Abstract: A system and method for correlating front-end and back-end transactions in a data center. The method includes gathering front-end and back-end transactions; analyzing pairs of transactions to detect correlated front-end and back-end transactions; saving correlated pairs in a database; and displaying the correlated pairs on a graphical user interface (GUI). In accordance with an embodiment of the invention the detection of correlated pairs may be performed using content matching analysis, time proximity analysis, and attributes analysis.

Abstract: A network device and method for learning and monitoring transactions executed by back-end systems in data servers. Specifically, it allows learning and monitoring at least standard query language (SQL) transactions sent from an application server hosting a web application to a database server and executed thereon. Monitoring of SQL transactions allows measuring performance parameters with regards to databases, databases' tables, operations and queries that are part of the transactions. Furthermore, the measurement of performance parameters with respect to HTTP requests of the respective SQL transactions is provided.

Abstract: A method and system for automatically learning and identifying web applications. The method discovers and identifies transactions, web applications, their modules, interfaces, and relationship between the modules. The method further includes dynamically creating application definers is provided.

Abstract: A service level management (SLM) system where the system learns the structure of a web application, monitors the operation of the application, and controls the processing of incoming requests to achieve optimal performance as defined in a service level agreement (SLA). The system is operative for example in enterprise web applications and in enterprise data centers that deploy web applications and optimally is capable of controlling and maintaining a level of service of web applications.

Abstract: A network sniffer where the sniffer learns the structure of a web application, monitors the operation of the application, and optionally controls the processing of incoming requests to achieve optimal performance as defined in a service level agreement (SLA). The network sniffer is operative for example in enterprise web applications and in enterprise data centers that deploy web applications and optimally is adapted to maintain a consistent level of service of web applications.