Design Feed Generation Infrastructure for IoT devices
Last updated: February 6, 2026
Quick Overview
Design a distributed feed generation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
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Design a distributed feed generation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
ML system design at Pinterest goes beyond model selection. This System Design Round question evaluates your ability to design end-to-end ML pipelines, from data collection to model serving, while considering production constraints like latency and reliability.
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 handle a 10x increase in prediction requests?
- How would you ensure fairness and reduce bias in the model?
- What would you do if model performance degrades over time?
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Requirements
Functional Requirements
- Feed Generation: Generate personalized feeds for IoT devices based on user preferences and behavior.
- Real-time Updates: Provide real-time updates to feeds as ...
Capacity Estimation
Assuming Pinterest has approximately 500 million active users and each user interacts with the feed generation system 10 times daily via IoT devices:
- Total Daily Requests: 500 million users * 1...
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