Boomi, Inc.

Jason R Walsh

A method for tailoring a visual element customizer to a domain-specific language (DSL) may comprise executing custom-scripted code instructions for a visual element customizer to associate an action and an operation with a subset of custom-DSL code instructions for performing the action within an executable operation, and receiving, via a first graphical user interface (GUI), an administrator instruction to generate a second GUI that points a business user to select at least one action and an operation with the visual element customizer. The method may also include receiving selections of visual elements representing an integration process and a user instruction to customize one of the selected visual elements to perform the action, and the operation under a custom DSL, and transmitting an executable run-time engine and the subset of custom-DSL code instructions for execution of the integration process at a remote location.

System and method for tailoring a customizer for integration process modeling visual element to a domain specific language for business integrations

An information handling system operating an intelligent real time listen and load balance system comprising a processor training a triggering event correlating neural network to identify a correlation between changes made to a dataset during previous triggering events and previous executions of a triggered integration process, based on previous co-occurrences of the triggering event dataset changes and the triggered integration process executions, determining that current changes to the dataset during a current triggering event correlates to the triggered integration process, indicating new or modified data requires execution of the triggered integration process, and determining predicted triggered integration process execution metrics for a plurality of cloud computing nodes based on received performance metrics for the plurality of cloud computing nodes. The processor may also identify an optimal cloud computing node by comparing the predicted execution metrics for each of the cloud computing nodes for execution of the triggered integration process.

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Ardmore, PA, United States of America

Jason R Walsh