Input data for an operating system command of an automation process is received. The operating system command is generated based on the received input data. The generated operating system command is parsed to identify one or more metrics. The identified one or more metrics are automatically evaluated to determine a security risk associated with the generated operating system command.

The exemplary embodiments are related to a pipeline manager configured to manage a software development pipeline. The pipeline manager receives, via a user interface (UI), a representation of a pipeline comprising a plurality of blocks, wherein each block comprises a defined input and a defined output, executes each block of the pipeline, validates output of each block of the pipeline based on the execution of the block and stores the output of each block and updating data that defines the pipeline based on the output of each block.

The exemplary embodiments are related to a pipeline manager configured to manage a software development pipeline. The pipeline manager receives, via a user interface (UI), a representation of a pipeline comprising a plurality of blocks, wherein each block comprises a defined input and a defined output, executes each block of the pipeline, validates output of each block of the pipeline based on the execution of the block and stores the output of each block and updating data that defines the pipeline based on the output of each block.

A code tracking system monitors usage of application code executed by one or more computing devices. Characteristics of the usage of the application code are determined. Using the characteristics of the usage of the application code, a modification to an entry of application code executed by the one or more computing devices is detected. The detected modification to the entry of application code is communicated to a code management system. The code management system presents the modification to the entry of the application code to a user of the code management system.

A code tracking system monitors usage of application code executed by one or more computing devices. Characteristics of the usage of the application code are determined. Using the characteristics of the usage of the application code, a modification to an entry of application code executed by the one or more computing devices is detected. The detected modification to the entry of application code is communicated to a code management system. The code management system presents the modification to the entry of the application code to a user of the code management system.

An industrial integrated development environment (IDE) includes a training component that improves the IDE's automated design tools over time based on analysis of aggregated project data submitted by developers over time. The industrial IDE can apply analytics (e.g., artificial intelligence, machine learning, etc.) to project data submitted by developers across multiple industrial enterprises to identify commonly used control code, visualizations, device configurations, or control system architectures that are frequently used for a given industrial function, machine, or application. This learned information can be encoded in a training module, which can be leveraged by the IDE to generate programming, visualization, or configuration recommendations. The IDE can automatically add suitable control code, visualizations, or configuration data to new control projects being developed based on an inference of the developer's design goals and knowledge of how these goals have been implemented by other developers.

Systems and methods for managing change requests are disclosed. A system for managing change requests may include a memory storing instructions and at least one processor configured to execute instructions to perform operations including: receiving, from a client device, a change request; routing the change request to a first similarity determination pipeline, based on the first classification, identifying an implementation device; and transmitting the change request to the implementation device. The first similarity determination pipeline may be configured to: extract at least one first request element from the change request; determine a first group of change requests based on the at least one first extracted request element; determine a first similarity metric between the change request and the first group of change requests; and determine a first classification of the change request based on the first similarity metric.

A computing device may access a hierarchical tree structure defining a data model for a workflow tool. The workflow tool being configured for building, deploying and releasing application code of an application to one or more cloud computing platforms. The hierarchical tree structure having a plurality of nodes that store data related to the application code. The computing device may receive a request to add a projects-child node associated with a code repository to the hierarchical tree structure. The computing device may add the projects-child node to the hierarchy as a child node of the identified organization-parent node. The projects-child node can be configured to support one or more dependent child nodes depending from the projects-child node. The dependent child nodes can include at least one of an applications-child node, a builds-child node, a deployments-child node, an artifacts-child node, or a releases-child node.

A computing device may access a hierarchical tree structure defining a data model for a workflow tool. The workflow tool being configured for building, deploying and releasing application code of an application to one or more cloud computing platforms. The hierarchical tree structure having a plurality of nodes that store data related to the application code. The computing device may receive a request to add a projects-child node associated with a code repository to the hierarchical tree structure. The computing device may add the projects-child node to the hierarchy as a child node of the identified organization-parent node. The projects-child node can be configured to support one or more dependent child nodes depending from the projects-child node. The dependent child nodes can include at least one of an applications-child node, a builds-child node, a deployments-child node, an artifacts-child node, or a releases-child node.

A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: monitoring an interaction of a user with a data center monitoring and management console throughout a plurality of developer journey steps, the interaction of the user including interaction with a plurality of application program interfaces; analyzing the interaction with the plurality of application program interfaces associated with each of the plurality of developer journey steps; and, generating an application program interface readiness score for each of the plurality of application program interfaces based upon the analyzing.