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    DIAGNOSTIC AND RECOVERY SIGNALS FOR DISCONNECTED APPLICATIONS IN HOSTED SERVICE ENVIRONMENT
    1.
    发明申请
    DIAGNOSTIC AND RECOVERY SIGNALS FOR DISCONNECTED APPLICATIONS IN HOSTED SERVICE ENVIRONMENT 审中-公开

    公开(公告)号：US20200036613A1

    公开(公告)日：2020-01-30

    申请号：US16589961

    申请日：2019-10-01

    申请人： Microsoft Technology Licensing, LLC

    发明人： Kiran NALLABOTHULA ,  Nagaraj PATIL ,  Nagaraju PALLA

    IPC分类号： H04L12/26 ,  H04L29/08 ,  H04L12/24

    摘要： An assistance service through its local client application or agent at a user's device (or devices) may collect diagnostic related information associated with the user's operating environment (physical and software operation parameters and configurations) and monitor a health of one or more applications. Upon detecting an issue or being activated by the user, the local client application or agent may perform diagnostic and/or recovery actions. In some cases, the diagnostic related signals may be sent directly by the application being monitored or diagnosed to its hosting service or the assistance service. Upon detecting a disconnect of the application being monitored or diagnosed, the local client application or agent may determine an alternative server and transmit the diagnostic related signals to the alternative server. An alert indicating the disconnect of the application may also be sent.

    CLOUD-BASED RECOVERY SYSTEM
    2.
    发明申请
    CLOUD-BASED RECOVERY SYSTEM 审中-公开

    公开(公告)号：US20190258536A1

    公开(公告)日：2019-08-22

    申请号：US16405202

    申请日：2019-05-07

    申请人： Microsoft Technology Licensing, LLC

    发明人： Kiran NALLABOTHULA ,  Dylan SYMINGTON ,  Nagaraju PALLA ,  Amanda A. ALVARADO ,  Ricardo Soares STERN

    IPC分类号： G06F11/07 ,  G06F11/22

    摘要： A method, performed by a computing system deployed in a server environment, comprises receiving, from a client computing device that is remote from the server environment, a problem scenario identifier that identifies a problem scenario indicative of a problem associated with the client computing device, identifying a problem-specific diagnostic analyzer, that is specific to the problem associated with the client computing device, based on mapping information that maps the problem scenario to the problem-specific diagnostic analyzer, running the problem-specific diagnostic analyzer to obtain problem-specific diagnostic data that is specific to the problem associated with the client computing device, the problem-specific diagnostic data including first data associated with the client computing device and second data associated with the server environment, identifying a suggested recovery action based on the problem-specific diagnostic data, and communicating the suggested recovery action to the client computing device.

    ANOMALY DETECTION AND CLASSIFICATION USING TELEMETRY DATA
    4.
    发明申请
    ANOMALY DETECTION AND CLASSIFICATION USING TELEMETRY DATA 审中-公开

    公开(公告)号：US20180241693A1

    公开(公告)日：2018-08-23

    申请号：US15958293

    申请日：2018-04-20

    申请人： Microsoft Technology Licensing, LLC

    发明人： Nagaraj PATIL ,  Kiran NALLABOTHULA ,  Christopher BARNES ,  Nagaraju PALLA

    IPC分类号： H04L12/911 ,  H04L12/24

    CPC分类号： H04L47/827 ,  H04L41/064 ,  H04L41/147 ,  H04L61/1511

    摘要： Historical telemetry data can be used to generate predictions for various classes of data at various aggregates of a system that implements an online service. An anomaly detection process can then be utilized to detect anomalies for a class of data at a selected aggregate. An example anomaly detection process includes receiving telemetry data originating from a plurality of client devices, selecting a class of data from the telemetry data, converting the class of data to a set of metrics, aggregating the set of metrics according to a component of interest to obtain values of aggregated metrics over time for the component of interest, determining a prediction error by comparing the values of the aggregated metrics to a prediction, detecting an anomaly based at least in part on the prediction error, and transmitting an alert message of the anomaly to a receiving entity.

    ANOMALY DETECTION AND CLASSIFICATION USING TELEMETRY DATA
    6.
    发明申请
    ANOMALY DETECTION AND CLASSIFICATION USING TELEMETRY DATA 审中-公开

    公开(公告)号：US20190116131A1

    公开(公告)日：2019-04-18

    申请号：US16219221

    申请日：2018-12-13

    申请人： Microsoft Technology Licensing, LLC

    发明人： Nagaraj PATIL ,  Kiran NALLABOTHULA ,  Christopher BARNES ,  Nagaraju PALLA

    IPC分类号： H04L12/911 ,  H04L12/24

    CPC分类号： H04L47/827 ,  H04L41/064 ,  H04L41/147 ,  H04L61/1511

    摘要： Historical telemetry data can be used to generate predictions for various classes of data at various aggregates of a system that implements an online service. An anomaly detection process can then be utilized to detect anomalies for a class of data at a selected aggregate. An example anomaly detection process includes receiving telemetry data originating from a plurality of client devices, selecting a class of data from the telemetry data, converting the class of data to a set of metrics, aggregating the set of metrics according to a component of interest to obtain values of aggregated metrics over time for the component of interest, determining a prediction error by comparing the values of the aggregated metrics to a prediction, detecting an anomaly based at least in part on the prediction error, and transmitting an alert message of the anomaly to a receiving entity.