Methods, systems, devices, and software are disclosed for generating a network usage profile. Certain embodiments of the network usage profile include a devices-by-node profile, indicating the set of customer devices available for use in communicating with a customer-side network node located at a customer side of an access network over a period of time, where some of the customer devices are not in operative communication with the customer-side network node during a portion of that time. Other embodiments associate the network usage profile with customer information to generate device-by-customer profiles. Still other embodiments associate the network usage profile with network traffic information to generate traffic-by-device profiles. Even other embodiments associate the multiple sources and types of information to generate traffic-by-customer profiles and/or traffic-by-device-by-customer profiles. Any of the profiles may then be accessed by one or more parties for use in affecting various network services, including targeting content delivery.

The disclosure herein describes predicting potential impact of issues reported in incident ticket data on infrastructure element. A ticket manager component includes an impact model utilizing machine learning to analyze real-time event and metric data with incident-related data to generate predicted impact data. The predicted impact data identifies potentially impacted infrastructure elements, such as, potentially impacted users, predicted infrastructure components impacted by the issue and/or an updated time-period associated with the issue. The ticket manager component creates labeled incident tickets by updating user-generated incident tickets with additional data generated by the impact model, including predicted impact data and/or additional details associated with the issue. The labeled incident tickets are provided back to the model as training data to further refine predictions generated by the model.

The disclosure herein describes predicting potential impact of issues reported in incident ticket data on infrastructure element. A ticket manager component includes an impact model utilizing machine learning to analyze real-time event and metric data with incident-related data to generate predicted impact data. The predicted impact data identifies potentially impacted infrastructure elements, such as, potentially impacted users, predicted infrastructure components impacted by the issue and/or an updated time-period associated with the issue. The ticket manager component creates labeled incident tickets by updating user-generated incident tickets with additional data generated by the impact model, including predicted impact data and/or additional details associated with the issue. The labeled incident tickets are provided back to the model as training data to further refine predictions generated by the model.

An embodiment includes a method of secured, remote device access through dynamic scope adjustment in an incident management system. The method includes receiving an incident report indicative of a technical issue at a first device. Responsive to receipt of the incident report, the method includes determining that the first device is assigned an information technology (IT) support provider and dynamically elevating the first device to a scope of the IT support provider. Following a correction of at least a portion of the technical issue by the IT support provider, the method includes dynamically relegating the first device from the scope to prevent remote access to the first device following the correction.

An embodiment includes a method of secured, remote device access through dynamic scope adjustment in an incident management system. The method includes receiving an incident report indicative of a technical issue at a first device. Responsive to receipt of the incident report, the method includes determining that the first device is assigned an information technology (IT) support provider and dynamically elevating the first device to a scope of the IT support provider. Following a correction of at least a portion of the technical issue by the IT support provider, the method includes dynamically relegating the first device from the scope to prevent remote access to the first device following the correction.

Techniques are described in which a network management system (NMS) is configured to determine a root cause of degraded network performance based on SLE metrics and the locations associated with network devices providing the SLE metrics. The NMS can determine service level experience (SLE) metrics associated with each client device on a network and location data for each client device of the plurality of client devices. The NMS can generate a time series of parameter vectors, where each parameter vector includes SLE metrics corresponding to each client device of the plurality of client devices. Each parameter vector is associated with the location of the client device corresponding to the SLE metrics. The NMS can determine, based on the time series of parameter vectors and associated locations, a root cause for a degradation in SLE metrics associated with the one or more of the client devices.

Various techniques include detecting noise resulting from data network impairments and analyzing the noise to determine a likely source and location of the data network impairments. The analysis is used to generate noise reports that instruct network technicians how to check network devices for network impairments. The instructions can be provided on portable electronic devices that are further configured to receive data characterizing any impairments identified at the network devices. The data generated by the network technicians can be used to improve the ability of the techniques to correctly identify the source of data network impairments.

Various techniques include detecting noise resulting from data network impairments and analyzing the noise to determine a likely source and location of the data network impairments. The analysis is used to generate noise reports that instruct network technicians how to check network devices for network impairments. The instructions can be provided on portable electronic devices that are further configured to receive data characterizing any impairments identified at the network devices. The data generated by the network technicians can be used to improve the ability of the techniques to correctly identify the source of data network impairments.

Detect, at a cable/fiber broadband network termination unit of a cable/fiber broadband multi-service operator, an interruption in service to a cable/fiber broadband network customer unit—small cell pair. Responsive to detecting the interruption, the termination unit advises a charging server of the operator of the interruption in service, a corresponding identifier of the customer unit—small cell pair, and a corresponding account identifier. Responsive to termination unit advising the charging server, the charging server advises a backend server of an associated cellular network of a customer identifier corresponding to the account identifier. Responsive to the charging server advising the backend server, the backend server advises a policy control function of the associated cellular network to modify network parameters of the associated cellular network to compensate for the interruption in service.

Detect, at a cable/fiber broadband network termination unit of a cable/fiber broadband multi-service operator, an interruption in service to a cable/fiber broadband network customer unit—small cell pair. Responsive to detecting the interruption, the termination unit advises a charging server of the operator of the interruption in service, a corresponding identifier of the customer unit—small cell pair, and a corresponding account identifier. Responsive to termination unit advising the charging server, the charging server advises a backend server of an associated cellular network of a customer identifier corresponding to the account identifier. Responsive to the charging server advising the backend server, the backend server advises a policy control function of the associated cellular network to modify network parameters of the associated cellular network to compensate for the interruption in service.