Design a multi-tenant Recommendation System
Last updated: November 12, 2025
Quick Overview
Design a multi-tenant recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Coinbase
System Design
Software Engineer
Coinbase
November 12, 2025Software Engineer
System Design Round
System Design
Medium
80
12
279 solved
Design a multi-tenant recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Coinbase asks this during the System Design Round 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
- 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
Failure handling and fault tolerance
High-level architecture and component design
Database selection and data modeling
Requirements gathering and capacity estimation
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 implement rate limiting to protect the system?
- How would you handle a 10x increase in traffic overnight?
- How do you ensure data consistency across multiple services?
- How would you handle schema migrations with zero downtime?
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Requirements
Functional Requirements:
- Multi-Tenant Support: The system must handle recommendations for multiple clients (tenants) independently while sharing resources.
- Real-Time Recommendations:...
Capacity Estimation
- User Base Estimation: Let's assume 10 million users across all tenants.
- QPS Calculation: If each user makes 5 recommendation requests per day, total requests per day = 10 million users *...
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