In a multi-instance API, what makes distributed rate limiting safe?

Problem Statement

Explanation

Atomic operations ensure increments and expirations are consistent across nodes. LUA scripts in Redis let you read, decide, and write in one step. Local caches can assist for reads but should not replace a single source of truth for limits.

Code Solution

SolutionRead Only

EVAL token_bucket.lua 1 user:key rate burst now

Practice Sets

This question appears in the following practice sets:

Rate Limiting & Traffic Shaping

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In a multi-instance API, what makes distributed rate limiting safe?

Problem Statement

Explanation

Code Solution

Practice Sets

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Master Interviews Anywhere, Anytime

In a multi-instance API, what makes distributed rate limiting safe?

Problem Statement

Explanation

Code Solution

Practice Sets

Related Questions

Which statement best describes the Single Responsibility Principle?

Open–Closed Principle encourages what practice when adding features?

High-Level Design (HLD) typically focuses on which artifacts?

Which UML diagram best captures interactions over time between components?

Which pairing describes a healthy design goal?

More from System Design

Master Interviews
Anywhere, Anytime