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    • 61. 发明授权
    • Time series metric data modeling and prediction
    • 时间序列量度数据建模与预测
    • US09323599B1
    • 2016-04-26
    • US14814815
    • 2015-07-31
    • AppDynamics, Inc.
    • Arjun IyerYuchen Zhao
    • G06F11/00G06F11/07
    • G06F11/079G06F9/45508G06F11/0706G06F11/0751G06F11/30G06F11/3452G06F2201/81G06F2201/875G06N7/005
    • A system that utilizes a plurality of time series of metric data to more accurately detect anomalies and model and predict metric values. Streams of time series metric data are processed to generate a set of independent metrics. In some instances, the present system may automatically analyze thousands of real-time streams. Advanced machine learning and statistical techniques are used to automatically find anomalies and outliers from the independent metrics by learning latent and hidden patterns in the metrics. The trends of each metric may also be analyzed and the trends for each characteristic may be learned. The system can automatically detect latent and hidden patterns of metrics including weekly, daily, holiday and other application specific patterns. Anomaly detection is important to maintaining system health and predicted values are important for customers to monitor and make planning and decisions in a principled and quantitative way.
    • 利用多个时间序列度量数据来更精确地检测异常并建模和预测度量值的系统。 处理时间序列量度数据流以生成一组独立度量。 在某些情况下,本系统可以自动分析数千个实时流。 高级机器学习和统计技术用于通过学习潜在和隐藏的度量标准,从独立度量中自动找出异常值和异常值。 还可以分析每个度量的趋势,并且可以了解每个特征的趋势。 该系统可以自动检测包括每周,每日,假期和其他应用程序特定模式的潜在和隐藏的度量模式。 异常检测对维护系统健康至关重要,预测值对客户来说是重要的,以原则和定量的方式监控和制定规划和决策。
    • 63. 发明申请
    • CUSTOM CORRELATION OF A DISTRIBUTED BUSINESS TRANSACTION
    • 分销业务交易的自定义关联
    • US20150067146A1
    • 2015-03-05
    • US14018349
    • 2013-09-04
    • AppDynamics, Inc.
    • Todd RakerSuraj PuvvadaManoj AcharyaVinay Srinivasaiah
    • H04L12/26
    • G06F11/3068G06F11/3006G06F11/3495G06F2201/865G06F2201/87G06F2201/875
    • A mechanism is provided for customizing communication of correlation data between servers using a custom or proprietary communication protocol. The system may modify a payload transmitted between servers to include monitoring parameters. The payload may be modified by expanding a portion of the payload or otherwise inserting data into the payload. The portion may include a header, footer, an additional property, a field, or other portion of the header. A mechanism may detect both outgoing calls and incoming requests to either modify the request with the payload or retrieve the payload from the request. The configuration preferences received from a user may be used to process the detected calls and modify a payload at a designed portion suitable to be expanded. Once sent, the configuration parameters may be used by a recipient server to detect the request with the modified payload and retrieve the monitoring parameter. The monitoring parameter may be used to correlate distributed transactions that occur over a set of servers which communicate with non-standard protocols.
    • 提供了一种用于使用自定义或专有通信协议自定义服务器之间的相关数据的通信的机制。 系统可以修改在服务器之间传输的有效载荷以包括监视参数。 可以通过扩展有效载荷的一部分或以其他方式将数据插入有效载荷来修改有效载荷。 该部分可以包括报头,页脚,附加属性,字段或报头的其他部分。 机制可以检测出呼叫和传入请求,以便用有效载荷修改请求或从请求中检索有效载荷。 可以使用从用户接收的配置偏好来处理检测到的呼叫并修改在适于被扩展的设计部分的有效载荷。 一旦发送,接收方服务器可以使用配置参数来检测具有修改的有效载荷的请求并检索监视参数。 监视参数可用于将在与非标准协议通信的一组服务器上发生的分布式事务相关联。
    • 66. 发明申请
    • PERFORMING CALL STACK SAMPLING
    • 执行呼叫堆栈采样
    • US20140068068A1
    • 2014-03-06
    • US14071523
    • 2013-11-04
    • AppDynamics, Inc.
    • Jyoti BansalBhaskar Sunkara
    • H04L12/26
    • H04L43/04H04L43/022H04L43/045H04L43/10H04L43/16H04L67/02H04L67/22
    • The present technology may determine an anomaly in a portion of a distributed business application. Data can automatically be captured and analyzed for the portion of the application associated with the anomaly. By automatically capturing data for just the portion associated with the anomaly, the present technology reduces the resource and time requirements associated with other code-based solutions for monitoring transactions. A method for sampling an application thread to monitor a request may begin with detecting a diagnostic event with respect to the processing of a request. A thread call stack associated with the request may be sampled in response to detecting the diagnostic event. A state of the call stack may be stored with timing information based on the sampling. The call stack state and timing information may be transmitted to a remote server.
    • 本技术可以确定分布式业务应用的一部分中的异常。 与异常有关的部分应用程序可以自动捕获和分析数据。 通过自动捕获与异常相关的部分的数据,本技术减少与用于监视事务的其他基于代码的解决方案相关联的资源和时间要求。 用于对应用线程进行采样以监视请求的方法可以从检测关于请求的处理的诊断事件开始。 响应于检测到诊断事件,可以对与请求相关联的线程调用栈进行采样。 可以基于采样来存储具有定时信息的呼叫栈的状态。 呼叫栈状态和定时信息可以被发送到远程服务器。