Abstract: Application runtime data is obtained from an application monitoring system which monitors execution of an application, and traffic monitoring data is obtained from a traffic monitoring system which monitors traffic to/from the application as the clients interact with the application. Corresponding application runtime data and traffic monitoring data can be selectively output to assist an operator in investigating an anomalous condition. The data can be classified and selectively output according to one or more hierarchies which characterize the interactions. The hierarchies can include a domain level, a business process level (where a domain is made up of a number of business processes), a business transaction level (where a business process is made up of different business transactions), an individual transaction level (where a business transaction is made up of different transactions), and a transaction component level (where a transaction is made up of one or more transaction components).

Abstract: Programmatic root cause analysis of application performance problems is provided in accordance with various embodiments. Transactions having multiple components can be monitored to determine if they are exceeding a threshold for their execution time. Monitoring the transactions can include instrumenting one or more applications to gather component level information. For transactions exceeding a threshold, the data collected for the individual components can be analyzed to automatically diagnose the potential cause of the performance problem. Time-series analytical techniques are employed to determine normal values for transaction and component execution times. The values can be dynamic or static. Deviations from these normal values can be detected and reported as a possible cause. Other filters in addition to or in place of execution times for transactions and components can also be used.

Abstract: Programmatic root cause analysis of application performance problems is provided in accordance with various embodiments. Transactions having multiple components can be monitored to determine if they are exceeding a threshold for their execution time. Monitoring the transactions can include instrumenting one or more applications to gather component level information. For transactions exceeding a threshold, the data collected for the individual components can be analyzed to automatically diagnose the potential cause of the performance problem. Time-series analytical techniques are employed to determine normal values for transaction and component execution times. The values can be dynamic or static. Deviations from these normal values can be detected and reported as a possible cause. Other filters in addition to or in place of execution times for transactions and components can also be used.

Abstract: Application runtime data is obtained from an application monitoring system which monitors execution of an application, and traffic monitoring data is obtained from a traffic monitoring system which monitors traffic to/from the application as the clients interact with the application. Corresponding application runtime data and traffic monitoring data can be selectively output to assist an operator in investigating an anomalous condition. The data can be classified and selectively output according to one or more hierarchies which characterize the interactions. The hierarchies can include a domain level, a business process level (where a domain is made up of a number of business processes), a business transaction level (where a business process is made up of different business transactions), an individual transaction level (where a business transaction is made up of different transactions), and a transaction component level (where a transaction is made up of one or more transaction components).

Abstract: Application runtime data is obtained from an application monitoring system which monitors execution of an application, and traffic monitoring data is obtained from a traffic monitoring system which monitors traffic to/from the application as the clients interact with the application. Corresponding application runtime data and traffic monitoring data can be selectively output to assist an operator in investigating an anomalous condition. The data can be classified and selectively output according to one or more hierarchies which characterize the interactions. The hierarchies can include a domain level, a business process level (where a domain is made up of a number of business processes), a business transaction level (where a business process is made up of different business transactions), an individual transaction level (where a business transaction is made up of different transactions), and a transaction component level (where a transaction is made up of one or more transaction components).

Abstract: Application runtime data is obtained from an application monitoring system which monitors execution of an application, and traffic monitoring data is obtained from a traffic monitoring system which monitors traffic to/from the application as the clients interact with the application. Corresponding application runtime data and traffic monitoring data can be selectively output to assist an operator in investigating an anomalous condition. The data can be classified and selectively output according to one or more hierarchies which characterize the interactions. The hierarchies can include a domain level, a business process level (where a domain is made up of a number of business processes), a business transaction level (where a business process is made up of different business transactions), an individual transaction level (where a business transaction is made up of different transactions), and a transaction component level (where a transaction is made up of one or more transaction components).