Abstract: Techniques for an optimization service of a service provider network to provide users with machine-generated narratives that include human-intelligible, credible, and transparent recommendations and rationales for recommended VM instance types. The optimization service may gather various information or data about the workload, such as utilization characteristics of the underlying computing resources, and decompose the workloads through a number of dimensions that can be used to describe the workload. Further, the optimization service may analyze the utilization characteristics and/or other data to determine more optimized VM instance types for the workloads that are to be recommended to the users, and also rationales that describes why each recommendation is an appropriate fit for the workload being assessed.

Abstract: A work stealer apparatus includes a determination module. The determination module is to determine to steal work from a first hardware computation unit of a first type for a second hardware computation unit of a second type that is different than the first type. The work is to be queued in a first work queue, which is to correspond to the first hardware computation unit, and which is to be stored in a shared memory that is to be shared by the first and second hardware computation units. A synchronized work stealer module is to steal the work through a synchronized memory access to the first work queue. The synchronized memory access is to be synchronized relative to memory accesses to the first work queue from the first hardware computation unit.

Abstract: A computing device may include a memory and a processor cooperating with the memory and configured to provide a first application layer within a virtual machine responsive to a client device, with the first application layer including a first version of a first virtual application and at least one second virtual application compatible with the first version of the first virtual application. The processor may be further configured to provide a second application layer within the virtual machine responsive to the client device, with the second application layer including a second version of the first virtual application, and the second version being different than the first version in the first application layer. Further, the second version of the virtual application is not compatible with the at least one second virtual application.

Abstract: Apparatuses, methods and storage media associated with a consolidate device infrastructure to provide rapid device service are disclosed herein. In embodiments, a system comprises a portal to provide a presentation tier of services; a business logic layer to provide a logic tier of services; and a plurality of data management servers remotely and separately disposed in a plurality of locations to provide a data tier of services and a hardware tier of services. The presentation tier of services, logic tier of services, the data tier of services, and the hardware tier of services may cooperate to selectively provide a subset of a plurality of resources associated with the data management servers for use, in response to a device resource request received through the portal. Other embodiments may be described and/or claimed.

Abstract: Dynamically allocating workloads to a fixed number of CPU resources within a compute platform. Determining whether a workload should be in a Dedicated Class of workloads and assigned to a dedicated CPU resource or in a Shared Class of workloads that is handled by a set of at least one shared CPU resource, wherein a shared CPU resource may service more than one workload. The determination may be made based on a comparison of a parameter from two samples of a parameter taken at different times. The determination may be made using metadata associated with the workload. The determination may be made repeatedly so that some workloads may change from being in the Dedicated Class to the Shared Class or from the Shared Class to the Dedicated Class. High availability virtual network functions may be handled economically by deeming the failover workloads to be in the Shared Class.

Abstract: Described herein is a system and method of connectivity migration of an executing virtual application and/or guest operating system. State associated with a first instance of an application and/or a guest operating system executing on a first virtual machine is captured. Information regarding connectivity state associated with a plurality of running connections between the first virtual machine and client device(s) is also captured (e.g., layers 2, 3 and 4). The captured state information can be provided to a second virtual machine which utilizes the captured station information to establish state for a second instance of the application, a second instance of the guest operating system, and/or connectivity of the plurality of running connections between the second virtual machine and client device(s). The state of the second instance of the application can be synchronized with the state of the second instance of the guest operating system.

Abstract: An apparatus stores status information and workload information for each task executed by a user. The apparatus detects, based on the status information, completion of a first task, and withholds notification of first help information related to software selected based on a usage state of the software in the first task. The apparatus detects, based on the status information, completion of a second task after completion of the first task, and calculates, based on the workload information, an index value indicating a total workload of completed tasks including the first and second tasks. When the index value is greater than a threshold, the apparatus allows providing the user with notification of the first help information and second help information related to the software selected based on a usage state of the software in the second task; otherwise the apparatus withholds notification of the first and second help information.

Abstract: Embodiments of the present disclosure provides systems and methods for batch accessing. The system includes a plurality of buffers configured to store data; a plurality of processor cores that each have a corresponding buffer of the plurality of buffers; a buffer controller configured to generate instructions for performing a plurality of buffer transactions on at least some buffers of the plurality of buffers; and a plurality of data managers communicatively coupled to the buffer controller, each data manager is coupled to a corresponding buffer of the plurality of buffers and configured to execute a request for a buffer transaction at the corresponding buffer according to an instruction received from the buffer controller.

Abstract: A virtual network system includes a first virtualized network function (VNF), a second VNF, a network functions virtualization infrastructure (NFVI), and a virtualized infrastructure manager (VIM). The VNF performs a network function. The second VNF provides a backup of the first VNF, and provides redundant configuration with the first VNF. The NFVI provides a virtual resource that is a virtualization of a physical resource. The VIM instructs the NFVI to provide the virtual resource as a resource for performing the first VNF and the second VNF, and instructs the NFVI to cancel provision of the virtual resource to the first VNF and to provide the virtual resource as a resource for performing the second VNF when the second VNF is performed and the first VNF is made a backup of the second VNF.

Abstract: Technologies are described herein to implement quantum hybrid computations. Embodiments include receiving a hybrid program, assigning respective functions corresponding to the hybrid program to either of CPU processing or QPU processing, scheduling processing for the respective functions, initiating execution of the hybrid program, and collating results of the execution of the classical-quantum hybrid program.

Abstract: A service management platform can implement functionality for one or more services, each of which can be independently used by a plurality of clients of the services. To activate the functionality of the one or more of the services, a hub server of the service management platform can assign a set of tasks to individual node servers for execution. The hub server can operate in a “supervisor environment” distinct from the processing environment used to execute the computationally intensive portions of the tasks. A task received at a node server can be managed by a supervisor process within the supervisor environment and executed by a native process within a native operating system environment, where the native process executes the computationally intensive calculations of the task and supervisor process provides communications and data transfer between the native process and rest of the service management platform.

Abstract: Examples described herein include systems and methods for prioritizing workloads, such as virtual machines, to enforce quality of service (“QoS”) requirements. An administrator can assign profiles to workloads, the profiles representing different QoS categories. The profiles can extend scheduling primitives that can determine how a distributed resource scheduler (“DRS”) acts on workloads during various workflows. The scheduling primitives can be used to prioritize workload placement, determine whether to migrate a workload during load balancing, and determine an action to take during host maintenance. The DRS can also use the profile to determine which resources at the host to allocate to the workload, distributing higher portions to workloads with higher QoS profiles. Further, the DRS can factor in the profiles in determining total workload demand, leading to more efficient scaling of the cluster.

Abstract: As requests are received, virtual computer systems are provisioned to process the requests. The virtual computer systems may be configured without various components typically implemented by virtual computer systems, such as traditional operating systems, network interfaces and the like. Application images for the virtual computer systems are configured so that execution of the applications can begin soon after provisioning, with minimal overhead the provisioning process contributing relatively little to any latency in processing the request.

Abstract: A remote agent, for providing data protection services to virtual machines, includes persistent storage and a backup manager. The persistent storage is for storing a resource allocation calendar and lifecycle policies associated with the virtual machines. The backup manager obtains a virtual machine data package from a virtual machine of the virtual machines; identifies a computational load change point based on the lifecycle policies; predicts a magnitude of a computational load during a period of time demarcated by the computational load change point using, at least in part, the virtual machine data package; updates the resource allocation calendar to obtain an updated resource allocation calendar, the updating is based on: the identified computational load change point, and the magnitude of the computational load during the period of time; and generates a backup for the virtual machine using the updated resource allocation calendar.

Abstract: A method for enhancing a workload manager for a computer system includes sampling and storing usage of a resource of the computer system as resource usage values, comparing said resource usage values with predetermined performance goal values, assigning a time-stamped priority value to an application that is running based on at least one of the performance goal values by the workload manager, retrieving a portion of the resource usage values and a related portion of the performance goal values for the application, identifying a future workload demand value by applying a time-series analysis algorithm to the resource usage values and the performance goal values for the application resulting in workload demand time frames and related amplitudes of the workload demand time frames, and adjusting a dispatch priority value for the application by setting a minimum dispatch priority for the application based on the future workload demand value.

Abstract: The disclosed technology is generally directed to virtual machines. In one example of the technology, data associated with a virtual machine configuration request is received. A first virtual machine to be reconfigured is provided. The first virtual machine is booted. The first virtual machine is a system virtual machine, the first virtual machine is re-provisioned into be reconfigured in accordance with the virtual machine configuration request without rebooting the first virtual machine.

Abstract: Various examples are disclosed for avoiding power-on failures during virtualization of graphics processing units. A computing environment can be directed to, in response to a virtual machine being powered on, identify a profile for a virtual graphics processing unit (vGPU) designated for the virtual machine, the profile specifying an amount of memory required by the vGPU, identify that the virtual machine is unable to be assigned to any of a plurality of physical graphics processing units (GPUs) based on the amount of memory required by the vGPU, free fat least the amount of memory required by the vGPU by performing a migration of at least one existing virtual machine from a first one of the physical GPUs to a second one of the physical GPUs, and assign the virtual machine to an available one of the physical GPUs and a corresponding host.

Abstract: Methods, computer-readable media, and systems are included for generating information about latency ratings corresponding to a memory pool and a CPU pool. An example method includes for each CPU of the CPU pool, estimating a first latency rating for said each CPU towards the memory pool, and for each memory unit of the memory pool, estimating a second latency rating for said each memory unit towards the CPU pool. The CPUs are organized into a first plurality of groups of CPUs based on the estimated first latency rating, where each CPU of each group of the first plurality of groups has a first common latency rating towards the memory pool. The memory units are organized into a second plurality of groups of memory units based on the estimated second latency rating, where each memory unit of each group of the second plurality of groups has a second common latency rating towards the CPU pool.

Abstract: The present invention discloses a cooperative scheduling method and system for a computing resource and a network resource of a container cloud platform. The method includes: obtaining a load value of a container in a physical machine of a data center; calculating a load margin of a current container; if the load margin of the current container is less than 0, generating a first container sequence; if the load margin of the current container is greater than 0, obtaining a load value of a next container managed by a current physical machine, calculating a load margin of the next container, and updating the calculated load margin of the next container to the load margin of the current container. According to the method and the system of the present invention, resource utilization can be effectively improved.

Abstract: Examples may include techniques to live migrate a virtual machine (VM) using disaggregated computing resources including compute and memory resources. Examples include copying data between allocated memory resources that serve as near or far memory for compute resources supporting the VM at a source or destination server in order to initiate and complete the live migration of the VM.