MANAGING RESOURCE CONSOLIDATION CONFIGURATIONS
    24.
    发明申请
    MANAGING RESOURCE CONSOLIDATION CONFIGURATIONS 审中-公开
    管理资源综合配置

    公开(公告)号:US20170070446A1

    公开(公告)日:2017-03-09

    申请号:US15354607

    申请日:2016-11-17

    Abstract: Systems and methods for monitoring the performance associated with fulfilling resource requests and determining optimizations for improving such performance are provided. A processing device obtains and processes performance information associated with processing a request corresponding to two or more embedded resources. The processing device uses the processed performance information to determine a consolidation configuration to be associated with a subsequent request for the content associated with the two or more embedded resources. In some embodiments, in making such a determination, the processing device assesses performance information collected and associated with subsequent requests corresponding to the content associated with the two or more embedded resources and using each of a variety of alternative consolidation configurations. Aspects of systems and methods for generating recommendations to use a particular consolidation configuration to process a subsequent request corresponding to the content associated with the two or more embedded resources are also provided.

    Abstract translation: 提供了用于监视与履行资源请求相关联的性能并确定优化以改善此类性能的系统和方法。 处理装置获得并处理与处理与两个或更多个嵌入资源相对应的请求相关联的性能信息。 处理设备使用经处理的性能信息来确定与对与两个或多个嵌入式资源相关联的内容的后续请求相关联的整合配置。 在一些实施例中,在进行这样的确定时,处理装置评估与对应于与两个或更多个嵌入式资源相关联的内容的后续请求收集并且与各种替代合并配置中的每一个相关联的性能信息。 还提供了用于产生用于使用特定合并配置来处理对应于与两个或更多个嵌入式资源相关联的内容的后续请求的建议的系统和方法的方面。

    TIME SERIES METRIC DATA MODELING AND PREDICTION
    27.
    发明申请
    TIME SERIES METRIC DATA MODELING AND PREDICTION 审中-公开
    时间系列公制数据建模与预测

    公开(公告)号:US20170031744A1

    公开(公告)日:2017-02-02

    申请号:US15134263

    申请日:2016-04-20

    Abstract: A system that utilizes a plurality of time series of metric data to more accurately detect anomalies and model and predict metric values. Streams of time series metric data are processed to generate a set of independent metrics. In some instances, the present system may automatically analyze thousands of real-time streams. Advanced machine learning and statistical techniques are used to automatically find anomalies and outliers from the independent metrics by learning latent and hidden patterns in the metrics. The trends of each metric may also be analyzed and the trends for each characteristic may be learned. The system can automatically detect latent and hidden patterns of metrics including weekly, daily, holiday and other application specific patterns. Anomaly detection is important to maintaining system health and predicted values are important for customers to monitor and make planning and decisions in a principled and quantitative way.

    Abstract translation: 利用多个时间序列度量数据来更精确地检测异常并建模和预测度量值的系统。 处理时间序列量度数据流以生成一组独立度量。 在某些情况下,本系统可以自动分析数千个实时流。 高级机器学习和统计技术用于通过学习潜在和隐藏的度量标准,从独立度量中自动找出异常值和异常值。 还可以分析每个度量的趋势,并且可以了解每个特征的趋势。 该系统可以自动检测包括每周,每日,假期和其他应用程序特定模式的潜在和隐藏的度量模式。 异常检测对维护系统健康至关重要,预测值对客户来说是重要的,以原则和定量的方式监控和制定规划和决策。

    Provisioning Cloud Resources
    30.
    发明申请
    Provisioning Cloud Resources 有权
    配置云资源

    公开(公告)号:US20160352646A1

    公开(公告)日:2016-12-01

    申请号:US15236689

    申请日:2016-08-15

    Applicant: Red Hat, Inc.

    Abstract: Cloud resource provisioning is described. A cloud resource provisioning method may include receiving, by a processor, a cloud resource usage data identifying a first cloud resource consumed, a first usage level associated with the first cloud resource, a second cloud resource consumed, and a second usage level associated with the second cloud resource, wherein the first and second cloud resources are in respective first and second clouds. The method may further include assigning a first importance indicator to the first cloud resource. The method may further include assigning a second importance indicator to the second cloud resource. The method may further include analyzing the first and second importance indicators to identify a preference for the first cloud resource over the second cloud resource. The method may further include causing, in view of the analyzing, the first cloud resource to be provisioned at least at the first usage level and the second cloud resource to be provisioned at a reduced usage level below the second usage level.

    Abstract translation: 描述云资源配置。 云资源配置方法可以包括由处理器接收识别消耗的第一云资源的云资源使用数据,与第一云资源相关联的第一使用级别,所消耗的第二云资源以及与所述第一云资源相关联的第二使用水平 第二云资源,其中所述第一和第二云资源在相应的第一和第二云中。 该方法还可以包括将第一重要性指示符分配给第一云资源。 该方法还可以包括将第二重要性指示符分配给第二云资源。 该方法还可以包括分析第一和第二重要性指示符以识别第二云资源对第一云资源的偏好。 该方法可以进一步包括:考虑到分析,至少在第一使用级别提供第一云资源并且以低于第二使用级别的降低的使用水平来提供第二云资源。

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