Systems and methods for transaction/file-based management of a plurality of processes associated with various jobs are provided. Through the management of discrete applications, a file distribution manager/scheduler orchestrates automated execution of different types of jobs. The processes executed for the various processes can vary based on job type, or other parameters.

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

Embodiments relate to a computing system for solving differential equations. The system is configured to receive problem packages corresponding to problems to be solved, each comprising at least a differential equation and a domain, and to select a solver of a plurality of solvers, based upon availability of each of the plurality of solvers. Each solver comprises a coordinator that partitions the domain of the problem into a plurality of sub-domains, and assigns each of the plurality of sub-domains to a differential equation accelerator (DEA) of a plurality of DEAs. Each DEA comprises at least two memory units, and processes the sub-domain data over a plurality of time-steps by passing the sub-domain data through a selected systolic array from one memory unit, and storing the processed sub-domain data in the other memory unit, and vice versa.

This application discloses a method for dynamically triggering instantiation of an edge application server, and an apparatus. The method includes: A first device receives first information, where the first information is for requesting information about an edge application server of a first application, or is for requesting information about a first edge enabler server, where the first edge enabler server is configured to provide information about an edge application server of a first application; and the first device requests, based on the first information, an edge application server management function entity to instantiate the edge application server of the first application. In embodiments of this application, the edge application server is instantiated based on a user requirement, so that dynamic scheduling and flexible use of a resource are improved, and quality of service experience of an edge application is improved.

A method for cloud service includes receiving, by processing circuitry that operates for a cloud service, a request including a first reporting descriptor object including (i) a first variables descriptor object associated with variables, (ii) a first events descriptor object associated with events, and (iii) a reporting interval. The method also includes generating, by the processing circuitry, at a time within the reporting interval, a message including a second reporting descriptor object with (i) a second variables descriptor object having updated values for the variables and (ii) a second events descriptor object associated with a subset of the events. The method also includes sending, by the processing circuitry, the message to a recipient.

Techniques for implementing rollback of infrastructure changes in an infrastructure orchestration service are described. In certain examples, an infrastructure orchestration service is disclosed that manages both provisioning and deploying of infrastructure assets within a cloud environment. The service receives a plan comprising a set of instructions associated with a set of infrastructure assets of an execution target and identifies a first state of the set of infrastructure assets. The service executes the set of instructions in the plan to achieve a second state for the set of infrastructure assets. Based in part on the executing, the service receives a trigger for rolling back the plan to restore the set of infrastructure assets in the plan to the first state and executes a rollback plan for the plan. The service then transmits a result associated with the execution of the rollback plan.

Described are examples for deploying workloads in a cloud-computing environment. In an aspect, based on a desired number of workloads of a process to be executed in a cloud-computing environment and based on one or more failure probabilities, an actual number of workloads of the process to execute in the cloud-computing environment to provide a level of service can be determined and deployed. In another aspect, a standby workload can be executed as a second instance of the process without at least a portion of the separate configuration used by the multiple workloads, and based on detecting termination of one of multiple workloads, the standby workload can be configured to execute based on the separate configuration of the separate instance of the process corresponding to the one of the multiple workloads.

A method for data provisioning a serverless computing cluster. A plurality of user defined functions (UDFs) are received for execution on worker nodes of the serverless computing cluster. For a first UDF, one or more data locations of UDF data needed to execute the first UDF are determined. At a master node of the serverless computing cluster, a plurality of worker node tickets are received, each ticket indicating a resource availability of a corresponding worker node. The one or more data locations and the plurality of worker node tickets are analyzed to determine eligible worker nodes capable of executing the first UDF. The master node transmits a pre-fetch command to one or more of the eligible worker nodes, causing the eligible worker nodes to become a provisioned worker node for the first UDF by storing a pre-fetched first UDF data before the first UDF is assigned for execution.

A lightweight, workload-agnostic application management agent (AMA) automatically upgrading application agents on a virtual machine (VM). The AMA is installed in the VM as part of a Gold image installation. The AMA detects a workload-type of the VM and sends the workload information to an application manager. The AMA continuously monitors the VM for any change in workload type, and any change causes the AMA to install a respective workload-specific agent (WSA) for the new workload in the VM. The AMA accesses the new WSA from the application manager though a push or pull operation. Applications are thus automatically upgraded through VM resident agents. The user needs only to update policies and load updated software to the application manager without manually upgrading the WSA agents themselves.

Aspects of the present disclosure relate to controlling resource consumption of a server and storage array. In embodiments, a request can be received by a server that is communicatively coupled to a storage array. Further, the services required to process the request can be identified. Additionally, services' activation can be controlled based on a mapping of request-related actions and initiated services.