Architect a high-throughput Rate Limiting Engine
Last updated: March 22, 2026
Quick Overview
Design a high-throughput rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
TikTok
March 22, 20260
11
3,736 solved
Design a high-throughput rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during Onsite at TikTok. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. TikTok values engineers who can think about scalability from day one.
What the Interviewer Expects
- Drive the design discussion proactively with minimal interviewer guidance
- Perform detailed capacity estimation and use it to inform design decisions
- Design for global scale with multi-region deployment and data consistency
- Deep dive into 2-3 critical components with implementation-level detail
- Address complex trade-offs: CAP theorem, eventual consistency, conflict resolution
- Discuss operational excellence: deployment strategy, chaos engineering, SLOs/SLIs
- Propose a phased rollout plan from MVP to full-scale system
Key Topics to Cover
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- What happens if one of your database nodes goes down?
- How would you migrate from a monolithic to a microservices architecture?
- What would the deployment pipeline look like for this system?
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Requirements
Functional Requirements
- Rate Limiting: Support various rate-limiting algorithms (e.g., token bucket, leaky bucket) to restrict user actions (e.g., video uploads, comments).
- **User Identi...
Capacity Estimation
Back-of-Envelope Calculations
- Traffic Estimation: Assume TikTok has 1 billion active users. If each user makes an average of 5 requests per minute, total requests per minute would be:
- ...
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