Aspects of the disclosure relate to a cloud-based parallel processing and cognitive learning computing platform. A computing platform may receive query data comprising a plurality of requested metrics. The computing platform may select a secondary node to process the query request from a plurality of secondary nodes of the computing platform. The computing platform may send the query request to the secondary node. The computing platform may send a request to generate a metric mapping table for a first requested metric to a cognitive learning module of the computing platform. The cognitive learning module may generate the metric mapping table for the first requested metric using neuron clusters that comprise a plurality of unique programmable quadratic function neurons. The computing platform may calculate a value for the first requested metric based on the metric mapping table.

A multi-hypervisor system, comprising: a plurality of hypervisors comprising a first hypervisor and a second hypervisor, at least one of the plurality of hypervisors being a transient hypervisor; and at least one Span VM, concurrently executing on each of the plurality of hypervisors, the at least one transient hypervisor being adapted to be dynamically at least one of injected and removed under the at least one Span VM concurrently with execution of the at least one Span VM on another hypervisor, wherein the at least one Span VM has a single and consistent at least one of memory space, virtual CPU state, and set of input/output resources, shared by the plurality of hypervisors.

A system, method, and computer-readable storage medium provide single sign-on (SSO) in a nested virtualization environment by routing authentication tokens received from an authentication server through the hierarchy of virtual machines (VMs) using secure data communications tunnels between each hypervisor and its respective VMs. A key store stores SSO authentication tokens for users of the nested VMs, and a key controller ensures that each login by a user to a separate VM is associated with its own token. Each login request is uniquely tagged to identify the particular VM requesting credentials, so that the responsive authentication token can be properly routed through the hierarchy. Moreover, session preferences may be associated with each user and/or each VM, enabling a rules evaluator to determine, for each login request, whether SSO functionality should be provided or whether the user should be required instead to provide new login credentials.

Methods, apparatus, systems, and articles of manufacture are disclosed for rack nesting in virtualized server systems. An example apparatus includes a resource discoverer to identify resources to be allocated to the nested rack based on a policy indicative of one or more physical racks from which to identify the resources, and determine candidate resources from the resources to be allocated to the nested rack based on a capacity parameter indicative of a quantity of the resources available to be allocated to the nested rack, the candidate resources to have first hypervisors, and a nested rack controller to generate the nested rack by deploying second hypervisors on the first hypervisors, the second hypervisors to facilitate communication between the candidate resources and one or more virtual machines on the second hypervisors, the nested rack to execute one or more computing tasks based on the communication.

A system and method of emulating virtual processor identifiers includes a nested hypervisor requesting a virtual processor identifier, which identifies a virtual processor, the request triggering an exit to a host hypervisor. The host hypervisor identifies a request including the virtual processor identifier. The host hypervisor generates a key defining an association between a virtual machine and the virtual processor identifier. The host hypervisor stores the key.

A processing system allows external systems to customize and extend services without increasing system intricacy. The processing platform maintains cloud containers that support virtual machines for external systems. An external system provides code for execution on a virtual machine that is supported by a cloud container. Cloud containers provide a boundary for executing code such that the processing platform may limit types of code an external system can run at a cloud container. The external system code can provide new services or may build upon existing public services, and external systems may designate their services as being available to other external systems by publishing the access information in a global application programming interface (API) maintained by the processing platform. Since the external systems submit instructions for execution within their assigned cloud containers, the services and applications are developed without affecting the underlying functionality of the processing platform.

Systems and methods for memory management for virtual machines. An example method may comprise running, by a host computer system, a Level 0 hypervisor managing a Level 1 virtual machine running a Level 1 hypervisor which manages a Level 2 virtual machine having encrypted memory pages. The Level 1 hypervisor may generate a shadow page table where each shadow page table entry of the plurality of shadow page table entries maps a Level 2 guest virtual address of a Level 2 address space associated with the Level 2 virtual machine to a corresponding Level 1 guest physical address of a Level 1 address space associated with the Level 1 virtual machine. The Level 0 hypervisor may generate a Level 0 page table comprising a plurality of Level 0 page table entries that maps a Level 1 guest physical address to a corresponding Level 0 host physical address.

A first command is received from a workload, by a host system executing a nested container storage interface (CSI) driver, to create a persistent volume. The nested CSI driver converts the first command used by the workload to create the persistent volume to a second command used by the host system to increase a capacity of a previously generated persistent volume allocated to the workload. The second command is transmitted to an undercluster CSI driver of the host system, wherein the second command causes the undercluster CSI driver to increase the capacity of the previously generated persistent volume.

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.

The disclosed computer-implemented method may include identifying a video game configured to be available to stream from a server within a cloud gaming environment; pre-loading an instance of the video game on the server before receiving a request by a user to stream the video game to a client system; receiving the request by the user to stream the video game; and allocating the pre-loaded instance of the video game to the user for streaming to the client system in response to receiving the request by the user to stream the video game, thereby reducing a latency between the user submitting the request and the video game being ready for the user to stream. Various other methods, systems, and computer-readable media are also disclosed.