Design a Load Balancing for Datadog
Last updated: October 14, 2025
Quick Overview
Design a multi-tenant load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Datadog
October 14, 20258
5
3,910 solved
Design a multi-tenant load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This ML system design question from Datadog's Onsite tests your ability to think about ML systems at scale. The interviewer expects discussion of data quality, feature stores, model serving infrastructure, and A/B testing strategy.
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
- What is your model retraining strategy?
- How would you handle the cold start problem?
- How would you ensure fairness and reduce bias in the model?
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