Design a Logging Service
Last updated: June 3, 2026
Quick Overview
Design a distributed logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Booking.com
June 3, 202635
9
3,106 solved
Design a distributed logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Booking.com asks this during the System Design Round 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
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 optimize costs as the system scales?
- What monitoring and alerting would you set up on day one?
- How would you handle a 10x increase in traffic overnight?
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Requirements
- Functional Requirements:
- Collect logs from various services across Booking.com, including web applications, mobile apps, and backend services.
- Support real-time log ingestion and queryin...
Capacity Estimation
Assuming Booking.com processes approximately 1 billion requests per day:
-
Requests per second (QPS):
- 1 billion requests / 86400 seconds = ~11,574 requests per second.
-
Log Size:
- A...
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