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Methods and systems to detect business disruptions, determine potential causes of those business disruptions, or both

机译:用于检测业务中断,确定这些业务中断的潜在原因或两者的方法和系统

摘要

Multivariate analysis can be performed to determine whether a computing environment is encountering a business disruption (e.g., relatively long end-user response times) or other problem. Cluster analysis (comparing more recent data with a particular cluster of good operating data), predictive modeling, or other suitable multivariate analysis can be used. A probable cause analysis may be performed in conjunction with the multivariate analysis. A probable cause analysis may be used when one or more abnormal instruments, abnormal components, abnormal load patterns, suspicious actions (such as resource provisioning or deprovisioning activities), software or hardware updates or failures, recent changes to the computing environment (component provisioning, change of a control, etc.), or any combination thereof. The probable cause analysis can include ranking potential causes based on likelihood, and such ranking can include statistical analysis, policy violations, recent changes to the computing environment, or any combination thereof.
机译:可以执行多变量分析以确定计算环境是否遇到业务中断(例如,相对长的最终用户响应时间)或其他问题。可以使用聚类分析(将较新的数据与良好运行数据的特定聚类进行比较),预测模型或其他合适的多元分析。可能的原因分析可以与多元分析结合进行。当一个或多个异常工具,异常组件,异常负载模式,可疑动作(例如资源供应或取消供应活动),软件或硬件更新或故障,计算环境的最新更改(组件供应,控件等的更改,或其任意组合。可能原因分析可以包括基于可能性对潜在原因进行排名,并且这种排名可以包括统计分析,策略违规,对计算环境的最新更改或其任意组合。

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