Build a fault-tolerant Logging Pipeline
Last updated: June 12, 2026
Quick Overview
Design a fault-tolerant logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Zoom
System Design
Software Engineer
Zoom
June 12, 2026Software Engineer
Onsite
System Design
Easy
19
5
2,912 solved
Design a fault-tolerant logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Zoom 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
Security and authentication
High-level architecture and component design
Caching strategies (local, distributed, CDN)
Consistency models and replication
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 do you ensure data consistency across multiple services?
- How would you handle a 10x increase in traffic overnight?
- How would you handle a region-wide outage?
- What happens if one of your database nodes goes down?
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Requirements
- Functional Requirements:
- Capture logs from multiple services (e.g., video calls, user interactions) in real-time.
- Ensure logs include metadata such as timestamp, user ID, session I...
Capacity Estimation
- Traffic Estimation:
- Assume Zoom has approximately 300 million daily active users.
- In peak periods, let’s say 10% of users are active, resulting in 30 million users.
- If each use...
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