Design Caching Infrastructure for real-time analytics
Last updated: July 29, 2025
Quick Overview
Design a distributed caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Compass
July 29, 202543
3
1,203 solved
Design a distributed caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Compass 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
- Drive the design discussion proactively with minimal interviewer guidance
- Perform detailed capacity estimation and use it to inform design decisions
- Design for global scale with multi-region deployment and data consistency
- Deep dive into 2-3 critical components with implementation-level detail
- Address complex trade-offs: CAP theorem, eventual consistency, conflict resolution
- Discuss operational excellence: deployment strategy, chaos engineering, SLOs/SLIs
- Propose a phased rollout plan from MVP to full-scale system
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 happens if one of your database nodes goes down?
- How would you implement rate limiting to protect the system?
- How do you ensure data consistency across multiple services?
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Requirements
Functional Requirements
- Real-time Data Caching: The system should cache data from various analytics sources to serve real-time queries with low latency.
- Multi-region Support: The sys...
Capacity Estimation
Assuming Compass has approximately 10 million active users, with each user making an average of 5 requests per minute:
- Total Requests per Minute: 10M users * 5 requests/user = 50M requests/minut...
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