Fault root cause positioning method of micro-service system

Abstract

The invention discloses a fault root cause positioning method for a micro-service system, which comprises the following steps of: acquiring call chain data in the micro-service system in real time, converting the call chain data into four business indexes and monitoring in real time, when an exception is found, constructing a service topological graph, a process topological graph and a host topological graph by using a call chain in an exception time period, calculating an abnormal score of each node on the topological graph, and finally positioning to a root cause node, namely a process node or a host node, according to a sequence from large depth to small depth and from process to host. According to the obtained call chain data, the topological relation of the host level can be dynamically constructed, the topological relation of the process level and the topological relation of the service level can also be dynamically constructed, and data guarantee is provided for more accurate root cause positioning. According to the method, the call chain data in the abnormal time period are analyzed in real time by utilizing an unsupervised algorithm, and training data and labels are not needed.

Description

technical field [0001] The invention relates to the technical field of computer applications, in particular to a method for locating the root cause of a fault in a microservice system. Background technique [0002] With the popularization and extensive use of microservice systems, the root cause location method based on alarm data cannot adapt to the dynamic changes of microservice systems, and most of them build static service dependencies based on CMDB data. However, most of the existing data call chain collection tools can only obtain the dependencies between services, and cannot obtain the process information and host information of each service in real time. Therefore, most root cause location solutions based on call chains can only locate root cause failures. Service, cannot be specific to the process or host where the root cause service resides. [0003] In some existing technical solutions, CMDB data or TCP / IP data are needed to construct the topological relationshi...

AI Technical Summary

Problems solved by technology

[0002] With the popularity and extensive use of microservice systems, the root cause location method based on alarm data cannot adapt to the dynamic changes of microservice systems, and most of them build static service dependencies based on CMDB data

However, most of the existing data call chain collection tools can only obtain the dependencies between services, and cannot obtain the process information and host information of each service in real time. Therefore, most root cause location solutions based on call chains can only locate root cause failures. service, cannot be specific to the process or host where the root cause service resides

[0003] In some existing technical solutions, CMDB data or TCP / IP data are needed to construct the topological relationship at the host level, which cannot adapt to the dynamically changing connection relationship between hosts in the microservice system

Moreover, this type of data does not have process information and service information, so it cannot be located more accurately, that is, it cannot accurately locate the fault of which process or service on the host

[0004] In some existing technical solutions, the use of alarm information for root cause location requires learning and training based on a large amount of historical alarm data, which not only cannot be accurately located in the initial stage of positioning system deployment, but also cannot adapt to the dynamic changes of the microservice system.

[0005] In some existing technical solutions, only the average time-consuming and error rate are used to find abnormal time periods based on business indicators

Images