Design a distributed Ad Serving System

Last updated: September 2, 2025

Quick Overview

Design a distributed ad serving system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Snowflake
System Design
Machine Learning Engineer
Snowflake
September 2, 2025
Machine Learning Engineer
Onsite
System Design
Hard

0

13

4,386 solved


Design a distributed 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 Onsite at Snowflake. 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. Snowflake 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
Monitoring, logging, and alerting
Requirements gathering and capacity estimation
High-level architecture and component design
Message queues and async processing
Load balancing and horizontal scaling
Partitioning and sharding strategies
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
  • What would the deployment pipeline look like for this system?
  • How would you handle a 10x increase in traffic overnight?
  • How do you ensure data consistency across multiple services?
Practice a Similar Problem on Codemia

Solve a related problem with our interactive workspace, get AI feedback, and view detailed solutions.

Solve on Codemia
Sample Answer
Requirements Clarification

Before diving into the architecture, clarify the scope with the interviewer. For distributed Ad Serving System, key functional requirements include: w...

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...


Submit Your Answer
Markdown supported

Related Questions