Abstract: Embodiments of apparatus, systems, and methods are described for creating and managing an abstract, API-based infrastructure base model. The API-based model can abstract infrastructure assets, such as infrastructure components or connections between components, into a metadata model using standardized syntax and interfaces, for defining and building an infrastructure. Using a modeling document, connections and components of an infrastructure can be abstracted into an API-based model having semantics that covers them all. Connections and infrastructure components can be made available for selection, arrangement, and grouping to build complex infrastructure models without requiring complex API coding by the user. Other infrastructure models having different API definitions can be by abstracted to standardize the assets for building new APIs. The APIs can be further modified and exported to another or the same implementation project.

Abstract: Disclosed herein are system, method, and device embodiments for implementing flow analysis in an integration platform system. An integration platform may provide a declaratively-configurable asset within an integration-application design tool, configure the declaratively-configurable asset based on declarative configuration information via the integration-application design tool, and package the declaratively-configurable asset into an integration application. Further, the integration platform may calculate a statistic associated with the declaratively-configurable asset based on the declarative configuration information during an execution of the integration application, and cause display of a graphic representation of the declaratively-configurable asset and the statistic in a monitoring tool.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing clustering and monitoring functionality. An embodiment operates by determining that an application programming interface (API) call has been made from a first application to a second application. Metric data regarding a performance of one or more computing devices responsive to the determined API call is received. The received metric data associated with the determined API call is clustered into one of a plurality of predetermined clusters associated with the performance of the one or more computing devices responsive to one or more previous API calls. A notification indicating a system state of the one or more computing devices is determined based on the clustering, and provided.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing anomaly feedback monitoring and detection. An embodiment operates by determining a first set of data corresponding to an anomaly indicating an undesirable data state for a first application. A subset of data from a second set of data corresponding to the undesirable data state is identified, wherein the second set of data is associated with communications between the first application and a second application. A notification identifying the anomaly is provided. Feedback associated with the anomaly is received. Data corresponding to the anomaly is updated based on the feedback.