AIOPS AS A CLOUD-BASED SERVICE
    1.
    发明公开

    公开(公告)号:US20230186326A1

    公开(公告)日:2023-06-15

    申请号:US17550810

    申请日:2021-12-14

    CPC classification number: G06Q30/0201

    Abstract: Systems and methods are provided for utilizing a bidirectional intermediate data transport layer to connect multiple customers to a shared, cloud-based AIOps service. As a feature of the intermediate data transport layer, each customer (and their data) may be isolated from other customers. In various examples, the cloud-based AIOps service may receive sensor data from customer systems via the intermediate data transport layer. The cloud-based AIOps service may analyze this sensor data (e.g. detect anomalies, perform root cause analyses, find optimal conditions, etc.), and modify the operation of one or more of the customer systems (e.g. modify the settings/configuration of a sensor on a piece of connected infrastructure) via the intermediate data transport layer. In certain examples, in addition to (or instead of) modifying the operation of one or more of the customer systems, the cloud-based AIOps service may provide an on-premises notification to a customer.

    IMPROVING DATA MONITORING AND QUALITY USING AI AND MACHINE LEARNING

    公开(公告)号:US20220404235A1

    公开(公告)日:2022-12-22

    申请号:US17351085

    申请日:2021-06-17

    Abstract: Systems and methods are provided for improving statistical and machine learning drift detection models that monitor computing health of a data center environment. For example, the system can receive streams of sensor data from a plurality of sensors in a data center; clean the streams of sensor data; generate, using a machine learning (ML) model, an anomaly score and a dynamic threshold value based on the cleaned streams of sensor data; determine, using the ML model and based on the anomaly score and the dynamic threshold value, a correctness indicator for a first sensor in the plurality of sensors; and using the correctness indicator, correct the first sensor.

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