Methods and apparatus to determine container priorities in virtualized computing environments

    公开(公告)号:US11025495B1

    公开(公告)日:2021-06-01

    申请号:US16802591

    申请日:2020-02-27

    Applicant: VMWARE, INC.

    Abstract: Example methods and apparatus to determine container priorities in virtualized computing environments are disclosed herein. Examples include: a cluster controller to classify a first container into a cluster based on the first container having a number of distinct allocated resources within a threshold number of distinct allocated resources corresponding to a second container; a container ranking generator to: determine resource utilization rank values for a resource usage type of a number of distinct allocated resources, the resource utilization rank values indicative that the first container utilizes the resource usage type more than the second container; determine an aggregated resource utilization rank value for the first container based on aggregating ones of the resource utilization rank values corresponding to the first container; and a container priority controller to generate a priority class for the first container based on the aggregated resource utilization rank value.

    Methods and apparatus to determine container priorities in virtualized computing environments

    公开(公告)号:US11575576B2

    公开(公告)日:2023-02-07

    申请号:US17332771

    申请日:2021-05-27

    Applicant: VMWARE, INC.

    Abstract: An example apparatus includes memory, and at least one processor to execute instructions to assign first containers to a first cluster and second containers to a second cluster based on the first containers including first allocated resources that satisfy a first threshold number of allocated resources and the second containers including second allocated resources that satisfy a second threshold number of allocated resources, determine a representative interaction count value for a first one of the first containers, the representative interaction count value based on a first network interaction metric corresponding to an interaction between the first one of the first containers and a combination of at least one of the first containers and at least one of the second containers, and generate a priority class for the first one of the first containers based on the representative interaction count value.

    DEPENDENT SYSTEM OPTIMIZATION FOR SERVERLESS FRAMEWORKS

    公开(公告)号:US20200241930A1

    公开(公告)日:2020-07-30

    申请号:US16392652

    申请日:2019-04-24

    Applicant: VMWARE, INC.

    Abstract: Various aspects are disclosed for optimization of dependent systems for serverless frameworks. In some examples, a load test executes instances of a function on a dependent system to generate datapoints. The datapoints are organized, using a clustering algorithm, into an acceptable group and at least one unacceptable group. A maximum number of concurrent instances of the function is determined based on a number of instances specified by at least one datapoint selected from the acceptable group. A live workload is performed on the dependent system. The live workload includes instances of the function that are assigned to the dependent system according to the maximum number of concurrent instances.

    GENERATING METRICS FOR QUANTIFYING COMPUTING RESOURCE USAGE

    公开(公告)号:US20200026565A1

    公开(公告)日:2020-01-23

    申请号:US16037298

    申请日:2018-07-17

    Applicant: VMware, Inc.

    Abstract: Various examples are disclosed for generating metrics for quantifying computing resource usage. A computing environment can identify a computing function that utilizes a plurality of computing services hosted in at least one virtual machine. The computing environment can determine a first cost metric for the at least one virtual machine based on hardware resources used by the at least one virtual machine and determine a second cost metric for individual ones of the computing services based on virtual machine resources used by the individual ones of the computing services and the first cost metric. A third cost metric can be determined for the computing function as a function of the second cost metric and a utilization ratio.

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