Design a low-latency Order Processing System
Last updated: July 2, 2025
Quick Overview
Design a low-latency order processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
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Design a low-latency order processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at LinkedIn 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
- 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
- What would the deployment pipeline look like for this system?
- How would you handle a 10x increase in traffic overnight?
- How would you optimize costs as the system scales?
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Requirements
Functional Requirements
- Order Submission: Users should be able to submit orders in real-time via a web interface or API.
- Order Status Tracking: Users must be able to query the status...
Capacity Estimation
Assuming LinkedIn has around 800 million users:
- Daily Active Users (DAU): Let's say 10% are active daily, which is 80 million users.
- Order Submission Rate: If each user submits an average ...
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