MACHINE LEARNING MONITORING OF WIRELESS NETWORK INFRASTRUCTURE APPLICATION SERVERS

    公开(公告)号:US20230370338A1

    公开(公告)日:2023-11-16

    申请号:US17745277

    申请日:2022-05-16

    CPC classification number: H04L41/16 H04L41/0672 H04L41/147

    Abstract: Machine learning systems and techniques are described herein for monitoring application servers within the computing infrastructure of a wireless network. A machine learning system may train and execute models based on performance metrics, error data, and failures from application servers configured to perform various functions relating to communication session authorization, monitoring, and charging for voice, data, and messaging communication services over the wireless network. Machine learning models may be configured to predict service degradations, detect performance anomalies, and determine root causes, and various models may output particular application servers, components, and/or predicted times of certain events. Based on the outputs of the machine learning models, the machine learning system may perform various actions for the wireless network infrastructure, including data outputting and/or executing processes on the application servers to analyze, restart, and/or repair particular components.

    GLOBAL ALERT MANAGEMENT
    56.
    发明公开

    公开(公告)号:US20230344698A1

    公开(公告)日:2023-10-26

    申请号:US18303539

    申请日:2023-04-19

    Applicant: Alkira, Inc.

    CPC classification number: H04L41/0609 H04L12/4633 H04L41/0654

    Abstract: Disclosed is a system that includes a plurality of regional cloud exchange platforms coupled to a distributed alert triaging engine. A system can include a first regional cloud exchange platform and a second regional cloud exchange platform, each of which includes a regional cloud services monitoring engine and a regional cloud exchange monitoring engine, and an alert triaging engine that provides a triaged alert, or portion thereof, to an appropriate audience.

    ACTION RECOMMENDATIONS FOR OPERATIONAL ISSUES

    公开(公告)号:US20230318905A1

    公开(公告)日:2023-10-05

    申请号:US17697078

    申请日:2022-03-17

    CPC classification number: H04L41/0631 H04L41/0654

    Abstract: An information technology (IT) component associated with a first alert having an alert type is identified. A first list of recommended actions associated with the IT component is output. The first list includes a recommended action. A first user input of a user-selected action is received. An alert-to-component likelihood between the IT component and the alert type is decreased based on a determination that the first list does not include the user-selected action. The IT component is identified as being associated with a second alert based on the alert-to-component likelihood exceeding an alert-to-component likelihood threshold. A second list of recommended actions associated with the IT component is output. The second list does not include the recommended action and includes the user-selected action. A second user input of the user-selected action is received. A request to execute the user-selected action is transmitted.

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