Design a large-scale Ad Serving Platform
Last updated: March 10, 2026
Quick Overview
Design a low-latency ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Databricks
System Design
Software Engineer
Databricks
March 10, 2026Software Engineer
System Design Round
System Design
Hard
135
8
2,513 solved
Design a low-latency ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Databricks 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
- 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
Partitioning and sharding strategies
High-level architecture and component design
Requirements gathering and capacity estimation
Monitoring, logging, and alerting
Message queues and async processing
API design and rate limiting
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 schema migrations with zero downtime?
- How would you handle a region-wide outage?
- How do you ensure data consistency across multiple services?
- How would you implement rate limiting to protect the system?
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Requirements
Functional Requirements:
- Ad Request Handling: The system must handle millions of ad requests per second, delivering relevant ads based on user context and targeting criteria.
- **Real-time...
Capacity Estimation
Capacity Estimation:
- Traffic Volume: Assume the platform will handle 10 million ad requests per second at peak, with an average response size of 1 KB.
- Data Storage: Each ad request g...
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