Design Analytics Infrastructure for microservices
Last updated: November 6, 2025
Quick Overview
Design a real-time analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
MongoDB
November 6, 20256
6
2,668 solved
Design a real-time analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
MongoDB 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
- 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
- What would the deployment pipeline look like for this system?
- How would you implement rate limiting to protect the system?
- What happens if one of your database nodes goes down?
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