Rate Control in Distributed Systems

Introduction

Rate control is about limiting the number of requests or operations to prevent system overload.

Techniques

• Token Bucket: Allows bursts but limits average rate.
• Leaky Bucket: Smooths out bursts, enforces a steady rate.
• Fixed Window: Simple, but can cause spikes at window boundaries.
• Sliding Window: More accurate, tracks requests over a moving window.

Use Cases

• API gateways
• Distributed databases
• Microservices

Conclusion

Effective rate control protects your system from overload and ensures fair resource usage.