Systems, computer program products, and methods are described herein for implementing data analytics in a mainframe environment. The present invention is configured to determine one or more data analytics resources associated with natural language processing algorithms; initiate one or more compiler protocols on the one or more data analytics resources to build one or more executable code for the one or more data analytics resources capable of being executed on a mainframe environment; establish a communication link with a job control language (JCL) subsystem associated with the mainframe environment; transmit the one or more executable code for the one or more data analytics resources to the JCL subsystem; generate one or more job control statements configured to be executable on the mainframe environment; generate a log of the one or more job control statements; and initiate an execution of the one or more job control statements on the mainframe environment.

Software is deployed to, and executed at, one or more computing devices in a computing system based on current conditions in the computing system and the capabilities of the different computing devices to handle the software. A request to run a software process calls a manager which determines an optimal place to run the software process. The manager can consider factors such as response time, user demands, bandwidth, processor utilization, storage utilization, security considerations, compatibility considerations and cost. Once a computing device is selected to run the software process, the manager facilitates movement of code and/or data to the computing device.

A method for managing resources, a computing device, and a computer-readable storage medium are provided. The method includes obtaining device information of multiple physical devices included in a computing node to confirm physical devices supporting a predetermined hardware resource management method; initializing at least one physical device among the physical devices supporting the predetermined hardware resource management method as a unified device view device; allocating a virtual storage address of the unified device view device, where the virtual storage address is mapped to a physical storage address of the physical device participating in the unified device view; transmitting data to the virtual storage address of the unified device view device; and issuing a computing task to the unified device view device via a task queue for using the physical device participating in the unified device view to execute the computing task.

Embodiments enable display updates other than a video stream in a graphical user interface (GUI) to be rendered, encoded, and transmitted exclusive of the video stream. A virtual machine generates a GUI that includes an encoded video stream and other display updates. A virtual graphics processing unit (VGPU) stack associated with the VM renders the other display updates of the GUI to a framebuffer. The rendered display updates are encoded and transmitted to a client for display. The encoded video stream, or a modified (e.g., reduced bit rate) version of the encoded video stream, may be transmitted to the client, such that the client can display the encoded video stream within the GUI. For example, the encoded video stream may be selectively transmitted to the client based on the performance capabilities of the client.

A multitenant infrastructure server (MTIS) is configured to provide an environment to execute a computer routine of an arbitrary application. The MTIS receives a request from a webtask server to execute the computer routine in a webtask container. The computer routine is executed in the webtask container at the MTIS. Upon successful execution of the computer routine, a result set is returned to the webtask server. If the execution of the computer routine is unsuccessful, an error notification is returned to the webtask server. The resources consumed during the execution of the computer routine are determined. The webtask container is destroyed to prevent persistent storage of the computer routine on the MTIS.

A query referencing a function associated with a remote software component is received by a network-based data warehouse system. Temporary security credentials corresponding to a role at a cloud computing service platform are obtained. The role has permission to send calls to a web endpoint corresponding to the remote software component. A request comprising input data and electronically signed using the temporary security credentials is sent to a web Application Programming Interface (API) management system of the cloud computing service platform. The request, when received by the web API management system, causes the web API management system to invoke external functionality provided by the remote software component at the web endpoint with respect to the input data. A response comprising a result of invoking the external functionality is received from the web API management system, and the result data is processed according to the query.

Disclosed are systems and methods for determining an execution location for a utility component. In an exemplary aspect, the systems and methods comprise receiving, at a client device, a request to execute the utility component that performs an action on a target component; determining the execution location of the utility component; determining whether the execution location is on the client device or on a remote application server; and responsive to determining the execution location is on the remote application server, transmitting the request to be executed within a remote session between the client device and the remote application server.

An on-demand code execution environment present in points of presence (POPs) and in regions serviced by the POPs is provided herein. For example, a POP may receive a request to execute a task associated with user-defined code. If the POP determines that the computing resources necessary to execute a received task are not available or that the POP should not execute the received task for another reason (e.g., the task is not commonly received and the computing resources needed to execute the task are therefore best allocated for other requests), the POP can forward the task to a region that the POP services for execution by an on-demand code execution environment present in the region. The on-demand code execution environment present in the region can execute the task and forward the results of the execution to the POP for distribution back to a user device that requested the task execution.

Software is deployed to, and executed at, one or more computing devices in a computing system based on current conditions in the computing system and the capabilities of the different computing devices to handle the software. A request to run a software process calls a manager which determines an optimal place to run the software process. The manager can consider factors such as response time, user demands, bandwidth, processor utilization, storage utilization, security considerations, compatibility considerations and cost. Once a computing device is selected to run the software process, the manager facilitates movement of code and/or data to the computing device.

A method, system, and computer-readable storage medium for creating and executing containerized applications in cloud computing are disclosed. For example, one method involves identifying a command. Such a command indicates an application to be executed by a compute node. The method also involves generating a job for transmission to the compute node. The job indicates a container. The compute node, upon receipt of the job, is configured to create an environment for such a container, execute the application within the container, and generate results of the execution of the application.