket Algorithm
   • Redis for distributed rate limiting
   • Load balancer for distribution

2. Components:

interface RateLimiter {
  isAllowed(clientId: string): boolean;
  updateCount(clientId: string): void;
  resetCount(clientId: string): void;
}

class TokenBucketRateLimiter implements RateLimiter {
  private readonly redis: Redis;
  private readonly limit: number;
  private readonly window: number;
  
  constructor(limit: number, windowInSeconds: number) {
    this.limit = limit;
    this.window = windowInSeconds;
  }
  
  async isAllowed(clientId: string): Promise<boolean> {
    const count = await this.redis.get(clientId);
    return count < this.limit;
  }
}

3. Implementation Details:

   • Use Redis INCR for atomic counters
   • Sliding window with Redis ZSET
   • Lua scripts for atomic operations

4. Scalability Considerations:

   • Horizontal scaling with Redis cluster
   • Cache synchronization
   • Fault tolerance

5. Monitoring & Alerts:

   • Request rate metrics
   • Rejection rate alerts
   • Latency monitoring

6. Trade-offs:

   • Memory vs Accuracy
   • Consistency vs Availability
   • Complexity vs Performance

Company Context (Amazon):

• Focus on scalability
• Consider distributed systems
• Emphasize operational excellence
• Cost optimization