Design a large-scale Recommendation Platform
Last updated: December 26, 2025
Quick Overview
Design a fault-tolerant recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Expedia
System Design
Software Engineer
Expedia
December 26, 2025Software Engineer
System Design Round
System Design
Medium
47
13
1,661 solved
Design a fault-tolerant recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Expedia 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
API design and rate limiting
Failure handling and fault tolerance
High-level architecture and component design
Consistency models and replication
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 happens if one of your database nodes goes down?
- How do you ensure data consistency across multiple services?
- What would the deployment pipeline look like for this system?
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Requirements
Functional Requirements
- User Recommendations: Provide personalized recommendations for hotels, flights, and activities based on user preferences and browsing history.
- **Real-Time Updates...
Capacity Estimation
Back-of-Envelope Calculations
- User Base: Assume 50 million active users per month.
- Requests Per Second (QPS): If each user generates an average of 5 requests per day:
- Total dail...
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