Every chapter so far taught you how to diagnose a problem you already know exists. You opened a ticket, ran ibstat, found the err-disabled port, fixed it. The loop started with a symptom.
This chapter teaches you how to know a problem exists before the ML engineer's Slack message arrives.
The difference between reactive diagnosis and proactive observability is not a matter of tools -- you already know most of the tools. It is a matter of when you look, what you watch continuously, and how you correlate signals across four separate data streams when something goes wrong at 3am on a 256-GPU training run worth $40,000 per hour.