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Method And System For Real-Time Causality And Root Cause Determination Of Transaction And Infrastructure Related Events Provided By Multiple, Heterogeneous Agents

机译:多个异构代理提供的事务和基础结构相关事件的实时因果关系确定方法和系统

摘要

A method is disclosed that estimates causal relationships between events based on heterogeneous monitoring data. The monitoring data consists in transaction tracing data, describing the execution performance of individual transactions, resource utilization measurements of infrastructure entities like processes or operating systems and network utilization measurement data. A topology model of the monitored environment describing its entities and the communication activities of these entities is incrementally created. The location of occurred events in the topology model is determined. The topology model is used in conjunction with a domain specific causality propagation knowledge base to calculate the possibility of causal relationships between events. Different causality determination mechanisms, based on the type of involved events are used to create graphs of causal related events. A set of root cause events, representing those events with greatest global impact on all other events in an event graph is calculated for each identified event graph.
机译:公开了一种基于异构监视数据来估计事件之间的因果关系的方法。监视数据包含事务跟踪数据,这些数据描述单个事务的执行性能,基础结构实体(如流程或操作系统)的资源利用率度量以及网络利用率度量数据。逐步创建描述其实体以及这些实体的通信活动的受监视环境的拓扑模型。确定发生的事件在拓扑模型中的位置。拓扑模型与领域特定因果关系传播知识库一起使用,以计算事件之间因果关系的可能性。基于所涉及事件的类型,不同的因果关系确定机制用于创建因果相关事件的图。对于每个已识别的事件图,将计算一组根本原因事件,这些事件代表事件图中所有其他事件具有最大的全局影响的那些事件。

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