Build a distributed Ad Serving Pipeline
Last updated: December 2, 2025
Quick Overview
Design a distributed ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Splunk
December 2, 2025101
15
4,070 solved
Design a distributed ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Splunk 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
- Clearly define functional and non-functional requirements
- Propose a reasonable high-level architecture with core components
- Choose appropriate data storage solutions with basic justification
- Discuss basic scaling strategies (horizontal scaling, caching)
- Identify potential bottlenecks and suggest simple solutions
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 handle a 10x increase in traffic overnight?
- 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 requests per second from users wanting to display ads.
- Ad Targeting: It should serve relevant ads bas...
Capacity Estimation
Assuming Splunk handles 100 million active users and each user generates 10 ad requests per minute:
- Total Requests: 100 million users * 10 requests/user/minute = 1 billion requests/minute.
- *...
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