Abstract: A system is provided for monitoring computing server performance using an artificial intelligence-based plugin. In particular, the system may be configured to continuously aggregate computing performance metric data of a computing device in the network, such as a server. The system may analyze the performance metric data using an artificial intelligence-based process to identify the hardware and/or software layers affected by computing workloads. Based on identifying the affected layers, the system may predict the impact of future workloads on the server and, based on the predictions, generate one or more recommendations for remediating server outages or downtime which may be caused by unanticipated volumes of network traffic, system calls, and the like. In this way, the system may provide an efficient way to optimize the use of computing resources within the network environment.

Abstract: Service and network management events are correlated, enabling a user to correlate all the application and network events that stem from a common fault without requiring repeated and exhaustive capturing of detailed knowledge of the network assets, the topological relationships and all possible events.

Abstract: Service and network management events are correlated, enabling a user to correlate all the application and network events that stem from a common fault without requiring repeated and exhaustive capturing of detailed knowledge of the network assets, the topological relationships and all possible events.

Abstract: Service and network management events are correlated, enabling a user to correlate all the application and network events that stem from a common fault without requiring repeated and exhaustive capturing of detailed knowledge of the network assets, the topological relationships and all possible events.