Abstract:
The present technology may determine an anomaly in a portion of a distributed business application. Data can automatically be captured and analyzed for the portion of the application associated with the anomaly. By automatically capturing data for just the portion associated with the anomaly, the present technology reduces the resource and time requirements associated with other code-based solutions for monitoring transactions. A method for sampling an application thread to monitor a request may begin with detecting a diagnostic event with respect to the processing of a request. A thread call stack associated with the request may be sampled in response to detecting the diagnostic event. A state of the call stack may be stored with timing information based on the sampling. The call stack state and timing information may be transmitted to a remote server.
Abstract:
The present technology may determine an anomaly in a portion of a distributed business application. Data can automatically be captured and analyzed for the portion of the application associated with the anomaly. By automatically capturing data for just the portion associated with the anomaly, the present technology reduces the resource and time requirements associated with other code-based solutions for monitoring transactions. A method for performing a diagnostic session for a request may begin with initiating collection of diagnostic data associated with a request. An application thread on each of two or more servers may be sampled. The application threads may be associated with the same business transaction and the business transaction may be associated with the request. The diagnostic data may be stored.
Abstract:
The present technology monitors a web application provided by one or more services. A service may be provided by applications. The monitoring system provides end-to-end business transaction visibility, identifies performance issues quickly and has dynamical scaling capability across monitored systems including cloud systems, virtual systems and physical infrastructures. A method for communicating data between servers may detect by a first computer a request to a second computer. The request and a first name may be sent to the second computer by the first computer. The first name and request information may be sent to a server by the first computer. The first name and a second computer identifier may be transmitted to the server by the second computer.
Abstract:
The present technology monitors a web application provided by one or more services. A service may be provided by applications. The monitoring system provides end-to-end business transaction visibility, identifies performance issues quickly and has dynamical scaling capability across monitored systems including cloud systems, virtual systems and physical infrastructures. A method for communicating data between servers may detect by a first computer a request to a second computer. The request and a first name may be sent to the second computer by the first computer. The first name and request information may be sent to a server by the first computer. The first name and a second computer identifier may be transmitted to the server by the second computer.
Abstract:
The present technology monitors a web application provided by one or more services. A service may be provided by applications. The monitoring system provides end-to-end business transaction visibility, identifies performance issues quickly and has dynamical scaling capability across monitored systems including cloud systems, virtual systems and physical infrastructures. A first parameter may be received from a first computer by a server. A second parameter may be received from a second computer by the server. A distributed application processed on the first computer and the second computer may be correlated based on the first parameter and the second parameter.
Abstract:
The present technology monitors a web application provided by one or more services. A service may be provided by applications. The monitoring system provides end-to-end business transaction visibility, identifies performance issues quickly and has dynamical scaling capability across monitored systems including cloud systems, virtual systems and physical infrastructures. In instances, a request may be received from a remote application. The request may be associated with a distributed transaction. Data associated with the request may be detected. A distributed transaction identifier may be generated for a distributed transaction based on the data associated with the request.
Abstract:
A system determines the performance of a network within the context of an application using that network. Network data is collected and correlated with an application that uses the network as well as a distributed transaction implemented by the application. The collected network data is culled, and the remaining data is rolled up into one or more metrics. The metrics, selected network data, and other data are reported in the context of the application that implements part of the distributed transaction. In this manner, specific network performance and architecture data is reported along with application context information.
Abstract:
The present technology may determine an anomaly in a portion of a distributed business application. Data can automatically be captured and analyzed for the portion of the application associated with the anomaly. By automatically capturing data for just the portion associated with the anomaly, the present technology reduces the resource and time requirements associated with other code-based solutions for monitoring transactions. A method for performing a diagnostic session for a request may begin with initiating collection of diagnostic data associated with a request. An application thread on each of two or more servers may be sampled. The application threads may be associated with the same business transaction and the business transaction may be associated with the request. The diagnostic data may be stored.
Abstract:
A system determines the performance of a network within the context of an application using that network. Network data is collected and correlated with an application that uses the network as well as a distributed transaction implemented by the application. The collected network data is culled, and the remaining data is rolled up into one or more metrics. The metrics, selected network data, and other data are reported in the context of the application that implements part of the distributed transaction. In this manner, specific network performance and architecture data is reported along with application context information.
Abstract:
Asynchronous handoffs between threads and other software components may be automatically detected, and the corresponding working objects may be tracked. The system may report monitoring information for an overall transaction that includes the original request and corresponding asynchronous requests. Automatically detecting asynchronous requests may include instrumenting a virtual machine, such as a Java Virtual Machine (JVM), to detect the creation of thread handoff objects and the object and/or thread execution. Thread handoff objects may automatically tracked, tracked based on data learned over time, tracked based on user input, and otherwise configured. In some embodiments, after detecting the creation of a thread handoff object, an identification of the object of the call may be identified as being tracked in another server or application.