Rate limiting algorithms (token bucket, leaky bucket) in HLD - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main purpose of rate limiting in system design?

Rate limiting controls how many requests a user or system can make in a given time to prevent overload and ensure fair resource use.

beginner

Describe the Token Bucket algorithm in simple terms.

Token Bucket allows requests if there are tokens available. Tokens are added at a steady rate. Each request uses one token. If no tokens, request is denied or delayed.

beginner

How does the Leaky Bucket algorithm control request flow?

Leaky Bucket processes requests at a fixed rate. Excess requests wait in a queue. If the queue is full, new requests are dropped.

intermediate

What is a key difference between Token Bucket and Leaky Bucket algorithms?

Token Bucket allows bursts of requests up to token count, while Leaky Bucket smooths out bursts by processing at a constant rate.

intermediate

Why might a system choose Token Bucket over Leaky Bucket for rate limiting?

Token Bucket is better for systems that allow short bursts of traffic, giving flexibility while still controlling average rate.

Which rate limiting algorithm allows bursts of requests up to a token limit?

A Token Bucket

B Leaky Bucket

C Fixed Window

D Sliding Log

Token Bucket allows bursts by accumulating tokens that can be spent quickly.

In the Leaky Bucket algorithm, what happens when the queue is full and a new request arrives?

A The request is dropped

B The request is processed immediately

C The bucket refills tokens

D The request is delayed indefinitely

New requests are dropped if the queue is full to prevent overload.

Which algorithm processes requests at a fixed, steady rate?

A Sliding Window

B Token Bucket

C Leaky Bucket

D Fixed Window

Leaky Bucket processes requests at a constant rate, smoothing bursts.

What does a token represent in the Token Bucket algorithm?

A A dropped request

B Permission to process one request

C A queued request

D A fixed time interval

Each token allows one request to be processed.

Why is rate limiting important in distributed systems?

A To reduce network latency

B To increase request speed

C To store more data

D To prevent system overload and ensure fair use

Rate limiting protects systems from overload and abuse.

Explain how the Token Bucket algorithm works and when it is useful.

Think of tokens as tickets to make requests.

Describe the Leaky Bucket algorithm and how it differs from Token Bucket.

Imagine water leaking from a bucket at a steady rate.