Abstract: A remote server computing system is configured to deploy a cloud-service-managed control plane and a cloud service data plane spanning the remote server computing system, a local edge computing device, and a local on-premises computing device connected in a hybrid cloud environment. Energy-related training data is received including a plurality of energy-related training data pairs. A machine learning function is trained using the plurality of training data pairs to predict a classified label for restricted energy-related data that is not accessible to the remote server computing system. The trained machine learning function is deployed to the one or more of the local edge computing device and the local on-premises computing device via the cloud service data plane. The remote server computing system is further configured to receive, via the cloud service data plane, classified output of the trained machine learning function.

Abstract: A remote server computing system is configured to deploy a cloud-service-managed control plane and a cloud service data plane spanning the remote server computing system, a local edge computing device, and a local on-premises computing device connected in a hybrid cloud environment. Energy-related training data is received including a plurality of energy-related training data pairs. A machine learning function is trained using the plurality of training data pairs to predict a classified label for restricted energy-related data that is not accessible to the remote server computing system. The trained machine learning function is deployed to the one or more of the local edge computing device and the local on-premises computing device via the cloud service data plane. The remote server computing system is further configured to receive, via the cloud service data plane, classified output of the trained machine learning function.

Abstract: A remote server computing system is configured to present a user interface with a plurality of deployment configuration options including compute configuration options and data storage configuration options for energy-related data within a hybrid cloud environment. The hybrid cloud environment comprises a cloud-service-managed control plane and a data plane utilizing local compute resources and storage. A data control policy is generated that provides cloud-service-managed governance over at least a portion of the data plane. The control plane is configured to enforce the data control policy by subjecting at least a portion of the energy-related data to a data transmission restriction or a local storage restriction. The data plane is used to deploy one or more cloud service functions configured to process at least the portion of the energy-related data and output one or more extracted features from at least the portion of the energy-related data to the data plane.