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.

The disclosed system implements techniques to secure communications for injecting a workload (e.g., a container) into a virtual network hosted by a cloud-based platform. Based on a delegation instruction received from a tenant, a virtual network of the tenant can connect to and execute a workload via a virtual machine that is part of a virtual network that belongs to a resource provider. To secure calls and authorize access to the tenant's virtual network, authentication information provided with a call from the virtual network of the resource provider may need to match authorization information made available via a publication service of the cloud-based platform. Additionally or alternatively, an identifier of a NIC used to make a call may need to correspond to a registered name of the resource provider for the call to be authorized. These checks provide increased security by preventing unauthorized calls to the tenant's virtual network.

Disclosed is a system and method for cloud workload provisioning. In one implementation, the present invention provides a system enabling an automated guidance to the user for the workload to be provisioned. The present invention matches the user's workload profile based on a wide variety of historical data set and makes easy for users to choose the cloud provisioning for various kinds of workloads. The system can automatically readjust a workload profile for cloud provisioning. The system can provide a manual selection option for cloud provisioning. In one embodiment, the present invention provides a system and method that derives a workload provision scaling factor mechanism using historic data set. Furthermore, the system and method can automatically or manually readjust the provision scaling factor based on a workload profile for cloud provisioning.

A system and method for backing up workloads for multiple tenants of a cloud computing system are disclosed. A method of backing up workloads for multiple tenants of a computing system includes triggering an archival process according to an archival policy set by a tenant, and executing the archival process by reading backup data of the tenant stored in a backup storage device of the computer system and transmitting the backup data to an archival store designated in the archival policy, and then deleting or invalidating the backup data stored in the backup storage device.

Disclosed are aspects of virtual graphics processing unit (vGPU) scheduling-aware virtual machine migration. Graphics processing units (GPUs) that are compatible with a current virtual GPU (vGPU) profile for a virtual machine are identified. A scheduling policy matching order for a migration of the virtual machine is determined based on a current vGPU scheduling policy for the virtual machine. A destination GPU is selected based on a vGPU scheduling policy of the destination GPU being identified as a best available vGPU scheduling policy according to the scheduling policy matching order. The virtual machine is migrated to the destination GPU.

The disclosure provides an approach for distribution of functions among data centers of a cloud system that provides function-as-a-service (FaaS). For example, the disclosure provides one or more function distributors configured to receive a request for loading or executing a function, automatically determine an appropriate data center to load or execute the function, and automatically load or execute the function on the determined data center. In certain embodiments, the function distributors are further configured to determine an appropriate data center to provide storage resources for the function and configure the function to utilize the storage resources of the determined data center.

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.

An apparatus comprises an interrupt distributor to distribute virtual interrupts to one or more physical processors, each virtual interrupt to be handled by one of a plurality of virtual processors mappable to said one or more physical processors; and control circuitry to maintain virtual processor interrupt tracking information corresponding to a given virtual processor. The virtual processor interrupt tracking information includes a pending interrupt record tracking which types of virtual interrupts are pending for the given virtual processor, and separate from the pending interrupt record, a pending interrupt status indication indicating a pending interrupt status for the given virtual processor. The pending interrupt status indicates whether the number of pending virtual interrupts for the given virtual processor is zero.

Systems and methods are described for exporting bucket data from one or more buckets to one or more worker nodes. The system can identify data from different bucket data from buckets stored in a data intake and query system that is to be processed by one or more worker nodes. The system can allocate one or more execution resources, such as a processing pipeline, to process and export the bucket data from the buckets. The system can assign bucket data corresponding to individual buckets to the execution resource based on a bucket distribution policy. The indexer can export the bucket data to the worker nodes for further processing based on the bucket data-execution resource assignment.

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.