Build a real-time Caching Pipeline
Last updated: August 5, 2025
Quick Overview
Design a real-time caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Compass
August 5, 202561
6
4,488 solved
Design a real-time caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during System Design Round at Compass. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Compass values engineers who can think about scalability from day one.
What the Interviewer Expects
- Clearly define functional and non-functional requirements
- Propose a reasonable high-level architecture with core components
- Choose appropriate data storage solutions with basic justification
- Discuss basic scaling strategies (horizontal scaling, caching)
- Identify potential bottlenecks and suggest simple solutions
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 optimize costs as the system scales?
- What would the deployment pipeline look like for this system?
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Requirements
- Functional Requirements:
- Provide a caching layer that can store frequently accessed data to reduce latency.
- Support real-time updates to cache when underlying data changes.
- ...
Capacity Estimation
- Traffic Estimation:
Assuming Compass has 10 million users, with each user making roughly 100 caching requests per day, the system needs to handle about 1 billion requests per day.- **Re...
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