Abstract: In accordance with an embodiment of the invention, a cloud computing system is disclosed. The system includes a software-defined data center (SDDC), the SDDC including at least one cluster supported within the SDDC and at least one host computer running within the cluster, wherein the at least one host computer is configured to support at least one workload comprising an operating system and an application, and a cloud infrastructure, the cloud infrastructure including at least one child VM, the at least one child VM configured to virtualize the at least one host computer running within the cluster, and at least one parent virtual machine, wherein additional child VMs are deployed by forking the at least one parent VM.

Abstract: Disclosed herein are techniques for performing workflow-aware NUMA (non-uniform memory access) optimizations. “Execution contexts” such as virtual machines or Docker containers are managed within a computer system that includes multiple NUMA nodes, each including a processor socket and memory local to that socket. NUMA optimization techniques are performed whereby execution contexts and/or data for such contexts are migrated between NUMA nodes. Migration may occur for various reasons, including for load balancing, to achieve fairness, or to increase the amount of data that is stored in memory local to a particular execution context. When it is known that an execution context will soon stop executing in a particular computer system, optimizations may provide little or no benefit. In such situations, the computer system performs modified NUMA optimizations, in which certain optimizations that would normally be performed are instead not performed.

Abstract: In accordance with an embodiment of the invention, a cloud computing system is disclosed. The system includes a software-defined data center (SDDC), the SDDC including at least one cluster supported within the SDDC and at least one host computer running within the cluster, wherein the at least one host computer is configured to support at least one workload comprising an operating system and an application, and a cloud infrastructure, the cloud infrastructure including at least one child VM, the at least one child VM configured to virtualize the at least one host computer running within the cluster, and at least one parent virtual machine, wherein additional child VMs are deployed by forking the at least one parent VM.

Abstract: The present disclosure includes detecting a failure associated with a first storage location on which a first agent virtual computing instance (AVCI) is deployed, wherein the first AVCI is being executed by a first hypervisor, stopping the execution of the first AVCI, determining whether a second AVCI that provides services analogous to the first AVCI is being executed by a second hypervisor and is deployed on a second storage location, creating a linked clone of the second AVCI on the second storage location responsive to the second AVCI being executed by the second hypervisor and deployed on the second storage location, redeploying the first AVCI on the second storage location responsive to the second AVCI not being executed by the second hypervisor or not deployed on the second storage location, and deleting files of the first AVCI from the first storage location after the failure is corrected.

Abstract: Disclosed herein are techniques for performing workflow-aware NUMA (non-uniform memory access) optimizations. “Execution contexts” such as virtual machines or Docker containers are managed within a computer system that includes multiple NUMA nodes, each including a processor socket and memory local to that socket. NUMA optimization techniques are performed whereby execution contexts and/or data for such contexts are migrated between NUMA nodes. Migration may occur for various reasons, including for load balancing, to achieve fairness, or to increase the amount of data that is stored in memory local to a particular execution context. When it is known that an execution context will soon stop executing in a particular computer system optimizations may provide little or no benefit. In such situations, the computer system performs modified NUMA optimizations, in which certain optimizations that would normally be performed are instead not performed.

Abstract: The present disclosure includes detecting a failure associated with a first storage location on which a first agent virtual computing instance (AVCI) is deployed, wherein the first AVCI is being executed by a first hypervisor, stopping the execution of the first AVCI, determining whether a second AVCI that provides services analogous to the first AVCI is being executed by a second hypervisor and is deployed on a second storage location, creating a linked clone of the second AVCI on the second storage location responsive to the second AVCI being executed by the second hypervisor and deployed on the second storage location, redeploying the first AVCI on the second storage location responsive to the second AVCI not being executed by the second hypervisor or not deployed on the second storage location, and deleting files of the first AVCI from the first storage location after the failure is corrected.