Design a fault-tolerant Order Processing System
Last updated: May 1, 2026
Quick Overview
Design a fault-tolerant order processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
CrowdStrike
May 1, 2026106
6
3,060 solved
Design a fault-tolerant order processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
CrowdStrike 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 handle a 10x increase in prediction requests?
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Requirements
Functional Requirements
- Order Creation: Users can place new orders via a web interface or API.
- Order Tracking: Users can track the status of their orders in real-time.
- **Payment P...
Capacity Estimation
Assuming CrowdStrike processes 1 million orders per day:
- Peak Load: During peak hours, let’s assume 20% of orders are processed (200,000 orders/hour or approximately 55 orders/second).
- **Data ...
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