API Performance: Implementing Smart Rate Limiting

Posted on December 02, 2024 • #api #performance #rate-limiting

Rate limiting is a crucial aspect of API performance and security. Today, let's explore how to implement intelligent rate limiting that balances user experience with server protection.

Token Bucket Algorithm

The token bucket algorithm is an elegant solution for rate limiting:

public class TokenBucket
{
    private readonly double capacity;
    private readonly double fillRate;
    private double tokens;
    private DateTime lastUpdated;

    public TokenBucket(double capacity, double fillRate)
    {
        this.capacity = capacity;
        this.fillRate = fillRate;
        this.tokens = capacity;
        this.lastUpdated = DateTime.Now;
    }

    public bool Consume(double tokens)
    {
        var now = DateTime.Now;
        var timePassed = (now - lastUpdated).TotalSeconds;
        this.tokens = Math.Min(this.tokens + timePassed * fillRate, capacity);
        lastUpdated = now;

        if (this.tokens >= tokens)
        {
            this.tokens -= tokens;
            return true;
        }
        return false;
    }
}

Implementation Tips

  1. Use Redis for distributed rate limiting
  2. Include rate limit headers in responses
  3. Implement gradual backoff for heavy users

Remember: good rate limiting isn't about blocking users—it's about shaping traffic to maintain optimal performance for everyone.