Design Ad Serving Infrastructure for global users
Last updated: September 22, 2025
Quick Overview
Design a low-latency ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
NVIDIA
September 22, 202575
8
867 solved
Design a low-latency ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
NVIDIA asks this during the Onsite to assess your architectural thinking. They want to see how you decompose a complex problem, choose appropriate technologies, and reason about failure modes. Strong candidates proactively discuss monitoring, alerting, and operational concerns.
What the Interviewer Expects
- Drive the design discussion proactively with minimal interviewer guidance
- Perform detailed capacity estimation and use it to inform design decisions
- Design for global scale with multi-region deployment and data consistency
- Deep dive into 2-3 critical components with implementation-level detail
- Address complex trade-offs: CAP theorem, eventual consistency, conflict resolution
- Discuss operational excellence: deployment strategy, chaos engineering, SLOs/SLIs
- Propose a phased rollout plan from MVP to full-scale system
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?
- How do you ensure data consistency across multiple services?
- What happens if one of your database nodes goes down?
- How would you handle schema migrations with zero downtime?
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Requirements
- Functional Requirements:
- Serve personalized ads to users based on their preferences and behavior.
- Support A/B testing for ad performance evaluation.
- Provide user segmentation and tar...
Capacity Estimation
To estimate capacity, let's assume:
- User Base: 1 billion monthly active users.
- Ad Requests: Each user makes 10 ad requests per day on average.
Calculations:
- Total ad requests per da...
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