Design a large-scale Image Processing Platform
Last updated: August 29, 2025
Quick Overview
Design a scalable image processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Shopify
August 29, 202530
9
1,007 solved
Design a scalable image processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Shopify 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?
- What happens if one of your database nodes goes down?
- How would you handle a 10x increase in traffic overnight?
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Requirements
Functional Requirements
- Image Upload: Users must be able to upload images via a REST API.
- Image Processing: Support operations such as resizing, cropping, and format conversion.
- *...
Capacity Estimation
Assuming Shopify processes 100 million images per month:
- Daily Requests: 100 million / 30 = ~3.33 million requests/day.
- Peak Load: Assuming peak hours account for 30% of daily traffic, it ...
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