Design and implement a precise sliding-window rate limiter for an API. Part A: Enforce a global cap of R requests within any rolling T-second window (true sliding window, not fixed window or token bucket). Specify the public interface, data structures, time resolution, and time/space complexity. Part B: Each request includes userId and userExperience fields. Enforce independent limits per userId and per userExperience concurrently (e.g., U requests per T seconds per userId and X requests per T seconds per userExperience). Explain key design choices: how to structure keys/counters to support multiple dimensions without double-counting; how to evict stale state efficiently; how to deploy and scale this in a distributed environment (sharding, coordination, clock skew, idempotency); and how you would test correctness and edge cases (bursts, boundary timestamps, window rollover).

This question evaluates understanding of precise sliding-window rate limiting, multi-dimensional counters, time-series state management, and distributed systems concerns such as sharding, clock skew, idempotency, and scalable state eviction.

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This is a hard difficulty System Design question, commonly asked during Technical Screen rounds at Roblox.

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Design sliding-window rate limiter with multi-keys

Design a Precise Sliding-Window Rate Limiter

Context

You are designing a rate limiter for an API that must enforce a true sliding-window limit (i.e., at any instant, only the last T seconds of traffic count toward the quota). You will first design a global limiter, then extend it to multi-dimensional limits.

Part A — Global Limit

Design and implement a precise sliding-window rate limiter that enforces a cap of R requests within any rolling T-second window (true sliding window; not fixed window or token bucket). Specify:

Public interface (inputs, return values, error semantics)
Data structures and state storage (single-host and distributed options)
Time source and resolution
Time and space complexity per request

Part B — Per-Dimension Limits

Each request includes two attributes: userId and userExperience.

Enforce all of the following limits concurrently:

Global limit: R requests per T seconds
Per-user limit: U requests per T seconds per userId
Per-experience limit: X requests per T seconds per userExperience

Explain key design choices:

How to structure keys/counters to support multiple dimensions without double-counting
How to evict stale state efficiently
How to deploy and scale in a distributed environment (sharding, coordination, clock skew, idempotency)
How to test correctness and edge cases (bursts, boundary timestamps, window rollover)

Part A — Global Limit

Design and implement a precise sliding-window rate limiter that enforces a cap of R requests within any rolling T-second window (true sliding window; not fixed window or token bucket). Specify:

Public interface (inputs, return values, error semantics)

Data structures and state storage (single-host and distributed options)

Time source and resolution

Time and space complexity per request

Part B — Per-Dimension Limits

Each request includes two attributes: userId and userExperience.

Enforce all of the following limits concurrently:

Global limit: R requests per T seconds

Per-user limit: U requests per T seconds per userId

Per-experience limit: X requests per T seconds per userExperience

Explain key design choices:

How to structure keys/counters to support multiple dimensions without double-counting

How to evict stale state efficiently

How to deploy and scale in a distributed environment (sharding, coordination, clock skew, idempotency)

How to test correctness and edge cases (bursts, boundary timestamps, window rollover)

Design sliding-window rate limiter with multi-keys

Quick Overview

Design a Precise Sliding-Window Rate Limiter

Context

Part A — Global Limit

Part B — Per-Dimension Limits

Solution

Comments (0)

Design sliding-window rate limiter with multi-keys

Quick Overview

Design a Precise Sliding-Window Rate Limiter

Context

Part A — Global Limit

Part B — Per-Dimension Limits

Solution

Comments (0)