CN109417564B - 协调器服务器及其方法与介质 - Google Patents

协调器服务器及其方法与介质 Download PDF

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CN109417564B
CN109417564B CN201780038698.8A CN201780038698A CN109417564B CN 109417564 B CN109417564 B CN 109417564B CN 201780038698 A CN201780038698 A CN 201780038698A CN 109417564 B CN109417564 B CN 109417564B
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coordinator server
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CN109417564A (zh
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S·M·巴勒
R·康纳
N·阿胡贾
M·甘谷利
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Intel Corp
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Intel Corp
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Abstract

用于基于资源利用阶段来指派工作负载的技术包括用于将一组工作负载指派给受管节点的协调器服务器。协调器服务器还用于从受管节点接收遥测数据，并根据遥测数据识别工作负载的历史资源利用阶段。此外，协调器服务器用于根据历史资源利用阶段并且当工作负载被执行时确定工作负载的预测的资源利用阶段，并根据预测的资源利用阶段当工作负载被执行时应用对受管节点之间的工作负载指派的调整。

Description

协调器服务器及其方法与介质
相关申请的交叉引用
本申请要求以下申请的优先权：2016年12月30日提交的题为“TECHNOLOGIES FORASSIGNING WORKLOADS BASED ON RESOURCE UTILIZATION PHASES”的美国专利申请序列号第15/395,273 号的优先权，该申请要求2016年7月22日提交的美国临时专利申请第 62/365,969号的优先权；2016年8月18日提交的美国临时专利申请第62/376,859号的优先权；以及2016年11月29日提交的美国临时专利申请第62/427,268号的优先权。
背景技术
在典型的基于云的计算环境中，服务器可以将工作负载指派给网络中的计算节点以代表客户端执行服务。操作云环境的实体感兴趣的是使每个计算节点中的资源利用最大化，以使云环境能够利用可用硬件提供最大的性能。然而，如果服务器指派严重依赖该资源的多个工作负载，则计算节点中可用的资源(例如，诸如处理器、存储器、通信电路等的组件)可能变得过载。结果，即使计算节点中的其他资源几乎空闲，计算节点的整体性能也可能受到不利影响。另一个挑战是工作负载可能不会始终具有相同的资源利用，而是可能会随着时间的推移而变化，大量使用一种资源，然后转换为大量使用其他资源。因此，管理员或者服务器可能难以确定始终提供高资源利用的计算节点之间的工作负载指派而不会使任何资源过载。
附图说明
这里描述的概念在附图中通过示例的方式示出，而不是作为限制。为了说明的简单和清楚，附图中示出的元件不一定按比例绘制。在认为合适的情况下，在附图中重复使用附图标记以指示相对应的或者类似的元件。
图1是根据各种实施例的其中可以实现这里描述的一种或者多种技术的数据中心的概念性概述的图；
图2是图1的数据中心的机架的逻辑配置的示例实施例的图；
图3是根据各种实施例的其中可以实现本文描述的一种或者多种技术的另一数据中心的示例实施例的图；
图4是根据各种实施例的其中可以实现这里描述的一种或者多种技术的数据中心的另一示例实施例的图；
图5是表示可以在图1、图3和图4的数据中心的各种板(sled)之间建立的链路层连接的连接方案的图；
图6是可以表示根据一些实施例的图1-图4中所描绘的机架中的任何特定一个机架的架构的机架架构的图；
图7是可以与图6的机架架构一起使用的板的示例实施例的图；
图8是用于针对具有扩展能力的板提供支撑的机架架构的示例实施例的图；
图9是根据图8的机架架构实现的机架的示例实施例的图；
图10是设计用于与图9的机架结合使用的板的示例实施例的图；
图11是根据各种实施例的其中可以实现这里描述的一种或者多种技术的数据中心的示例实施例的图；
图12是用于基于资源利用阶段在一组受管节点之间指派工作负载的系统的至少一个实施例的简化框图；
图13是图12的系统的协调器服务器的至少一个实施例的简化框图；
图14是可以由图12和图13的协调器服务器建立的环境的至少一个实施例的简化框图；以及
图15-图17是用于基于资源利用阶段在受管节点之间指派工作负载的可以由图12-图14的协调器服务器执行的方法的至少一个实施例的简化流程图；
图18是一时间段内工作负载的处理器利用的曲线图；以及
图19是图18的时间段内另一工作负载的处理器利用的曲线图。
具体实施方式
虽然本公开的概念易于进行各种修改和替换形式，但是其具体实施例已经通过附图中的示例示出并且将在本文中详细描述。然而，应该理解的是，并不意图将本公开的概念限制于所公开的特定形式，而是相反，意图是覆盖与本公开和所附权利要求一致的所有修改、等同物和替代方案。
说明书中对“一个实施例”、“实施例”、“说明性实施例”等的引用指示所描述的实施例可包括特定特征、结构或者特性，但是每个实施例可以或者可以不一定包括该特定特征、结构或者特性。而且，这些短语不一定指的是同一实施例。此外，当结合实施例描述特定特征、结构或者特性时，认为结合其他实施例实现这样的特征、结构或者特性在本领域技术人员的知识范围内，无论是否明确描述。另外，应当意识到，以“至少一个A、B 和C”的形式包括在列表中的项目可以表示(A)；(B)；(C)；(A和B)； (A和C)；(B和C)；或者(A、B和C)。类似地，以“A、B或者C中的至少一个”形式列出的项目可以表示(A)；(B)；(C)；(A和B)；(A 和C)；(B和C)；或者(A、B和C)。
在一些情况下，所公开的实施例可以以硬件、固件、软件或者其任何组合来实现。所公开的实施例还可以实现为由暂时或者非暂时性机器可读 (例如，计算机可读)存储介质承载或者存储的指令，所述指令可以由一个或多个处理器读取和执行。机器可读存储介质可以体现为用于以机器可读形式存储或者传输信息的任何存储设备、机制或者其他物理结构(例如，易失性或者非易失性存储器、介质盘或者其他介质设备)。
在附图中，可以以特定布置和/或者顺序示出一些结构或者方法特征。然而，应该意识到，可能不需要这样的特定布置和/或者排序。而是，在一些实施例中，这些特征可以以不同于说明性附图中所示的方式和/或者顺序来布置。另外，在特定图中包含结构或者方法特征并不意味着暗示在所有实施例中都需要这样的特征，并且在一些实施例中，可以不包括这些特征或者可以与其他特征组合。
图1示出了数据中心100的概念性概述，该数据中心100通常可以代表数据中心或者其他类型的计算网络，其中可以根据各种实施例实现本文描述的一种或者多种技术。如图1所示，数据中心100通常可以包含多个机架，每个机架可以容纳包括相应一组物理资源的计算设备。在图1中描绘的特定非限制性示例中，数据中心100包含四个机架102A至102D，其容纳计算设备，该计算设备包括相应的一组物理资源(PCR)105A至105D。根据该示例，数据中心100的共同的一组物理资源106包括分布在机架102A 至102D之间的各组物理资源105A至105D。物理资源106可以包括多种类型的资源，例如，处理器、协处理器、加速器、现场可编程门阵列(FPGA)、存储器和存储装置。实施例不限于这些示例。
说明性数据中心100在许多方面不同于典型的数据中心。例如，在说明性实施例中，其上放置诸如CPU、存储器和其他部件之类的部件的电路板子(“板”)被设计用于提高热性能。特别地，在说明性实施例中，板(sled) 比典型的板子(board)浅。换句话说，板从前到后较短，冷却风扇位于其中。这减少了空气必须穿过板上组件的路径的长度。此外，板上的组件与典型的电路板相比间隔得更远，并且这些组件被设置成减少或者消除阴影(即，一个组件在另一组件的空气流动路径中)。在说明性实施例中，诸如处理器之类的处理组件位于板的顶侧，而诸如DIMM之类的附近存储器位于板的底侧。由于该设计提供的增强的气流，组件可以以比典型系统更高的频率和功率水平来操作，从而提高性能。此外，板被配置为与每个机架 102A、102B、102C、102D中的电源和数据通信电缆盲匹配，增强了它们被快速移除、升级、重新安装和/或者更换的能力。类似地，位于板上的各个组件(例如处理器、加速器、存储器和数据存储驱动器)被配置为由于它们彼此间隔增加而容易升级。在说明性实施例中，组件还包括硬件证明特征以证明其真实性。
此外，在说明性实施例中，数据中心100利用支持包括以太网和 Omni-Path在内的多个其他网络架构的单个网络架构(“结构”)。在说明性实施例中，板经由光纤耦合到交换机，光纤提供比典型的双绞线布线(例如，类别5、类别5e、类别6等)更高的带宽和更低的延迟。由于高带宽、低延迟互连和网络架构，数据中心100可以在使用中使物理地分解的资源池化，所述资源例如存储器、加速器(例如，图形加速器、FPGA、ASIC 等)以及数据存储驱动器，并根据需要将它们提供给计算资源(例如，处理器)，使计算资源能够访问池化资源，就好像它们是本地的一样。说明性数据中心100另外接收针对各种资源的利用信息，基于过去的资源利用来预测不同类型的工作负载的资源利用，并基于该信息动态地重新分配资源。
数据中心100的机架102A、102B、102C、102D可以包括便于各种类型的维护任务的自动化的物理设计特征。例如，数据中心100可以使用设计为机器人访问，并且接受和容纳可机器人操纵的资源板的机架来实现。此外，在说明性实施例中，机架102A、102B、102C、102D包括集成电源，所述集成电源接收比针对电源的典型电压更大的电压。增加的电压使电源能够向每个板上的组件提供额外的电力，使组件能够以高于典型频率的频率运行。
图2示出了数据中心100的机架202的示例性逻辑配置。如图2所示，机架202通常可以容纳多个板，每个板可以包括相应的一组物理资源。在图2中描绘的特定非限制性示例中，机架202容纳包括相应的一组物理资源205-1至205-4的板204-1至204-4，每组物理资源构成包括在机架202 中的集合的一组物理资源206的一部分。关于图1，如果机架202代表例如机架102A，则物理资源206可以对应于机架102A中包括的物理资源105A。在该示例的上下文中，物理资源105A因此可以由相应的一组物理资源组成，所述物理资源包括包含在机架202的板204-1至204-4中的物理存储资源 205-1、物理加速器资源205-2、物理存储器资源204-3和物理计算资源205-5。实施例不限于该示例。每个板可以包含各种类型的物理资源(例如，计算、存储器、加速器、存储装置)中的每一个的池。通过具有包括分解的资源的机器人可访问和机器人可操纵的板，每种类型的资源能够彼此独立地并且以其自己的优化刷新率升级。
图3示出了数据中心300的示例，该数据中心300通常可以表示可以根据各种实施例实现本文描述的一种或者多种技术的数据中心。在图3中描绘的特定非限制性示例中，数据中心300包括机架302-1至302-32。在各种实施例中，数据中心300的机架可以以限定和/或者容纳各种访问路径的方式布置。例如，如图3所示，数据中心300的机架可以以限定和/或者容纳访问路径311A、311B、311C和311D的方式布置。在一些实施例中，这种访问路径的存在通常使得自动维护设备(例如机器人维护设备)能够物理地访问容纳在数据中心300的各种机架中的计算设备并执行自动维护任务(例如，替换故障的板、升级板)。在各种实施例中，可以选择访问路径311A、311B、311C和311D的尺寸、机架302-1至302-32的尺寸和/或者数据中心300的物理布局的一个或多个其他方面以促进这种自动化操作。实施例不限于此上下文。
图4示出了数据中心400的示例，该数据中心400通常可以代表可以根据各种实施例实现本文描述的一种或者多种技术的数据中心。如图4所示，数据中心400可以以光学结构412为特征。光学结构412通常可以包括光信令介质(例如光学电缆)和光学交换基础设施的组合，数据中心400 中的任何特定板可以经由它们向数据中心400中的每个其他板发送信号(并且从其接收)。光学结构412提供给任何给定板的信令连接可以包括到同一机架中的其他板和其他机架中的板的连接。在图4中描绘的特定非限制性示例中，数据中心400包括四个机架402A至402D。机架402A至402D容纳相应的一对板404A-1和404A-2、404B-1和404B-2、440C-1和404C-2 以及404D-1和404D-2。因此，在该示例中，数据中心400包括总共八个板。经由光学结构412，每个这样的板可以具有与数据中心400中的七个其他板中的每一个的信令连接。例如，经由光学结构412，机架402A中的板404A-1 可以具有与机架402A中的板404A-2，以及分布在数据中心400的其他机架402B、402C和402D之间的六个其他板404B-1、404B-2、440C-1、440C-2、 440D-1和404D-2的信令连接。实施例不限于该示例。
图5示出了连接方案500的概述，该连接方案500通常可以表示在一些实施例中可以在数据中心的各种板(例如，图1、图3和图4的示例数据中心100、300和400中的任何一个)之间建立的链路层连接。可以使用以双模光交换基础设施514为特征的光学结构来实现连接方案500。双模光交换基础设施514通常可以包括能够经由相同的统一的一组光信令介质根据多个链路层协议接收通信，并适当地切换这种通信的交换基础设施。在各种实施例中，可以使用一个或多个双模光交换机515来实现双模光交换基础设施514。在各种实施例中，双模光交换机515通常可以包括高基数交换机。在一些实施例中，双模光交换机515可以包括多层交换机，例如四层交换机。在各种实施例中，双模光交换机515可以以集成硅光子为特征，与传统交换机设备相比，硅光子使双模光交换机能够以显著减少的延迟切换通信。在一些实施例中，双模光交换机515可以构成叶脊架构中的叶片交换机530，叶脊架构另外包括一个或多个双模光脊交换机520。
在各种实施例中，双模光交换机能够经由光学结构的光信令介质接收承载因特网协议(IP分组)的以太网协议通信和根据第二高性能计算(HPC) 链路层协议(例如，英特尔的Omni-Path架构的，Infiniband)的通信。如图5所反映的，对于具有到光学结构的光信令连接的任何特定的一对板 504A和504B，连接方案500因此可以经由以太网链路和HPC链路提供对链路层连接的支持。因此，单个高带宽、低延迟交换结构可以支持以太网和HPC通信。实施例不限于该示例。
图6示出了机架架构600的总体概述，该机架架构600可以代表根据一些实施例的图1至图4中所描绘的机架中的任何特定一个的架构。如图6 所反应的，机架架构600通常可以以多个板空间为特征，板可以插入其中，每个板空间可以经由机架访问区域601进行机器人可访问。在图6所描绘的特定非限制性示例中，机架架构600以五个板空间603-1至603-5为特征。板空间603-1至603-5以相应的多功能连接器模块(MPCM)616-1至616-5 为特征。
图7示出了可以代表这种类型的板的板704的示例。如图7所示，板 704可以包括一组物理资源705，以及MPCM 716，其被设计成当板704插入板空间(例如图6中的板空间603-1至603-5中的任何)时与配对MPCM 耦合。板704还可以以扩展连接器717为特征。扩展连接器717通常可以包括插座、插槽或者其他类型的连接元件，其能够接受一种或者多种类型的扩展模块，例如扩展板718。通过与扩展板718上的配对连接器耦合，扩展连接器717可以为物理资源705提供对驻留在扩展板718上的补充计算资源705B的访问。实施例不限于此上下文。
图8示出了可以表示如下的机架架构的机架架构800的示例，该机架架构可以被实现以便为以扩展能力为特征的板(例如，图7的板704)提供支持。在图8中描绘的特定非限制性示例中，机架架构800包括七个板空间803-1至803-7，其以相应的MPCM 816-1至816-7为特征。板空间803-1 至803-7包括相应的主区域803-1A至803-7A和相应的扩展区域803-1B至 803-7B。关于每个这样的板空间，当相对应的MPCM与插入的板的配对 MPCM耦合时，主区域通常可以构成物理地容纳插入的板的板空间的区域。在插入的板配置有这种模块的情况下，扩展区域通常可以构成可以物理地容纳扩展模块的板空间的区域，例如图7的扩展板718。
图9示出了机架902的示例，其可以代表根据一些实施例的根据图8 的机架架构800实现的机架。在图9中描绘的特定非限制性示例中，机架 902以七个板空间903-1至903-7为特征，其包括相应的主区域903-1A至 903-7A和相应的扩展区域903-1B至903-7B。在各种实施例中，可以使用空气冷却系统来实现机架902中的温度控制。例如，如图9中所反映的那样，机架902可以以多个风扇919为特征，风扇919通常被布置为在各种板空间903-1至903-7内提供空气冷却。在一些实施例中，板空间的高度大于传统的“1U”服务器高度。在这样的实施例中，与传统机架配置中使用的风扇相比，风扇919通常可包括相对慢的大直径冷却风扇。相对于以较高速度运行的较小直径的冷却风扇而言，以较低速度运行的较大直径的冷却风扇可以延长风扇寿命，同时仍能提供相同的冷却量。板比传统的机架尺寸物理上更浅。此外，每个板上都布置了组件以减少热阴影(即，没有沿气流方向串联布置)。因此，更宽、更浅的板允许设备性能的提高，因为由于改进的冷却，设备可以在更高的热封套(例如，250W)下操作(即，没有热阴影，设备之间的空间更大，更大的散热器空间等)。
MPCM 916-1至916-7可以被配置为向插入的板提供对源自相应的电源模块920-1至920-7的电源的访问，每个电源模块可以从外部电源921汲取电力。在一些实施例中，外部电源921可以向机架902输送交流(AC)电力，并且电力模块920-1至920-7可以被配置为将这种AC电力转换为直流 (DC)电力以供源于插入的板。在一些实施例中，例如，功率模块920-1至920-7可以被配置为将277伏AC电力转换为12伏DC电力，以经由相应的MPCM 916-1至916-7提供给插入的板。实施例不限于该示例。
MPCM 916-1至916-7还可以被布置为向插入的板提供到双模光交换基础设施914的光信令连接，双模光交换基础设施914可以与图5的双模光交换基础设施514相同或者相似。在各种实施例中，包含在MPCM 916-1 至916-7中的光学连接器可以被设计成与插入的板的MPCM中包含的配对光学连接器耦合，以向这种板提供经由各长度的光缆922-1至922-7与双模光学交换基础设施914的光信令连接。在一些实施例中，每个这样长度的光缆可以从其对应的MPCM延伸到在机架902的板空间外部的光学互连织机923。在各种实施例中，光学互连织机923可以布置成穿过支撑柱或者支架902的其他类型的承载元件。实施例不限于此上下文。由于插入的板经由MPCM连接到光交换基础设施，因此可以节省通常耗费于手动配置机架布线以容纳新插入的板的资源。
图10示出了板1004的示例，其可以代表根据一些实施例的设计用于与图9的机架902结合使用的板。板1004可以以MPCM 1016为特征，MPCM 1016包括光学连接器1016A和电源连接器1016B，并且被设计成与将 MPCM 1016插入到板空间中相结合而与板空间的配对MPCM耦合。将 MPCM 1016与这样的配对MPCM耦合可以使电源连接器1016与配对 MPCM中包括的电源连接器耦合。这通常使得板1004的物理资源1005能够经由电源连接器1016和电力传输介质1024从外部源获取电力，电力传输介质1024将电力连接器1016导电地耦合到物理资源1005。
板1004还可以包括双模光网络接口电路1026。双模光网络接口电路 1026通常可以包括能够根据图9的双模光学交换基础设施914支持的多个链路层协议中的每一个通过光信令介质进行通信的电路。在一些实施例中，双模光网络接口电路1026能够进行以太网协议通信和根据第二高性能协议的通信。在各种实施例中，双模光网络接口电路1026可以包括一个或多个光收发器模块1027，每个光收发器模块1027能够在一个或多个光信道中的每一个上发送和接收光信号。实施例不限于此上下文。
将MPCM 1016与给定机架中的板空间的配对MPCM耦合可以使光学连接器1016A与配对MPCM中包括的光学连接器耦合。这通常可以经由一组光学信道1025中的每一个在板的光缆与双模光网络接口电路1026之间建立光学连接。双模光网络接口电路1026可以经由电信令介质1028与板 1004的物理资源1005进行通信。除了板的尺寸和板上的用于提供改进的冷却并且能够在相对较高的热封套(例如，250W)下操作的组件的布置之外，如上面参考图9所述，在一些实施例中，板还可包括一个或多个附加特征以便于空气冷却，例如布置成耗散由物理资源1005生成的热量的热管和/ 或者散热器。值得注意的是，尽管图10中所描绘的示例性板1004没有以扩展连接器为特征，但是根据一些实施例以板1004的设计元件为特征的任何给定板也可以以扩展连接器为特征。实施例不限于此上下文。
图11示出了数据中心1100的示例，该数据中心1100通常可以表示可以根据各种实施例的实现本文描述的一种或者多种技术的数据中心。如图 11所反映的，可以实现物理基础设施管理框架1150A以便于管理数据中心 1100的物理基础设施1100A。在各种实施例中，物理基础设施管理框架 1150A的一个功能可以是管理数据中心1100内的自动维护功能，例如使用机器人维护设备来为物理基础设施1100A内的计算设备提供服务。在一些实施例中，物理基础设施1100A可以以先进的遥测系统为特征，该遥测系统执行遥测报告，该遥测报告足够鲁棒以支持物理基础设施1100A的远程自动化管理。在各种实施例中，由这种先进的遥测系统提供的遥测信息可以支持诸如故障预测/预防能力和容量规划能力之类的特征。在一些实施例中，物理基础设施管理框架1150A还可以被配置为使用硬件证明技术来管理物理基础设施组件的认证。例如，机器人可以在安装之前通过分析从与要安装的每个组件相关联的射频识别(RFID)标签收集的信息来验证组件的真实性。实施例不限于此上下文。
如图11所示，数据中心1100的物理基础设施1100A可以包括光学结构1112，其可以包括双模光交换基础设施1114。光学结构1112和双模光交换基础设施1114可以分别与图4的光学结构412和图5的双模光交换基础设施514相同或者相似，并且可以在数据中心1100的板之间提供高带宽、低延迟、多协议连接。如上所述，参考图1，在各种实施例中，这种连接的可用性可以使得对诸如加速器、存储器和存储装置之类的资源分解和动态地池化成为可能。在一些实施例中，例如，一个或多个池化的加速器板1130 可以包括在数据中心1100的物理基础设施1100A中，每个物理基础设施 1100A可以包括加速器资源的池，所述加速器资源诸如例如协处理器和/或者FPGA，它们经由光学结构1112和双模光交换基础设施1114可以用于对其他板的全局访问。
在另一个示例中，在各种实施例中，一个或多个池化的存储板1132可以包括在数据中心1100的物理基础设施1100A中，每个物理基础设施 1100A可以包括可经由光学结构1112和双模光学交换基础设施1114对其他板进行全局访问的存储资源的池。在一些实施例中，这种池化的存储板1132 可以包括固态存储设备(例如，固态驱动器(SSD))的池。在各种实施例中，一个或多个高性能处理板1134可以包括在数据中心1100的物理基础设施110A中。在一些实施例中，高性能处理板1134可以包括高性能处理器以及增强空气冷却从而产生高达250W或者更高的热封套的冷却特征的池。在各种实施例中，任何给定的高性能处理板1134可以以扩展连接器1117 为特征，该扩展连接器1117可以接受远存储器扩展板，使得该高性能处理板1134本地可用的远存储器从处理器和包含在板上的附近存储器分解。在一些实施例中，这样的高性能处理板1134可以使用包括低延迟SSD存储的扩展板而被配置有远存储器。光学基础设施允许一个板上的计算资源利用远程加速器/FPGA、存储器和/或者SSD资源，这些资源在位于同一机架或者数据中心任何其他机架上的板上分解。远程资源可以位于上面参考图5 描述的脊-叶网络架构中的一个交换机跳跃或者两个交换机跳跃上。实施例不限于此上下文。
在各种实施例中，可以将一个或多个抽象层应用于物理基础设施1100A 的物理资源，以便定义虚拟基础设施，例如软件定义的基础设施1100B。在一些实施例中，可以分配软件定义的基础设施1100B的虚拟计算资源1136 以支持对云服务1140的供应。在各种实施例中，可以将特定的一组虚拟计算资源1136分组以便以SDI服务1138的形式供应给云服务1140。云服务 1140的示例可以包括但不限于软件即服务(SaaS)服务1142、平台即服务(PaaS)服务1144以及基础设施即服务(IaaS)服务1146。
在一些实施例中，可以使用虚拟基础设施管理框架1150B来进行软件定义的基础设施1100B的管理。在各种实施例中，虚拟基础设施管理框架 1150B可以被设计为结合管理虚拟计算资源1136和/或者SDI服务1138向云服务1140的指派来实现工作负载指纹技术和/或者机器学习技术。在一些实施例中，虚拟基础设施管理框架1150B可以结合执行这样的资源指派来使用/咨询遥测数据。在各种实施例中，可以实现应用/服务管理框架1150C 以便针对云服务1140提供QoS管理能力。实施例不限于此上下文。
如图12所示，用于利用遥测数据的在线分析执行协调的说明性系统 1210包括与一组受管节点1260通信的协调器服务器1240。每个受管节点 1260可以体现为资源(例如，物理资源206)组件，诸如计算资源(例如，物理计算资源205-4)、存储资源(例如，物理存储资源205-1)、加速器资源(例如，物理加速器资源205-2)或者来自相同或者不同的板(例如，板 204-1、204-2、204-3、204-4等)或者机架(例如，机架302-1至302-32中的一个或多个)的其他资源(例如，物理存储器资源205-3)。每个受管节点1260可以在将工作负载指派给受管节点1260时或者在任何其他时间由协调器服务器1240建立、定义或者“旋转”，并且可以存在，而不管当前是否有任何工作负载指派给受管节点1260。系统1210可以根据上面参考图1、图3、图4和图11所描述的数据中心100、300、400、1100来实现。在说明性实施例中，受管节点1260的集合包括受管节点1250、1252和1254。虽然在集合中示出了三个受管节点1260，但是应当理解，在其他实施例中，该集合可以包括不同数量的受管节点1260(例如，数十万个)。系统1210 可以位于数据中心中并且向通过网络1230与系统1210通信的客户端设备1220提供存储服务和计算服务(例如，云服务)。协调器服务器1240可以支持诸如OpenStack之类的云操作环境，并且受管节点1250可以代表用户端设备1220来执行一个或多个应用或者进程(即，工作负载)，例如在虚拟机或者容器中。如本文中更详细讨论的，操作中的协调器服务器1240被配置为将工作负载指派给受管节点1260并接收遥测数据，其可以体现为指示在受管节点1260执行指派给它们的工作负载时每个受管节点1260的性能和条件的数据，从遥测数据中识别资源利用阶段，所述资源利用阶段指示特定类型的组件(例如，处理器、存储器、通信电路等)的利用超过阈值量一时间段，在此称为阶段驻留。
基于检测工作负载的资源利用阶段中的模式，协调器服务器1240还被配置为预测每个工作负载的未来资源利用阶段并调整受管节点1260之间的工作负载的指派。在调整指派时，协调器服务器1240可以执行从一个受管节点1260到另一个受管节点1260的工作负载的实时迁移和/或者临时延迟工作负载中的一个或多个的执行，以引起互补的工作负载阶段(例如，高处理器利用阶段和低处理器利用阶段，高存储器利用阶段和低存储器利用阶段等)在受管节点1260内同时发生。因此，通过在受管节点1260之间指派工作负载以匹配补充资源利用阶段，协调器服务器1240在减少使资源过载的风险时在受管节点1260中更高效地使用可用硬件资源。
现在参考图13，协调器服务器1240可以体现为能够执行本文描述的功能的任何类型的计算设备，包括发出用于执行云服务的请求，接收云服务的结果，将工作负载指派给计算设备，分析指示工作负载被执行时的性能和条件(例如，资源利用、一个或多个温度、风扇速度等)的遥测数据，识别历史资源利用阶段，预测未来资源利用阶段以及调整工作负载的指派以当工作负载被执行时提高资源利用。例如，协调器服务器1240可以体现为计算机、分布式计算系统、一个或多个板(例如，板204-1、204-2、204-3、 204-4等)、服务器(例如，独立式、机架安装式、刀片式等)、多处理器系统、网络设备(例如，物理或者虚拟)、台式计算机、工作站、膝上型计算机、笔记本计算机、基于处理器的系统或者网络设备。如图13所示，说明性协调器服务器1240包括中央处理单元(CPU)1302、主存储器1304、输入/输出(I/O)子系统1306、通信电路1308以及一个或多个数据存储设备 1312。当然，在其他实施例中，协调器服务器1240可以包括其他或者附加组件，例如通常在计算机中找到的组件(例如，显示器、外围设备等)。另外，在一些实施例中，说明性组件中的一个或多个可以并入另一组件中，或者以其他方式形成另一组件的一部分。例如，在一些实施例中，主存储器1304或者其部分可以并入在CPU 1302中。
CPU 1302可以体现为能够执行本文描述的功能的任何类型的处理器。 CPU 1302可以体现为单核或者多核处理器、微控制器或者其他处理器或者处理/控制电路。在一些实施例中，CPU 1302可以体现为、包括或者耦合到现场可编程门阵列(FPGA)、专用集成电路(ASIC)、可重新配置的硬件或者硬件电路或者促进本文描述的功能的执行的其他专用硬件。如上所述，受管节点1260可以包括跨多个板分布的资源，并且在这样的实施例中，CPU1302可以包括位于同一板或者不同板上的其部分。类似地，主存储器1304 可以体现为能够执行本文描述的功能的任何类型的易失性(例如，动态随机存取存储器(DRAM)等)或者非易失性存储器或者数据存储装置。在一些实施例中，主存储器1304的全部或者一部分可以集成到CPU 1302中。在操作中，主存储器1304可以存储在操作期间使用的各种软件和数据，诸如遥测数据、策略数据、工作负载标签、工作负载分类、资源利用阶段数据、工作负载调整数据、操作系统、应用、程序、库和驱动程序。如上所述，受管节点1260可以包括跨多个板分布的资源，并且在这样的实施例中，主存储器1304可以包括位于相同板或者不同板上的其部分。
I/O子系统1306可以体现为电路和/或者组件，以便于与CPU 1302、主存储器1304和协调器服务器1240的其他组件的输入/输出操作。例如，I/O 子系统1306可以体现为或者以其他方式包括存储器控制器集线器、输入/ 输出控制集线器、集成传感器集线器、固件设备、通信链路(例如，点对点链路、总线链路、电线、电缆、光导、印刷电路板迹线等)，和/或者促进输入/输出操作的其他组件和子系统。在一些实施例中，I/O子系统1306可以形成片上系统(SoC)的一部分，并且与CPU 1302、主存储器1304和协调器服务器1240的其他组件中的一个或多个一起并入在单个集成电路芯片上。
通信电路1308可以体现为能够通过网络1230在协调器服务器1240与另一计算设备(例如，客户端设备1220和/或者受管节点1260)之间进行通信的任何通信电路、设备或者其集合。通信电路1308可以被配置为使用任何一种或者多种通信技术(例如，有线或者无线通信)和相关联的协议 (例如，以太网、
Figure BDA0001914975910000141
WiMAX等)来实现这种通信。
说明性通信电路1308包括网络接口控制器(NIC)1310，其也可以称为主机结构接口(HFI)。NIC 1310可以体现为一个或多个插件板、子卡、网络接口卡、控制器芯片、芯片组或者可以由协调器服务器1240用来与另一计算设备(例如，客户端设备1220和/或者受管节点1260)连接的其他设备。在一些实施例中，NIC 1310可以体现为包括一个或多个处理器的片上系统(SoC)的一部分，或者包括在也包含一个或多个处理器的多芯片封装上。在一些实施例中，NIC 1310可以包括都在NIC 1310的本地的本地处理器(未示出)和/或者本地存储器(未示出)。在这样的实施例中，NIC 1310 的本地处理器可能能够执行本文描述的CPU1302的功能中的一个或多个。附加地或者可替代地，在这样的实施例中，NIC 1310的本地存储器可以在板级、插槽级、芯片级和/或者其他级别集成到协调器服务器1240的一个或多个组件中。如上所述，受管节点1260可以包括跨多个板分布的资源，并且在这样的实施例中，通信电路1308可以包括位于同一板或者不同板上的其部分。
一个或多个说明性数据存储设备1312可以体现为被配置用于数据的短期或者长期存储的任何类型的设备，例如存储器设备和电路、存储卡、硬盘驱动器、固态驱动器或者其他数据存储设备。每个数据存储设备1312可以包括存储用于数据存储设备1312的数据和固件代码的系统分区。每个数据存储设备1312还可以包括存储用于操作系统的数据文件和可执行文件的操作系统分区。
另外，协调器服务器1240可以包括显示器1314。显示器1314可以体现为或者以其他方式使用任何合适的显示技术，包括例如液晶显示器 (LCD)、发光二极管(LED)显示器、阴极射线管(CRT)显示器、等离子显示器和/或者可用于计算设备的其他显示器。显示器1314可以包括触摸屏传感器，其使用任何合适的触摸屏输入技术来检测对显示器上显示的信息的用户触觉选择，包括但不限于电阻式触摸屏传感器、电容式触摸屏传感器、表面声波(SAW)触摸屏传感器、红外触摸屏传感器、光学成像触摸屏传感器、声学触摸屏传感器和/或者其他类型的触摸屏传感器。
附加地或者替代地，协调器服务器1240可以包括一个或多个外围设备 1316。这样的外围设备1316可以包括通常在计算设备中找到的任何类型的外围设备，诸如扬声器、鼠标、键盘和/或者其他输入/输出设备、接口设备和/或者其他外围设备。
客户端设备1220和受管节点1260可以具有与图13中描述的组件类似的组件。协调器服务器1240的那些组件的描述同样适用于客户端设备1220 和受管节点1260的组件的描述，并且为了描述的清楚，本文不再重复。此外，应当意识到，客户端设备1220和受管节点1260中的任何一个可以包括通常在计算设备中找到的其他组件、子组件和设备，这些组件、子组件和设备在上面未参考协调器服务器1240讨论，并且为了描述的清楚起见，不在此讨论。
如上所述，客户端设备1220、协调器服务器1240和受管节点1260说明性地经由网络1230进行通信，网络1230可以体现为任何类型的有线或者无线通信网络，包括全球网络(例如，互联网)、局域网(LAN)或者广域网(WAN)、蜂窝网络(例如，全球移动通信系统(GSM)、3G、长期演进(LTE)、全球微波接入互操作性(WiMAX)等)、数字用户线(DSL) 网络、有线网络(例如，同轴网络、光纤网络等)或者其任何组合。
现在参考图14，在说明性实施例中，协调器服务器1240可以在操作期间建立环境1400。说明性环境1400包括网络通信器1420、遥测监视器1430、策略管理器1440和资源管理器1450。环境1400的每个组件可以体现为硬件、固件、软件或者其组合。这样，在一些实施例中，环境1400的组件中的一个或多个可以体现为电路或者电子设备的集合(例如，网络通信器电路1420、遥测监视器电路1430、策略管理器电路1440、资源管理器电路 1450等)。应当意识到，在这样的实施例中，网络通信器电路1420、遥测监视器电路1430、策略管理器电路1440或者资源管理器电路1450中的一个或多个可以形成CPU 1302、主存储器1304、I/O子系统1306和/或者协调器服务器1240的其他组件中的一个或多个的一部分。在说明性实施例中，环境1400包括遥测数据1402，其可以体现为指示当受管节点1260执行指派给它们的工作负载时每个受管节点1260的性能和条件(例如，资源利用、一个或多个温度、风扇速度等)的数据。另外，说明性环境1400包括指示关于受管节点1260的组件的热量产生、功耗和预期寿命的用户定义的偏好的策略数据1404。此外，说明性环境1400包括工作负载标签1406，其可以体现为唯一标识由受管节点1260执行的每个工作负载的任何标识符(例如，进程号、可执行文件名、字母数字标签等)。此外，说明性环境1400 包括可以体现为指示每个工作负载的一般资源利用趋势(例如，处理器密集、存储器密集、网络带宽密集等)的任何数据的工作负载分类1408。虽然工作负载分类1408提供关于受管节点1260中的各种类型资源的一般(例如，平均)利用的信息，但是说明性实施例1400还包括阶段数据1410，其可以体现为指示对于每个工作负载，资源利用阶段(即，特定类型的受管节点资源的利用时间段高于阈值量)和那些阶段的时间长度(即，阶段驻留)的任何数据。此外，说明性环境1400包括工作负载调整数据1412，其可以体现为指示从一个受管节点1260到另一个受管节点1260的一个或多个工作负载的重新指派(例如，实时迁移)、对一个或多个工作负载的执行的开始或者恢复的时间偏移(例如，用于对齐受管节点1260内的补充资源利用阶段)，和/或者对每个受管节点1260内的组件的设置的调整的任何数据，诸如一个或多个工作负载可用的处理器容量(例如，要使用的核的数量、时钟速度、可用处理器周期的百分比等)、一个或多个工作负载可用的存储器资源容量(例如，要使用的存储器的量和/或者对易失性存储器和/ 或者非易失性存储器的存储器存取的频率)，和/或者一个或多个工作负载可用的通信电路容量(例如，网络带宽)。
在说明性环境1400中，网络通信器1420(其可以体现为如上所述的硬件、固件、软件、虚拟化硬件、仿真架构和/或者其组合)被配置为促进分别去往协调器服务器1240和来自协调器服务器1240的入站和出站网络通信(例如，网络业务、网络分组、网络流等)。为此，网络通信器1420被配置为从一个系统或者计算设备(例如，客户端设备1220)接收和处理数据分组，并准备数据分组并将其发送到另一个计算设备或者系统(例如，受管节点1260)。因此，在一些实施例中，网络通信器1420的功能的至少一部分可以由通信电路1308执行，并且在说明性实施例中，由NIC 1310 执行。
遥测监视器1430(其可以体现为如上所述的硬件、固件、软件、虚拟化硬件、仿真架构和/或者其组合)被配置为在受管节点1260执行指派给它们的工作负载时从受管节点1260收集遥测数据1402。遥测监视器1430可以针对更新的遥测数据1402持续地主动轮询每个受管节点1260，或者可以被动地从受管节点1260接收遥测数据1402，例如通过针对更新的遥测数据 1402在特定网络端口上侦听。遥测监视器1430可以进一步对遥测数据1402 进行解析和分类，例如通过将遥测数据1402分离成用于每个受管节点1260 的单个文件或者数据集。策略管理器1440(其体现为硬件、固件、软件、虚拟化硬件、仿真架构和/或者其组合，如上所述)可以被配置为接收和存储策略数据1404，如上所述，策略数据1404指示关于受管节点1260的组件的热量产生、功耗和预期寿命(即，磨损)的用户定义的偏好。策略管理器1440还被配置为将策略数据1404提供给资源管理器1450以协助确定对受管节点1260当中的工作负载指派的调整，并用于调整一个或多个受管节点内的设置(例如，一个或多个工作负载可用的处理器容量、一个或多个工作负载可用的存储器资源容量和/或者可用于一个或多个工作负载的通信电路容量)以优化资源利用，这受限于策略数据1404中定义的策略。
资源管理器1450(可以体现为硬件、固件、软件、虚拟化硬件、仿真架构和/或者其组合)被配置为从遥测数据1402生成数据分析、识别工作负载、对工作负载进行分类、识别工作负载的资源利用趋势、预测工作负载的未来资源利用，并调整工作负载到受管节点1260的指派和受管节点1260 的设置，以在保持符合策略数据1404的同时增加资源利用(例如，减少空闲资源量)而不使该资源过载。为此，资源管理器1450包括工作负载标记器1452、工作负载分类器1454、工作负载行为预测器1458、工作负载放置器1462和节点设置调整器1464。在说明性实施例中，工作负载标记器1452 被配置为将工作负载标签1406指派给当前执行或者安排由受管节点1260 中的一个或多个执行的每个工作负载。工作负载标记器1452可以根据工作负载的可执行名称、工作负载的全部或者部分代码的散列或者基于用于唯一标识每个工作负载的任何其他方法来生成工作负载标签。在说明性实施例中，工作负载分类器1454被配置为基于每个工作负载的资源利用使用来对每个标记的工作负载进行分类。例如，工作负载分类器1454可以将一组标记的工作负载分类为一致的处理器密集型，将另一组标记的工作负载分类为一致的存储器密集型，而将另一组工作负载分类为具有不同资源利用的阶段(高存储器存使用和低处理器使用，其次是高处理器使用和低存储器使用等)。在说明性实施例中，工作负载分类器1454包括阶段确定器1456，其可以生成指示工作负载的资源利用阶段和相对应的阶段驻留的阶段数据 1410。
在说明性实施例中，工作负载行为预测器1458被配置为分析遥测数据 1402、工作负载分类1408以及阶段数据1410，以基于其先前的使用来预测各种工作负载的未来资源利用需求。在说明性实施例中，工作负载行为预测器1458包括阶段预测器1460，其可被配置为从阶段数据1410识别在工作负载的资源利用阶段中的模式(例如，循环、资源利用阶段的序列、在工作负载的给定资源利用阶段之后倾向于发生的一个或多个资源利用阶段等)，确定给定工作负载的当前资源利用阶段，基于模式预测下一资源利用阶段，并(例如，基于阶段驻留)确定直到工作负载转换到预测的资源利用阶段的剩余时间量。在说明性实施例中，工作负载放置器1462被配置为最初将工作负载指派给各个受管节点1260，并且基于遥测数据1402、工作负载分类1408、阶段数据1410和策略数据1404确定是否可以通过在受管节点1260之间重新指派工作负载和/或者抵消工作负载的执行时间来对齐补充资源利用阶段，而不违反策略数据中的策略的情况下(例如，不生成超过阈值量的热量，不消耗超过功率的阈值量等)，从而更高效地使用受管节点1260的资源(例如，减少空闲资源量并减少过度使用的资源上的负载)。类似地，在说明性实施例中，节点设置调整器1464被配置为确定对受管节点1262内的设置的一个或多个调整，以根据优化资源使用和维护符合策略数据1404中的策略的目标来提供或者限制工作负载可用的资源。设置可以与操作系统和/或者受管节点1260的组件的固件或者驱动程序相关联。
应当意识到，工作负载标记器1452、工作负载分类器1454、阶段确定器1456、工作负载行为预测器1458、阶段预测器1460、工作负载放置器 1462和节点设置调整器1464中的每一个可以单独地体现为硬件、固件、软件、虚拟化硬件、仿真架构和/或者其组合。例如，工作负载标记器1452 可以体现为硬件组件，而工作负载分类器1454、阶段确定器1456、工作负载行为预测器1458、阶段预测器1460、工作负载放置器1462和节点设置调整器1464体现为虚拟化硬件组件或者硬件、固件、软件、虚拟化硬件、仿真架构和/或者其组合的其他组合。
现在参考图15，在使用中，协调器服务器1240可以执行用于基于资源利用阶段在受管节点1260之间指派工作负载的方法1500。方法1500开始于框1502，其中协调器服务器1240确定是否基于资源利用阶段来管理工作负载。在说明性实施例中，如果协调器服务器1240通电，与受管节点1260 通信，并且已经从客户端设备1220接收至少一个请求以提供云服务(即，执行一个或多个工作负载)，则协调器服务器1240确定管理工作负载。在其他实施例中，协调器服务器1240可以基于其他因素来确定是否管理工作负载。无论如何，响应于管理工作负载的确定，在说明性实施例中，方法 1500前进到框1504，其中协调器服务器1240接收策略数据(例如，策略数据1404)。在这样做时，协调器服务器1240可以通过图形用户界面(未示出)从用户(例如，管理员)、从配置文件或者从另一个源接收策略数据 1404。在接收策略数据1404时，协调器服务器1240可以接收指示受管节点1260中的一个或多个的目标生命周期的服务生命周期策略数据。另外或者可选地，协调器服务器1240可以接收功耗策略数据，所述功耗策略数据指示在受管节点1260执行工作负载时受管节点1260的目标功率使用或者功率使用的阈值量。协调器服务器1240可以附加地或者替代地接收热策略数据，该热策略数据指示当受管节点1260执行工作负载时受管节点1260 不会超过的目标温度或者温度阈值。附加地或者替代地，协调器服务器1240 可以接收其他类型的策略数据，所述其他类型的策略数据指示在工作负载的执行期间要满足的阈值或者目标。
在接收到策略数据1404之后，在说明性实施例中，方法1500前进到框1506，其中协调器服务器1240将初始工作负载指派给受管节点1260。在说明性实施例中，协调器服务器1240尚未接收到将要通知关于在受管节点1260之间指派工作负载的位置的决定的遥测数据1402。因此，协调器服务器1240可以基于任何合适的方法将工作负载指派给受管节点1260，例如将每个工作负载指派给空闲的第一可用受管节点(即，当前未执行工作负载)、随机指派工作负载、或者通过任何其他方法。
在指派了工作负载之后，方法1500前进到框1508，其中当执行(即，运行)工作负载时，协调器服务器1240从受管节点1260接收遥测数据1402。在接收遥测数据1402时，协调器服务器1240可以接收处理器利用数据，该处理器利用数据指示由每个受管节点1260执行的每个工作负载所消耗的处理器使用量，如框1510所指示的。此外，如框1514所指示的，协调器服务器1240可以接收每个受管节点1260的存储器利用数据。存储器利用数据可以体现为英特尔高速缓存指派技术(CAT)数据、英特尔高速缓存监视技术(CMT)数据、英特尔存储器带宽监视(MBM)数据和/或者指示由每个受管节点1260执行的每个工作负载对存储器使用的量或者频率的其他数据。
在接收存储器利用数据时，协调器服务器1240可以接收指示与工作负载和/或者高速缓存未命中率信息相关联的高速缓存访问的频率的高速缓存利用数据，如框1514所指示的。另外或者可选地，如框1516所指示的，在接收存储器利用数据时，协调器服务器1240可以接收易失性存储器利用数据，所述易失性存储器利用数据指示所使用的易失性存储器(例如，主存储器1304)的量、对易失性存储器的存取频率、页面错误数据，和/或者指示每个受管节点1260内易失性存储器的利用的其他信息。协调器服务器 1240可以附加地或者替代地接收非易失性存储器利用数据，所述非易失性存储器利用数据指示从数据存储设备1312存储和/或者取回的数据量和/或者每个工作负载向每个受管节点1260中的数据存储设备1312发出写请求和/或者读请求的频率，如框1518所指示的。
在接收遥测数据1402时，协调器服务器1240可以附加地或者替代地接收指示由每个受管节点1260执行的每个工作负载所使用的网络带宽的量 (例如，通信电路的容量)的网络利用数据，如在框1520中所指示的。协调器服务器1240还可以接收其他遥测数据，例如电力使用数据和/或者热量生成数据。无论如何，在接收到遥测数据1402之后，方法1500前进到图 16的框1522，其中协调器服务器1240在工作负载正在执行时生成数据分析。
现在参考图16，在说明性实施例中，在生成数据分析时，协调器服务器1240识别历史资源利用阶段和相对应的阶段驻留，如框1524所指示的。例如，如框1526所指示的，协调器服务器1240可以识别在一时间段(例如，三秒)内，高于或者低于工作负载的平均使用的组件使用(例如，当工作负载的平均使用为50％时，处理器利用为70％或者30％)。附加地或者替代地，如框1528所指示的，协调器服务器1240可以识别在一时间段内高于或者低于受管节点1260的组件的可用容量的预定阈值(例如，50％) 的组件使用。这样，在示例性实施例中，协调器服务器1240识别高处理器利用阶段(例如，30％处理器利用)和低处理器利用阶段(例如，70％处理器利用)，如框1530所指示的。类似地，在说明性实施例中，协调器服务器1240识别高存储器利用阶段和低存储器利用阶段，如框1532所指示的。另外，在说明性实施例中，协调器服务器1240识别高网络带宽利用阶段和低网络带宽利用阶段，如框1534指所指示的。此外，在说明性实施例中，并且如框1536所指示的，协调器服务器1240识别阶段数据1410中的资源利用阶段的模式，例如通过将字母字符指派给工作负载的每个识别的资源利用阶段，生成与资源利用阶段的序列相对应的字符序列的前缀树，并根据工作负载的阶段数据1410中每个序列的出现频率，向前缀树中的每个序列指派权重。这样，对于资源利用阶段的任何给定的序列(即，前缀)，协调器服务器1240可以针对与该前缀匹配的一个或多个潜在序列搜索前缀树，并基于权重(例如，最频繁出现的序列具有最大权重)来确定最可能发生哪个潜在序列。例如，协调器服务器1240可以识别其中一个或多个工作负载循环通过低存储器使用与高处理器利用的资源利用阶段，随后是低处理器利用和高存储器使用或者其他资源利用阶段的模式。
在生成数据分析时，在说明性实施例中，协调器服务器1240还生成工作负载的简档，如框1538所指示的。在这样做时，在说明性实施例中，协调器服务器1240生成工作负载的标签1406以用于唯一地识别每个工作负载，如框1540所指示的。另外，在说明性实施例中，协调器服务器1240 生成工作负载的分类1408，如框1542所指示的。
在说明性实施例中，如框1544所指示的，在生成数据分析时，协调器服务器1240还预测工作负载的未来资源利用阶段，例如通过将每个工作负载的当前资源利用与在框1536中识别的模式进行比较以确定每个工作负载的当前阶段，然后从模式中识别工作负载的即将到来的阶段。在这样做时，在说明性实施例中，协调器服务器1240使用前缀树和权重，如上面结合框 1536所描述的，以确定未来资源利用阶段的概率，如框1546所指示的。例如，协调器服务器1240可以识别前缀树中具有0.60权重的一个匹配序列，表示60％的发生概率，因为它在过去的60％的时间(例如，在阶段数据1410 中)发生，以及在前缀树中具有0.40权重的另一个匹配序列，表示发生概率为40％，因为它在过去的40％的时间发生。此外，在说明性实施例中，协调器服务器1240基于所指派的工作负载来确定资源过载的概率，如框1548所指示的。例如，如果预测指派给同一受管节点1260的两个工作负载在相同的时间段内转变到处理器密集阶段(例如，预测每个工作负载请求超过可用处理器容量的50％)，协调器服务器1240可以根据指派给前缀树中的相对应的序列的权重来确定发生过载的概率(例如，通过将第一工作负载的匹配序列的权重(例如0.7)乘以第二工作负载的匹配序列的权重(例如0.8)，组合权重为0.56，概率为56％)。
在生成数据分析之后，方法1500前进到图17的框1550，其中协调器服务器1240根据数据分析确定在工作负载被执行时对工作负载指派的调整，以提高资源利用并避免受管节点1260的任何组件的过载。这样做，协调器服务器1240确定对同一受管节点1260的补充工作负载的指派。在说明性实施例中，补充工作负载体现为这样的工作负载，当同时执行时，不会使任何组件过载并且将导致对受管节点160的可用组件的高利用。例如，在工作负载分类1408中被分类为处理器密集且对存储器利用较轻的工作负载可以与处理器利用较高且存储器利用较高的工作负载互补。类似地，具有各种资源利用阶段的工作负载可以与具有其自己的一组资源利用阶段的另一工作负载互补，只要工作负载的执行被偏移或者以其他方式调度以减少相同资源的高利用阶段在两种工作负载中同时发生的可能性。这样，在说明性实施例中，协调器服务器1240确定工作负载的资源利用阶段的时间对齐以对齐资源利用峰值和谷值。
现在参考图18，一个工作负载的处理器利用的趋势1800包括高处理器利用阶段1802，接着是低处理器资源利用阶段1804。相反，现在参考图 19，另一工作负载的处理器利用的趋势1900包括低处理器利用阶段1902，接着是高处理器利用阶段1904。通过调度一个工作负载的高处理器利用阶段1802与另一工作负载的低处理器利用阶段1902一起发生并且一个工作负载的低处理器利用阶段1804与另一个工作负载的高处理器利用阶段1904 一起发生，这些互补阶段变得对齐。
返回参考图17，在说明性实施例中，协调器服务器1240可以确定向不同的受管节点1260的工作负载的重新指派(例如，将补充工作负载合并到同一受管节点1260)，如框1556所指示的。另外或者可选地，如框1558所指示的，协调器服务器1240可以确定对工作负载的执行时间的调整(例如，偏移)，例如通过临时暂停和恢复工作负载以使其资源利用峰值和谷值与由同一受管节点1260执行的另一工作负载的资源利用谷值和峰值对齐。在说明性实施例中，协调器服务器1240将对工作负载分配的调整限制为仅具有预测的资源利用阶段的那些工作负载，其中发生概率(例如，权重)高于预定阈值(例如，高于0.5或者50％)。通过这样做，协调器服务器1240 可以避免计算针对不太可能发生的资源利用阶段的调整的成本。
协调器服务器1240还可以确定特定于节点的调整，如框1562所指示的。特定于节点的调整可以体现为对受管节点1260中的一个或多个内的设置的改变，例如在操作系统中、组件的驱动器和/或者固件(例如，CPU 1302、存储器1304、通信电路1308、一个或多个数据存储设备1312等)，以提高资源利用。这样，在说明性实施例中，在确定特定于节点的调整时，协调器服务器1240可以确定处理器限制调整，例如一个或多个工作负载的时钟速度和/或者对处理器关联。另外或者可选地，协调器服务器1240可以确定存储器使用调整，诸如易失性存储器(例如，存储器1304)的指派和/或者数据存储容量(例如，一个或多个数据存储设备1312的容量)、存储器总线速度和/或者其他与存储器相关的设置。另外或者可选地，协调器服务器 1240可以确定网络带宽调整，例如要指派给受管节点1260中的每个工作负载的通信电路1308的可用带宽。另外或者可选地，协调器服务器1240可以确定一个或多个更多风扇速度调整以增加或者减少受管节点1260内的冷却。在框1564中，协调器服务器1240可以修改对工作负载的指派的调整和/或者特定于节点的调整以符合策略数据1404。作为示例，策略数据1404 可以指示功耗不超过预定阈值，并且鉴于阈值，协调器服务器1240确定将 CPU 1302的速度降低到满足阈值并将处理器密集型工作负载重新指派为远离受管节点1260，因为在降低的速度下，CPU 1302将无法在预定时间段(例如，在客户端设备1220的用户与系统1210的运营商之间的服务水平协议 (SLA)中指定的时间段)内完成处理器密集型工作负载。
在框1566中，协调器服务器1240确定是否确定了调整。如果不是，则方法1500循环回到图15的框1508，其中当工作负载被执行时，协调器服务器1240再次从受管节点1260接收遥测数据1402。否则，如果确定了调整，则方法1500前进到框1568，其中协调器服务器1240应用所确定的调整。在这样做时，协调器服务器1240可以发出一个或多个请求以在两个受管节点1260之间执行工作负载的实时迁移(即，工作负载重新指派)，如框1570所指示的。在说明性实施例中，迁移是实时的，因为，如上所述，不是等待直到完成工作负载以分析遥测数据1402，而是协调器服务器1240 收集并分析遥测数据1402，并在线进行调整(即，当工作负载正在执行时)。附加地或者替代地，协调器服务器1240可以延迟一个或多个工作负载的执行以对齐受管节点1260内的资源利用阶段，如框1572所指示的。附加地或者替代地，如框1574所指示的，协调器服务器1240可以向受管节点1260 中的一个或多个发出用于应用上面参考框1562所描述的节点特定的调整的一个或多个请求。在应用调整之后，方法1500循环回到图15的框1508，其中协调器服务器1240从受管节点1260接收附加遥测数据1402。
示例
下面提供本文公开的技术的说明性示例。这些技术的实施例可以包括下面描述的示例中的任何一个或多个，以及任何组合。
示例1包括一种协调器服务器，用于基于资源利用阶段在一组受管节点之间指派工作负载，所述协调器服务器包括：一个或多个处理器；一个或多个存储器设备，其中存储有多个指令，多个指令当由一个或多个处理器执行时，使得所述协调器服务器用于：将一组工作负载指派给所述受管节点；从所述受管节点接收遥测数据，其中所述遥测数据指示当工作负载被执行时受管节点中的每个的资源利用；根据所述遥测数据识别工作负载的历史资源利用阶段，其中每个历史资源利用阶段指示在一时间段内满足阈值量的特定类型的受管节点组件的利用；根据历史资源利用阶段并且当工作负载被执行时，确定工作负载的预测的资源利用阶段，其中每个预测的资源利用阶段指示满足在一未来时间段内满足阈值量的特定类型的受管节点组件的预测利用；以及根据预测的资源利用阶段当工作负载被执行时应用对受管节点之间的工作负载指派的调整。
示例2包括示例1的主题，并且其中识别历史资源利用阶段包括确定所述历史资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
示例3包括示例1和2中任一项的主题，并且其中确定预测的资源利用阶段包括：确定所述预测的资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
示例4包括示例1-3中的任何一个的主题，并且其中应用对所述工作负载的指派的调整包括：将具有第一类型的预测的资源利用阶段的所述工作负载中的一个和具有第二类型的预测的资源利用阶段的所述工作负载中的第二个指派给同一受管节点，以用于在未来时间段期间执行。
示例5包括示例1-4中任一项的主题，并且其中，应用对所述工作负载的指派的调整包括：延迟第一工作负载的执行，以将所述第一工作负载的第一预测的资源利用阶段与同一受管节点上的第二工作负载的第二预测的资源利用阶段在时间上对齐。
示例6包括示例1-5中任一项的主题，并且其中确定历史资源利用阶段包括：确定在该时间段期间特定受管节点组件的利用是否大于特定受管节点组件的平均利用；以及响应于确定利用大于平均利用，确定所述历史资源利用阶段指示满足阈值量的受管节点组件的利用。
示例7包括示例1-6中任一项的主题，并且其中确定历史资源利用阶段包括：确定在该时间段期间特定受管节点组件的利用是否大于特定受管节点组件的可用容量的预定量；以及响应于确定利用大于可用容量的预定量，确定所述历史资源利用阶段指示满足阈值量的特定受管节点组件的利用。
示例8包括示例1-7中任一项的主题，并且其中识别所述工作负载的历史资源利用阶段包括识别所述工作负载中的一个或多个的历史资源利用阶段的模式。
示例9包括示例1-8中任一项的主题，并且其中，所述多个指令当被执行时还使得所述协调器服务器用于：确定在未来时间段内第一工作负载的预测的资源利用将发生的概率；将确定的概率与预定的概率阈值进行比较；响应于确定概率满足预定的概率阈值，将第一工作负载添加到要在时间上对齐的一组工作负载；并且其中调整工作负载的指派包括调整在要在时间上对齐的一组工作负载中的工作负载的指派。
示例10包括示例1-9中任一项的主题，并且其中识别历史资源利用阶段包括：确定阶段驻留，所述阶段驻留指示所述特定类型的受管节点组件的利用满足所述阈值量的时间段的长度。
示例11包括示例1-10中任一项的主题，并且其中，应用对所述受管节点之间的所述工作负载的指派的调整包括：发出用于执行从第一受管节点到第二受管节点的工作负载的实时迁移的请求。
示例12包括示例1-11中任一项的主题，并且其中，应用对所述受管节点之间的所述工作负载的指派的调整包括：将具有预测的高处理器利用的第一工作负载和具有预测的低处理器利用的第二工作负载指派给所述同一受管节点以用于在未来的时间段期间执行。
示例13包括示例1-12中任一项的主题，并且其中，应用对受管节点之间的工作负载的指派的调整包括：将具有预测的高存储器利用的第一工作负载和具有预测的低存储器利用的第二工作负载指派给同一受管节点，以用于在未来时间段期间执行。
示例14包括示例1-13中任一项的主题，并且其中，应用对受管节点之间的工作负载的指派的调整包括：将具有预测的高网络带宽利用的第一工作负载和具有预测的低网络带宽利用的第二工作负载指派给同一受管节点，以用于在未来时间段期间执行。
示例15包括一种用于基于资源利用阶段在一组受管节点之间指派工作负载的方法，该方法包括：由协调器服务器将一组工作负载指派给受管节点；由协调器服务器从受管节点接收遥测数据，其中所述遥测数据指示当工作负载被执行时受管节点中的每个的资源利用；由协调器服务器并根据遥测数据识别工作负载的历史资源利用阶段，其中每个历史资源利用阶段指示一时间段内满足阈值量的特定类型的受管节点组件的利用；由协调器服务器并且根据历史资源利用阶段并且当工作负载被执行时，确定工作负载的预测的资源利用阶段，其中每个预测的资源利用阶段指示在一未来时间段内满足阈值量的特定类型的受管节点组件的预测利用；以及由协调器服务器并且根据预测的资源利用阶段，当工作负载被执行时应用对受管节点之间的工作负载的指派的调整。
示例16包括示例15的主题，并且其中识别历史资源利用阶段包括确定所述历史资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
示例17包括示例15和16中任一项的主题，并且其中确定预测的资源利用阶段包括确定所述预测的资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
示例18包括示例15-17中任一项的主题，并且其中应用对所述工作负载的指派的调整包括：将具有第一类型的预测的资源利用阶段的工作负载中的一个和具有第二类型的预测的资源利用阶段的工作负载中的第二个指派给同一受管节点以用于在未来时间段期间执行。
示例19包括示例15-18中任一项的主题，并且其中应用对所述工作负载的指派的调整包括：延迟第一工作负载的执行以将所述第一工作负载的第一预测的资源利用阶段与同一受管节点上的所述第二工作负载的第二预测的资源利用阶段在时间上对齐。
示例20包括示例15-19中任一项的主题，并且其中确定历史资源利用阶段包括：确定在该时间段期间特定受管节点组件的利用是否大于特定受管节点组件的平均利用；以及响应于确定利用大于平均利用，确定历史资源利用阶段指示满足阈值量的受管节点组件的利用。
示例21包括示例15-20中任一项的主题，并且其中确定历史资源利用阶段包括：确定在该时间段期间特定受管节点组件的利用是否大于特定受管节点组件的可用容量的预定量；以及响应于确定该利用大于可用容量的预定量，确定历史资源利用阶段指示满足阈值量的特定受管节点组件的利用。
示例22包括示例15-21中任一项的主题，并且其中识别所述工作负载的历史资源利用阶段包括识别所述工作负载中的一个或多个的历史资源利用阶段的模式。
示例23包括示例15-22中任一项的主题，并且还包括：由协调器服务器确定在未来时间段期间将发生第一工作负载的预测的资源利用的概率；由协调器服务器将确定的概率与预定的概率阈值进行比较；由协调器服务器并且响应于确定概率满足预定的概率阈值，将第一工作负载添加到要在时间上对齐的一组工作负载；以及其中，调整工作负载的指派包括调整要在时间上对齐的一组工作负载中的工作负载的指派。
示例24包括示例15-23中任一项的主题，并且其中识别历史资源利用阶段包括确定阶段驻留，所述阶段驻留指示所述特定类型的受管节点组件的利用满足所述阈值量的时间段的长度。
示例25包括示例15-24中任一项的主题，并且其中应用对所述受管节点中的所述工作负载的指派的调整包括：发出用于执行从第一受管节点到第二受管节点的工作负载的实时迁移的请求。
示例26包括示例15-25中任一项的主题，并且其中应用对受管节点中的工作负载的指派的调整包括：将具有预测的高处理器利用的第一工作负载和具有预测的低处理器利用的第二工作负载指派给同一受管节点，以用于在未来时间段期间执行。
示例27包括示例15-26中任一项的主题，并且其中应用对受管节点中的工作负载的指派的调整包括：将具有预测的高存储器利用的第一工作负载和具有预测的低存储器利用的第二工作负载指派给同一受管节点，以用于在未来时间段期间执行。
示例28包括示例15-27中任一项的主题，并且其中应用对受管节点中的工作负载的指派的调整包括：将具有预测的高网络带宽利用的第一工作负载和具有预测的低网络带宽利用的第二工作负载指派给同一受管节点，以用于在未来时间段期间执行。
示例29包括一个或多个机器可读存储介质，包括存储在其上的多个指令，其响应于被执行，使得协调器服务器用于执行示例15-28中任一项的方法。
示例30包括一种协调器服务器，用于基于资源利用阶段在一组受管节点之间指派工作负载，该协调器服务器包括：一个或多个处理器；耦合到一个或多个处理器的通信电路；一个或多个存储器设备，其中存储有多个指令，多个指令当由一个或多个处理器执行时，使得协调器服务器执行示例15-28中任一项的方法。
示例31包括一种协调器服务器，用于基于资源利用阶段在一组受管节点之间指派工作负载，协调器服务器包括：资源管理器电路，用于将一组工作负载指派给受管节点；遥测监视器电路，用于从受管节点接收遥测数据，其中遥测数据指示当工作负载被执行时受管节点中的每个的资源利用；其中，资源管理器电路还用于：根据所述遥测数据识别工作负载的历史资源利用阶段，其中每个历史资源利用阶段指示一时间段内满足阈值量的特定类型的受管节点组件的利用；根据历史资源利用阶段并且当工作负载被执行时，确定工作负载的预测的资源利用阶段，其中每个预测的资源利用阶段指示一未来时间段内满足阈值量的特定类型的受管节点组件的预测利用；以及根据预测的资源利用阶段当工作负载被执行时应用对受管节点之间的工作负载指派的调整。
示例32包括示例31的主题，并且其中识别历史资源利用阶段包括确定所述历史资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
示例33包括示例31和32中任一项的主题，并且其中确定预测的资源利用阶段包括：确定所述预测的资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
示例34包括示例31-33中任一项的主题，并且其中应用对所述工作负载的指派的调整包括：将具有第一类型的预测的资源利用阶段的所述工作负载中的一个和具有第二类型的预测的资源利用阶段的所述工作负载中的第二个指派给同一受管节点，以用于在未来时间段期间执行。
示例35包括示例31-34中任一示例的主题，并且其中应用对所述工作负载的指派的调整包括：延迟第一工作负载的执行，以将所述第一工作负载的第一预测的资源利用阶段与同一受管节点上的第二工作负载的第二预测的资源利用阶段在时间上对齐。
示例36包括示例31-35中任一示例的主题，并且其中确定历史资源利用阶段包括：确定在该时间段期间特定受管节点组件的利用是否大于特定受管节点组件的平均利用；以及响应于确定该利用大于平均利用，确定所述历史资源利用阶段指示满足阈值量的受管节点组件的利用。
示例37包括示例31-36中任一项的主题，并且其中确定历史资源利用阶段包括：确定在该时间段期间特定受管节点组件的利用是否大于特定受管节点组件的可用容量的预定量；以及响应于确定该利用大于可用容量的预定量，确定所述历史资源利用阶段指示满足阈值量的特定受管节点组件的利用。
示例38包括示例31-37中任一项的主题，并且其中识别所述工作负载的历史资源利用阶段包括识别所述工作负载中的一个或多个的历史资源利用阶段的模式。
示例39包括示例31-38中任一示例的主题，并且其中，资源管理器电路还用于确定在未来时段期间第一工作负载的预测的资源利用将发生的概率；将确定的概率与预定的概率阈值进行比较；并且，响应于确定概率满足预定的概率阈值，将第一工作负载添加到要在时间上对齐的一组工作负载，其中调整工作负载的指派包括调整要在时间上对齐的一组工作负载中的工作负载的指派。
示例40包括示例31-39中任一项的主题，并且其中识别历史资源利用阶段包括：确定阶段驻留，所述阶段驻留指示所述特定类型的受管节点组件的利用满足所述阈值量的时间段的长度。
示例41包括示例31-40中任一项的主题，并且其中，应用对所述受管节点之间的所述工作负载的指派的调整包括：发出用于执行从第一受管节点到第二受管节点的工作负载的实时迁移的请求。
示例42包括示例31-41中任一项的主题，并且其中，应用对所述受管节点中的所述工作负载的指派的调整包括：将具有预测的高处理器利用的第一工作负载和具有预测的低处理器利用的第二工作负载指派给所述同一受管节点以用于在未来的时间段期间执行。
示例43包括示例31-42中任一项的主题，并且其中，应用对受管节点中的工作负载的指派的调整包括：将具有预测的高存储器利用的第一工作负载和具有预测的低存储器利用的第二工作负载指派给同一受管节点，以用于在未来时间段期间执行。
示例44包括示例31-43中任一项的主题，并且其中，应用对受管节点中的工作负载的指派的调整包括：将具有预测的高网络带宽利用的第一工作负载和具有预测的低网络带宽利用的第二工作负载指派给同一受管节点，以用于在未来时间段期间执行。
示例45包括一种协调器服务器，用于基于资源利用阶段在一组受管节点之间指派工作负载，该协调器服务器包括用于将一组工作负载指派给受管节点的电路；用于从受管节点接收遥测数据的电路，其中遥测数据指示当工作负载被执行时受管节点中的每个的资源利用；用于根据遥测数据识别工作负载的历史资源利用阶段的单元，其中每个历史资源利用阶段指示在一时间段内满足阈值量的特定类型的受管节点组件的利用；用于根据历史资源利用阶段并且当工作负载被执行时确定工作负载的预测的资源利用阶段的单元，其中每个预测的资源利用阶段指示在一未来时间段内满足阈值量的特定类型的受管节点组件的预测利用；以及用于根据预测的资源利用阶段当工作负载被执行时应用对受管节点之间的工作负载的指派的调整的单元。
示例46包括示例45的主题，并且其中用于识别历史资源利用阶段的所述单元包括用于确定所述历史资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个的单元。
示例47包括示例45和46中任一项的主题，并且其中用于确定预测的资源利用阶段的所述单元包括用于确定所述预测的资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个的单元。
示例48包括示例45-47中任一项的主题，并且其中用于应用对所述工作负载的指派的调整的所述单元包括：用于将具有第一类型的预测的资源利用阶段的工作负载中的一个和具有第二类型的预测的资源利用阶段的工作负载中的第二个指派给同一受管节点以用于在未来时间段期间执行的单元。
示例49包括示例45-48中任一项的主题，并且其中用于应用对所述工作负载的指派的调整的所述单元包括：用于延迟第一工作负载的执行以将所述第一工作负载的第一预测的资源利用阶段与同一受管节点上的所述第二工作负载的第二预测的资源利用阶段在时间上对齐的单元。
示例50包括示例45-49中任一项的主题，并且其中用于确定历史资源利用阶段的所述单元包括：用于确定在该时间段期间特定受管节点组件的利用是否大于特定受管节点组件的平均利用的单元；以及用于响应于确定该利用大于平均利用而确定历史资源利用阶段指示满足阈值量的受管节点组件的利用的单元。
示例51包括示例45-50中任一项的主题，并且其中用于确定历史资源利用阶段的所述单元包括：用于确定在该时间段期间特定受管节点组件的利用是否大于特定受管节点组件的可用容量的预定量的单元；以及用于响应于确定该利用大于可用容量的预定量而确定历史资源利用阶段指示满足阈值量的特定受管节点组件的利用的单元。
示例52包括示例45-51中任一项的主题，并且其中用于识别所述工作负载的历史资源利用阶段的所述单元包括用于识别所述工作负载中的一个或多个的历史资源利用阶段的模式的单元。
示例53包括示例45-52中任一项的主题，并且还包括用于确定在未来时间段期间第一工作负载的预测的资源利用将发生的概率的单元；用于将所确定的概率与预定的概率阈值进行比较的单元；用于响应于确定概率满足预定的概率阈值而将第一工作负载添加到要在时间上对齐的一组工作负载的单元；并且其中用于调整工作负载的指派的单元包括用于调整在时间上对齐的一组工作负载中的工作负载的指派的单元。
示例54包括示例45-53中任一项的主题，并且其中用于识别历史资源利用阶段的所述单元包括用于确定阶段驻留的单元，所述阶段驻留指示所述特定类型的受管节点组件的利用满足所述阈值量的时间段的长度。
示例55包括示例45-54中任一示例的主题，并且其中用于应用对所述受管节点中的所述工作负载的指派的调整的所述单元包括：用于发出用于执行从第一受管节点到第二受管节点的工作负载的实时迁移的请求的单元。
示例56包括示例45-55中任一项的主题，并且其中用于应用对受管节点之间的工作负载的指派的调整的所述单元包括用于将具有预测的高处理器利用的第一工作负载指派和具有预测的低处理器利用的第二工作负载指派给同一受管节点以用于在未来时间段期间执行的单元。
示例57包括示例45-56中任一项的主题，并且其中用于应用对受管节点之间的工作负载的指派的调整的单元包括用于将具有预测的高存储器利用的第一工作负载和具有预测的低存储器利用的第二工作负载指派给同一受管节点以用于在未来时间段期间执行的单元。
示例58包括示例45-57中任一项的主题，并且其中用于应用对受管节点之间的工作负载的指派的调整的所述单元包括用于将具有高网络带宽利用的第一工作负载和具有预测的低网络带宽利用的第二工作负载指派给同一受管节点以用于在未来时间段期间执行的单元。

Claims (26)

1.一种用于基于资源利用阶段来在一组受管节点之间指派工作负载的协调器服务器，所述协调器服务器包括：
一个或多个处理器；
一个或多个存储器设备，其中存储有多个指令，所述多个指令当由所述一个或多个处理器执行时，使得所述协调器服务器用于：
将一组工作负载指派给所述受管节点；
从所述受管节点接收遥测数据，其中，所述遥测数据指示当所述工作负载被执行时所述受管节点中的每个的资源利用；
根据所述遥测数据识别所述工作负载的历史资源利用阶段，其中，每个历史资源利用阶段指示在一时间段内满足阈值量的特定类型的受管节点组件的利用；
根据所述历史资源利用阶段并且当所述工作负载被执行时，确定所述工作负载的预测的资源利用阶段，其中，每个预测的资源利用阶段指示在一未来时间段内满足所述阈值量的特定类型的受管节点组件的预测的利用；以及
根据所述预测的资源利用阶段，当所述工作负载被执行时应用对所述受管节点之间的所述工作负载的指派的调整。
2.如权利要求1所述的协调器服务器，其中，识别历史资源利用阶段包括确定所述历史资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
3.如权利要求1所述的协调器服务器，其中，确定预测的资源利用阶段包括确定所述预测的资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
4.如权利要求1所述的协调器服务器，其中，应用对所述工作负载的指派的调整包括将具有第一类型的预测的资源利用阶段的所述工作负载中的一个和具有第二类型的预测的资源利用阶段的所述工作负载中的第二个指派给同一受管节点，以用于在所述未来时间段期间执行。
5.如权利要求1所述的协调器服务器，其中，应用对所述工作负载的指派的调整包括延迟第一工作负载的执行，以将所述第一工作负载的第一预测的资源利用阶段与同一受管节点上的第二工作负载的第二预测的资源利用阶段在时间上对齐。
6.如权利要求1所述的协调器服务器，其中，确定历史资源利用阶段包括：
确定在所述时间段期间特定受管节点组件的利用是否大于所述特定受管节点组件的平均利用；以及
响应于确定所述利用大于所述平均利用，确定所述历史资源利用阶段指示满足所述阈值量的所述受管节点组件的利用。
7.如权利要求1所述的协调器服务器，其中，确定历史资源利用阶段包括：
确定在所述时间段期间所述特定受管节点组件的利用是否大于所述特定受管节点组件的可用容量的预定量；以及
响应于确定所述利用大于所述可用容量的预定量，确定所述历史资源利用阶段指示满足所述阈值量的所述特定受管节点组件的利用。
8.如权利要求1所述的协调器服务器，其中，识别所述工作负载的历史资源利用阶段包括识别所述工作负载中的一个或多个的历史资源利用阶段的模式。
9.如权利要求1所述的协调器服务器，其中，所述多个指令当被执行时，还使得所述协调器服务器用于：
确定在所述未来时间段期间第一工作负载的预测的资源利用将发生的概率；
将确定的概率与预定的概率阈值进行比较；
响应于确定所述概率满足所述预定的概率阈值，将所述第一工作负载添加到要在时间上对齐的一组工作负载；并且
其中，调整所述工作负载的指派包括调整所述要在时间上对齐的一组工作负载中的所述工作负载的指派。
10.如权利要求1所述的协调器服务器，其中，识别历史资源利用阶段包括确定阶段驻留，所述阶段驻留指示所述特定类型的受管节点组件的利用满足所述阈值量的时间段的长度。
11.如权利要求1所述的协调器服务器，其中，应用对所述受管节点之间的所述工作负载的指派的调整包括：发出用于执行从第一受管节点到第二受管节点的工作负载的实时迁移的请求。
12.如权利要求1所述的协调器服务器，其中，应用对所述受管节点之间的所述工作负载的指派的调整包括：将具有预测的高处理器利用的第一工作负载和具有预测的低处理器利用的第二工作负载指派给同一受管节点以用于在所述未来的时间段期间执行。
13.一种用于基于资源利用阶段来在一组受管节点之间指派工作负载的协调器服务器，所述协调器服务器包括：
用于将一组工作负载指派给所述受管节点的电路；
用于从所述受管节点接收遥测数据的电路，其中，所述遥测数据指示当所述工作负载被执行时所述受管节点中的每个的资源利用；
用于根据所述遥测数据识别所述工作负载的历史资源利用阶段的电路，其中，每个历史资源利用阶段指示一时间段内满足阈值量的特定类型的受管节点组件的利用；
用于根据所述历史资源利用阶段并且当所述工作负载被执行时，确定所述工作负载的预测的资源利用阶段的电路，其中，每个预测的资源利用阶段指示在一未来时间段内满足所述阈值量的特定类型的受管节点组件的预测的利用；以及
用于根据所述预测的资源利用阶段，当所述工作负载被执行时应用对所述受管节点之间的所述工作负载的指派的调整的电路。
14.如权利要求13所述的协调器服务器，其中，用于识别历史资源利用阶段的所述电路包括用于确定所述历史资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个的电路。
15.如权利要求13所述的协调器服务器，其中，用于确定预测的资源利用阶段的所述电路包括用于确定所述预测的资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个的电路。
16.如权利要求13所述的协调器服务器，其中，用于应用对所述工作负载的指派的调整的所述电路包括用于将具有第一类型的预测的资源利用阶段的所述工作负载中的一个和具有第二类型的预测的资源利用阶段的所述工作负载中的第二个指派给同一受管节点以用于在所述未来时间段期间执行的电路。
17.如权利要求13所述的协调器服务器，其中，用于应用对所述工作负载的指派的调整的所述电路包括用于延迟第一工作负载的执行以将所述第一工作负载的第一预测的资源利用阶段与同一受管节点上的第二工作负载的第二预测的资源利用阶段在时间上对齐的电路。
18.如权利要求13所述的协调器服务器，其中，用于确定历史资源利用阶段的所述电路包括：
用于确定在所述时间段期间特定受管节点组件的利用是否大于所述特定受管节点组件的平均利用的电路；以及
用于响应于确定所述利用大于所述平均利用，确定所述历史资源利用阶段指示满足所述阈值量的所述受管节点组件的利用的电路。
19.如权利要求13所述的协调器服务器，其中，用于确定历史资源利用阶段的所述电路包括：
用于确定在所述时间段期间特定受管节点组件的利用是否大于所述特定受管节点组件的可用容量的预定量的电路；以及
用于响应于确定所述利用大于所述可用容量的预定量，确定所述历史资源利用阶段指示满足所述阈值量的所述特定受管节点组件的利用的电路。
20.如权利要求13所述的协调器服务器，其中，用于识别所述工作负载的历史资源利用阶段的所述电路包括用于识别所述工作负载中的一个或多个的历史资源利用阶段的模式的电路。
21.如权利要求13所述的协调器服务器，还包括：
用于确定在所述未来时间段期间第一工作负载的预测的资源利用将发生的概率的电路；
用于将确定的概率与预定的概率阈值进行比较的电路；
用于响应于确定所述概率满足所述预定的概率阈值，将所述第一工作负载添加到要在时间上对齐的一组工作负载的电路；以及
其中，用于调整所述工作负载的指派的所述电路包括用于调整所述要在时间上对齐的一组工作负载中的所述工作负载的指派的电路。
22.如权利要求13所述的协调器服务器，其中，用于识别历史资源利用阶段的所述电路包括用于确定阶段驻留的电路，所述阶段驻留指示所述特定类型的受管节点组件的利用满足所述阈值量的时间段的长度。
23.一种用于基于资源利用阶段来在一组受管节点之间指派工作负载的方法，所述方法包括：
由协调器服务器将一组工作负载指派给所述受管节点；
由所述协调器服务器从所述受管节点接收遥测数据，其中，所述遥测数据指示当所述工作负载被执行时所述受管节点中的每个的资源利用；
由所述协调器服务器并且根据所述遥测数据识别所述工作负载的历史资源利用阶段，其中，每个历史资源利用阶段指示一时间段内满足阈值量的特定类型的受管节点组件的利用；
由所述协调器服务器并且根据所述历史资源利用阶段并且当所述工作负载被执行时，确定所述工作负载的预测的资源利用阶段，其中，每个预测的资源利用阶段指示在一未来时间段内满足所述阈值量的特定类型的受管节点组件的预测的利用；以及
由所述协调器服务器并且根据所述预测的资源利用阶段，当所述工作负载被执行时应用对所述受管节点之间的所述工作负载的指派的调整。
24.如权利要求23所述的方法，其中，识别历史资源利用阶段包括确定所述历史资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
25.如权利要求23所述的方法，其中，确定预测的资源利用阶段包括确定所述预测的资源利用阶段是处理器密集型、存储器密集型或者网络带宽密集型中的一个。
26.一个或者多个包括存储在其上的多个指令的机器可读存储介质，所述多个指令响应于被执行，使得协调器服务器用于执行如权利要求23-25中任一项所述的方法。
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