Architect a event-driven Caching Engine
Last updated: January 30, 2026
Quick Overview
Design a event-driven caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Neon
System Design
Software Engineer
Neon
January 30, 2026Software Engineer
System Design Round
System Design
Hard
43
7
2,063 solved
Design a event-driven caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Neon asks this during the System Design Round 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
- 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
Consistency models and replication
High-level architecture and component design
Database selection and data modeling
Monitoring, logging, and alerting
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 region-wide outage?
- How would you handle a 10x increase in traffic overnight?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
- Functional Requirements:
- Support millions of read/write requests per second with low latency.
- Provide a caching mechanism for frequently accessed data, including support for TTL (Time-To...
Capacity Estimation
- Traffic Estimation:
- Assume an application serving 1 million users, with an average of 100 requests per user per day.
- Total requests per day = 1,000,000 users * 100 requests = 100,000,000...
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