Introduction
Welcome to "Ads Systems At Scale". This book provides a comprehensive guide to building and scaling advertising systems at production scale.
Why Ads Systems Are Uniquely Hard to Build
Advertising systems are among the most complex and high-stakes machine learning systems in production. They require:
- Real-time inference at massive scale
- Sophisticated ranking and auction mechanisms
- Careful balance between user experience and revenue
- Robust monitoring and experimentation frameworks
- Handling of three-sided marketplace dynamics
The Three-Sided Marketplace: Users, Advertisers, Platform Revenue
At the heart of every advertising system is a three-sided marketplace:
- End Users - The people consuming content who see ads
- Advertisers - The businesses paying to reach users
- The Platform - The intermediary that must balance user experience with advertiser needs while maximizing revenue
Each party has different objectives that often conflict, making the optimization problem uniquely challenging.
What This Book Covers and Who It's For
This book is designed for:
- ML Engineers building production ad systems
- System Architects designing scalable ad infrastructure
- Product Managers understanding the technical tradeoffs
- Researchers working on advertising and auction mechanisms
We'll cover everything from foundational concepts to deep dives into specific problems like budget pacing, frequency capping, and fraud detection.
Let's begin!