Reliability & Scalability Architecture

Rate Limiting Algorithms

Algorithmic strategies (Token Bucket, Leaky Bucket, Sliding Window Counter) used to throttle inbound network traffic and protect backend APIs from overload.

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Deep Dive

How Rate Limiting Algorithms Works in Production

Under-the-hood mechanics and technical implementation details.

Technical Deep Dive

Detailed Architecture

Rate limiting controls the rate of traffic sent or received by a network interface. The three standard algorithms evaluated in system design are: 1) Token Bucket (tokens added at fixed rate; allows bursts up to bucket capacity); 2) Leaky Bucket (requests processed at constant outflow rate; smooths bursts); 3) Sliding Window Counter (combines previous and current window counts with linear interpolation to eliminate boundary burst vulnerabilities).

Key Architectural Rule / Formula:

Sliding Window Count = Current Window Count + (Previous Window Count * (1 - Elapsed Ratio))

Engineering Trade-Offs

Trade-Off Dimensions & Analysis

Evaluating advantages and drawbacks during architecture interviews.

Dimension	Advantages (Pros)	Drawbacks & Costs (Cons)
Token Bucket vs Leaky Bucket	Token Bucket allows bursts of valid traffic; Leaky Bucket guarantees perfectly smooth outbound processing.	Token Bucket can cause downstream spikes; Leaky Bucket drops legitimate bursts if queue fills up.
Sliding Window Counter	Prevents the 2x boundary traffic spike flaw of Fixed Window counters with low memory.	Requires atomic Redis lua scripts or multi-key transaction locks to update concurrently.

Interview Application

How to Frame Rate Limiting Algorithms in System Design Rounds

Senior-level talking points and related interview problems.

Interview Strategy

Evaluating in Loops

A classic system design interview question asked across all tech companies to protect API Gateways and microservices.

Applied System Design Scenarios

API Rate Limiter
Payment Gateway Processor
Video Streaming Ingestion

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