Abstract: An example method of scheduling a workload in a virtualized computing system including a host cluster having a virtualization layer directly executing on hardware platforms of hosts is described. The virtualization layer supports execution of virtual machines (VMs) and is integrated with an orchestration control plane. The method includes: receiving, at the orchestration control plane, a workload specification for the workload; selecting, at the orchestration control plane, a plurality of nodes for the workload based on the workload specification, each of the plurality of nodes implemented by a host of the hosts; selecting, by the orchestration control plane in cooperation with a virtualization management server managing the host cluster, a node of the plurality of nodes; and deploying, by the orchestration control plane in cooperation with the virtualization management server, the workload on a host in the host cluster implementing the selected node.

Abstract: Various aspects are disclosed for unified resource management for multiple workload schedulers. A resource manager receives a candidate host request from a workload scheduler. The resource manager transmits a set of candidate host snapshots for candidate hosts that match the workload resource requirements. The resource manager receives a workload allocation request for a host and reserves hardware resources on the host that match the workload resource requirements. The resource manager provides, to the workload scheduler, an indication that the hardware resources are successfully reserved for execution of the workload.

Abstract: System and computer-implemented method for recommending guidelines for managed objects for a computing environment uses a transductive embedding technique on a graph of the computing environment to generate initial embeddings for the nodes of the graph. An inductive embedding technique is then applied on the initial embeddings and features of the nodes of the graph to produce final embeddings for the nodes of the graph, which are used to execute a link classification operation on the final embeddings for at least some nodes of the graph to select a recommended guideline for a target managed object.

Abstract: The present disclosure relates to workload placement based on datastore connectivity group. Some embodiments include separating a cluster having a plurality of hosts and a plurality of datastores into a plurality of datastore connectivity groups (DCGs), wherein the hosts and the datastores of each cluster are fully connected, for each DCG, executing distributed resource scheduler (DRS) to determine a best host and executing storage DRS to determine a best datastore, and executing a workload placement program to determine a best host-datastore pair from among the plurality of DCGs.

Abstract: Aspects of managing inventory for data transport connections within a virtualized computing environment are described. A virtualized management system managing a cluster of host devices obtains a data transport capacity parameter and an aggregate memory consumption value from respective host devices. The virtualized management system further identifies an update status associated with each of the host devices. In response to receiving a data transport connection request, the virtualized management system selects a host from the cluster of hosts to satisfy the data transport connection request based at least in part on the upgrade status, data transport capacity parameter and aggregate memory consumption value.

Abstract: Techniques are disclosed for reallocating host resources in a virtualized computing environment when certain criteria have been met. In some embodiments, a system identifies a host disabling event. In view of the disabling event, the system identifies a resource for reallocation from a first host to a second host. Based on the identification, the computer system disassociates the identified resource's virtual identifier from the first host device and associates the virtual identifier with the second host device. Thus, the techniques disclosed significantly reduce a system's planned and unplanned downtime.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for state convergence associated with high availability application migration in a virtualized environment. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of execute or instantiate the machine readable instructions to identify a high availability slot in a virtual server rack including a first virtual machine (VM) associated with first configuration data that identifies the first VM as a protected VM, transmit second configuration data to a second VM that identifies the first VM as a nonprotected VM and the second VM as the protected VM, after a determination that a network partition is identified based on a failure of a request to retrieve the second configuration data from the second VM, and transfer data from the first VM to the second VM after causing the removal of the network partition.

Abstract: An example method may include receiving a first GUI selection of a first management server corresponding to a first cluster of virtual infrastructure objects, receiving a second GUI selection of one or more first virtual infrastructure object tags to be assigned to at least one virtual infrastructure object from the first cluster of virtual infrastructure objects after a creation process of a first policy, wherein the first policy is configured to regulate the at least one virtual infrastructure object from the first cluster of virtual infrastructure objects with the one or more first virtual infrastructure object tags, receiving first real-time feedback associated with the first cluster of virtual infrastructure objects and the one or more first virtual infrastructure object tags from the first management server, and displaying a object count in a first GUI element supported by the configuration client.

Abstract: Described herein are systems, methods, and software to manage the migration of virtual machines between hosts. In one example, a management service for a cluster of hosts identifies a virtual machine to migrate and identifies current resource requirements of the virtual machine and current resource availability at the hosts of cluster. The management service further determines that two or more of the hosts possess current resource availability to support the current resource requirements of the virtual machine and identifies available headroom resources on each of the two or more hosts. Based on the available headroom resources, the management service further selects a host from the two or more hosts and initiates a migration of the virtual machine to the selected host.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for high availability (HA) application migration in a virtualized environment. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to at least one of execute or instantiate the instructions to identify an HA slot in a virtual server rack, the HA slot to facilitate a failover of an application executing on a first virtual machine (VM) in the virtual server rack, the first VM identified as a protected VM, deploy a second VM in the HA slot, transfer data from the first VM to the second VM, and, in response to not identifying a failure of at least one of the first or second VMs during the transfer, trigger a shutdown of the first VM, and synchronize migration data associated with the virtual server rack to identify the second VM as the protected VM.

Abstract: The disclosure provides an approach for the dynamic configuration of virtualized objects. A virtual object may be associated with a desired state defining a first plurality of resources for allocating to the virtual object. The first plurality of resources correspond to one or more resource types. Techniques include determining that each of a plurality of hosts does not have sufficient available resources to allocate the first plurality of resources to the virtual object according to the desired state. Techniques include selecting, a first host of the plurality of hosts to run the virtual object. Techniques include allocating a second plurality of resources to the virtual object from the first host, wherein the second plurality of resources is less than the first plurality of resources, and running the virtual object in the first host.

Abstract: Workloads are scheduled on a common set of resources distributed across a cluster of hosts using at least two schedulers that operate independently. The resources include CPU, memory, network, and storage, and the workloads may be virtual objects, including VMs, and also operations including live migration of virtual objects, network file copy, reserving spare capacity for high availability restarts, and selecting hosts that are to go into maintenance mode. In addition, the at least two independent schedulers are assigned priorities such that the higher priority scheduler is executed to schedule workloads in its inventory on the common set of resources before the lower priority scheduler is executed to schedule workloads in its inventory on the common set of resources.

Abstract: Aspects of managing inventory for data transport connections within a virtualized computing environment are described. A virtualized management system managing a cluster of host devices obtains a data transport capacity parameter and an aggregate memory consumption value from respective host devices. The virtualized management system further identifies an update status associated with each of the host devices. In response to receiving a data transport connection request, the virtualized management system selects a host from the cluster of hosts to satisfy the data transport connection request based at least in part on the upgrade status, data transport capacity parameter and aggregate memory consumption value.

Abstract: Aspects of workload reallocation within a software-defined data center (SDDC) undergoing an upgrade are described. As upgrades become available for services and other types of applications installed on a cluster of host devices within a data center, an upgrade of the installed services may be required for each of the host devices. During a cluster upgrade, the order in which hosts in the cluster are upgraded is determined as a function of evacuation costs and evacuation policies associated with each host device in the computing cluster. In addition, a maintenance cost associated with a workload needing to be evacuated from a host undergoing an upgrade is determined based on the upgrade sequence. The maintenance cost can then be used as a factor for selecting an optimal candidate host for migrating the workload to when the host the workload is currently running on is being upgraded.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for high availability (HA) application migration in a virtualized environment. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to at least one of execute or instantiate the instructions to identify an HA slot in a virtual server rack, the HA slot to facilitate a failover of an application executing on a first virtual machine (VM) in the virtual server rack, the first VM identified as a protected VM, deploy a second VM in the HA slot, transfer data from the first VM to the second VM, and, in response to not identifying a failure of at least one of the first or second VMs during the transfer, trigger a shutdown of the first VM, and synchronize migration data associated with the virtual server rack to identify the second VM as the protected VM.

Abstract: Examples described herein include systems and methods for backing up and recovering a software-defined data center (“SDDC”). In one example, entities of the SDDC, such as virtual machines, hosts, and clusters, can coexist with corresponding entity stores. The entity stores can store current state information for each SDDC entity. For example, an identifier or name of a virtual machine can be stored in that virtual machine's corresponding entity store. When recovery of a controller is needed, the controller can rebuild state information that has changed after the controller was backed up, by retrieving state information from entity stores of the various SDDC entities.

Abstract: The present disclosure describes a technique for honoring virtual machine placement constraints established on a first host implemented on a virtualized computing environment by receiving a request to migrate one or more virtual machines from the first host to a second host and without violating the virtual machine placement constraints, identifying an architecture of the first host, provisioning a second host with an architecture compatible with that of the first host, adding the second host to the cluster of hosts, and migrating the one or more virtual machines from the first host to the second host.

Abstract: Examples described herein include systems and methods for backing up and recovering a software-defined data center (“SDDC”). In one example, entities of the SDDC, such as virtual machines, hosts, and clusters, can coexist with corresponding entity stores. The entity stores can store current state information for each SDDC entity. For example, an identifier or name of a virtual machine can be stored in that virtual machine's corresponding entity store. When recovery of a controller is needed, the controller can rebuild state information that has changed after the controller was backed up, by retrieving state information from entity stores of the various SDDC entities.

Abstract: The disclosure provides an approach for the dynamic configuration of virtualized objects. A virtual object may be associated with a desired state defining a first plurality of resources for allocating to the virtual object. The first plurality of resources correspond to one or more resource types. Techniques include determining that each of a plurality of hosts does not have sufficient available resources to allocate the first plurality of resources to the virtual object according to the desired state. Techniques include selecting, a first host of the plurality of hosts to run the virtual object. Techniques include allocating a second plurality of resources to the virtual object from the first host, wherein the second plurality of resources is less than the first plurality of resources, and running the virtual object in the first host.

Abstract: An example method of placing resources in domains in a virtualized computing system is described. A host cluster includes a virtualization layer executing on hardware platforms of the hosts. The method includes: determining, at a virtualization management server, definitions of the domains and resource groups, each of the domains including a plurality of placement targets, each of the resource groups including a plurality of the resources; receiving, at the virtualization management server from the user, affinity/anti-affinity rules that control placement of the resource groups within the domains; and placing, by the virtualization management server, the resource groups within the domains based on the affinity/anti-affinity rules.