Abstract: A system and method for real-time discovery and monitoring of multidimensional topology models describing structural aspects of applications and of computing infrastructure used to execute those applications is disclosed. Different types of agents are deployed to the monitored application execution infrastructure dedicated to capture specific topological aspects of the monitored system. Virtualization agents detect and monitor the virtualization structure of virtualized hardware used in the execution infrastructure, operating system agents deployed to individual operating systems monitor resource utilization, performance and communication of processes executed by the operating system and transaction agents deployed to processes participating in the execution of transactions, providing end-to-end transaction trace and monitoring data describing individual transaction executions.

Abstract: A system and method for real-time discovery and monitoring of multidimensional topology models describing structural aspects of applications and of computing infrastructure used to execute those applications is disclosed. Different types of agents are deployed to the monitored application execution infrastructure dedicated to capture specific topological aspects of the monitored system. Virtualization agents detect and monitor the virtualization structure of virtualized hardware used in the execution infrastructure, operating system agents deployed to individual operating systems monitor resource utilization, performance and communication of processes executed by the operating system and transaction agents deployed to processes participating in the execution of transactions, providing end-to-end transaction trace and monitoring data describing individual transaction executions.

Abstract: A system and method for real-time discovery and monitoring of multidimensional topology models describing structural aspects of applications and of computing infrastructure used to execute those applications is disclosed. Different types of agents are deployed to the monitored application execution infrastructure dedicated to capture specific topological aspects of the monitored system. Virtualization agents detect and monitor the virtualization structure of virtualized hardware used in the execution infrastructure, operating system agents deployed to individual operating systems monitor resource utilization, performance and communication of processes executed by the operating system and transaction agents deployed to processes participating in the execution of transactions, providing end-to-end transaction trace and monitoring data describing individual transaction executions.

Abstract: A system and method for real-time discovery and monitoring of multidimensional topology models describing structural aspects of applications and of computing infrastructure used to execute those applications is disclosed. Different types of agents are deployed to the monitored application execution infrastructure dedicated to capture specific topological aspects of the monitored system. Virtualization agents detect and monitor the virtualization structure of virtualized hardware used in the execution infrastructure, operating system agents deployed to individual operating systems monitor resource utilization, performance and communication of processes executed by the operating system and transaction agents deployed to processes participating in the execution of transactions, providing end-to-end transaction trace and monitoring data describing individual transaction executions.

Abstract: A combined transaction execution monitoring, transaction classification and transaction execution performance anomaly detection system is disclosed. The system receives and analyzes transaction tracing data which may be provided by monitoring agents deployed to transaction executing entities like processes. In a first classification stage, parameters are extracted from received transaction tracing data, and the transaction tracing data is tagged with the extracted classification data. A subsequent measure extraction stage analyzes the classified transaction tracing data and creates corresponding measurements which are tagged with the transaction classifier. A following statistical analysis process maintains statistical data describing the long term statistical behavior of classified measures as a baseline, and also calculates corresponding statistical data describing the current statistical behavior of the classified measures.

Abstract: A combined transaction execution monitoring, transaction classification and transaction execution performance anomaly detection system is disclosed. The system receives and analyzes transaction tracing data which may be provided by monitoring agents deployed to transaction executing entities like processes. In a first classification stage, parameters are extracted from received transaction tracing data, and the transaction tracing data is tagged with the extracted classification data. A subsequent measure extraction stage analyzes the classified transaction tracing data and creates corresponding measurements which are tagged with the transaction classifier. A following statistical analysis process maintains statistical data describing the long term statistical behavior of classified measures as a baseline, and also calculates corresponding statistical data describing the current statistical behavior of the classified measures.

Abstract: A combined transaction execution monitoring, transaction classification and transaction execution performance anomaly detection system is disclosed. The system receives and analyzes transaction tracing data which may be provided by monitoring agents deployed to transaction executing entities like processes. In a first classification stage, parameters are extracted from received transaction tracing data, and the transaction tracing data is tagged with the extracted classification data. A subsequent measure extraction stage analyzes the classified transaction tracing data and creates corresponding measurements which are tagged with the transaction classifier. A following statistical analysis process maintains statistical data describing the long term statistical behavior of classified measures as a baseline, and also calculates corresponding statistical data describing the current statistical behavior of the classified measures.

Abstract: A transaction monitoring and tracing system which combines transactional performance monitoring aspects with infrastructure performance and utilization measures, like e.g. used memory or CPU load of transaction executing computing infrastructure. The system uses two types of agents deployed to the monitored system, a transaction and process agent, which is deployed to a process executing monitored transactions, and a host agent, which is deployed to a computer system executing processes monitored by a transaction and process agent. The transaction and process agent provides transaction tracing and process infrastructure measurements, the host agent provides host or operating system infrastructure measurements. All three types of measurements are tagged by the corresponding agent in a way that allows a later correlation of corresponding tracing and measurement data by an external monitoring node.

Abstract: A system and method for real-time discovery and monitoring of multidimensional topology models describing structural aspects of applications and of computing infrastructure used to execute those applications is disclosed. Different types of agents are deployed to the monitored application execution infrastructure dedicated to capture specific topological aspects of the monitored system. Virtualization agents detect and monitor the virtualization structure of virtualized hardware used in the execution infrastructure, operating system agents deployed to individual operating systems monitor resource utilization, performance and communication of processes executed by the operating system and transaction agents deployed to processes participating in the execution of transactions, providing end-to-end transaction trace and monitoring data describing individual transaction executions.

Abstract: A performance monitoring system is presented for monitoring and tracing individual transactions, where transaction processing includes sending and receiving messages using messaging systems that do not allow the augmentation of existing messages with monitoring system specific correlation information. Agents are deployed to sender and receiver applications that monitor and report transactions. Both sender and receiver applications are instrumented with sensors that detect and report sending or receiving of such immutable messages. Those sensors also extract correlation data from sent and received data allowing the identification of matching corresponding send/receive pairs. A mapping agent is used to retrieve mapping information from a messaging system which may alter the additional message identification data while messages travel through the system. This mapping information is additionally used for the correlation process.

Abstract: A transaction monitoring and tracing system which combines transactional performance monitoring aspects with infrastructure performance and utilization measures, like e.g. used memory or CPU load of transaction executing computing infrastructure. The system uses two types of agents deployed to the monitored system, a transaction and process agent, which is deployed to a process executing monitored transactions, and a host agent, which is deployed to a computer system executing processes monitored by a transaction and process agent. The transaction and process agent provides transaction tracing and process infrastructure measurements, the host agent provides host or operating system infrastructure measurements. All three types of measurements are tagged by the corresponding agent in a way that allows a later correlation of corresponding tracing and measurement data by an external monitoring node.

Abstract: A combined transaction execution monitoring, transaction classification and transaction execution performance anomaly detection system is disclosed. The system receives and analyzes transaction tracing data which may be provided by monitoring agents deployed to transaction executing entities like processes. In a first classification stage, parameters are extracted from received transaction tracing data, and the transaction tracing data is tagged with the extracted classification data. A subsequent measure extraction stage analyzes the classified transaction tracing data and creates corresponding measurements which are tagged with the transaction classifier. A following statistical analysis process maintains statistical data describing the long term statistical behavior of classified measures as a baseline, and also calculates corresponding statistical data describing the current statistical behavior of the classified measures.

Abstract: A performance monitoring system is presented for monitoring and tracing individual transactions, where transaction processing includes sending and receiving messages using messaging systems that do not allow the augmentation of existing messages with monitoring system specific correlation information. Agents are deployed to sender and receiver applications that monitor and report transactions. Both sender and receiver applications are instrumented with sensors that detect and report sending or receiving of such immutable messages. Those sensors also extract correlation data from sent and received data allowing the identification of matching corresponding send/receive pairs. A mapping agent is used to retrieve mapping information from a messaging system which may alter the additional message identification data while messages travel through the system. This mapping information is additionally used for the correlation process.