Design a large-scale Monitoring Platform
Last updated: August 1, 2025
Quick Overview
Design a low-latency monitoring system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Redfin
August 1, 202523
4
4,646 solved
Design a low-latency monitoring 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 Redfin. 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. Redfin 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
- What monitoring and alerting would you set up on day one?
- How would you handle a region-wide outage?
- How would you handle a 10x increase in traffic overnight?
- What happens if one of your database nodes goes down?
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Requirements
- Functional Requirements:
- Real-time monitoring of system metrics (CPU, memory, request latency, error rates) from multiple services.
- Ability to aggregate and visualize metrics on a dashbo...
Capacity Estimation
Assuming 10 million requests per day, this translates to approximately:
- Requests per second: 10,000 requests / (24 hours * 3600 seconds) = ~115 requests/second.
- Data Storage Needs: If we a...
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