Design a Rate Limiting for Twilio
Last updated: April 17, 2026
Quick Overview
Design a fault-tolerant rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Twilio
April 17, 202632
6
964 solved
Design a fault-tolerant rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This ML system design question from Twilio's System Design Round tests your ability to think about ML systems at scale. The interviewer expects discussion of data quality, feature stores, model serving infrastructure, and A/B testing strategy.
What the Interviewer Expects
- Map the business problem to a concrete ML objective
- Propose reasonable features and a baseline model
- Discuss basic model evaluation metrics
- Outline a simple serving architecture
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 is your model retraining strategy?
- How would you handle the cold start problem?
- How would you run A/B tests on different model versions?
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Requirements
- Functional Requirements:
- Rate limiting based on user ID and API key to control the number of requests per time window (e.g., 100 requests per minute).
- Support for configurable rate...
Capacity Estimation
Assuming Twilio handles approximately 10 million requests per day, we can break this down:
- Requests per second (RPS):
- 10 million requests / 86400 seconds = ~115.74 requests/second.
To...
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