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, 2025
Software 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
  1. Start by clarifying functional and non-functional requirements with the interviewer.
  2. Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
  3. Draw a high-level architecture first, then deep dive into 1-2 critical components.
  4. Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
  5. 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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Sample Answer
Requirements Clarification

Before diving into the architecture, clarify the scope with the interviewer. For large-scale Recommendation Platform, key functional requirements incl...

Capacity Estimation

Estimate the scale to drive design decisions. Assume 100M DAU with an average of 10 actions per user per day = 1B requests/day ~ 12K QPS average, ~36K...


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