KubeCon + CloudNative North America 2022

The European Union and the United States have set up a target of at least 50% - 55% net reduction in greenhouse gas emissions by 2030. But, with the sprawling of the cloud-native workloads and the increased demand for resources: are we doing enough?

Many community efforts and open source projects enable the observability of the power consumption from software resources to hardware resources. How can we combine the visibility provided by these tools to achieve the organization's sustainability goals? 

In this talk, we combine CNCF projects and other open source communities tools to create and continuously improve Machine Learning models for cluster operations. These ML models consider a holistic view of a system: from application runtimes, node metrics, cluster metrics, and network metrics to the tracing of the interactions among the distributed components. These ML models are used for the "smart operations" of the distributed systems aligning to the organization's carbon and power optimization goals.