Systems and methods for workload migration recommendations in heterogeneous workspace environments are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: identify a set of workspaces launched by a set of users, among a plurality of workspaces launched by a plurality of users, where each workspace in the set of workspaces is associated with a performance or user experience metric below a threshold value; select, among a plurality of workloads executed within the set of workspaces, one or more workloads suitable for migration; and for each user of the set of users, determine whether to migrate any of the selected one or more workloads based, at least in part, upon an allocation of cloud and device resources available to the plurality of users.

In a computing system in which resources are available for performance of computing tasks allocated to them, and tasks are requested by requesting computers, a scheduler is associated with each of the requesting computers, to enable that computer to obtain resource for performance of the tasks. Each scheduler obtains resources, in accordance with a locally formulated preference list of resources, on the basis of scheduling tokens issued by resources indicative of reciprocal prioritisation of tasks by resources.

Adaptive storage processing for storage-as-a-service, including detecting, by a cloud-based monitoring system, a storage system state for a storage system by monitoring the storage system in real-time remotely via a network; selecting, by the cloud-based monitoring system based on the storage system state, an entry in a tunables repository, wherein the entry in the tunables repository comprises a tunable parameter for the storage system state; accessing, by the cloud-based monitoring system via the network, a gateway for the storage system; and modifying, by the cloud-based monitoring system via the gateway, the tunable on the storage system based on the tunable parameter for the storage system state.

Example techniques for pod migration across nodes of a cluster are described. In an example, in response to receiving a request to migrate a pod from a first region of a cloud computing platform to a second region of the cloud computing platform, the pod may be migrated from a first node in the first region to a second node in the second region. The first node and the second node may each be a part of a cluster of nodes.

A method, system, and apparatus determines that one or more tasks should be relocated from a first processor to a second processor by comparing performance metrics to associated thresholds or by using other indications. To relocate the one or more tasks from the first processor to the second processor, the first processor is stalled and state information from the first processor is copied to the second processor. The second processor uses the state information and then services incoming tasks instead of the first processor.

An apparatus and method are described for efficiently processing and reassigning interrupts. For example, one embodiment of an apparatus comprises: a plurality of cores; and an interrupt controller to group interrupts into a plurality of interrupt domains, each interrupt domain to have a set of one or more interrupts assigned thereto and to map the interrupts in the set to one or more of the plurality of cores.

The disclosed computer-implemented method may include (1) provisioning a cloud gaming environment with a plurality of containers that share a single operating system instance, (2) allocating each container within the plurality of containers to a corresponding user, (3) executing, concurrently, within each container within the plurality of containers a corresponding video game instance and (4) streaming, concurrently, from the cloud gaming environment, a video game instance from each container within the plurality of containers to a corresponding client system. Various other methods, systems, and computer-readable media are also disclosed.

Adaptive storage processing for storage-as-a-service, including detecting, by a cloud-based monitoring system, a storage system state for a storage system by monitoring the storage system in real-time remotely via a network; selecting, by the cloud-based monitoring system based on the storage system state, an entry in a tunables repository, wherein the entry in the tunables repository comprises a tunable parameter for the storage system state; accessing, by the cloud-based monitoring system via the network, a gateway for the storage system; and modifying, by the cloud-based monitoring system via the gateway, the tunable on the storage system based on the tunable parameter for the storage system state.

Technologies for dynamic accelerator selection include a compute sled. The compute sled includes a network interface controller to communicate with a remote accelerator of an accelerator sled over a network, where the network interface controller includes a local accelerator and a compute engine. The compute engine is to obtain network telemetry data indicative of a level of bandwidth saturation of the network. The compute engine is also to determine whether to accelerate a function managed by the compute sled. The compute engine is further to determine, in response to a determination to accelerate the function, whether to offload the function to the remote accelerator of the accelerator sled based on the telemetry data. Also the compute engine is to assign, in response a determination not to offload the function to the remote accelerator, the function to the local accelerator of the network interface controller.

The compression and decompression of files can be selectively offloaded to a hardware controller. A hardware controller, such as the controller of an SSD or other drive, can include a compression engine that is configured to implement compression techniques. A filter driver in the I/O pathway on a computing device may be configured to intercept an application's attempt to write a file to or read a file from the SSD or other drive and to selectively offload compression or decompression of the file to a compression engine on the SSD or other drive.