Abstract: One embodiment collects performance data for an application server that processes transactions received from a client computer to a database server. An application log is created from the performance data and used for capacity planning in a multi-tiered architecture.

Abstract: One embodiment is a method that determines application performance signatures occurring at an application server in a multi-tier architecture. The method then analyzes the application performance signatures to determine whether a change in transaction performance at the application server results from a modification to an application.

Abstract: A method for analyzing a latency of a transaction performance is provided.

Abstract: One embodiment collects performance data for an application server that processes transactions received from a client computer to a database server. An application log is created from the performance data and used for capacity planning in a multi-tiered architecture.

Abstract: One embodiment is a method that determines application performance signatures occurring at an application server in a multi-tier architecture. The method then analyzes the application performance signatures to determine whether a change in transaction performance at the application server results from a modification to an application.

Abstract: One embodiment is a method that determines transaction latencies occurring at an application server and a database server in a multi-tier architecture. The method then analyzes the transaction latencies at the application server with Central Processing Unit (CPU) utilization during a monitoring window to determine whether a change in transaction performance at the application server results from an update to an application.

Abstract: A method comprises receiving, by learning logic, historical metrics of a computing system being monitored. The learning logic determines, from the received historical metrics, forms of sub-functions that are included in an equation, wherein each sub-function represents a dependency between two components linked in a hierarchical structure representing the computing system being monitored. State determination logic receives metric values of the computing system being monitored, and determines states that minimize the equation composed of the sub-functions over the received metric values. Finally, anomalous behavior of the computing system may be detected based on the determined states.

Abstract: A computer system includes a signature creation engine operable to determine signatures representing states of a computer resource from metrics for the computer resource. The computer system also includes a database operable to store the signatures along with an annotation for each signature including information relating to a state of the computer resource. The computer system is operable to determine a recurrent problem of the computer resource from stored signatures.

Abstract: A method comprises receiving, by learning logic, historical metrics of a computing system being monitored. The learning logic determines, from the received historical metrics, forms of sub-functions that are included in an equation, wherein each sub-function represents a dependency between two components linked in a hierarchical structure representing the computing system being monitored. State determination logic receives metric values of the computing system being monitored, and determines states that minimize the equation composed of the sub-functions over the received metric values. Finally, anomalous behavior of the computing system may be detected based on the determined states.

Abstract: A computer system includes a signature creation engine operable to determine signatures representing states of a computer resource from metrics for the computer resource. The computer system also includes a database operable to store the signatures along with an annotation for each signature including information relating to a state of the computer resource. The computer system is operable to determine a recurrent problem of the computer resource from stored signatures.

Abstract: Systems, methods, and software used in performing automated diagnosis and identification of or forecasting service level object states. Some embodiments include building classifier models based on collected metric data to detect and forecast service level objective (SLO) violations. Some such systems, methods, and software further include automated detecting and forecasting of SLO violations along with providing alarms, messages, or commands to administrators or system components. Some such messages include diagnostic information with regard to a cause of a SLO violation. Some embodiments further include storing data representative of system performance and detected and forecast system SLO states. This data can then be used to generate reports of system performance including representations of system SLO states.

Abstract: A method for describing and comparing data center physical and logical topologies and device configurations. The present invention compares a stored expected network infrastructure description with a current network infrastructure description gathered through the use of monitoring agents. The infrastructure descriptions are compared to discover any differences between the expected infrastructure and the current infrastructure. Devices in the current infrastructure which are configured differently, added, or missing from the expected infrastructure description are listed as well as changes to the logical topology of the current network. The present invention facilitates monitoring the network infrastructure and detecting unauthorized changes or access to the network.