Architect a event-driven Ad Serving Engine
Last updated: December 30, 2025
Quick Overview
Design a event-driven ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Robinhood
December 30, 2025295
12
4,876 solved
Design a event-driven ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Robinhood asks this during the System Design Round 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
- Systematically gather requirements and estimate capacity (QPS, storage, bandwidth)
- Design a scalable architecture with clear component responsibilities
- Make well-reasoned database and caching decisions with trade-off analysis
- Address consistency vs availability trade-offs specific to the use case
- Discuss partitioning strategy, replication, and data modeling
- Cover failure handling, monitoring, and alerting strategies
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 implement rate limiting to protect the system?
- How would you handle schema migrations with zero downtime?
- How would you optimize costs as the system scales?
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Requirements
Functional Requirements
- Ad Serving: Serve targeted ads based on user behavior and preferences in real-time.
- Event Processing: Process user events (e.g., app opens, trades, etc.) to u...
Capacity Estimation
Assuming Robinhood has approximately 10 million daily active users:
- Peak Load: If we estimate that 20% of users will be active simultaneously during peak hours, we can expect 2 million concurre...
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