Various techniques for emulating edge locations in cloud-based networks are described. An example method includes generating an emulated edge location in a region. The emulated edge location can include one or more first computing resources in the region. A host in the region may launch a virtualized resource a portion of the one or more first computing resources. Output data that was output by the virtualized resource in response to input data can be received and reported to a user device, which may provide a request to migrate the virtualized resource to a non-emulated edge location. The non-emulated edge location may include one or more second computing resources that are connected to the region by an intermediary network. The virtualized resource can be migrated from the first computing resources to at least one second computing resource in the non-emulated edge location.

A method for containerized workload scheduling can include determining a network state for a first hypervisor in a virtual computing cluster (VCC). The method can further include determining a network state for a second hypervisor. Containerized workload scheduling can further include deploying a container to run a containerized workload on a virtual computing instance (VCI) deployed on the first hypervisor or the second hypervisor based, at least in part, on the determined network state for the first hypervisor and the second hypervisor.

A system for container migration includes containers running instances of an application running on a cluster, an orchestrator with a controller, a memory, and a processor in communication with the memory. The processor executes to monitor a vitality metric of the application. The vitality metric indicates that the application is in either a live state or a dead state. Additionally, horizontal scaling for the application is disabled and the application is scaled-down until the vitality metric indicates that the application is in the dead state. Responsive to the vitality metric indicating that the application is in the dead state, the application is scaled-up until the vitality metric indicates that the application is in the live state. Also, responsive to the vitality metric indication transitioning from the dead state to the live state, the application is migrated to a different cluster while the horizontal scaling of the application is disabled.

Systems and methods are disclosed for scheduling threads on a processor that has at least two different core types, such as an asymmetric multiprocessing system. Each core type can run at a plurality of selectable voltage and frequency scaling (DVFS) states. Threads from a plurality of processes can be grouped into thread groups. Execution metrics are accumulated for threads of a thread group and fed into a plurality of tunable controllers for the thread group. A closed loop performance control (CLPC) system determines a control effort for the thread group and maps the control effort to a recommended core type and DVFS state. A closed loop thermal and power management system can limit the control effort determined by the CLPC for a thread group, and limit the power, core type, and DVFS states for the system. Deferred interrupts can be used to increase performance.

Techniques for optimizing CPU usage in a host system based on VM guest OS power and performance management are provided. In one embodiment, a hypervisor of the host system can capture information from a VM guest OS that pertains to a target power or performance state set by the guest OS for a vCPU of the VM. The hypervisor can then perform, based on the captured information, one or more actions that align usage of host CPU resources by the vCPU with the target power or performance state.

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.

An interaction method, including displaying, by a first electronic device, a multi-task management interface, including N device labels corresponding to N electronic devices and including a first, second and third device label of the first, second and third electronic device, receiving a first operation for dragging the first task record to the second device label performed by a user on a first task record, enabling, in response to the first operation, the second electronic device to display at least one first task corresponding to the first task record, receiving a second operation for dragging the second task record to the third device label performed by a user on a second task record in the multi-task management interface, and enabling, by the first electronic device in response to the second operation, the third electronic device to display at least one of second task corresponding to the second task record.

To more properly size resources in a destination to which IT resources will be migrated, a system for appraising a resource configuration estimates a source's load model representing a load of first resources in a first computer system which is the source of migration and estimates a destination's load model representing a load of second resources to be built by migrating the first resources to a second computer system based on the source's load model. The system compares performance requirements of the first resources against the destination's load model and finds the destination's load model that is conformable to the performance requirements. When determining design values of the second resources' configuration, the system corrects those design values based on the destination's load model estimated conformable to the performance requirements to decrease design margins of the resource configuration using a design correction value defined to meet a service level requested.

Examples include a method of live migrating a virtual device by creating a virtual device in a virtual machine, creating first and second interfaces for the virtual device, transferring data over the first interface, detecting a disconnection of the virtual device from the virtual machine, switching data transfers for the virtual device from the first interface to the second interface, detecting a reconnection of the virtual device to the virtual machine, and switching data transfers for the virtual device from the second interface to the first interface.

A system enabling a hypervisor to assign processor resources for specific tasks to be performed by a virtual machine. An example method may comprise: receiving, by a hypervisor running on a host computer system, a virtual processor (“vCPU”) assignment request from a virtual device driver running on a virtual machine managed by the hypervisor, assigning a vCPU for executing a task associated with the assignment request, and causing the virtual device driver to execute the task using the vCPU.