Build a multi-tenant Order Processing Pipeline
Last updated: January 13, 2026
Quick Overview
Design a multi-tenant order processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Capital One
January 13, 202698
8
1,908 solved
Design a multi-tenant order processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Capital One asks this during the Onsite to assess your understanding of the full ML lifecycle. They want to see how you translate a business problem into an ML objective, design the feature pipeline, and plan for model monitoring and retraining.
What the Interviewer Expects
- Map the business problem to a concrete ML objective
- Propose reasonable features and a baseline model
- Discuss basic model evaluation metrics
- Outline a simple serving architecture
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 ensure fairness and reduce bias in the model?
- What would you do if model performance degrades over time?
- How would you run A/B tests on different model versions?
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Requirements
Functional Requirements
- Multi-Tenancy: The system should support multiple tenants (e.g., different business units within Capital One) with data isolation.
- Order Processing: Should ha...
Capacity Estimation
Assuming Capital One processes 100 million orders annually:
- Daily Orders: 100 million / 365 ≈ 274,000 orders/day.
- Peak Load: Assuming peak hours can handle 10% of daily orders:
- Peak or...
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