Information technology networked cloud service monitoring

    公开(公告)号:US11537627B1

    公开(公告)日:2022-12-27

    申请号:US16147181

    申请日:2018-09-28

    Applicant: Splunk Inc.

    Abstract: Systems and methods ingest machine data including logs, metadata, and cost and usage information from multiple heterogeneous cloud services. The machine data is saved as events. An application retrieves the metadata, events, metrics, and logs and causes an easy to understand visual representation of costs, resource usage, and non-compliance for each of a client's cloud services. Further, the data across the client's multiple heterogeneous cloud services is normalized to provide visual representations that compare the costs, resource usage, and non-compliance across the client's multiple heterogeneous cloud services. Further, machine learning aspects of the application can provide recommendations and trend analysis for cloud service asset usage.

    Networked cloud service monitoring

    公开(公告)号:US11886455B1

    公开(公告)日:2024-01-30

    申请号:US18146256

    申请日:2022-12-23

    Applicant: Splunk Inc.

    CPC classification number: G06F16/248 G06F16/951

    Abstract: Systems and methods ingest machine data including logs, metadata, and cost and usage information from multiple heterogeneous cloud services. The machine data is saved as events. An application retrieves the metadata, events, metrics, and logs and causes an easy to understand visual representation of costs, resource usage, and non-compliance for each of a client's cloud services. Further, the data across the client's multiple heterogeneous cloud services is normalized to provide visual representations that compare the costs, resource usage, and non-compliance across the client's multiple heterogeneous cloud services. Further, machine learning aspects of the application can provide recommendations and trend analysis for cloud service asset usage.

    Layered feature set levels in service monitoring system

    公开(公告)号:US12255773B1

    公开(公告)日:2025-03-18

    申请号:US17587747

    申请日:2022-01-28

    Applicant: SPLUNK Inc.

    Abstract: An example method of implementing a layered feature set management model by a service monitoring system includes: monitoring a feature set configuration associated with a specified application instance; setting, based on the feature set configuration, a feature set level transition marker associated with the specified application instance; identifying, based on a current feature set level associated with the specified application instance and the feature set level transition marker, a new feature set level associated with the specified application instance; identifying a new feature set corresponding to the new feature set level and one or more roles associated with a specified user; and configuring a graphical user interface (GUI) enabling the new feature set for the specified user of the specified application instance.

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