Design a geo-distributed Rate Limiting System
Last updated: July 9, 2025
Quick Overview
Design a geo-distributed rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
MongoDB
System Design
Software Engineer
MongoDB
July 9, 2025Software Engineer
Onsite
System Design
Medium
30
4
2,398 solved
Design a geo-distributed rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
MongoDB asks this during the Onsite to assess your architectural thinking. They want to see how you decompose a complex problem, choose appropriate technologies, and reason about failure modes. Strong candidates proactively discuss monitoring, alerting, and operational concerns.
What the Interviewer Expects
- Systematically gather requirements and estimate capacity (QPS, storage, bandwidth)
- Design a scalable architecture with clear component responsibilities
- Make well-reasoned database and caching decisions with trade-off analysis
- Address consistency vs availability trade-offs specific to the use case
- Discuss partitioning strategy, replication, and data modeling
- Cover failure handling, monitoring, and alerting strategies
Key Topics to Cover
Monitoring, logging, and alerting
Security and authentication
Database selection and data modeling
Partitioning and sharding strategies
Failure handling and fault tolerance
Load balancing and horizontal scaling
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 handle a region-wide outage?
- How would you handle a 10x increase in traffic overnight?
- How would you migrate from a monolithic to a microservices architecture?
- How do you ensure data consistency across multiple services?
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Requirements
- Functional Requirements:
- The system must enforce rate limits based on user-defined policies (e.g., 100 requests per minute).
- Support geo-distributed clients, allowing rate limits t...
Capacity Estimation
- Assumptions:
- Assume a user base of 10 million active users, with each user making an average of 10 requests per minute.
- This leads to a total of 1 billion requests per minute.
-...
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