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, 2026
Software 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
  1. Start by clarifying functional and non-functional requirements with the interviewer.
  2. Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
  3. Draw a high-level architecture first, then deep dive into 1-2 critical components.
  4. Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
  5. 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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Sample Answer
Requirements Clarification

Before diving into the architecture, clarify the scope with the interviewer. For large-scale Ad Serving Platform, key functional requirements include:...

Capacity Estimation

Estimate the scale to drive design decisions. Assume 100M DAU with an average of 10 actions per user per day = 1B requests/day ~ 12K QPS average, ~36K...


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