Distributed Rate Limiting — Five Problems That Break Your Counters

Why Local Rate Limiting Breaks A rate limiter on a single server works exactly as advertised. But most production systems aren't a single server — they're 10, 50, or 200 instances behind a load balancer. And that changes the math. If your limit is 100 requests per minute and you have 50 instances, the load balancer sprays traffic round-robin. Each instance sees ~2 requests per minute from any given user. Every instance says "well under the limit." Nobody rejects anything. The user sends 3,000 requests. All pass. Your per-instance rate limiter silently became a limit × num_instances rate limiter. You didn't change the code. You changed the deployment. The fix is shared state — usually Redis. All instances read and write to the same counter, so the global count is enforced globally. But the moment you introduce shared state over a network, five new problems appear. Problem 1: The Race You Can't See Two requests from the same user arrive at the same millisecond, hitting two different inst