Examples may include techniques to decrease a live migration time for a virtual machine (VM). Examples include selecting data to copy or not copy during a live migration of the VM from a source host server to a destination host server.

Examples may include a computing platform having a host driver to get a packet descriptor of a received packet stored in a receive queue and to modify the packet descriptor from a first format to a second format. The computing platform also includes a guest virtual machine including a guest driver coupled to the host driver, the guest driver to receive the modified packet descriptor and to read a packet buffer stored in the receive queue using the modified packet descriptor, the packet buffer corresponding to the packet descriptor.

Methods, apparatus, systems, and articles of manufacture are disclosed to improve workload domain management of virtualized server systems. An example apparatus includes a resource pool handler to generate a pool of virtualized servers including a first virtualized server based on a policy, ones of the virtualized servers to be allocated to a workload domain to execute an application, a resource status analyzer to determine a health status associated with the workload domain and determine whether the health status satisfies a threshold based on the policy, and a resource allocator to allocate the first virtualized server to the workload domain to execute the application when the health status is determined to satisfy the threshold.

Dependent containers can be managed based on context. When an application is deployed in a container and relies on a service or other resource external to the container, context about the container, the application and any data paths the container may require can be monitored and used to calculate a container instance weight, an application weight and a data path weight. Such weights can then be used to calculate a per container weight which in turn can be used to determine if any changes in container type or location may be more optimal for an application. Such weights can also be used to calculate a per solution weight which in turn can be used to determine if any changes in container type or location may be more optimal for a solution.

In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may: monitor, by a management console, power consumption of a virtual machine (VM) executed by a first hypervisor on a first physical information handling system (IHS); migrate, by the management console, the VM from the first hypervisor to a second hypervisor on a second physical IHS; provide, by the first hypervisor, VM migration information to the management console; determine, by the management console, if the second hypervisor has been discovered based at least on the VM migration information; if so, refresh a hypervisor inventory to include identification information associated with the second hypervisor; if not, discover the second hypervisor; detect the VM; associate the VM with the second hypervisor; and monitor, by the management console, the power consumption of the VM executed by the second hypervisor on the second physical IHS.

A method, computer program product, and computer system for implementing tasks on managed nodes. A specified task to be performed by an Ansible module on one or more managed nodes of two or more managed nodes is received. The one or more managed nodes are determined based on an attribute value of a hostDecision attribute of the Ansible module. The attribute value may be primaryNode, allNodes, or Dynamic, where: primary Node requires the one or more managed nodes to be a primary node, allNodes requires the one or more managed nodes to be the two or more managed nodes, and Dynamic requires the one or more managed nodes to be determined dynamically based on runtime information. The Ansible module is sent to the one or more managed nodes to perform the task on the one or more managed nodes.

Technologies for managing configuration-free platform firmware include a compute device, which further includes a management controller. The management controller is to receive a system configuration request to access a system configuration parameter of the compute device and access the system configuration parameter in response to a receipt of the system configuration request.

Some embodiments may be associated with a cloud computing environment. A serverless runtime workload may execute an eBPF program via a kprobe which gets invoked when function code is executed as a Linux process. The system may determine, by the kprobe function associated with an identifier, that an orchestrator is evicting the serverless runtime workload. Responsive to the determination, a userspace program may be invoked via the eBPF in tandem with the kprobe acting as an interception mechanism. The system may then capture the current workload process state data associated with the serverless runtime workload based on the identifier. A clustered memory-based storage component may store the captured current workload process state data in association with the identifier. A subsequent serverless runtime workload may determine that the orchestrator is restoring the serverless runtime workload. Responsive to the determination, the system may load the workload process state data from the clustered memory-based storage component.

A system includes a machine readable storage medium storing instructions and a processor to execute the instructions. The instructions include receiving a local workflow including a native action from a first user device and determining whether information to execute the native action as a cloud action is complete. In response to determining that information for the native action is complete, determining whether a comparable cloud action is available for the native action. In response to determining that a comparable cloud action is available for the native action, saving the native action as a cloud action in a cloud work-flow. In response to determining that a comparable cloud action is not available for the native action or in response to determining that information to execute the native action is not complete, saving the native action as a local action in the cloud workflow.

Disclosed are various embodiments for optimized memory tiering. An ideal tier size for a first memory and an ideal tier size for a second memory can be determined for a process. Then, a host computing device can be identified that can accommodate the ideal tier size for the first memory and the second memory. Subsequently, the process can be assigned to the host computing device.