Fault root cause positioning method and system for micro-service architecture information system

Abstract

The invention discloses a fault root cause positioning method and system for a micro-service architecture information system. The system comprises an index data collection module, an anomaly detection module, a micro-service dependence graph construction module and a reverse tracking module. A root cause positioning algorithm based on a fault propagation chain model is designed by establishing a dynamic correlation analysis method between micro-services, the propagation process of related faults is identified while the fault root cause service is positioned, the interpretability of fault positioning and diagnosis is improved, and the method can be applied to a micro-service architecture information system and is high in practicability. The accuracy of dynamic association modeling in the micro-service architecture information system is improved, the use convenience of a fault diagnosis tool of the micro-service architecture information system is improved through a micro-service performance index data driving method, and the deployment time and energy are saved.

Description

technical field [0001] The invention belongs to the field of information technology, and relates to a fault diagnosis technology of an information system, in particular to a method and a system for locating the root cause of a fault in a microservice architecture information system. Background technique [0002] The fault diagnosis of the existing microservice architecture information system mainly adopts the method of constructing the dependency graph of microservices. Related works include: ADD[1], Orion[2], MonitorRank[3], Sieve[4], Microscope[5] ], CloudRanger[6]. Among them, Orion [2] constructs correlations by analyzing network traffic delay distribution between services, and diagnoses service and instance failures of the system. Both MonitorRank[3] and Sieve[4] use service call records and performance index data. The former uses correlation coefficients and second-order random walks to diagnose service faults, while the latter uses the analysis method of Granger caus...

AI Technical Summary

Problems solved by technology

Methods By adopting a new modeling method and establishing a dynamic association analysis method between microservices, it overcomes the problem that the service dependency relationship in the existing microservice architecture information system fault diagnosis technology can only be static; the design is based on the fault propagation chain model The unique root cause location algorithm provides the specific propagation process of related faults while locating the root cause of the fault service, which improves the interpretability of fault diagnosis

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