Design Search Infrastructure for IoT devices

Last updated: October 6, 2025

Quick Overview

Design a multi-tenant search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Robinhood
System Design
Software Engineer
Robinhood
October 6, 2025
Software Engineer
System Design Round
System Design
Hard

10

6

2,418 solved


Design a multi-tenant search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

ML system design at Robinhood 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
  • Design the full ML lifecycle from data collection to model monitoring
  • Address cold start, exploration/exploitation, and model freshness
  • Discuss multi-objective optimization and ranking systems
  • Plan for model debugging, fairness, and bias mitigation
  • Design the feature store and training pipeline for scale
  • Address model versioning, canary deployments, and rollback strategies
  • Discuss the data flywheel and long-term system evolution
Key Topics to Cover
Model serving and latency optimization
A/B testing and experimentation
Model selection and architecture
Data collection and labeling strategy
Monitoring and model degradation detection
How to Approach This
  1. Start by clarifying functional and non-functional requirements with the interviewer.
  2. Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
  3. Draw a high-level architecture first, then deep dive into 1-2 critical components.
  4. Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
  5. Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
  • How would you ensure fairness and reduce bias in the model?
  • How would you handle a 10x increase in prediction requests?
  • What is your model retraining strategy?
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Sample Answer
Requirements

Functional Requirements

  1. Multi-tenant Architecture: Support multiple IoT devices from various tenants with isolation of data and processing.
  2. Search Functionality: Fast and relevant se...
Capacity Estimation

Assuming Robinhood has around 10 million IoT devices, each generating an average of 1 request per second:

  1. Total Requests per Second: 10 million requests.
  2. Daily Requests: 10 million requ...

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