Root cause positioning method and device, storage medium and electronic equipment

Abstract

The invention relates to the field of computer processing, in particular to a root cause positioning method, a root cause positioning device, a storage medium and electronic equipment. The root cause positioning method comprises the following steps: when service abnormality detection is performed based on calling index data of a called service device in a device calling pair to obtain a result of service abnormality, obtaining service abnormality detection information; performing dependency anomaly detection based on dependency index data of dependency equipment corresponding to the abnormal service equipment in the service anomaly detection information to obtain dependency anomaly detection information; constructing an exception attribute graph according to the service exception detection information and the dependency exception detection information; and when a plurality of abnormal service devices exist, calculating a root cause score of each abnormal service device by using the abnormal attribute graph, and sorting based on the root cause score of each abnormal service device to obtain a service device root cause sorting result. According to the root cause positioning method provided by the invention, fault root cause positioning of the equipment in the system can be accurately and quickly carried out.

Description

Technical field

[0001] The present disclosure relates to the field of computer processing, specifically to root cause positioning methods, root cause positioning devices, storage media and electronic devices. Background

[0002] Service system anomalies can be caused by a variety of reasons, sometimes because of network jitter, sometimes because of machine failures, and sometimes even because of human changes. Therefore, effective root cause localization can better trace abnormal traceability and quickly locate problems.

[0003] With the rapid development of artificial intelligence, more and more machine learning algorithms are applied to fault location. In practical applications, you can process the data, use inductive algorithms to generate readable rules and decision trees, and then use decision trees to analyze new data, but with the update of software and hardware, the growth of business scale, will lead to the failure of analysis rules, inductive algorithms to generate rea...

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