Design Caching Infrastructure for global users
Last updated: September 14, 2025
Quick Overview
Design a event-driven caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
CrowdStrike
System Design
Software Engineer
CrowdStrike
September 14, 2025Software Engineer
Onsite
System Design
Medium
4
5
4,725 solved
Design a event-driven caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
CrowdStrike asks this during the Onsite 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
Message queues and async processing
Partitioning and sharding strategies
Consistency models and replication
High-level architecture and component design
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 would the deployment pipeline look like for this system?
- How do you ensure data consistency across multiple services?
- How would you optimize costs as the system scales?
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Requirements
Functional Requirements
- Event Processing: Handle millions of incoming requests related to threat detection events globally.
- Caching: Store frequently accessed data (e.g., user sessio...
Capacity Estimation
To estimate capacity:
- User Base: Assume 1 million active users.
- Requests per User: Each user generates about 10 requests per minute.
- Total Requests per Second (QPS): 1M users * 10...
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