Architect a geo-distributed Inventory Management Engine
Last updated: May 22, 2026
Quick Overview
Design a geo-distributed inventory management system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Booking.com
May 22, 2026118
3
1,016 solved
Design a geo-distributed inventory management 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 a region-wide outage?
- What monitoring and alerting would you set up on day one?
- How would you handle schema migrations with zero downtime?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
Functional Requirements
- Inventory Tracking: The system should maintain real-time inventory levels for millions of items across multiple geographic locations.
- Booking Management: User...
Capacity Estimation
Assuming Booking.com has roughly 1 million active users at peak times and each user makes about 10 requests per minute:
- Total QPS:
- Active users: 1,000,000
- Requests per user: 10
- T...
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