How to control load on handles (rate limiting)?

Various approaches are used to control load on API endpoints (rate limiting) to restrict the number of requests from a single client within a certain period. This helps protect the service from overloads and abuse.

Main methods:

• Token Bucket — a certain number of tokens are issued to the client, each request 'spends' a token. Tokens are replenished over time.
• Leaky Bucket — requests are processed at a fixed rate, excess requests are queued or discarded.
• Fixed Window — counts requests over a fixed interval (e.g., per minute).
• Sliding Window — provides a more precise count of requests over a sliding time window.

In Kotlin, rate limiting can be implemented using libraries such as resilience4j or bucket4j. Example with bucket4j:

import io.github.bucket4j.Bandwidth
import io.github.bucket4j.Bucket
import io.github.bucket4j.Refill
import java.time.Duration

val limit = Bandwidth.classic(10, Refill.greedy(10, Duration.ofMinutes(1)))
val bucket = Bucket.builder().addLimit(limit).build()

fun handleRequest() {
    if (bucket.tryConsume(1)) {
        // Process request
    } else {
        // Return 429 Too Many Requests error
    }
}

You can also use proxy servers (Nginx, Envoy) or API Gateways with built-in rate limiting for centralized control.