A computer system that updates a pretrained predictive model is described. During operation, the computer system may receive, from an electronic device, information specifying user feedback about a network incident. Then, the computer system may update, based at least in part on the user feedback, the pretrained predictive model that outputs severity classifications of network incidents, where a difference between a severity classification of the updated pretrained predictive model and a user severity classification associated with the user feedback is reduced relative to an initial difference between an initial severity classification of the pretrained predictive model and the user severity classification. Moreover, the computer system may receive information specifying a second network incident. Next, the computer system may compute a second severity classification of the second network incident using the updated pretrained predictive model.

Systems and methods for dynamically routing notifications based on device statuses are disclosed herein. For instance, a notification may be generated for a user account corresponding to an application that is installed on a plurality of devices. A system identifies a status of each of the plurality of devices and uses the status of each of the plurality of devices to select a particular device to receive the notification. The system then transmits the notification to the selected particular device.

Systems and methods for dynamically routing notifications based on device statuses are disclosed herein. For instance, a notification may be generated for a user account corresponding to an application that is installed on a plurality of devices. A system identifies a status of each of the plurality of devices and uses the status of each of the plurality of devices to select a particular device to receive the notification. The system then transmits the notification to the selected particular device.

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 network element configured to support Connectivity Fault Management (CFM) for Operation, Administration and Maintenance (OAM) includes circuitry configured to track faults in the CFM via a defect indication variable that includes multiple bits wherein each bit is one of a certain priority level of a plurality of priority levels and a reserved value, and, responsive to one or more of detection of a new fault and clearing of an existing fault, update the defect indication variable accordingly based on a corresponding priority level of the new fault or the existing fault.

This application provides a configuration error information transmission method and a device. When generating a plurality of pieces of configuration error information after configuring a batch of configuration parameter groups, a user plane network element may report the configuration error information to a control plane network element based on reporting priorities of the configuration error information. According to embodiments, reporting can be performed based on the reporting priorities of the configuration error information. In this way, a user or the control plane network element can configure, by configuring the reporting priorities, an order of precedence of the configuration error information to be reported by the user plane network element.

Methods, apparatuses, or computer program products provide for generating a predictive causal probability score data object. A complex federated service network may be monitored to identify a service incident data object associated with a service incident. A predictive causal machine learning model may generate a predictive causal probability score data object based at least in part on a service incident time associated with the service incident data object. The predictive causal probability score data object may be output.

Various methods, apparatuses/systems, and media for automatic generation and management of cloud service provider events are provided. A service provider computing device defines a maturity level of an event; publishes an event schema associated with the maturity level of the event; and transmits the event to an event platform that is configured to provide infrastructure for event production and consumption. The event platform validates the event based on the event schema; calculates a validation score for the event upon validation of the event; and publishes the validation score on a website. A consumer computing device consumes the published event from the event platform.

Systems, apparatuses, methods, and computer program products are disclosed for managing open issues. An example method includes obtaining a dashboard access request for a portion of open issues managed by the issue management system, the issue management system storing variables associated with each open issue of the open issues; obtaining a dashboard data package based on scores for the portion of open issues, the scores indicating a severity level of the open issues of the portion of open issues and being based on the variables that are stored in the issue management system; and performing an action set using the dashboard data package to manage the portion of open issues.

Disclosed is a system to prioritize multiple issues associated with a wireless telecommunication network. The system obtains the multiple issues associated with the wireless telecommunication network, where an issue among the multiple issues impacts a UE associated with the wireless telecommunication network. The system obtains a number of UEs impacted by the issue, an indication of importance of severity associated with the issue, and an indication of importance of current UE experience. Based on the number of UEs impacted by the issue, the indication of importance of severity of the issue, and the indication of importance of current UE experience, the system computes a priority associated with the issue. Based on the priority, the system prioritizes the multiple issues to obtain a prioritized list. The system provides the prioritized list indicating an order in which to resolve the multiple issues.