Design a real-time Ad Serving System
Last updated: February 19, 2026
Quick Overview
Design a real-time ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Elastic
February 19, 202610
11
4,082 solved
Design a real-time ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during System Design Round at Elastic. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Elastic values engineers who can think about scalability from day one.
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
- How would you migrate from a monolithic to a microservices architecture?
- How would you handle a 10x increase in traffic overnight?
- How would you optimize costs as the system scales?
- How would you implement rate limiting to protect the system?
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Requirements
Functional Requirements
- Ad Selection: Serve relevant ads to users based on their profiles and real-time context (location, device type, etc.).
- Real-time Bidding: Enable advertisers...
Capacity Estimation
To estimate capacity, let’s consider the following assumptions:
- User Base: 100 million active users.
- Requests per User: Average of 5 requests per user per day.
- Total Daily Requests: ...
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