Metric data processing and storage

    公开(公告)号:US12067016B1

    公开(公告)日:2024-08-20

    申请号:US17548417

    申请日:2021-12-10

    Abstract: Data being identified includes a first portion of data and a second portion of data. Based on identifying the data, a data structure is generated. The data structure can include a first section having a first symbol associated with the first portion of data and a second symbol associated with the second portion of data. Further, the first section can include a first offset value corresponding to the first portion of data and a second offset value corresponding to the second portion of data. The data structure can include a second section with a plurality of pointers that reference at least a plurality of symbols including at least the first and second symbol. The data structure can be referenced to process one or more queries against the data.

    System and method for generating dynamic sparse exponential histograms

    公开(公告)号:US10983888B1

    公开(公告)日:2021-04-20

    申请号:US16218391

    申请日:2018-12-12

    Abstract: Systems and methods for generating dynamic sparse exponential histograms. The system includes a network-based service and a data compression engine to generate a sparse exponential histogram (SEH) representation of a distribution of a plurality of data values of a performance metric of the network-based service. The data compression engine is configured to, map each data value to a bin of an exponential histogram. Responsive to a determination that the mapped bin is not indicated in the SEH representation and that a bin quantity limit would be exceeded by adding the mapped bin, the data compression engine is configured to increase a bin size parameter by a scaling factor to expand data value ranges of the bins, merge bins indicated in the SEH representation according to the expanded data value ranges to reduce the quantity of bins indicated in the SEH representation, and indicate the scaling factor in the SEH representation.

    DATASTORE FOR AGGREGATED MEASUREMENTS FOR METRICS

    公开(公告)号:US20180131761A1

    公开(公告)日:2018-05-10

    申请号:US15865043

    申请日:2018-01-08

    CPC classification number: H04L67/1095 H04L67/1004

    Abstract: A computing resource monitoring service receives a request to store a measurement for a metric associated with a computing resource. The request includes the measurement itself and metadata for the measurement, which specifies attributes of the measurement. Based at least in part on the metadata, the computing resource monitoring service generates a fully-qualified metric identifier and, using the identifier, selects a logical partition for placement of the measurement. From the logical partition, the computing resource monitoring service transmits the measurement to an aggregator sub-system comprising one or more in-memory datastores. The computing resource monitoring service stores the measurement in an in-memory datastore within the aggregator sub-system.

    Automatic scaling of computing resources using aggregated metrics

    公开(公告)号:US09880880B2

    公开(公告)日:2018-01-30

    申请号:US14752760

    申请日:2015-06-26

    CPC classification number: G06F9/505 G06F9/5061 G06F9/5077 G06F9/5083

    Abstract: A computing resource monitoring service receives a plurality of measurements for a metric associated with an auto-scale group. Each measurement is associated with metadata for the measurement, which specifies attributes for the measurement. The computing resource monitoring service determines, for each measurement and based at least in part on the metadata, a fully qualified metric identifier for the measurement. The service partitions the plurality of measurements into a plurality of logical partitions associated with one or more in-memory datastores. The service transmits the measurements from the plurality of logical partitions to the one or more datastores for storage of the measurements. These measurements are provided to one or more computing resource managers for the auto-scale group to enable automatic scaling of computing resources of the group based at least in part on the measurements.

    AUTOMATIC SCALING OF COMPUTING RESOURCES USING AGGREGATED METRICS
    7.
    发明申请
    AUTOMATIC SCALING OF COMPUTING RESOURCES USING AGGREGATED METRICS 有权
    使用聚合度量的计算资源自动调整

    公开(公告)号:US20160378552A1

    公开(公告)日:2016-12-29

    申请号:US14752760

    申请日:2015-06-26

    CPC classification number: G06F9/505 G06F9/5061 G06F9/5077 G06F9/5083

    Abstract: A computing resource monitoring service receives a plurality of measurements for a metric associated with an auto-scale group. Each measurement is associated with metadata for the measurement, which specifies attributes for the measurement. The computing resource monitoring service determines, for each measurement and based at least in part on the metadata, a fully qualified metric identifier for the measurement. The service partitions the plurality of measurements into a plurality of logical partitions associated with one or more in-memory datastores. The service transmits the measurements from the plurality of logical partitions to the one or more datastores for storage of the measurements. These measurements are provided to one or more computing resource managers for the auto-scale group to enable automatic scaling of computing resources of the group based at least in part on the measurements.

    Abstract translation: 计算资源监视服务接收与自动比例组相关联的度量的多个测量。 每个测量与测量的元数据相关联,该元数据指定测量的属性。 计算资源监视服务针对每个测量并且至少部分地基于元数据确定用于测量的完全限定的度量标识符。 服务将多个测量分割成与一个或多个内存中数据存储相关联的多个逻辑分区。 该服务将测量从多个逻辑分区发送到一个或多个数据存储以存储测量结果。 这些测量被提供给自动量表组的一个或多个计算资源管理器,以使得能够至少部分地基于测量来自动缩放组中的计算资源。

    System for optimizing serialization of values

    公开(公告)号:US10318516B1

    公开(公告)日:2019-06-11

    申请号:US14862019

    申请日:2015-09-22

    Inventor: Gary Taylor

    Abstract: A first value of a first data type is obtained as input. A second value of a second data type is obtained based at least in part on the first value. The second value is determined to match the first value without losing precision. The second value is determined to be greater than a maximum value for a third data type, and less than or equal to a maximum value for a fourth data type. A marker value is stored in a first storage location, the marker value indicating that a second storage location holds a value of the fourth data type. The second value is stored in the second storage location as the fourth data type.

    Datastore for aggregated measurements for metrics

    公开(公告)号:US10270854B2

    公开(公告)日:2019-04-23

    申请号:US15865043

    申请日:2018-01-08

    Abstract: A computing resource monitoring service receives a request to store a measurement for a metric associated with a computing resource. The request includes the measurement itself and metadata for the measurement, which specifies attributes of the measurement. Based at least in part on the metadata, the computing resource monitoring service generates a fully-qualified metric identifier and, using the identifier, selects a logical partition for placement of the measurement. From the logical partition, the computing resource monitoring service transmits the measurement to an aggregator sub-system comprising one or more in-memory datastores. The computing resource monitoring service stores the measurement in an in-memory datastore within the aggregator sub-system.

    ARCHITECTURE FOR METRICS AGGREGATION WITHOUT SERVICE PARTITIONING
    10.
    发明申请
    ARCHITECTURE FOR METRICS AGGREGATION WITHOUT SERVICE PARTITIONING 有权
    没有服务分类的量度聚合的架构

    公开(公告)号:US20160380866A1

    公开(公告)日:2016-12-29

    申请号:US14752759

    申请日:2015-06-26

    CPC classification number: H04L47/783 H04L41/5009 H04L41/5061

    Abstract: A web server computer system receives a plurality of measurements for a metric from one or more computing resources associated with the web server computer system. Each measurement includes metadata for the measurement, which specifies attributes of the measurement. The web server computer system determines, for each measurement and based at least in part on the metadata, a fully qualified metric identifier for the measurement. The web server computer system uses the fully qualified metric identifier to partition the plurality of measurements into various partitions. Once completed, the web server computer system transmits a request to one or more aggregator sub-systems of a computing resource monitoring service to store the plurality of measurements.

    Abstract translation: web服务器计算机系统从与web服务器计算机系统相关联的一个或多个计算资源接收用于度量的多个测量。 每个测量包括用于测量的元数据,其指定测量的属性。 web服务器计算机系统针对每个测量并且至少部分地基于元数据确定用于测量的完全限定度量标识符。 Web服务器计算机系统使用完全限定的度量标识符将多个测量分割成各个分区。 一旦完成,web服务器计算机系统向计算资源监视服务的一个或多个聚合器子系统发送请求以存储多个测量。

Patent Agency Ranking