Design Monitoring Infrastructure for microservices
Last updated: August 25, 2025
Quick Overview
Design a geo-distributed monitoring system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
HRT
August 25, 20259
14
3,296 solved
Design a geo-distributed monitoring system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
HRT asks this during the Technical Screen 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
- How would you handle schema migrations with zero downtime?
- How would you implement rate limiting to protect the system?
- What monitoring and alerting would you set up on day one?
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Requirements
Functional Requirements
- Data Ingestion: The system should ingest monitoring data from multiple microservices across various regions, supporting metrics, logs, and traces.
- *Data Storage...
Capacity Estimation
Assuming HRT has around 1,000 microservices, each generating about 10 metrics every second (and logs), we can do some calculations:
- Requests per Second (RPS): 1,000 services * 10 metrics = 10,0...
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