公开(公告)号：US09106589B2

公开(公告)日：2015-08-11

申请号：US14326300

申请日：2014-07-08

Applicant: Amazon Technologies, Inc.

Inventor： Zhuo Zhang ,  Swaminathan Subramanian ,  Muhammad Ali Siddiqui

IPC: G06F15/177 ,  G06F15/173 ,  G06F3/00 ,  H04L12/911 ,  G06F9/06

CPC classification number: H04L47/823 ,  G06F9/06 ,  G06F9/505 ,  G06F2209/5019

Abstract: Techniques are described for performing automated predictions of program execution capacity or other capacity of computing-related hardware resources that will be used to execute software programs in the future, such as for a group of computing nodes that execute one or more programs for a user. The predictions that are performed may in at least some situations be based on historical data regarding corresponding prior actual usage of execution-related capacity (e.g., for one or more prior years), and may include long-term predictions for particular future time periods that are multiple months or years into the future. In addition, the predictions of the execution-related capacity for particular future time periods may be used in various manners, including to manage execution-related capacity at or before those future time periods, such as to prepare sufficient execution-related capacity to be available at those future time periods.

Abstract translation: 描述了用于执行将用于执行将来的软件程序的程序执行能力或计算相关硬件资源的其他容量的自动预测的技术，例如对于为用户执行一个或多个程序的一组计算节点。 所执行的预测可以在至少一些情况下基于关于执行相关能力的相应的先前实际使用的历史数据（例如，对于一个或多个以前的年份），并且可以包括对于特定未来时间段的长期预测， 是未来的几个月或几年。 此外，可以以各种方式使用对特定未来时间段的执行相关能力的预测，包括在该未来时间段之前或之前管理与执行相关的能力，例如准备足够的与执行相关的能力可用 在那些未来的时期。

公开(公告)号：US20140325072A1

公开(公告)日：2014-10-30

申请号：US14326300

申请日：2014-07-08

Applicant: Amazon Technologies, Inc.

Inventor： Zhuo Zhang ,  Swaminathan Subramanian ,  Muhammad Ali Siddiqui

IPC: H04L12/911

CPC classification number: H04L47/823 ,  G06F9/06 ,  G06F9/505 ,  G06F2209/5019

Abstract: Techniques are described for performing automated predictions of program execution capacity or other capacity of computing-related hardware resources that will be used to execute software programs in the future, such as for a group of computing nodes that execute one or more programs for a user. The predictions that are performed may in at least some situations be based on historical data regarding corresponding prior actual usage of execution-related capacity (e.g., for one or more prior years), and may include long-term predictions for particular future time periods that are multiple months or years into the future. In addition, the predictions of the execution-related capacity for particular future time periods may be used in various manners, including to manage execution-related capacity at or before those future time periods, such as to prepare sufficient execution-related capacity to be available at those future time periods.

Abstract translation: 描述了用于执行将用于执行将来的软件程序的程序执行能力或计算相关硬件资源的其他容量的自动预测的技术，例如对于为用户执行一个或多个程序的一组计算节点。 所执行的预测可以在至少一些情况下基于关于执行相关能力的相应的先前实际使用的历史数据（例如，对于一个或多个以前的年份），并且可以包括对于特定未来时间段的长期预测， 是未来几个月或几年。 此外，可以以各种方式使用对特定未来时间段的执行相关能力的预测，包括在该未来时间段之前或之前管理与执行相关的能力，例如准备足够的与执行相关的能力可用 在那些未来的时期。

公开(公告)号：US08812646B1

公开(公告)日：2014-08-19

申请号：US13937036

申请日：2013-07-08

Applicant: Amazon Technologies, Inc.

Inventor： Zhuo Zhang ,  Swaminathan Subramanian ,  Muhammad Ali Siddiqui

IPC: G06F15/177 ,  G06F15/173 ,  G06F3/00

CPC classification number: H04L47/823 ,  G06F9/06 ,  G06F9/505 ,  G06F2209/5019

Abstract: Techniques are described for performing automated predictions of program execution capacity or other capacity of computing-related hardware resources that will be used to execute software programs in the future, such as for a group of computing nodes that execute one or more programs for a user. The predictions that are performed may in at least some situations be based on historical data regarding corresponding prior actual usage of execution-related capacity (e.g., for one or more prior years), and may include long-term predictions for particular future time periods that are multiple months or years into the future. In addition, the predictions of the execution-related capacity for particular future time periods may be used in various manners, including to manage execution-related capacity at or before those future time periods, such as to prepare sufficient execution-related capacity to be available at those future time periods.

Abstract translation: 描述了用于执行将用于执行将来的软件程序的程序执行能力或计算相关硬件资源的其他容量的自动预测的技术，例如对于为用户执行一个或多个程序的一组计算节点。 所执行的预测可以在至少一些情况下基于关于执行相关能力的相应的先前实际使用的历史数据（例如，对于一个或多个以前的年份），并且可以包括对于特定未来时间段的长期预测， 是未来几个月或几年。 此外，可以以各种方式使用对特定未来时间段的执行相关能力的预测，包括在该未来时间段之前或之前管理与执行相关的能力，例如准备足够的与执行相关的能力可用 在那些未来的时期。

公开(公告)号：US08745218B1

公开(公告)日：2014-06-03

申请号：US13711451

申请日：2012-12-11

Applicant: Amazon Technologies, Inc.

Inventor： Joshua M. Goodspeed ,  Zhuo Zhang ,  Swaminathan Subramanian ,  Muhammad Ali Siddiqui

IPC: G06F15/173

CPC classification number: G06F9/5083 ,  G06F2209/5019 ,  G06F2209/508 ,  G06Q30/02

Abstract: Techniques are described for managing program execution capacity or other capacity of computing-related hardware resources used to execute software programs, such as for a group of computing nodes that is in use executing one or more programs for a user. Dynamic modifications to the program execution capacity of the group may include adding or removing computing nodes, such as in response to automated determinations that previously specified triggers are currently satisfied, and may be automatically governed at particular times based on automatically generated predictions of program execution capacity that will be used at those times by the group, such as to verify that requested dynamic execution capacity modifications at a time are within the predicted execution capacity values for that time. In some situations, the techniques are used in conjunction with a fee-based program execution service that executes multiple programs on behalf of multiple users of the service.

Abstract translation: 描述了用于管理程序执行能力或用于执行软件程序的计算相关硬件资源的其他容量的技术，例如对于正在使用的一组计算节点，用于为用户执行一个或多个程序。 对组的程序执行能力的动态修改可以包括添加或删除计算节点，例如响应于先前指定的触发器当前满足的自动确定，并且可以基于自动生成的程序执行能力的预测在特定时间自动地管理 这将被组合在这些时间使用，例如以验证一次所请求的动态执行能力修改是否处于该时间的预测执行能力值内。 在某些情况下，这些技术与代表服务的多个用户执行多个程序的费用程序执行服务结合使用。