Architect a real-time Rate Limiting Engine
Last updated: March 26, 2026
Quick Overview
Design a real-time rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
MongoDB
System Design
Machine Learning Engineer
MongoDB
March 26, 2026Machine Learning Engineer
Onsite
System Design
Medium
10
12
3,936 solved
Design a real-time 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
Partitioning and sharding strategies
Failure handling and fault tolerance
Security and authentication
Database selection and data modeling
High-level architecture and component design
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?
- What would the deployment pipeline look like for this system?
- What monitoring and alerting would you set up on day one?
- What happens if one of your database nodes goes down?
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Requirements
- Functional Requirements:
- Allow users to define rate limits per API endpoint.
- Track usage per user/API key in real-time.
- Support burst traffic while enforcing limits.
- Provide a da...
Capacity Estimation
- Request Rate: Assume we need to handle 5 million requests per second (QPS).
- User Base: Estimating 1 million active users, each making an average of 5 requests per second.
- **Storage Needs...
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