Build a geo-distributed Rate Limiting Pipeline
Last updated: February 22, 2026
Quick Overview
Design a geo-distributed rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Rippling
February 22, 20264
4
1,845 solved
Design a geo-distributed rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Rippling asks this during the Technical Screen 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
- 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 handle a 10x increase in traffic overnight?
- How would you handle a region-wide outage?
- What happens if one of your database nodes goes down?
- How do you ensure data consistency across multiple services?
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Requirements
Functional Requirements
- API Endpoints: Provide endpoints to set, get, and delete rate limits for specific users or IPs.
- Rate Limiting: Implement a geo-distributed rate limiting mec...
Capacity Estimation
Assuming Rippling handles 1 million requests per day per customer and has 1000 customers, we can estimate:
- Total Requests: 1,000,000 requests/customer * 1000 customers = 1,000,000,000 requests/d...
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