Abstract: Concepts and technologies are disclosed herein for a realtime dynamic virtual network topology discovery engine to discover a dynamic network topology in virtualized networks in realtime. A processor that executes a network topology discovery engine can obtain network data that can describe elements of a data center and operational state of the elements. Obtaining network data can include obtaining network data from a network topology inventory database and through detecting operational state change events from virtual network components. The processor can construct a network topology model based upon the network data. The network topology model can include an object (representing an element of the data center) and an attribute representing a state of the element. The processor can update the network topology model in realtime. The network topology model and configurations can be stored for root cause analysis of fault events, resource orchestration in SDN networks, and other applications.

Abstract: A service impact event analyzer is used to evaluate service assurance risk in cloud SDN networks. Using data fusion, an alarm subset dataset is generated from a raw trap dataset. Service impact events are identified in the subset dataset. The service impact events are categorized into service impacted event categories, and a model is created for associating the event categories with process function classes. Time durations of the service impact events are computed using correlated secondary alarms from the alarm subset dataset. The service assurance risk is evaluated using the model and the time duration.

Abstract: A service impact event analyzer is used to evaluate service assurance risk in cloud SDN networks. Using data fusion, an alarm subset dataset is generated from a raw trap dataset. Service impact events are identified in the subset dataset. The service impact events are categorized into service impacted event categories, and a model is created for associating the event categories with process function classes. Time durations of the service impact events are computed using correlated secondary alarms from the alarm subset dataset. The service assurance risk is evaluated using the model and the time duration.

Abstract: Concepts and technologies are disclosed herein for a realtime dynamic virtual network topology discovery engine to discover a dynamic network topology in virtualized networks in realtime. A processor that executes a network topology discovery engine can obtain network data that can describe elements of a data center and operational state of the elements. Obtaining network data can include obtaining network data from a network topology inventory database and through detecting operational state change events from virtual network components. The processor can construct a network topology model based upon the network data. The network topology model can include an object (representing an element of the data center) and an attribute representing a state of the element. The processor can update the network topology model in realtime. The network topology model and configurations can be stored for root cause analysis of fault events, resource orchestration in SDN networks, and other applications.