The title of the book may be "in the AI age", but this is not specifically about AI observability. It is about harnessing AI tooling to work alongside and within your stack to gain the richest insights understanding and insights into your applications and systems.

This is clearly a work based on extensive experience in the trenches of building sophisticated observability solutions to manage large and complex applications. There is a wealth of tactical detail that goes into considerable depth.

At the same time, this is a book which explores observability at multiple levels. There is an awareness observability is more than just collecting metrics, logs or traces. It is also about being proactive, developing deep understandings and aligning trechnology with business outcomes.

Taking a slightly similar approach to the way in which the Phoenix Project anchored the DevOps philosophy in the context of a fictional engineering team DevOps, this book illustrates the value of applying ai-driven observability principles to "Acme financial services" and charts the experiences of a team of observability engineers over successive iterations.

This is not just a book to read and file away, it is also a manual to keep by your side for building and refining your observability strategy.