Abstract: This disclosure describes techniques and mechanisms for providing an intelligent de-scheduler filtering system that minimizes service disruptions within a network. The techniques may provide continuous monitoring of clusters within a dynamic system and provide an intelligent determination of pod(s) within a duster to move by utilizing a disruption score based on disruption policies, balancer policies, service level agreement policies, and other data associated with the cluster and/or pods. The techniques enable a subset of pods that are flagged as violating compute usage to be selected to be moved, such that the subset will result in the least disruption to move to help restore or realign compute resources in the system.

Abstract: This disclosure describes techniques and mechanisms for providing an intelligent de-scheduler filtering system that minimizes service disruptions within a network. The techniques may provide continuous monitoring of clusters within a dynamic system and provide an intelligent determination of pod(s) within a cluster to move by utilizing a disruption score based on disruption policies, balancer policies, service level agreement policies, and other data associated with the cluster and/or pods. The techniques enable a subset of pods that are flagged as violating compute usage to be selected to be moved, such that the subset will result in the least disruption to move to help restore or realign compute resources in the system.