Design a Distributed Rate Limiter for Canva APIs

Last updated: April 5, 2025

Quick Overview

Design a rate limiting system that protects Canva's APIs from abuse while maintaining fair access for legitimate users across global regions.

Canva
System Design
Software Engineer
Canva
April 5, 2025
Software Engineer
System Design
System Design
Medium

8

4

3,245 solved


Design a rate limiting system that protects Canva's APIs from abuse while maintaining fair access for legitimate users across global regions.

As Canva's platform grows with external APIs and integrations, rate limiting becomes critical to protect backend services. The system must handle millions of API calls with low latency overhead while supporting per-user, per-endpoint, and global rate limits.

What the Interviewer Expects
  • Compare rate limiting algorithms (fixed window, sliding window, token bucket, leaky bucket)
  • Design a distributed rate limiter that works across multiple API gateway instances
  • Handle rate limiting for authenticated and unauthenticated users differently
  • Ensure rate limiting adds minimal latency overhead to API requests
  • Discuss graceful degradation when the rate limiter itself is unavailable
Key Topics to Cover
Rate limiting algorithms and trade-offs
Distributed counting with Redis
API gateway integration
Graceful degradation patterns
How to Approach This
  1. Start by clarifying functional and non-functional requirements with the interviewer.
  2. Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
  3. Draw a high-level architecture first, then deep dive into 1-2 critical components.
  4. Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
  5. Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
  • How would you handle rate limiting across multiple geographic regions?
  • How would you implement tiered rate limits for free vs paid API users?
  • What happens if the central rate limit store (Redis) goes down?
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Sample Answer
Requirements

Functional Requirements

  1. Rate Limits: Implement per-user, per-endpoint, and global rate limits to control API access.
  2. User Authentication: Differentiate between authenticated and unau...
Capacity Estimation

To estimate the capacity:

  1. User Base: Assume 10 million active users.
  2. API Calls: Each user makes an average of 50 API calls per day.
  3. Peak Load: During peak hours, assume 20% of use...

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