Cloud Native technologies enjoy global success, in part because they can deal with higher scale than any technology before.

Good engineering principles can always be applied outside of their initial field. Several global leaders in car manufacturing and their suppliers are already using Cloud Native Observability for their IT workloads, their factories, and their cars.
Of special interest is their ability to use the same systems to both ensure their AI workloads are running correctly, and to use the well-formed data for machine learning applications.

In this session, we will go through
* The definition of Observability, and how to reason about the problem space
* Current Cloud Native technologies in the Observability space
* How to leverage Open Source for a cost-efficient way to collect, store, and analyze actionable data
* How to observe AI systems, and how to use the data for machine learning

At the end, you will have both a solid understanding of the foundations as well as applicable expert knowledge.