Design a Rate Limiter | System Design Interview

Most candidates jump straight to drawing boxes. This is how you actually
answer the rate limiter question — requirements, capacity math, where the limiter lives, and which algorithm to use (and which to avoid).

CHAPTERS
0:00 Introduction & Hook
2:07 Requirements
4:57 Capacity Estimation
7:09 High Level Design
11:42 Algorithm Deep Dive
25:57 Wrap Up

KEY CONCEPTS
• Client-side rate limiting is worthless — always enforce server-side
• 100M users at 50 bytes each = 50 MB in Redis (memory is not a bottleneck)
• 100,000 req/sec — single Redis node handles 100K–300K ops/sec
• Latency budget: 1.5ms total, 3.5ms headroom under the 5ms target
• Fixed Window: boundary spike lets users send 2× the limit — don't use in
production
• Sliding Window Log: accurate but too memory-expensive to scale
• Sliding Window Counter: hybrid approach — recommend this in interviews

ASKED AT
Amazon, Google, Stripe, Cloudflare

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