Build a geo-distributed Ad Serving Pipeline
Last updated: August 29, 2025
Quick Overview
Design a geo-distributed ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Figma
August 29, 202551
13
4,845 solved
Design a geo-distributed ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Figma 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
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 happens if one of your database nodes goes down?
- How would you handle a 10x increase in traffic overnight?
- How would you handle a region-wide outage?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
- Functional Requirements:
- Serve targeted ads to users based on their location, user profile, and real-time bidding (RTB) responses.
- Provide an API for ad creatives management, user segmen...
Capacity Estimation
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Assumptions:
- Peak traffic of 1 million requests per second (RPS) globally.
- Average response size of 1 KB per ad request.
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Calculations:
- Total Requests per Day: 1,000,000 RP...
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