For most organizations, observability solutions generate massive amounts of data. While it is nice to look at shiny graphs & metrics, the path to identifying patterns and optimizing performance can be a long one. Yet, all of this structured data has significant potential in helping us fine-tune the performance of our cloud-native applications.

In this session, we will show how machine learning can be leveraged to identify optimal configurations for applications deployed in Kubernetes to ensure performance and efficiency.