Design a Order Processing Service
Last updated: November 27, 2025
Quick Overview
Design a scalable order processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Figma
November 27, 2025207
3
453 solved
Design a scalable order processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Figma 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
- Clearly define functional and non-functional requirements
- Propose a reasonable high-level architecture with core components
- Choose appropriate data storage solutions with basic justification
- Discuss basic scaling strategies (horizontal scaling, caching)
- Identify potential bottlenecks and suggest simple solutions
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 handle a region-wide outage?
- How would you optimize costs as the system scales?
- What would the deployment pipeline look like for this system?
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Requirements
Functional Requirements
- Order Creation: Users can create new orders with product details, quantity, and payment information.
- Order Status Tracking: Users must be able to track the st...
Capacity Estimation
Assuming Figma has around 10 million users who may place orders:
- Daily Active Users: 1 million (10% of total users).
- Orders per User: Assume each active user places 1 order on average per ...
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