Design a large-scale URL Shortening Platform
Last updated: December 2, 2025
Quick Overview
Design a scalable url shortening system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Booking.com
December 2, 20253
4
3,876 solved
Design a scalable url shortening system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Booking.com asks this during the Onsite to assess your understanding of the full ML lifecycle. They want to see how you translate a business problem into an ML objective, design the feature pipeline, and plan for model monitoring and retraining.
What the Interviewer Expects
- Design the full ML lifecycle from data collection to model monitoring
- Address cold start, exploration/exploitation, and model freshness
- Discuss multi-objective optimization and ranking systems
- Plan for model debugging, fairness, and bias mitigation
- Design the feature store and training pipeline for scale
- Address model versioning, canary deployments, and rollback strategies
- Discuss the data flywheel and long-term system evolution
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 run A/B tests on different model versions?
- How would you debug a model that works well offline but poorly online?
- What would you do if model performance degrades over time?
Practice a Similar Problem on Codemia
Solve a related problem with our interactive workspace, get AI feedback, and view detailed solutions.
Solve on CodemiaSample Answer
Requirements
Functional Requirements:
- URL Shortening: Users can input a long URL and receive a shortened version.
- Redirection: When the shortened URL is accessed, it should redirect to the origin...
Capacity Estimation
Assuming an average of 10 million URL shortening requests per day:
- Requests per Second: 10,000,000 requests/day ÷ 86,400 seconds/day = ~115.74 requests/second.
- Storage Requirements: Each...
Submit Your Answer
