Design a large-scale distributed rate limiter

Q: Design a large-scale distributed rate limiter

This question evaluates system design competency in distributed systems, focusing on scalability, multi-tenant isolation, rate-limiting algorithms, consistency and failover trade-offs, and operational concerns such as observability and safe degradation.

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Question

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Problem

Design a multi-tenant, large-scale distributed Rate Limiter service used by many internal teams.

The service should allow product teams to enforce request limits (e.g., per user, per API key, per IP, per tenant) at very high QPS.

Requirements to clarify

Who calls it? (internal services via gateway/service mesh; optional external-facing)
Limit types: per-second / per-minute limits; burst handling
Algorithms: fixed window / sliding window / token bucket / leaky bucket
Correctness: strict vs best-effort; allowable over-limit error
Scope: single region vs multi-region ; cross-region failover
Isolation: per-tenant quotas, noisy-neighbor protection, hotspot keys (large customers)
Operational needs: observability, config rollout, auditability, safe degradation

Expected output

Explain a concrete architecture (components + data model + API), and walk through:

request path and decision logic
storage/sharding strategy
multi-region consistency trade-offs
failure modes (store down, partitions) and fail-open vs fail-close
evolution plan as scale grows

Design a large-scale distributed rate limiter

Quick Overview

Problem

Requirements to clarify

Expected output

Solution

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