Abstract: The present disclosure relates to systems, methods, and computer readable media for predicting deployment growth on one or more node clusters and selectively permitting deployment requests on a per cluster basis. For example, systems disclosed herein may apply tenant growth prediction system trained to output a deployment growth classification indicative of a predicted growth of deployments on a node cluster. The system disclosed herein may further utilize the deployment growth classification to determine whether a deployment request may be permitted while maintaining a sufficiently sized capacity buffer to avoid deployment failures for existing deployments previously implemented on the node cluster. By selectively permitting or denying deployments based on a variety of factors, the systems described herein can more efficiently utilize cluster resources on a per-cluster basis without causing a significant increase in deployment failures for existing customers.

Abstract: The present disclosure relates to systems, methods, and computer readable media for predicting deployment growth on one or more node clusters and selectively permitting deployment requests on a per cluster basis. For example, systems disclosed herein may apply tenant growth prediction system trained to output a deployment growth classification indicative of a predicted growth of deployments on a node cluster. The system disclosed herein may further utilize the deployment growth classification to determine whether a deployment request may be permitted while maintaining a sufficiently sized capacity buffer to avoid deployment failures for existing deployments previously implemented on the node cluster. By selectively permitting or denying deployments based on a variety of factors, the systems described herein can more efficiently utilize cluster resources on a per-cluster basis without causing a significant increase in deployment failures for existing customers.

Abstract: Predicting capacity of shared virtual machine (VM) resources by generating estimated remaining capacities (ERCs) for computing clusters within a virtualization system rather than continuously monitoring actual remaining capacities (ARCs). Generating ERCs for a virtualization system's computing cluster(s) by using physical resource allocation flux data and/or VM type exchange probabilities provides benefits over continuously monitoring ARCs. The physical resource allocation flux data may correspond to commissioning and decommissioning VMs into the cluster and may be obtained during a blind period when current ARCs are unknown. For example, the physical resource allocation flux may be an indication of how many instances of each VM type are commissioned and/or decommissioned from the cluster over a time interval of interest.

Abstract: Predicting capacity of shared virtual machine (VM) resources by generating estimated remaining capacities (ERCs) for computing clusters within a virtualization system rather than continuously monitoring actual remaining capacities (ARCs). Generating ERCs for a virtualization system's computing cluster(s) by using physical resource allocation flux data and/or VM type exchange probabilities provides benefits over continuously monitoring ARCs. The physical resource allocation flux data may correspond to commissioning and decommissioning VMs into the cluster and may be obtained during a blind period when current ARCs are unknown. For example, the physical resource allocation flux may be an indication of how many instances of each VM type are commissioned and/or decommissioned from the cluster over a time interval of interest.

Abstract: Predicting capacity of shared virtual machine (VM) resources by generating estimated remaining capacities (ERCs) for computing clusters within a virtualization system rather than continuously monitoring actual remaining capacities (ARCs). Generating ERCs for a virtualization system's computing cluster(s) by using physical resource allocation flux data and/or VM type exchange probabilities provides benefits over continuously monitoring ARCs. The physical resource allocation flux data may correspond to commissioning and decommissioning VMs into the cluster and may be obtained during a blind period when current ARCs are unknown. For example, the physical resource allocation flux may be an indication of how many instances of each VM type are commissioned and/or decommissioned from the cluster over a time interval of interest.

Abstract: Predicting capacity of shared virtual machine (VM) resources by generating estimated remaining capacities (ERCs) for computing clusters within a virtualization system rather than continuously monitoring actual remaining capacities (ARCs). Generating ERCs for a virtualization system's computing cluster(s) by using physical resource allocation flux data and/or VM type exchange probabilities provides benefits over continuously monitoring ARCs. The physical resource allocation flux data may correspond to commissioning and decommissioning VMs into the cluster and may be obtained during a blind period when current ARCs are unknown. For example, the physical resource allocation flux may be an indication of how many instances of each VM type are commissioned and/or decommissioned from the cluster over a time interval of interest.

Abstract: Described herein are systems and methods for secure configuration provisioning of network credentials to configure a device to join one or more networks. One implementation provides for distribution of network credentials to associated devices without user intervention while maintaining security and avoiding distribution of the network credentials to external devices, such as a third-party server. Devices may be associated by purchase from a common merchant, registration to a common account, and so forth.