Abstract: A method, system, and computer program product for implementing automated serverless runtime container allocation is provided. The method includes defining a number of runtime containers and associated characteristics required for each worker node of a plurality of worker nodes for execution of a specified workload. The specified workload is dispatched to the plurality of worker nodes and a specified portion of the specified workload is assigned to each worker node. An application executing a universal runtime container that includes potential application runtimes and associated supported software versions within a layered modifiable format is generated and unused layers are removed from the universal runtime container. The specified workload is executed via the universal runtime container and a set of available universal runtime containers is refilled on an associated work node.

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: Examples described herein include virtualized environments including a virtualized file server. Examples of file server virtual machine managers are described which may setup and/or configure file server virtual machines in accordance with a target number of connections and/or a target throughput for the virtualized file server. The virtualized file server may be scaled up, scaled down, scaled in, and/or scaled out.

Abstract: A device may receive, from a virtual machine deployed on the device, a request to register for an event associated with a hardware component of the device, and may create a path to a script associated with providing information about the event when the event occurs. The device may provide the script to an event plugin associated with the event and the hardware component, and may register the event plugin with a kernel associated with the device. The device may receive, the kernel, information indicating occurrence of the event associated with the hardware component, and may cause, via the event plugin, execution of the script based on the occurrence of the event associated with the hardware component. The device may provide, based on execution of the script, a notification to the virtual machine, where the notification may indicate the occurrence of the event associated with the hardware component.

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: Generally described, one or more aspects of the present application relate to scaling a cluster of compute capacity used to execute containerized applications or tasks. For example, a waiting area can be maintained, in which tasks that are requested to be executed in a cluster but are not able to be accommodated in the cluster due to the cluster not having sufficient compute capacity usable to execute such tasks are stored. The scaling of the cluster can be performed based on the characteristics of the tasks in the waiting area, such that the cost associated with adding too much compute capacity to the cluster can be reduced, while also reducing the time it takes to reach the desired level of compute capacity that can accommodate all of the requested tasks.

Abstract: An example electronic apparatus is for accelerating a para-virtualization network interface. The electronic apparatus includes a descriptor hub performing bi-directionally communication with a guest memory accessible by a guest and with a host memory accessible by a host. The guest includes a plurality of virtual machines. The host includes a plurality of virtual function devices. The virtual machines are communicatively coupled to the electronic apparatus through a central processing unit. The communication is based upon para-virtualization packet descriptors and network interface controller virtual function-specific descriptors. The electronic apparatus also includes a device association table communicatively coupled to the descriptor hub and to store associations between the virtual machines and the virtual function devices. The electronic apparatus further includes an input-output memory map unit (IOMMU) to perform direct memory access (DMA) remapping and interrupt remapping.

Abstract: Systems and methods for automated workflow comprise assigning a set of first targets to an uncompiled first workflow. The uncompiled first workflow specifies a first set of process modules. Each such module is associated with a subset of unit operations. Each unit operation includes a time interval and specifies an instrument. For each target in the set of first targets, the uncompiled workflow is translated into an instance of a compiled first workflow comprising a linear temporal order of unit operations, each including execution instructions for an addressed instrument. A set of second targets is obtained and assigned a second uncompiled workflow. Compilation of the second uncompiled workflow for each second target produces a different instance of a compiled second workflow. Each second compiled workflow comprises a linear temporal order of unit operations, with each unit operation including execution instructions for an addressed instrument and specifying a time interval.

Abstract: Systems and methods of executing multiple scripts at an extension point are provided. If there are multiple scripts that are associated with an extension point for a service instance in a SAAS platform, a script execution schedule is determined. This can indicate the order of execution of the multiple scripts, but may also specify how the inputs and outputs of the multiple script executions are obtained. For example, the inputs for multiple scripts can be the same, and be those provided by the SAAS platform at the extension point. In this case, in effect the multiple scripts are executed independently. Alternatively, the output of one script can function as the input to another script, which requires a certain order of execution. After all of the scripts are executed, output rules are used to determine an overall output of the script execution to be returned the platform through the extension point.

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: Workload planning with quality-of-service (‘QoS’) integration, including: determining, for each of a plurality of entities, one or more QoS thresholds associated with the entity; determining, for each of the plurality of entities, one or more resource utilization levels associated with the entity; and determining, in dependence upon the one or more QoS thresholds associated with the plurality of entities, the one or more resource utilization levels associated with the plurality of entities, and one or more overprovisioning factors associated with the storage system, a risk factor that identifies the likelihood that one or more system resources will be overconsumed by the plurality of entities.

Abstract: Systems, computer program products, and methods are described herein for monitoring and automatically controlling batch processing. The present invention may be configured to receive a plurality of data processing requests and determine a processing plan for the plurality of data processing requests. The present invention may be configured to provide, to processing applications and based on the processing plan, actions for performance by the processing applications to complete the plurality of data processing requests. The present invention may be configured to predict, while the processing applications are performing the actions and using a completion time predicting machine learning model, completion times for the plurality of data processing requests.

Abstract: In an example embodiment, a solution is provided that causes a binary used by an in-memory database application to be deployed in a separate container. The container with the binary may be called a “sidecar” to the container with the in-memory database application. Both containers mount the same path in the hosts shared filesystem to expose the binary to the application. There is no permanent connection between the two containers, and thus the binary can be updated individually without inducing a downtime of the in-memory database application.

Abstract: A memory system is provided to include a first virtual function controller in communication with a first virtual machine of a host and configured to receive, from the first virtual machine, a command for accessing a namespace and provide, to the first virtual machine, a response to the command; a second virtual function controller in communication with a second virtual machine of the host and configured to be coupled to the namespace and receive the command from the first virtual function controller based on status information of the first virtual function controller and the second virtual function controller; a buffer memory configured to provide an area for data corresponding to the command; and a memory controller configured to access the namespace based on the command and provide the buffer memory with the data.

Abstract: The present application discloses a system, readable storage medium, and method for analyzing a cause of training-task queuing, wherein the method includes the steps of: obtaining a required resource that is required by a training task inputted by a user and a remaining resource of a cluster; in responding to that the remaining resource does not satisfy the required resource, obtaining a plurality of cluster center data that are pre-generated in a cluster model; regarding the required resource and the remaining resource as sample data, and calculating distances between the sample data and each of the cluster center data; and feeding back a cause corresponding to the cluster center datum that has a minimum distance with the sample data.

Abstract: The aspects of the present disclosure provide a method and an apparatus for implementing hardware resource allocation. For example, the apparatus includes processing circuitry. The processing circuitry obtains a first value that is indicative of an allocable resource quantity of a hardware resource in a computing device. The processing circuitry also receives a second value that is indicative of a requested resource quantity of the hardware resource by a user, and then determines whether the second value is greater than the first value. When the second value is determined to be less than or equal to the first value, the processing circuitry requests the computing device to allocate the hardware resource of the requested resource quantity to the user, and subtracts the second value from the first value to update the allocable resource quantity of the hardware resource in the computing device.

Abstract: A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process. The process acquires topology information that indicates a calling relationship between containers that operate in a first information processing device. The process also identifies a second container that is one of calls of a first container that calls two or more containers, and a third container that does not call another container based on the topology information. Next, the process moves, to a second information processing device, a container group that is connected by the calling relationship from the second container to the third container.

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 system and method for scanning of virtual machine images. The method includes creating a virtual machine instance of a virtual machine based on a virtual machine image of the virtual machine and an application programming interface (API) of an environment in which the virtual machine is to be deployed, wherein the virtual machine image has an entry point such that the virtual machine instance executes the entry point; and replacing the entry point of the virtual machine instance with a lightweight script, wherein the lightweight script is configured to retrieve a static scanner executable, to execute the static scanner executable, and to send results of the scanning.

Abstract: An information processing system executes a series of processes. The information processing system includes a computer which manages, among multiple programs for executing the series of processes, a first program included in the information processing system and one or more second programs registered in the information processing system. The computer controls execution of the series of processes including a process executed by the second program and controls a virtual server for executing the second program.