Design a large-scale Rate Limiting Platform
Last updated: October 30, 2025
Quick Overview
Design a fault-tolerant rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
MongoDB
October 30, 2025569
12
3,537 solved
Design a fault-tolerant rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at MongoDB typically last 45-60 minutes. You are expected to drive the conversation, starting from requirements gathering through to a detailed architecture. The interviewer will evaluate your ability to handle ambiguity and make practical engineering decisions.
What the Interviewer Expects
- Clearly define functional and non-functional requirements
- Propose a reasonable high-level architecture with core components
- Choose appropriate data storage solutions with basic justification
- Discuss basic scaling strategies (horizontal scaling, caching)
- Identify potential bottlenecks and suggest simple solutions
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
- How would you implement rate limiting to protect the system?
- How would you handle a 10x increase in traffic overnight?
- What happens if one of your database nodes goes down?
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Requirements
Functional Requirements:
- Rate Limiting: The system should allow setting limits on the number of API requests per user, per IP address, or per application within a defined timeframe (e.g., 1...
Capacity Estimation
Assuming we need to handle 1 million users, each making up to 100 requests per minute:
- Total Requests: 1,000,000 users * 100 requests/minute = 100,000,000 requests/minute.
- Throughput: 100,...
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