Abstract: The disclosure provides an approach for resource-aware software-defined data center (SDDC) upgrades. Embodiments include identifying a plurality of upgrade phases for upgrading components of a plurality of computing devices across a plurality of SDDCs. Embodiments include identifying a plurality of time slots based on support resource availability information. Embodiments include determining one or more constraints related to the plurality of SDDCs, wherein the one or more constrains comprise at least one constraint related to physical computing resource utilization. Embodiments include receiving physical computing resource utilization information related to the plurality of computing devices. Embodiments include assigning the plurality of upgrade phases to particular time slots of the plurality of time slots based on the one or more constraints and the physical computing resource utilization information for the plurality of computing devices.

Abstract: A method for scheduling computing resources without container migration includes determining a resource availability for one or more hosts, a resource allocation for one or more virtual machines (VMs), and a resource usage for one or more containers. The method further includes calculating a target resource configuration for one or more VMs, wherein calculating a target resource configuration comprises determining an upper limit of resource demand on a VM from one or more containers allocated on the VM, based at least in part on the resource usage. The method also includes removing or adding resources to each of the one or more VMs for which a target resource configuration was calculated to achieve the target resource configuration for each VM. The method further includes allocating the one or more VMs on the one or more hosts based on the resource availability of the one or more hosts.

Abstract: A method for scheduling computing resources with container migration includes determining a resource availability for one or more hosts, a resource allocation for one or more virtual machines (VMs), and a resource usage for one or more containers. The method includes identifying the hosts on which VMs and containers can be consolidated based on resource availability. The method also includes calculating a target resource configuration for one or more VMs. The method further includes removing or adding resources to the VMs for which a target resource configuration was calculated to achieve the target resource configuration. The method further includes allocating the one or more VMs on the one or more hosts based on the resource availability of the one or more hosts, and allocating the one or more containers on the one or more VMs based on the resource configuration of each VM and the resource usage of each container.

Abstract: The current document is directed to methods and systems for efficiently executing OSL-virtualization containers within the execution environments provided by virtual machines that execute above traditional virtualization layers within large, virtualized, distributed computing systems. The currently disclosed methods and systems anticipate the need for additional virtual machines in order to meet anticipated demands for one or more computational resources by the containers. In addition, the methods and systems provision and launch virtual machines with computational-resource allocations that minimize overhead and computational-resource wastage. In one implementation, computational-resource utilization of ATMs and containers within the virtualized, distributed computer system are periodically monitored in order to estimate future demand for the computational resource and, when necessary, to launch additional virtual machines to meet the estimated future demand for the computational resource.

Abstract: A method for scheduling computing resources with container migration includes determining a resource availability for one or more hosts, a resource allocation for one or more virtual machines (VMs), and a resource usage for one or more containers. The method includes identifying the hosts on which VMs and containers can be consolidated based on resource availability. The method also includes calculating a target resource configuration for one or more VMs. The method further includes removing or adding resources to the VMs for which a target resource configuration was calculated to achieve the target resource configuration. The method further includes allocating the one or more VMs on the one or more hosts based on the resource availability of the one or more hosts, and allocating the one or more containers on the one or more VMs based on the resource configuration of each VM and the resource usage of each container.

Abstract: A method for scheduling computing resources without container migration includes determining a resource availability for one or more hosts, a resource allocation for one or more virtual machines (VMs), and a resource usage for one or more containers. The method further includes calculating a target resource configuration for one or more VMs, wherein calculating a target resource configuration comprises determining an upper limit of resource demand on a VM from one or more containers allocated on the VM, based at least in part on the resource usage. The method also includes removing or adding resources to each of the one or more VMs for which a target resource configuration was calculated to achieve the target resource configuration for each VM. The method further includes allocating the one or more VMs on the one or more hosts based on the resource availability of the one or more hosts.

Abstract: The current document is directed to methods and systems for efficiently executing OSL-virtualization containers within the execution environments provided by virtual machines that execute above traditional virtualization layers within large, virtualized, distributed computing systems. The currently disclosed methods and systems anticipate the need for additional virtual machines in order to meet anticipated demands for one or more computational resources by the containers. In addition, the methods and systems provision and launch virtual machines with computational-resource allocations that minimize overhead and computational-resource wastage. In one implementation, computational-resource utilization of ATMs and containers within the virtualized, distributed computer system are periodically monitored in order to estimate future demand for the computational resource and, when necessary, to launch additional virtual machines to meet the estimated future demand for the computational resource.