Abstract: A monitoring system monitors the amount of time spent by specific application components, such as Java components, during execution of specific web site transactions. A probe that runs on an application server initially instruments these components (preferably at component load time) to add code for tracking execution start and stop times. When a monitored transaction is executed by the application server, the probe measures the execution times of the invoked components—preferably at the component method level. The resulting measurement data is reported to a reports server, and is used to provide transaction-specific breakdowns of the amount of time spent by each instrumented component, and optionally each instrumented method within such components. In one embodiment, the probe only monitors transactions initiated by agent-generated transaction request messages that are marked or “colored” for monitoring, and thus ignores transactions initiated by actual users.

Abstract: A monitoring system monitors the amount of time spent by specific application components, such as Java components, during execution of specific web site transactions. A probe that runs on an application server initially instruments these components (preferably at component load time) to add code for tracking execution start and stop times. When a monitored transaction is executed by the application server, the probe measures the execution times of the invoked components—preferably at the component method level. The resulting measurement data is reported to a reports server, and is used to provide transaction-specific breakdowns of the amount of time spent by each instrumented component, and optionally each instrumented method within such components. In one embodiment, the probe only monitors transactions initiated by agent-generated transaction request messages that are marked or “colored” for monitoring, and thus ignores transactions initiated by actual users.

Abstract: A system for monitoring the post-deployment performance of a web-based or other transactional server is disclosed. The monitoring system includes an agent component that monitors the performance of the transactional server as seen from one or more geographic locations and reports the performance data to a reports server and/or centralized database. The performance data may include, for example, transaction response times, server response times, network response times and measured segment delays along network paths. Using the reported performance data, the system provides a breakdown of time involved in completion of a transaction into multiple time components, including a network time and a server time. Users view the transaction breakdown data via a series of customizable reports, which assist the user in determining whether the source of the performance problem. Additional features permit the source to be identified with further granularity.

Abstract: A monitoring system monitors the amount of time spent by specific application components, such as Java components, during execution of specific web site transactions. A probe that runs on an application server initially instruments these components (preferably at component load time) to add code for tracking execution start and stop times. When a monitored transaction is executed by the application server, the probe measures the execution times of the invoked components—preferably at the component method level. The resulting measurement data is reported to a reports server, and is used to provide transaction-specific breakdowns of the amount of time spent by each instrumented component, and optionally each instrumented method within such components. In one embodiment, the probe only monitors transactions initiated by agent-generated transaction request messages that are marked or “colored” for monitoring, and thus ignores transactions initiated by actual users.

Abstract: A monitoring system monitors the amount of time spent by specific application components, such as Java components, during execution of specific web site transactions. A probe that runs on an application server initially instruments these components (preferably at component load time) to add code for tracking execution start and stop times. When a monitored transaction is executed by the application server, the probe measures the execution times of the invoked components—preferably at the component method level. The resulting measurement data is reported to a reports server, and is used to provide transaction-specific breakdowns of the amount of time spent by each instrumented component, and optionally each instrumented method within such components. In one embodiment, the probe only monitors transactions initiated by agent-generated transaction request messages that are marked or “colored” for monitoring, and thus ignores transactions initiated by actual users.

Abstract: A monitoring system monitors the amount of time spent by specific application components, such as Java components, during execution of specific web site transactions. A probe that runs on an application server initially instruments these components (preferably at component load time) to add code for tracking execution start and stop times. When a monitored transaction is executed by the application server, the probe measures the execution times of the invoked components—preferably at the component method level. The resulting measurement data is reported to a reports server, and is used to provide transaction-specific breakdowns of the amount of time spent by each instrumented component, and optionally each instrumented method within such components. In one embodiment, the probe only monitors transactions initiated by agent-generated transaction request messages that are marked or “colored” for monitoring, and thus ignores transactions initiated by actual users.

Abstract: A system for monitoring and analyzing the post-deployment performance of a web-based or other transactional server is disclosed. The monitoring system includes agent components that monitor and report various performance parameters associated with the transactional server, such as response times seen by end users, server and network times, and various server resource utilization parameters. A web-based reports server displays the data collected by the agents through a series of charts and graphs that indicate whether correlations exist between the response times and lower level parameters. A root cause analysis system applies statistical algorithms to the collected data to detect performance degradations in specific parameters, and uses predefined parameter dependency rules to correlate high level performance problems to likely sources or causes of such problems.

Abstract: A monitoring system monitors the amount of time spent by specific application components, such as Java components, during execution of specific web site transactions. A probe that runs on an application server initially instruments these components (preferably at component load time) to add code for tracking execution start and stop times. When a monitored transaction is executed by the application server, the probe measures the execution times of the invoked components—preferably at the component method level. The resulting measurement data is reported to a reports server, and is used to provide transaction-specific breakdowns of the amount of time spent by each instrumented component, and optionally each instrumented method within such components. In one embodiment, the probe only monitors transactions initiated by agent-generated transaction request messages that are marked or “colored” for monitoring, and thus ignores transactions initiated by actual users.

Abstract: A system for monitoring and analyzing the post-deployment performance of a web-based or other transactional server is disclosed. The monitoring system includes agent components that monitor and report various performance parameters associated with the transactional server, such as response times seen by end users, server and network times, and various server resource utilization parameters. A web-based reports server displays the data collected by the agents through a series of charts and graphs that indicate whether correlations exist between the response times and lower level parameters. A root cause analysis system applies statistical algorithms to the collected data to detect performance degradations in specific parameters, and uses predefined parameter dependency rules to correlate high level performance problems to likely sources or causes of such problems.

Abstract: A system for monitoring the post-deployment performance of a web-based or other transactional server is disclosed. The monitoring system includes an agent component that monitors the performance of the transactional server as seen from one or more geographic locations and reports the performance data to a reports server and/or centralized database. The performance data may include, for example, transaction response times, server response times, network response times and measured segment delays along network paths. Using the reported performance data, the system provides a breakdown of time involved in completion of a transaction into multiple time components, including a network time and a server time. Users view the transaction breakdown data via a series of customizable reports, which assist the user in determining whether the source of the performance problem. Additional features permit the source to be identified with further granularity.

Abstract: A system for monitoring and analyzing the post-deployment performance of a web-based or other transactional server is disclosed. The monitoring system includes an agent component that monitors and reports the performance of the transactional server over time as seen from one or more user locations. The performance data includes response times indicative of delays experienced by end users. Concurrently with the monitoring of end user performance, a server agent component monitors and reports server resource utilization parameter measurements. A web-based reports server displays the data collected by the two types of agents through a series of charts and graphs that indicate whether correlations exist between the response times and specific server resource utilization parameters. The collected data may also be analyzed using a root cause analysis system that detects performance degradations and identifies likely sources of such degradations.