Design Caching Infrastructure for mobile apps
Last updated: November 27, 2025
Quick Overview
Design a scalable caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Dropbox
November 27, 202515
15
3,200 solved
Design a scalable caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Dropbox asks this during the Technical Screen 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
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 a 10x increase in traffic overnight?
- How would you implement rate limiting to protect the system?
- How would you handle schema migrations with zero downtime?
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Requirements
Functional Requirements
- Cache Read Requests: The system should handle cache read requests from mobile apps for frequently accessed data such as user profiles, shared files, and metadata. 2....
Capacity Estimation
Assuming Dropbox has 500 million active users and each user makes approximately 10 requests per day for cached data:
- Total Daily Requests: 500 million users * 10 requests/user = 5 billion requ...
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