公开(公告)号：US20180165693A1

公开(公告)日：2018-06-14

申请号：US15377824

申请日：2016-12-13

Applicant: VMware, Inc.

Inventor： Lalit Jain ,  Janislav Jankov

IPC: G06Q30/02 ,  G06F9/455

CPC classification number: G06Q30/0201 ,  G06F9/45558 ,  G06F2009/4557 ,  G06F2009/45591

Abstract: Methods and systems that identify objects of a data center that exhibit correlated-extreme behavior are described. The objects may be, but are not limited to, virtual machines (“VMs”), containers, server computers, clusters of server computers, and the data center itself. Metric data is collected for the various objects and the methods identify the objects that exhibit correlated-extreme behavior. In particular, the methods and systems narrow a search for correlated-extreme behavior of consumers of computational resources of a data center when a provider of the computational resources exhibits unexpected or extreme behavior.

公开(公告)号：US11080093B2

公开(公告)日：2021-08-03

申请号：US16013503

申请日：2018-06-20

Applicant: VMware, Inc.

Inventor： Rachil Chandran ,  Lalit Jain ,  Harutyun Beybutyan ,  James Ang ,  Leah Nutman ,  Keshav Mathur

IPC: G06F9/46 ,  G06F9/50 ,  G06F17/18 ,  G06N7/00

Abstract: Computational methods and systems to reclaim capacity of a virtual infrastructure of distributed computing system are described. Methods and systems are directed to forecasting usage of resources that form a virtual infrastructure of a distributed computing system. Streams of metric data that represent usage of resources of the virtual infrastructure assigned to a virtual object are collected. A binary sequence of active status metric data is computed for the virtual object based on the streams of metric data. Forecasted active status metric data are computed in a forecast interval based on the sequence of active status metric data. Expected active or inactive status of virtual object over the forecast interval is determined from the forecasted active status metric data. If the virtual object is expected to inactive status over the forecast interval, resources assigned to the virtual object are reclaimed for use by active virtual objects.

公开(公告)号：US20190317816A1

公开(公告)日：2019-10-17

申请号：US16013503

申请日：2018-06-20

Applicant: VMware, Inc.

Inventor： Rachil Chandran ,  Lalit Jain ,  Harutyun Beybutyan ,  James Ang ,  Leah Nutman ,  Keshav Mathur

IPC: G06F9/50 ,  G06N7/00 ,  G06F17/18

Abstract: Computational methods and systems to reclaim capacity of a virtual infrastructure of distributed computing system are described. Methods and systems are directed to forecasting usage of resources that form a virtual infrastructure of a distributed computing system. Streams of metric data that represent usage of resources of the virtual infrastructure assigned to a virtual object are collected. A binary sequence of active status metric data is computed for the virtual object based on the streams of metric data. Forecasted active status metric data are computed in a forecast interval based on the sequence of active status metric data. Expected active or inactive status of virtual object over the forecast interval is determined from the forecasted active status metric data. If the virtual object is expected to inactive status over the forecast interval, resources assigned to the virtual object are reclaimed for use by active virtual objects.

公开(公告)号：US11204811B2

公开(公告)日：2021-12-21

申请号：US16180411

申请日：2018-11-05

Applicant: VMware, Inc.

Inventor： Lalit Jain ,  Rachil Chandran ,  Keshav Mathur ,  James Ang ,  Kien Chiew Wong ,  Leah Nutman

IPC: G06F9/46 ,  G06F9/50 ,  G06F17/18 ,  G06F9/455

Abstract: Computational methods and systems that estimate time remaining and right size for usable capacities of resources used to run virtual objects of a distributed computing system are described. For each stream of metric data that represents usage of a resource of a distributed computing system, a model for forecasting metric data is determined and used to compute forecasted metric data in a forecast interval. A resource utilization metric is computed from the forecasted metric data and may be used to estimate a time remaining before the usable capacity of the resource is expected to be insufficient and the resource usable capacity is adjusted. The resource utilization metric may be used to determine the capacity remaining is insufficient. A right-size usable capacity for the resource is computed based on the resource utilization metric and the usable capacity of the resource is adjusted to at least the right-size usable capacity.

公开(公告)号：US20190317826A1

公开(公告)日：2019-10-17

申请号：US16180411

申请日：2018-11-05

Applicant: VMware, Inc.

Inventor： Lalit Jain ,  Rachil Chandran ,  Keshav Mathur ,  James Ang ,  Kien Chiew Wong ,  Leah Nutman

IPC: G06F9/50 ,  G06F17/18 ,  G06F9/455

Abstract: Computational methods and systems that estimate time remaining and right size for usable capacities of resources used to run virtual objects of a distributed computing system are described. For each stream of metric data that represents usage of a resource of a distributed computing system, a model for forecasting metric data is determined and used to compute forecasted metric data in a forecast interval. A resource utilization metric is computed from the forecasted metric data and may be used to estimate a time remaining before the usable capacity of the resource is expected to be insufficient and the resource usable capacity is adjusted. The resource utilization metric may be used to determine the capacity remaining is insufficient. A right-size usable capacity for the resource is computed based on the resource utilization metric and the usable capacity of the resource is adjusted to at least the right-size usable capacity.