20. Logging and Monitoring

Knowledge transfer checkpoint

Connect Logging and Monitoring back to the local-AI decision you are learning to make. The practical question is not only whether the code or concept works, but whether it still works when the model, runtime, hardware budget, privacy requirement, and latency target are real constraints.

Before moving on, write down four things: the local runtime or deployment surface involved, the memory or throughput constraint that could change the design, the verification signal that proves the lesson worked, and the failure mode you would check first if the result looked wrong. That turns this chapter from background knowledge into an operator habit.

A good answer should be specific enough that another reader could repeat the decision on their own machine. Name the model or component when there is one, record the relevant context or token budget, and prefer a measurable check over a vague statement such as "it seems faster" or "the setup is fine."