Design a large-scale Recommendation Platform
Last updated: September 13, 2025
Quick Overview
Design a distributed recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Datadog
System Design
Software Engineer
Datadog
September 13, 2025Software Engineer
System Design Round
System Design
Medium
13
11
2,318 solved
Design a distributed recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Datadog 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
Partitioning and sharding strategies
Requirements gathering and capacity estimation
High-level architecture and component design
Failure handling and fault tolerance
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 implement rate limiting to protect the system?
- How would you migrate from a monolithic to a microservices architecture?
- How would you handle a 10x increase in traffic overnight?
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Requirements
Functional Requirements:
- User Profile Management: Store user preferences, viewing history, and interactions for personalized recommendations.
- Recommendation Engine: Generate real-tim...
Capacity Estimation
Capacity Estimates:
- User Base: Assume 10 million active users.
- Requests per User: Assume each user sends an average of 10 requests per day for recommendations.
- **Total Daily Reque...
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