Build a fault-tolerant URL Shortening Pipeline
Last updated: September 8, 2025
Quick Overview
Design a fault-tolerant url shortening system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Adobe
September 8, 202521
6
456 solved
Design a fault-tolerant url shortening system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Adobe asks this during the System Design Round 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
- 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 a 10x increase in prediction requests?
- How would you run A/B tests on different model versions?
- How would you debug a model that works well offline but poorly online?
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 Clarification
Before diving into the architecture, clarify the scope with the interviewer. For fault-tolerant URL Shortening Pipeline, key functional requirements i...
Capacity Estimation
Estimate the scale to drive design decisions. Assume 100M DAU with an average of 10 actions per user per day = 1B requests/day ~ 12K QPS average, ~36K...
Submit Your Answer
