Design Caching Infrastructure for global users
Last updated: December 19, 2025
Quick Overview
Design a multi-tenant caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Brex
System Design
Machine Learning Engineer
Brex
December 19, 2025Machine Learning Engineer
System Design Round
System Design
Medium
21
14
2,110 solved
Design a multi-tenant caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Brex 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
High-level architecture and component design
Requirements gathering and capacity estimation
Caching strategies (local, distributed, CDN)
Message queues and async processing
Monitoring, logging, and alerting
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 handle schema migrations with zero downtime?
- How would you migrate from a monolithic to a microservices architecture?
- How would you handle a 10x increase in traffic overnight?
- What monitoring and alerting would you set up on day one?
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Requirements
- Functional Requirements:
- Support multi-tenant architecture to cache data for different Brex users securely.
- Handle diverse data types including user profiles, transaction data, and confi...
Capacity Estimation
- Assumptions:
- Brex has approximately 1 million active users.
- Each user makes an average of 10 requests per second.
- Total requests per second (QPS) = 1 million users * 10 requests/user...
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