Design Recommendation Infrastructure for real-time analytics
Last updated: December 17, 2025
Quick Overview
Design a high-throughput recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Mastercard
System Design
Software Engineer
Mastercard
December 17, 2025Software Engineer
Technical Screen
System Design
Medium
38
7
1,610 solved
Design a high-throughput recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Mastercard typically last 45-60 minutes. You are expected to drive the conversation, starting from requirements gathering through to a detailed architecture. The interviewer will evaluate your ability to handle ambiguity and make practical engineering decisions.
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
Database selection and data modeling
Load balancing and horizontal scaling
High-level architecture and component design
Security and authentication
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 monitoring and alerting would you set up on day one?
- How would you implement rate limiting to protect the system?
- How would you optimize costs as the system scales?
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Requirements
Functional Requirements
- Real-time Recommendations: The system should provide personalized recommendations to users based on their transaction history, preferences, and current trends.
- **...
Capacity Estimation
Back-of-Envelope Calculations
- Estimated Daily Active Users (DAUs): Assume 50 million users.
- QPS Calculation: During peak hours, let’s assume 20% of users are active, leading to 10 mi...
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