Site Reliability Engineering, 2nd Edition

Chapter 18. How SRE Supports AI

By Dan Dennison, Isaac Albarrán Muñoz, John Lunney, and Rita Lu

With Garrett Holthaus

A Note for Early Release Readers

With Early Release ebooks, you get books in their earliest form—the author’s raw and unedited content as they write—so you can take advantage of these technologies long before the official release of these titles.

This will be the 20th chapter of the final book. Please note that the GitHub repo will be made active later on.

If you’d like to be actively involved in reviewing and commenting on this draft, please reach out to the editor at [e-mail].

This chapter is one of two in this book which discusses the intersection of AI and Site Reliability Engineering. This chapter deals with the various aspects of the SRE discipline applied to the operation of AI services. The other chapter, How AI Supports SRE, discusses the application of AI to the SRE discipline.

AI is the overarching field dedicated to creating machines capable of human-like reasoning and problem-solving, encompassing everything from simple expert systems to autonomous agents that use large language models (LLMs) as reasoning engines. While Machine Learning (ML) is a specific subset of AI that allows systems to learn from data patterns without explicit programming—powering tasks like image recognition and fraud detection—the two fields often overlap. This is most evident in technologies like LLMs, which use deep learning (an ML technique) to achieve the sophisticated ...