Design Image Processing Infrastructure for IoT devices
Last updated: March 16, 2026
Quick Overview
Design a high-throughput image processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Lyft
March 16, 2026140
15
841 solved
Design a high-throughput image processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during System Design Round at Lyft. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Lyft values engineers who can think about scalability from day one.
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 monitoring and alerting would you set up on day one?
- 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 Uploading: IoT devices must be able to upload images to the processing infrastructure.
- Image Processing: The system should support various processing ta...
Capacity Estimation
Assuming Lyft's IoT devices generate approximately 1 million images per day, we can break down the capacity estimation as follows:
- Requests per second (RPS): 1,000,000 images / 86,400 seconds ≈...
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