Architect a scalable A/B Testing Engine
Last updated: November 12, 2025
Quick Overview
Design a scalable a/b testing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Vercel
November 12, 202512
4
2,483 solved
Design a scalable a/b testing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Vercel typically last 45-60 minutes. You are expected to drive the conversation, starting from requirements gathering through to a detailed architecture. The interviewer will evaluate your ability to handle ambiguity and make practical engineering decisions.
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
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 monitoring and alerting would you set up on day one?
- How would you handle schema migrations with zero downtime?
- How do you ensure data consistency across multiple services?
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Requirements
Functional Requirements
- User Segmentation: Ability to segment users based on various criteria (geography, device type, etc.).
- Experiment Creation: Users can create A/B tests, specify...
Capacity Estimation
Assuming a user base of 10 million with an average of 1 A/B test per user:
- Requests per Second (QPS):
- Peak request handling: 1 million concurrent users (10% of user base)
- 5 requests/us...
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