Architect a fault-tolerant Logging Engine
Last updated: November 27, 2025
Quick Overview
Design a fault-tolerant logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
ServiceNow
System Design
Software Engineer
ServiceNow
November 27, 2025Software Engineer
Onsite
System Design
Medium
105
8
2,786 solved
Design a fault-tolerant logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
ServiceNow 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
- Systematically gather requirements and estimate capacity (QPS, storage, bandwidth)
- Design a scalable architecture with clear component responsibilities
- Make well-reasoned database and caching decisions with trade-off analysis
- Address consistency vs availability trade-offs specific to the use case
- Discuss partitioning strategy, replication, and data modeling
- Cover failure handling, monitoring, and alerting strategies
Key Topics to Cover
Caching strategies (local, distributed, CDN)
API design and rate limiting
Requirements gathering and capacity estimation
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
- What would the deployment pipeline look like for this system?
- How would you handle schema migrations with zero downtime?
- How do you ensure data consistency across multiple services?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
- Functional Requirements:
- The logging engine must accept log entries from various sources (applications, services) via a REST API.
- Log entries should be categorized (e.g., INFO, WARN, ERR...
Capacity Estimation
- Traffic Estimation:
- Assuming 10,000 QPS, each log entry averages 500 bytes in size.
- Daily log throughput = 10,000 QPS * 60 seconds * 60 minutes * 24 hours = 864,000,000 log entries.
- ...
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