The invention concerns a method and a system for determining root-cause diagnosis of events occurring during the operation of a communication network comprising monitoring time signals representative of the operation of the network to detect the occurrence of an event relative to the network traffic, and for each detected event, during the duration of said event obtaining distributions of data on several dimensions of the network linked to said event, automatically determining an event root-cause diagnosis of the detected event, called single event diagnosis, comprising at least one element of said distributions, an element being a value taken by a network dimension having a contribution in said distributions of data, the single event diagnosis determination using rules of business logic configuration organized hierarchically, which are applied according to said hierarchy to select at least one element of said distributions, the selection of more than one element comprising machine learning clustering.

Dynamic management of data traffic workflows is performed. An event to perform a data traffic workflow at a remote performance location may be received. Computing resources to perform the data traffic workflow may be identified. Operations to perform the data traffic workflow may be dynamically directed by the identified computing resources to adaptively balance performance of the operations with operations for other data traffic workflows in order to meet respective performance requirements of the data traffic workflows.

Disclosed embodiments may include another system for prioritizing alerts. The alert prioritization system may include one or more processors and that may store instructions that are configured to cause the system to perform a method for prioritizing alerts. For example, the system may receive a first alert from a first application and determine, using a machine learning model, whether the first alert is similar to a previous alert. The determination may be based on the second alert satisfying a predetermined similarity threshold. When the first alert is similar to the previous alert, the system may associate a previous rating label with the first alert, the previous rating label being associated with the previous alert and transmit the first alert with the previous rating label to one or more user devices for display.

Systems and methods for tracking and reporting the existence or absence of faults in a Network Element (NE) or node of a network, network domain, or Maintenance Domain (MD) are provided. A method, according to one implementation, includes a step of tracking the existence or absence of a plurality of faults in a NE within a network domain. Each of the plurality of faults is categorized in one of a plurality of priority levels. In response to a detection of one or more new faults in the NE or a rectification of one or more old faults in the NE, the method further includes the step of updating a fault indication variable that individually signifies the existence or absence of a fault at each of the priority levels.

A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: monitoring data center assets within a data center; identifying an issue within the data center, the issue being associated with an operational situation associated with a particular component of the data center; associating the issue with a particular point in time; and, informing a user about the issue, the informing including information regarding the particular point in time, the informing including a graphical depiction of the particular component of the data center and the issue within the data center.

A method and apparatus are disclosed of providing a user application with a notification message. One example method may include receiving a notification message and identifying a predetermined category of a notification bar portion of the user application to display the notification message. The method may also include associating the notification message with the identified predetermined category and determining a level of importance of the notification message. The method may also provide displaying a notification indicator on the notification bar according to the predetermined category and to the notification type that corresponds to the level of importance.

Systems and methods include receiving alarms from a network; utilizing a machine learning model to classify the alarms as one of important and non-important; and displaying the important alarms and suppressing display of the non-important alarms. The systems and methods can further include training the machine learning model with historical alarm data that includes features related to an associated device and comments related to how a Network Operations Center (NOC) handles an associated alarm or group of alarms. The training can be via supervised machine learning with the features used as labels or via reinforcement learning with the features used as a reward.

An illustrative method for monitoring a cloud environment may include identifying, by at least one computing device and based on a scan of a cloud environment, a vulnerable software component in the cloud environment, determining, by the at least one computing device, an operational status for the vulnerable software component in the cloud environment, and generating, by the at least one computing device and based on the operational status for the vulnerable software component, an alert for the vulnerable software component.

A system is provided herein that can correlate service issues with system telemetry associated with the software session associated with those service issues. Using a statistical approach, the system can evaluate data across numerous software sessions to rank the importance of the reported service issues. To accomplish the ranking, the system can parse the reports of service issues on a periodic basis, can extract telemetry identifiers (IDs) from the logs, can query the telemetry, may compute the relative importance of detected issues (in the context of calls going on for that day), and then can report this impact hack to the service issue database.

Systems and methods for tracking and reporting the existence or absence of faults in a Network Element (NE) or node of a network, network domain, or Maintenance Domain (MD) are provided. A method, according to one implementation, includes a step of tracking the existence or absence of a plurality of faults in a NE within a network domain. Each of the plurality of faults is categorized in one of a plurality of priority levels. In response to a detection of one or more new faults in the NE or a rectification of one or more old faults in the NE, the method further includes the step of updating a fault indication variable that individually signifies the existence or absence of a fault at each of the priority levels.