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.

Abstract: A method for controlling and maintaining a level of service of web applications is disclosed. The method includes generating a context for each request sent from a client to a web server and for each reply sent from a web server to a client. Then it is determined whether the context belongs to an identified transaction. Statistics respective of the identified transaction is then gathered. Further, a determination is made whether at least one policy predefined for the identified application is violated. A plurality of corrective actions are performed if at least one policy is determined to be violated.

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 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 method for controlling and maintaining a level of service of web applications is disclosed. The method includes generating a context for each request sent from a client to a web server and for each reply sent from a web server to a client. Then it is determined whether the context belongs to an identified transaction. Statistics respective of the identified transaction is then gathered. Further, a determination is made whether at least one policy predefined for the identified application is violated. A plurality of corrective actions are performed if at least one policy is determined to be violated.

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 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 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.