Abstract: Methods and systems for a virtual machine environment are provided. One method includes allocating a memory for storing a dirty pages data structure for tracking writes to a virtual machine memory by an adapter coupled to a computing device and shared by a plurality of virtual machines; initiating a tracking operation by the adapter or a virtual function driver to track writes to the virtual memory; providing access to the dirty pages data structure in response to a query command, while the adapter or the virtual function driver tracks writes to the virtual machine memory; and providing a number of dirty pages within the dirty pages data structure and a pointer the dirty pages data structure by the adapter or the virtual function driver.

Abstract: Techniques are provided for enabling cross-process coordination between multiple instances of given microservice in a cloud computing system. A method includes running a plurality of active instances of a given microservice of a computing system comprising a distributed microservices architecture. A first active instance of the plurality of active instances executes a portion of program code of the given microservice to perform a job. The portion of the program code of the given microservice includes an instance synchronization element which is configured to enable cross-process coordination between the plurality of active instances of the given microservice with the support of a collaboration service.

Abstract: In some embodiments, a method for cluster resource scheduling, includes determining at least one load score; determining a memory score; determining an IO score; and monitoring a message bus for candidate messages when each of the at least one load score, memory score, and IO score is less than a pre-determined health threshold. In some embodiments, a host computer system for hosting a plurality of virtual machines (VMs), includes: a memory; a network adapter for communicating with the cluster by way of a message bus; a processor in electronic communication with the memory and the network adapter, wherein the processor is programmed to: determine at least one load score; determine a memory score; determine an IO score; and monitor the message bus for candidate messages when each of the at least one load score, memory score, and IO score is less than a pre-determined health threshold.

Abstract: An information handling system may include at least one processor, and a non-transitory memory coupled to the at least one processor. The information handling system may be configured to execute a configuration procedure to set up a plurality of information handling resources of the information handling system, and wherein the configuration procedure includes a plurality of logical groups related to different types of configuration. Each logical group may include one or more atomic groups, each atomic group including a plurality of logically related atomic operations. In response to a failure of a particular atomic operation of a particular atomic group, the information handling system may be configured to roll back the particular atomic operation and allow the configuration procedure to be restarted at a beginning of the particular atomic group.

Abstract: A method and apparatus of a device for resource management by using a hierarchy of resource management techniques with dynamic resource policies is described. The device terminates several misbehaving application programs when available memory on the device is running low. Each of those misbehaving application programs consumes more memory space than a memory consumption limit assigned to the application program. If available memory on the device is still low after terminating those misbehaving application programs, the device further sends memory pressure notifications to all application programs. If available memory on the device is still running low after sending the memory pressure notifications, the device further terminates background, idle, and suspended application programs. The device further terminates foreground application programs when available memory on the device is still low after terminating the background, idle, and suspended application programs.

Abstract: A Disaster Recovery (DR) verification process or system verifies readiness to execute a Disaster Recovery (DR) test. Such DR verification is automatically provided on a regular basis, with minimum impact on both a production and recovery environment. However, DR verification is only enabled at a time when no disaster recovery or DR testing of other sites is already under way. Configuration data needed for DR verification is constantly replicated from production to recovery, by dedicated data movers. DR verification allocates and configures recovery resources in an encapsulated environment, confirms successful their instantiation (such as boot up and network connections), and reports the outcome.

Abstract: One embodiment provides a method, including: receiving at least one deep learning job for scheduling and running on a distributed system comprising a plurality of nodes; receiving a batch size range indicating a minimum batch size and a maximum batch size that can be utilized for running the at least one deep learning job; determining a plurality of runtime estimations for running the at least one deep learning job; creating a list of optimal combinations of (i) batch sizes and (ii) numbers of the plurality of nodes for running both (a) the at least one deep learning job and (b) current deep learning jobs; and scheduling the at least one deep-learning job at the distributed system, responsive to identifying, by utilizing the list, that the distributed system has necessary processing resources for running both (iii) the at least one deep learning job and (iv) the current deep learning jobs.

Abstract: An apparatus for executing one or more commands, for use with a virtualization environment operable to execute one or more virtualization functions, the apparatus comprising: an interface operable to determine an identifier associated with a first virtualization function; a parser operable to determine one or more commands available for execution using the first virtualization function; a store for storing each determined command with the first virtualization function identifier; a searcher, responsive to input of a first command, for matching the first command with each determined command in order to determine one or more matching commands; and an executor, responsive to selection of a first matching command, for executing the associated first virtualization function and the first matching command.

Abstract: An aspect of the present disclosure facilitates early identification of problems in execution of background processes. In one embodiment, a digital processing system characterizes the consumption of multiple resources during normal prior executions of a background process and determines a baseline pattern of consumption of resources for the background process. The system then monitors a current pattern of consumption of the resources during a current execution of the background process, and checks whether the current pattern of consumption has a deviation from the baseline pattern of consumption. The system notifies a potential problem with the current execution of the background process if a deviation is determined to exist. The notifications enable a user to get an early indication of potential problems during the execution of the background process itself.

Abstract: A system that allows a contractor to remotely monitor and/or interact with its customers' building control systems, such as heating, ventilating and air conditioning (HVAC) systems, and analyze information obtained from the building control systems over time. Such a system may help the contractor monitor and diagnosis customer building control systems, setup service calls, achieve better customer relations, create more effective marketing opportunities, as well as other functions. In some cases, the disclosed system may include a controller that analyzes data from HVAC systems, determines a thermal model of a space environmentally controlled by an HVAC system, and provides an energy audit of the space that is environmentally controlled by the HVAC system. The controller may output a result of the energy audit to a user.

Abstract: A system enabling a hypervisor to assign processor resources for specific tasks to be performed by a virtual machine. An example method may comprise: receiving, by a hypervisor running on a host computer system, a virtual processor (“vCPU”) assignment request from a virtual device driver running on a virtual machine managed by the hypervisor, assigning a vCPU for executing a task associated with the assignment request, and causing the virtual device driver to execute the task using the vCPU.

Abstract: One example technique includes receiving a request for accessing a file from a container process. In response to receiving the request, the technique includes querying a mapping table corresponding to the container process to locate an entry corresponding to a file identifier of the requested file. The entry also includes data identifying a file location on the storage device from which the requested file is accessible. The technique further includes retrieving a copy of the requested file according to the file location identified by the data in the located entry in the mapping table and providing the retrieved copy of the requested file to the container process, thereby allowing the container process to access the requested file.

Abstract: In one set of embodiments, a computer system can analyze a layout of one or more storage objects of a VM to be placed within a cluster of host systems of a hyper-converged infrastructure (HCI) deployment. The computer system can further determine, based on the analyzing, that the one or more storage objects are stored on a single host system or within a single fault domain of the cluster. The computer system can then cause the VM to be placed on that single host system or within that single fault domain.

Abstract: An example method of managing storage for a containerized application executing in a virtualized computing system having a cluster of hosts and a virtualization layer executing thereon, is described. The method includes receiving, at a supervisor container orchestrator, a request for a first persistent volume lifecycle operation from a guest container orchestrator, the supervisor container orchestrator being part of an orchestration control plane integrated with the virtualization layer and configured to manage a guest cluster and virtual machines (VMs), supported by the virtualization layer, in which the guest cluster executes, the guest container orchestrator being part of the guest cluster; and sending, in response to the first persistent volume lifecycle operation, a request for a second persistent volume lifecycle operation from the supervisor container orchestrator to a storage provider of the virtualized computing system to cause the storage provider to perform an operation on a storage volume.

Abstract: A method including: receiving, by a computing device, a request from a user device for access to a hosted virtual machine; dedicating, by the computing device, a port to forward a cast of a particular hosted virtual machine instance to the user device; establishing a connection between the user device and the particular hosted virtual machine instance through the dedicated port; receiving, by the computing device and from the user device, instructions to execute an application on the particular hosted virtual machine instance; logging external calls made by the particular hosted virtual machine instance; and transmitting, by the computer device, the log of external calls to be stored on a server, the logs being synced by the server with the user device in substantially real time.

Abstract: The disclosure relates to systems, methods and computer-readable media for using system jobs for performing actions outside the constraints of batch compute jobs submitted to a compute environment such as a cluster or a grid. The method for modifying a compute environment from a system job disclosure associating a system job to a queuable object, triggering the system job based on an event and performing arbitrary actions on resources outside of compute nodes in the compute environment. The queuable objects include objects such as batch compute jobs or job reservations. The events that trigger the system job may be time driven, such as ten minutes prior to completion of the batch compute job, or dependent on other actions associated with other system jobs. The system jobs may be utilized also to perform rolling maintenance on a node by node basis.

Abstract: The disclosure relates to systems, methods and computer-readable media for using system jobs for performing actions outside the constraints of batch compute jobs submitted to a compute environment such as a cluster or a grid. The method for modifying a compute environment from a system job disclosure associating a system job to a queuable object, triggering the system job based on an event and performing arbitrary actions on resources outside of compute nodes in the compute environment. The queuable objects include objects such as batch compute jobs or job reservations. The events that trigger the system job may be time driven, such as ten minutes prior to completion of the batch compute job, or dependent on other actions associated with other system jobs. The system jobs may be utilized also to perform rolling maintenance on a node by node basis.

Abstract: A computer implemented method of scheduling a plurality of virtual machines for execution by a physical computing infrastructure is described. The plurality of virtual machines are deployable to a subset of the physical computing infrastructure to execute a computing task. The method includes determining a subset of the infrastructure and a time period for deployment of each virtual machine, so that the virtual machines are scheduled to execute to completion over an aggregate of all time periods. The determination is based on a mathematical optimization of a risk function for each of the plurality virtual machines that corresponds to a relative risk that at least one virtual machine will fail to fully execute its task to completion.

Abstract: Examples provide a method of communication between a client driver and a filesystem server. The client driver executes in a virtual machine (VM) and the filesystem server executes in a hypervisor. The method includes: allocating, by the client driver, shared memory in an address space of the VM for the communication; sending identification information for the shared memory from the client driver to the filesystem server through an inter-process communication channel between the client driver and the filesystem server; identifying, by the filesystem server in cooperation with a kernel of the hypervisor, the shared memory within an address space of the hypervisor, based on the identification information, to create a shared memory channel; sending commands from the client driver to the filesystem server through the shared memory channel; and receiving completion messages for the commands from the filesystem server to the client driver through the shared memory channel.

Abstract: Examples may include a method of instantiating a virtual machine; instantiating a virtual device to transmit data to and receive data from assigned resources of a shared physical device by receiving input data requesting assigned resources for the virtual device, allocating assigned resources to the virtual device based at least in part on the input data, and mapping a page location in an address space of the shared physical device for a selected one of the assigned resources to a page location in a memory-mapped input/output (MMIO) space of the virtual device; and assigning the virtual device to the virtual machine, the virtual machine to transmit data to and receive data from the physical device via the MMIO space of the virtual device.