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公开(公告)号：US08078913B2
公开(公告)日：2011-12-13
申请号：US12473900
申请日：2009-05-28
申请人： Moises Goldszmidt , Peter Bodik
发明人： Moises Goldszmidt , Peter Bodik
IPC分类号： G06F11/00
CPC分类号： G06F11/079 , G06F11/0709 , G06F11/3409 , G06F2201/81 , H04L41/0681
摘要： Methods for automatically identifying and classifying a crisis state occurring in a system having a plurality of computer resources. Signals are received from a device that collects the signals from each computer resource in the system. For each epoch, an epoch fingerprint is generated. Upon detecting a performance crisis within the system, a crisis fingerprint is generated consisting of at least one epoch fingerprint. The technology is able to identify that a performance crisis has previously occurred within the datacenter if a generated crisis fingerprint favorably matches any of the model crisis fingerprints stored in a database. The technology may also predict that a crisis is about to occur.
摘要翻译： 用于自动识别和分类在具有多个计算机资源的系统中发生的危机状态的方法。 从收集系统中每台计算机资源的信号的设备接收信号。 对于每个时期，都会产生一个时代指纹。 在检测到系统内的性能危机之后，产生由至少一个时代指纹组成的危机指纹。 该技术能够确定如果生成的危机指纹有利地匹配存储在数据库中的任何模型危机指纹，则数据中心之前发生了性能危机。 该技术还可能预测危机即将发生。
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公开(公告)号：US20100241903A1
公开(公告)日：2010-09-23
申请号：US12408570
申请日：2009-03-20
CPC分类号： G06F11/079 , G06F11/0709 , G06F11/0748 , H04L41/0681 , H04L43/0823 , H04L43/0888
摘要： The present invention extends to methods, systems, and computer program products for automatically generating and refining health models. Embodiments of the invention use machine learning tools to analyze historical telemetry data from a server deployment. The tools output fingerprints, for example, small groupings of specific metrics-plus-behavioral parameters, that uniquely identify and describe past problem events mined from the historical data. Embodiments automatically translate the fingerprints into health models that can be directly applied to monitoring the running system. Fully-automated feedback loops for identifying past problems and giving advance notice as those problems emerge in the future is facilitated without any operator intervention. In some embodiments, a single portion of expert knowledge, for example, Key Performance Indicator (KPI) data, initiates health model generation. Once initiated, the feedback loop can be fully automated to access further telemetry and refine health models based on the further telemetry.
摘要翻译： 本发明延伸到用于自动生成和改进健康模型的方法，系统和计算机程序产品。 本发明的实施例使用机器学习工具来分析来自服务器部署的历史遥测数据。 这些工具输出指纹，例如，特定指标加行为参数的小组，可以唯一地识别和描述从历史数据中挖掘的过去的问题事件。 实施例将指纹自动转换为可直接应用于监视运行系统的健康模型。 全面自动化的反馈回路用于识别过去的问题，并在未来出现这些问题时提前通知，无需任何操作员干预。 在一些实施例中，专家知识的单一部分，例如关键绩效指标（KPI）数据，启动健康模型生成。 一旦启动，反馈回路可以完全自动化，以进一步遥测和基于进一步的遥测来改进健康模型。
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公开(公告)号：US07962797B2
公开(公告)日：2011-06-14
申请号：US12408570
申请日：2009-03-20
IPC分类号： G06F11/00
CPC分类号： G06F11/079 , G06F11/0709 , G06F11/0748 , H04L41/0681 , H04L43/0823 , H04L43/0888
摘要： The present invention extends to methods, systems, and computer program products for automatically generating and refining health models. Embodiments of the invention use machine learning tools to analyze historical telemetry data from a server deployment. The tools output fingerprints, for example, small groupings of specific metrics-plus-behavioral parameters, that uniquely identify and describe past problem events mined from the historical data. Embodiments automatically translate the fingerprints into health models that can be directly applied to monitoring the running system. Fully-automated feedback loops for identifying past problems and giving advance notice as those problems emerge in the future is facilitated without any operator intervention. In some embodiments, a single portion of expert knowledge, for example, Key Performance Indicator (KPI) data, initiates health model generation. Once initiated, the feedback loop can be fully automated to access further telemetry and refine health models based on the further telemetry.
摘要翻译： 本发明延伸到用于自动生成和改进健康模型的方法，系统和计算机程序产品。 本发明的实施例使用机器学习工具来分析来自服务器部署的历史遥测数据。 这些工具输出指纹，例如，特定指标加行为参数的小组，可以唯一地识别和描述从历史数据中挖掘的过去的问题事件。 实施例将指纹自动转换为可直接应用于监视运行系统的健康模型。 全面自动化的反馈回路用于识别过去的问题，并在未来出现这些问题时提前通知，无需任何操作员干预。 在一些实施例中，专家知识的单一部分，例如关键绩效指标（KPI）数据，启动健康模型生成。 一旦启动，反馈回路可以完全自动化，以进一步遥测和基于进一步的遥测来改进健康模型。
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公开(公告)号：US20100306597A1
公开(公告)日：2010-12-02
申请号：US12473900
申请日：2009-05-28
申请人： Moises Goldszmidt , Peter Bodik
发明人： Moises Goldszmidt , Peter Bodik
CPC分类号： G06F11/079 , G06F11/0709 , G06F11/3409 , G06F2201/81 , H04L41/0681
摘要： Methods for automatically identifying and classifying a crisis state occurring in a system having a plurality of computer resources. Signals are received from a device that collects the signals from each computer resource in the system. For each epoch, an epoch fingerprint is generated. Upon detecting a performance crisis within the system, a crisis fingerprint is generated consisting of at least one epoch fingerprint. The technology is able to identify that a performance crisis has previously occurred within the datacenter if a generated crisis fingerprint favorably matches any of the model crisis fingerprints stored in a database. The technology may also predict that a crisis is about to occur.
摘要翻译： 用于自动识别和分类在具有多个计算机资源的系统中发生的危机状态的方法。 从收集系统中每台计算机资源的信号的设备接收信号。 对于每个时期，都会产生一个时代指纹。 在检测到系统内的性能危机之后，产生由至少一个时代指纹组成的危机指纹。 该技术能够确定如果生成的危机指纹有利地匹配存储在数据库中的任何模型危机指纹，则数据中心之前发生了性能危机。 该技术还可能预测危机即将发生。
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5.发明申请公开(公告)号：US20090144034A1
公开(公告)日：2009-06-04
申请号：US11949061
申请日：2007-12-03
申请人： Aleksandr Simma , Moises Goldszmidt
发明人： Aleksandr Simma , Moises Goldszmidt
CPC分类号： H04L41/0663 , H04L41/142 , H04L41/145
摘要： Dependencies between different channels or different services in a client or server may be determined from the observation of the times of the incoming and outgoing of the packets constituting those channels or services. A probabilistic model may be used to formally characterize these dependencies. The probabilistic model may be used to list the dependencies between input packets and output packets of various channels or services, and may be used to establish the expected strength of the causal relationship between the different events surrounding those channels or services. Parameters of the probabilistic model may be either based on prior knowledge, or may be fit using statistical techniques based on observations about the times of the events of interest. Expected times of occurrence between events may be observed, and dependencies may be determined in accordance with the probabilistic model.
摘要翻译： 客户端或服务器中的不同信道或不同业务之间的依赖关系可以从对构成这些信道或业务的分组的进入和传出的时间的观察来确定。 概率模型可用于正式表征这些依赖性。 概率模型可以用于列出输入分组和各种信道或服务的输出分组之间的依赖性，并且可以用于建立围绕这些信道或服务的不同事件之间的因果关系的预期强度。 概率模型的参数可以基于现有知识，或者可以使用基于关于感兴趣事件的时间的观察的统计技术来拟合。 可以观察事件之间的预期发生时间，并且依赖性可以根据概率模型来确定。
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公开(公告)号：US20090076794A1
公开(公告)日：2009-03-19
申请号：US11855099
申请日：2007-09-13
申请人： Kannan Achan , Moises Goldszmidt , Lev Ratinov
发明人： Kannan Achan , Moises Goldszmidt , Lev Ratinov
CPC分类号： G10L15/142 , G06F17/2715 , G06K9/6297
摘要： Mechanisms are disclosed for incorporating prototype information into probabilistic models for automated information processing, mining, and knowledge discovery. Examples of these models include Hidden Markov Models (HMMs), Latent Dirichlet Allocation (LDA) models, and the like. The prototype information injects prior knowledge to such models, thereby rendering them more accurate, effective, and efficient. For instance, in the context of automated word labeling, additional knowledge is encoded into the models by providing a small set of prototypical words for each possible label. The net result is that words in a given corpus are labeled and are therefore in condition to be summarized, identified, classified, clustered, and the like.
摘要翻译： 公开了将原型信息并入用于自动化信息处理，挖掘和知识发现的概率模型中的机制。 这些模型的示例包括隐马尔可夫模型（HMM），潜在狄利克雷分配（LDA）模型等。 原型信息将先前的知识注入到这些模型中，从而使它们更准确，有效和高效。 例如，在自动化字标识的上下文中，通过为每个可能的标签提供一小组原型字来将附加知识编码到模型中。 最终的结果是，给定语料库中的单词被标记，因此在其中被概括，识别，分类，聚类等等。
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公开(公告)号：US20080103729A1
公开(公告)日：2008-05-01
申请号：US11554980
申请日：2006-10-31
申请人： Paul Barham , Richard Black , Moises Goldszmidt , Rebecca Isaacs , John MacCormick , Richard Mortier
发明人： Paul Barham , Richard Black , Moises Goldszmidt , Rebecca Isaacs , John MacCormick , Richard Mortier
CPC分类号： H04L41/06 , H04L41/147 , H04L41/16 , H04L43/0811
摘要： Activity models are maintained on a plurality of computers on a network. When a user or a particular activity model at a computer discovers an error, it may query its own activity model to determine a possible source of the error. If it is determined to not be the likely source of the error, the activity model queries the activity models of those computers on the network that it depends on. These activity models may then query the activity models of the computers that their particular host computer depends on and so forth. Ultimately the results of these activity model queries may be used to diagnose the likely source of the error and may be presented to the requesting user as a report.
摘要翻译： 在网络上的多台计算机上维护活动模型。 当用户或计算机上的特定活动模型发现错误时，它可以查询其自己的活动模型以确定错误的可能来源。 如果确定不是错误的可能来源，则活动模型会查询网络上依赖的那些计算机的活动模型。 然后，这些活动模型可以查询其特定主机依赖的计算机的活动模型等等。 最终，这些活动模型查询的结果可以用于诊断错误的可能来源，并且可以作为报告呈现给请求用户。
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公开(公告)号：US20060188011A1
公开(公告)日：2006-08-24
申请号：US10987611
申请日：2004-11-12
申请人： Moises Goldszmidt , Ira Cohen , Terence Kelly , Julie Symons
发明人： Moises Goldszmidt , Ira Cohen , Terence Kelly , Julie Symons
IPC分类号： H03H7/30
CPC分类号： G06Q10/04
摘要： Systems, methods, and software used in performing automated diagnosis and identification of or forecasting service level object states. Some embodiments include building classifier models based on collected metric data to detect and forecast service level objective (SLO) violations. Some such systems, methods, and software further include automated detecting and forecasting of SLO violations along with providing alarms, messages, or commands to administrators or system components. Some such messages include diagnostic information with regard to a cause of a SLO violation. Some embodiments further include storing data representative of system performance and detected and forecast system SLO states. This data can then be used to generate reports of system performance including representations of system SLO states.
摘要翻译： 用于执行自动诊断和识别或预测服务级对象状态的系统，方法和软件。 一些实施例包括基于收集的度量数据建立分类器模型以检测和预测服务水平目标（SLO）违规。 一些这样的系统，方法和软件还包括自动检测和预测SLO违规以及向管理员或系统组件提供警报，消息或命令。 一些这样的消息包括关于SLO违规的原因的诊断信息。 一些实施例还包括存储表示系统性能的数据和检测和预测系统SLO状态。 然后，该数据可用于生成系统性能的报告，包括系统SLO状态的表示。
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公开(公告)号：US20170136362A1
公开(公告)日：2017-05-18
申请号：US15351190
申请日：2016-11-14
申请人： Jason Bucher , Alexandros Ntoulas , Xinxian Huang , Brett Bauleke , Moises Goldszmidt , Samer Ead
发明人： Jason Bucher , Alexandros Ntoulas , Xinxian Huang , Brett Bauleke , Moises Goldszmidt , Samer Ead
CPC分类号： A63F13/67 , A63F13/46 , A63F13/79 , A63F13/798
摘要： A system for automated tuning of a computer-implemented game is configured to enable definition of a performance metric indicative of player performance in a computer-implemented game that has tunable gameplay parameters. A performance target is defined that represents target values for the performance metric during progress in the game. The system executes a gameplay simulation using an automated player, and performs an iterative tuning operation based on results of the simulation. The tuning operation automatically determines a suggested value set for the tunable parameters.
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公开(公告)号：US07949745B2
公开(公告)日：2011-05-24
申请号：US11554935
申请日：2006-10-31
申请人： Paul Barham , Richard Black , Moises Goldszmidt , Rebecca Isaacs , John MacCormick , Richard Mortier
发明人： Paul Barham , Richard Black , Moises Goldszmidt , Rebecca Isaacs , John MacCormick , Richard Mortier
IPC分类号： G06F15/173
CPC分类号： H04L41/0645 , H04L41/142 , H04L41/16
摘要： An activity model is generated at a computer. The activity model may be generated by monitoring incoming and outgoing data in the computer. The collected data is analyzed to form a graph that describes and predicts what output is generated in response to received input. Later, a window of input and output data is collected from the computer. This collected window of data is used to query the activity model. The graph in the activity model is then used to give the probability that the collected window of data was collected from the computer used to generate the activity model. A high probability indicates that the computer is performing normally, while a low probability indicates that the computer may behaving erratically and there may be a problem with the computer.
摘要翻译： 在计算机上生成活动模型。 可以通过监视计算机中的传入和传出数据来生成活动模型。 分析所收集的数据以形成描述并预测响应于接收到的输入产生什么输出的图。 之后，从计算机收集输入和输出数据的窗口。 该收集的数据窗口用于查询活动模型。 然后使用活动模型中的图表给出从用于生成活动模型的计算机收集数据收集窗口的概率。 高概率表示计算机正常运行，而低概率表示计算机可能运行不规律，并且计算机可能存在问题。
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