Design a Caching Service
Last updated: October 16, 2025
Quick Overview
Design a fault-tolerant caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Microsoft
October 16, 202554
10
1,591 solved
Design a fault-tolerant caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Microsoft 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 monitoring and alerting would you set up on day one?
- How would you optimize costs as the system scales?
- What happens if one of your database nodes goes down?
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Requirements
Functional Requirements
- Key-Value Store: Ability to store and retrieve objects by unique keys.
- TTL (Time-To-Live): Support for setting expiration times on cached data.
- **Cache Inv...
Capacity Estimation
Assuming our caching service will serve 100 million requests per day, we can break this down:
- Requests per second: 100 million / 86400 seconds = ~1157 requests/second.
- Data Size: Assuming ...
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