Abstract: Method and system are provided for scoring events as likely cause events in a resource network. The method processes incoming events relating to resources in a resource network to correlate related events as a related group and maps the events of the related group onto nodes of a sub-topology representing resources of the resource network and having edges representing relationships between the resources. The method scores each event by discovering one or more paths between the node event and other node events of the related group, with the scoring based on a combination of an event classification weight and a discovered path score of aggregated relationship scores of edges of a discovered path.

Abstract: A method and system are provided for identification of constituent events in an event storm in operations management. The method includes: detecting an event storm by detecting an anomaly from a dynamic baseline range of expected event rates in a sample time period; and, when an event storm is detected, for each of a group of events grouped by an event category and occurring in a sample time period of an event storm, identifying the group of events as constituting part of the event storm if the rate of the event occurrences of the group in the sample time period is outside a threshold deviation from an average for that group.

Abstract: A method and system are provided for identification of constituent events in an event storm in operations management. The method includes: detecting an event storm by detecting an anomaly from a dynamic baseline range of expected event rates in a sample time period; and, when an event storm is detected, for each of a group of events grouped by an event category and occurring in a sample time period of an event storm, identifying the group of events as constituting part of the event storm if the rate of the event occurrences of the group in the sample time period is outside a threshold deviation from an average for that group.

Abstract: Network management data is managed by determining that a first version and a second version of a set of network management data have been created. The set of network management data is associated with a plurality of managed entities in a network. First and second network graphs are created based on the first version and second version of the set of network management data, respectively. The first and second network graphs include a first and second set of entities in the plurality of managed entities, respectively. A similarity metric is assigned between at least one or more entities in the first and second set of entities. At least a first entity in the first set of entities and at least a second entity in the second set of entities are determined to be identical entities based on the similarity metric being one of equal to and above a first given threshold.

Abstract: Network management data is managed by determining that a first version and a second version of a set of network management data have been created. The set of network management data is associated with a plurality of managed entities in a network. First and second network graphs are created based on the first version and second version of the set of network management data, respectively. The first and second network graphs include a first and second set of entities in the plurality of managed entities, respectively. A similarity metric is assigned between at least one or more entities in the first and second set of entities. At least a first entity in the first set of entities and at least a second entity in the second set of entities are determined to be identical entities based on the similarity metric being one of equal to and above a first given threshold.

Abstract: Improved and more efficient techniques are described for reducing the amount of work that needs to be performed by a database in a computer network in order to distribute event summary data to a large number of administrator clients. Delays experienced by event data at a database, e.g., due to delays in accessing a database, are reduced so that client can be notified of the events as soon as possible. Furthermore, event data obtained from both local and remote networks is efficiently coordinated using replica and union processes. Each monitoring location in the network includes both locally generated events, and a copy of remotely-generated events which are provided and maintained by one or more remote monitoring locations. The monitoring locations update one another with their event data.

Abstract: Described herein are methods and systems for preparing to efficiently distribute data to be extracted from a data store to clients and for distributing such prepared data to the clients. The methods and system have particular utility in the context of a network monitoring system which captures and stores network event data and makes the event data available to clients according to any desired view or summary. One method for preparing the data involves storing as primary requests one or more client requests for data to be extracted from the event database. Additional client requests for event are each compared to the stored primary requests to determine whether each additional request matches a stored primary request in accordance with a given criterion, such as a filter or summary formula. If the additional request matches a stored primary request, the additional client request is associated with the matching primary request.

Abstract: Described herein are methods and systems for preparing to efficiently distribute data to be extracted from a data store to clients and for distributing such prepared data to the clients. The methods and system have particular utility in the context of a network monitoring system which captures and stores network event data and makes the event data available to clients according to any desired view or summary. One method for preparing the data involves storing as primary requests one or more client requests for data to be extracted from the event database. Additional client requests for event are each compared to the stored primary requests to determine whether each additional request matches a stored primary request in accordance with a given criterion, such as a filter or summary formula. If the additional request matches a stored primary request, the additional client request is associated with the matching primary request.