Fault root cause inference positioning method and device based on artificial intelligence

Abstract

The embodiment of the invention provides a fault root cause inference positioning method and device based on artificial intelligence. The method comprises the steps of determining an existing fault set through a preset logic analysis statement, wherein the fault set comprises all existing faults; obtaining a fault knowledge graph, wherein the fault knowledge graph comprises an association relationship between each fault and the corresponding fault root cause; determining a fault root cause corresponding to each fault in the fault set according to the root cause topological graph correspondingto the fault knowledge graph; and according to the fault root cause and a preset algorithm, determining a key node corresponding to the fault so as to carry out fault processing in time according to the key node. A derivation relation between faults is established through carding based on the knowledge graph and applying a preset artificial intelligence first-order logic algorithm. According to the method, rules are defined for the fault, the root cause is searched for according to the rules and the currently sampled data, and finally the fault root cause is visually displayed through the topological graph of the software, so that the fault root cause can be rapidly, timely and accurately positioned to facilitate the technicians to process in time.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a method, device, storage medium and processor for inferring and locating the root cause of a fault based on artificial intelligence. Background technique [0002] After enterprises go to the cloud, a large number of production applications are concentrated on the virtual servers in the data center. This is of course due to the huge efficiency improvement brought about by server virtualization, but how to ensure the health of these virtual servers, as well as the efficiency of diagnosis and resolution when problems occur are highlighted. [0003] In addition to the inherent problems of the application itself, host virtualization and virtual machine performance, system connectivity, and key services of virtual machines, etc., may cause service interruptions and even lead to global serious problems. [0004] To this end, most enterprises deploy professional monitoring so...

AI Technical Summary

Problems solved by technology

However, these methods focus on providing sufficient information for post-event analysis by operation and maintenance personnel, and have cert...

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