Design a real-time Caching System
Last updated: November 21, 2025
Quick Overview
Design a real-time caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
CrowdStrike
November 21, 20252
14
4,897 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 Onsite at CrowdStrike. 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. CrowdStrike 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 implement rate limiting to protect the system?
- How would you handle a 10x increase in traffic overnight?
- How would you handle a region-wide outage?
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Requirements
Functional Requirements
- Real-time Data Retrieval: The caching system must provide low-latency access to frequently requested data.
- Data Invalidation: The system should support mechan...
Capacity Estimation
Assuming CrowdStrike has 1 million active users, with each user making approximately 10 requests per second, we can estimate:
- Total Requests: 1 million users * 10 requests/user = 10 million requ...
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