Abstract: By monitoring requests to and from components of an application, an application analysis engine generates an inter-component graph for an application that identifies how the various components in the application are connected. When a performance issue is detected in association with the application, a traversal module traverses the inter-component graph to determine the possible execution paths that may have been the cause of the detected issue. The traversal module transmits requests to the correlation module to compare the metrics time series of the different components in the execution path with the detected issue. The correlation module compares metrics time series with the issue metric to identify correlations between execution patterns. The results of the correlation may be presented in a report that visually identify the root cause of the detected issues.

Abstract: By monitoring requests to and from components of an application, an application analysis engine generates an inter-component graph for an application that identifies how the various components in the application are connected. When a performance issue is detected in association with the application, a traversal module traverses the inter-component graph to determine the possible execution paths that may have been the cause of the detected issue. The traversal module transmits requests to the correlation module to compare the metrics time series of the different components in the execution path with the detected issue. The correlation module compares metrics time series with the issue metric to identify correlations between execution patterns. The results of the correlation may be presented in a report that visually identify the root cause of the detected issues.

Abstract: By monitoring requests to and from components of an application, an application analysis engine generates an inter-component graph for an application that identifies how the various components in the application are connected. When a performance issue is detected in association with the application, a traversal module traverses the inter-component graph to determine the possible execution paths that may have been the cause of the detected issue. The traversal module transmits requests to the correlation module to compare the metrics time series of the different components in the execution path with the detected issue. The correlation module compares metrics time series with the issue metric to identify correlations between execution patterns. The results of the correlation may be presented in a report that visually identify the root cause of the detected issues.

Abstract: Evaluating application performance includes: obtaining a request, processing the request, including invoking a function that accesses an external resource, determining whether a response time associated with invoking the function exceeds a threshold, and in the event that the response time exceeds the threshold, capturing a runtime attribute associated with the function.

Abstract: Evaluating application performance includes: obtaining a request, processing the request, including invoking a function that accesses an external resource, determining whether a response time associated with invoking the function exceeds a threshold, and in the event that the response time exceeds the threshold, capturing a runtime attribute associated with the function.

Abstract: By monitoring requests to and from components of an application, an application analysis engine generates an inter-component graph for an application that identifies how the various components in the application are connected. When a performance issue is detected in association with the application, a traversal module traverses the inter-component graph to determine the possible execution paths that may have been the cause of the detected issue. The traversal module transmits requests to the correlation module to compare the metrics time series of the different components in the execution path with the detected issue. The correlation module compares metrics time series with the issue metric to identify correlations between execution patterns. The results of the correlation may be presented in a report that visually identify the root cause of the detected issues.

Abstract: A system for providing polymorphic image data for images in a graphical user interface on a computer system includes an operating system, and an imaging object structure, the imaging object structure included in the operating system and utilized to generate images in the graphical user interface. Additionally, the imaging object structure further comprises a subclass of imaging objects, the subclasses comprising singular imaging objects and composite imaging objects. The singular imaging objects further include, but are not limited to, text imaging objects, picture imaging objects, pattern imaging objects, and icon imaging objects. Additionally, the composite imaging objects generate composite images of a desired combination of singular images generated by the singular imaging objects. Further, the imaging object structure includes a SOM object structure.

Abstract: A system for providing polymorphic image data for images in a graphical user interface on a computer system includes an operating system, and an imaging object structure, the imaging object structure included in the operating system and utilized to generate images in the graphical user interface. Additionally, the imaging object structure further comprises a subclass of imaging objects, the subclasses includes singular imaging objects and composite imaging objects. The singular imaging objects further include, but are not limited to, text imaging objects, picture imaging objects, pattern imaging objects, and icon imaging objects. Additionally, the composite imaging objects generate composite images of a desired combination of singular images generated by the singular imaging objects. Further, the imaging object structure includes a SOM object structure.