Abstract: The disclosure provides an approach for collecting system state data relating to whether certain system states overload a processor assigned to a controller of the system. The approach further involves using the collected data to train a regression machine learning algorithm to predict whether indented or desired system states will result in processor overload. Depending on the prediction, the approach takes one of several steps to efficiently change system state.

Abstract: In one example, workload attributes associated with workloads running in a virtualized computing environment may be retrieved. A distance analysis may be performed using the retrieved workload attributes to generate a distance matrix that identifies a distance between each workload and each other workload. Further, a cluster analysis may be performed on the workloads based on the distance matrix to generate clusters, where each cluster may include identical workloads. Furthermore, the identical workloads in each cluster may be associated with at least one security policy to provide security services in the virtualized computing environment.

Abstract: The disclosure provides an approach for collecting system state data relating to whether certain system states overload a processor assigned to a controller of the system. The approach further involves using the collected data to train a regression machine learning algorithm to predict whether indented or desired system states will result in processor overload. Depending on the prediction, the approach takes one of several steps to efficiently change system state.