Design a large-scale Search Platform
Last updated: May 22, 2026
Quick Overview
Design a event-driven search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Tesla
May 22, 2026440
5
1,402 solved
Design a event-driven search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
ML system design at Tesla 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?
- How would you debug a model that works well offline but poorly online?
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Requirements
Functional Requirements
- Search Query Handling: The system should handle keyword-based search queries and return relevant results in real-time.
- Event-Driven Updates: The search index ...
Capacity Estimation
Assuming Tesla has approximately 1 million active users per day, with an average of 10 search queries per user, we expect:
- Total Requests Per Day: 1,000,000 users * 10 queries = 10,000,000 queri...
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