Abstract: A system and method to operate applications through positional virtualization technology. The system comprises a server including at least one processor and memory storing a persistent virtual world system comprising a data structure in which at least one virtual replica of at least one corresponding real object is represented, and at least one application run and hosted on at least one virtual machine virtually positioned in a location of the persistent virtual world system. Provisioning of the virtual machines is managed by a virtual machine management system stored in the memory of the server. One or more user devices connected to the servers via a network are configured to access and execute the applications hosted on the virtual machines of the at least one server and to receive resources thereof based on application requirements.

Abstract: An embodiment takes the form of a method carried out by a task-execution device. The task-execution device applies a first local-model update to a local model of the task-execution device. The first local-model update is applied based on a first global-model update to a global model of a global-model repository. The task-execution device generates an execution policy based on (i) a received task request identifying a requested task and (ii) the local model including the first local-model update. The task-execution device executes a performance of the requested task based on the generated execution policy, and obtains an observation of the performance of the requested task. Additionally, the task-execution device applies a second local-model update to the local model based on the obtained observation of the performance of the requested task, and provides the global-model repository with an indication of the second local-model update.

Abstract: Disclosed herein are systems and method efficiently executing a program operation on a cloud-based service. In an exemplary aspect, a method comprises receiving a request to perform a program operation on a cloud-based service and at least one user constraint for performing the program operation, and determining a plurality of sub-operations that are comprised in the program operation. The method comprises identifying a plurality of service component combinations offered by the service provider that can execute the program operation, and identifying, based on a status of each service component, at least one processing constraint of each service component. The method comprises determining, by a machine learning algorithm, a service component combination from the plurality of service component combinations for executing the program operation based on the at least one user constraint and processing constraints. The method comprises executing the program operation by the determined service component combination.

Abstract: Calls run through a virtual desktop infrastructure server are enhanced by opening a media channel between a personal computing device and a media server for a call initiated using a virtual desktop infrastructure server. A first stream of media data for the call is merged with a second stream of media data for the call in a single virtual channel of the protocol using a first packet queue to store packets of the first stream and a second packet queue to store packets of the second stream as the packets await transmission. A first packet of media data of the first stream is pushed into the first packet queue. A fill level of the first packet queue is compared to a first congest threshold associated with the first packet queue. Responsive to the fill level exceeding the first congest threshold, a congestion mitigation measure is invoked.

Abstract: An apparatus comprises a processing device that is configured to obtain a metadata structure corresponding to a workflow automation. The metadata structure defines a first tier comprising individual tasks, a second tier comprising a plurality of workflows each comprising a grouping of the individual tasks and a third tier comprising an orchestration comprising a grouping of the workflows. The processing device is configured to generate a graphical user interface (GUI) based on the metadata structure that is configured to present the plurality of tiers to a user. The GUI comprises a plurality of elements each activatable to enable or disable corresponding individual tasks and workflows. The GUI is presented to a user and an activation of a given element is received from the user. The activation disables the corresponding individual task or workflow for the workflow automation. The workflow automation is executed based at least in part on the activation.

Abstract: In an approach to improve the field of architecture generation by dynamically sizing computer system architecture requirements for virtual machines. Embodiments define static parameters and dynamic parameters for customer consuming resources of the computer system architecture and store data of the static parameters and dynamic parameters in data warehouse database (DWDB) tables. Further, embodiments compute, using the data of the DWDB tables, calculate the minimum, maximum, mean and standard deviation (SD) for the user count and the CPU and memory usage, and update the DWDB tables based on the minimum, maximum, and SD values per customer.

Abstract: Methods and systems for a meta federation broker extend requests for computing services across multiple different cloud computing environments using ontology models. The meta federation broker may receive, from a federation participant, a federation participant query that includes semantic query data. At least one federation service from a plurality of federation services can be determined, based on processing the federation participant query and ontological data defining a ontology model, each ontology model describing federation services based on relationships between components of a federated cloud computing environment. The meta federation broker can validate a federation cloud broker that provides the at least one federation service to the federation participant and facilitate brokering of the at least one federation service to the federation participant by the federation cloud broker.

Abstract: An example method of application identification in a virtualized computing system having a cluster of hosts, the hosts including virtualization layers supporting virtual machines (VMs), is described. The method includes: executing, by application analysis software, process discovery agents for the VMs; receiving, at the application analysis software from the process discovery agents, process metadata describing processes executing on the VMs; generating signatures for the processes based on the process metadata; and determining components of an application based on the signatures.

Abstract: A technique includes an agent executing on a plurality of nodes while a job is being concurrently executed by the plurality of nodes. The plurality of nodes is power-capped by an existing node power consumption budget. The technique includes managing power consumption of the plurality of nodes. The managing includes the agent determining a performance footprint that is associated with execution of the job; and the managing includes the agent determining a second node power consumption budget based on the performance footprint. The second node power consumption budget is different than the existing node power consumption budget. The managing includes the agent providing a power consumption request to a global power dispatcher to set a new node power consumption budget for the plurality of nodes.

Abstract: A method in one embodiment comprises implementing a kernel-based isolation layer, configuring a software container on the kernel-based isolation layer to include a dedicated operating system kernel as a library operating system, and executing one or more user processes in the software container. The method is performed by a cloud-based processing platform, an enterprise processing platform, or other type of processing platform comprising a plurality of processing devices, with each such processing device comprising a processor coupled to a memory. The library operating system illustratively runs in the software container at a privilege level that is the same as a privilege level of the one or more user processes executing in the software container. The library operating system is illustratively configured to support automatic translation of binaries of the one or more user processes in conjunction with converting system calls into corresponding function calls.

Abstract: A system includes a processor in communication with a memory, a virtual machine running on the processor, and a hypervisor. The hypervisor is configured to receive a workload definition file (“WDF”). The WDF is associated with a workload, and the WDF is packaged such that the WDF is configured to generate a workload definition device (“WDD”). Additionally, the hypervisor is configured to receive a request to deploy the WDD within the virtual machine. The request includes the WDF. The hypervisor is also configured to deploy the WDD within the virtual machine. The WDD is configured to automatically execute the workload responsive to meeting at least one execution criteria.

Abstract: An example method includes: executing, by application analysis software executing in the virtualized computing system, process discovery agents on the VMs; receiving, at the application analysis software from the process discovery agents, process metadata describing processes executing on the VMs; generating signatures for the processes based on the process metadata; determining components of an application based on the signatures; determining components of an application based on the signatures; identifying, for a first component of the components, a component-specific metadata collector; executing, by the application analysis software, the component-specific metadata collector on a first VM of the VMs; and receiving, at the application analysis software from the component-specific metadata collector, custom metadata further describing a first process of the processes associated with the first component.

Abstract: A resource integration method includes the following steps: a receiving module receives access information from a guest operating system on the host device; the access information is used to determine whether the frame rate is lower than a frame rate threshold; when the receiving module determines that the frame rate is lower than the frame rate threshold, the receiving module transmits an external resource request signal to the receiving module; after the receiving module receives the external resource request signal, a resource management module (which is located in the bridge module) selects an optimal external device from a specific category (among a plurality of categories in a candidate list), and a calculation operation or a storage operation corresponding to the specific category is transmitted to the optimal external device for calculation or storage by the bridge module.

Abstract: An atomicity securing apparatus that secures atomicity of collaborative services includes: an atomicity determination unit configured to determine, in a case in which there is an error response to a first service among a plurality of types of services configuring the collaborative services in response to a request to execute the plurality of types of services, whether or not a process for updating second services other than the first service in the plurality of types of services is completed in consideration of inquiry to a collaborative service execution apparatus that executes the collaborative services; a cancellation API request generation unit configured to generate a cancellation API request for canceling the process for updating the second services that is completed; and a cancellation API request transmission unit configured to transmit the generated cancellation API request to a server that provides the second services.

Abstract: Upon receiving a request to hibernate a hypervisor of a virtualization system running on a first computer, acts are carried out to capture a state of the hypervisor, where the state of the hypervisor comprises hypervisor logical resource parameters and an execution state of the hypervisor. After hibernating the hypervisor by quiescing the hypervisor and storing the state of the hypervisor into a data structure, the data structure is moved to a different location. At a later moment in time, the data structure is loaded onto a second computing machine and restored. The restore operation restores the hypervisor and all of its state, including all of the virtual machines of the hypervisor as well as all of the virtual disks and other virtual devices of the virtual machines. Differences between the first computing machine and the second computing machine are reconciled before execution of the hypervisor on the second machine.

Abstract: A dynamically configurable overprovisioned microprocessor optimally supports a variety of different compute application workloads and with the capability to tradeoff among compute performance, energy consumption, and clock frequency on a per-compute application basis, using general-purpose microprocessor designs. In some embodiments, the overprovisioned microprocessor comprises a physical compute resource and a dynamic configuration logic configured to: detect an activation-warranting operating condition; undarken the physical compute resource responsive to detecting the activation-warranting operating condition; detect a configuration-warranting operating condition; and configure the overprovisioned microprocessor to use the undarkened physical compute resource responsive to detecting the configuration-warranting operating condition.

Abstract: Events to be executed by one or more serverless functions are received from an events queue. A determination that a first set of the events are to be executed by one or more serverless functions at a local host system and a second set of the events are to be executed at one or more serverless functions at a remote host system is made. The first set of the events are directed to the one or more serverless functions at the local host system and the second set of the events are directed to the one or more serverless functions at the remote host system.

Abstract: An example virtualized computing system includes: a host cluster having a virtualization layer directly executing on hardware platforms of hosts, the virtualization layer supporting execution of virtual machines (VMs), the VMs including pod VMs and native VMs, the pod VMs including container engines supporting execution of containers in the pod VMs, the native VMs including applications executing on guest operating systems; an orchestration control plane integrated with the virtualization layer and including a master server and native VM controllers, the master server managing lifecycles of the pod VMs and the native VMs; and management agents, executing in the native VMs, configured to receive decoupled information from the master server through the native VM controllers and to provide the decoupled information for consumption by the applications executing in the native VMs, the decoupled information including at least one of configuration information and secret information.

Abstract: Described herein is a system for identifying controls not aligned with updated compliance data. The system may scrub external data sources for updated compliance data. The system may detect and extract the updated compliance data from the external data sources. The system may identify and correlate controls of compliance applications currently using compliance data which has now been updated. The system determines whether a control exists to cover the updated compliance data. In the event, a control does not exist or an existing control does not cover the updated compliance data, a requirement may be generated for generating a new control or modifying an existing control for the updated compliance data.

Abstract: A data management system comprises: a storage appliance configured to store a snapshot of a virtual machine; and one or more processors in communication with the storage appliance. The one or more processors are configured to perform operations including: identifying a plurality of shards of the virtual machine; requesting a snapshot of each of the plurality of shards; receiving the shards asynchronously; ordering the received snapshot shards sequentially into a results queue; and storing a single snapshot of the virtual machine based on the ordered snapshot shards. Operations may further include maintaining a flow control queue that limits the number of snapshot shards requested.