Self-organized mapping model based cloud software performance exception error diagnosis method and system

Abstract

The invention discloses a self-organized mapping model based cloud software performance exception error diagnosis method. The method comprises the steps of tracking and recording system call information of to-be-detected software during running in a cloud environment; analyzing a system call sequence during software running in a virtual machine with a performance exception, and dividing a system call sequence corresponding to each process; according to the process system call sequence obtained by division, establishing a detection model and performing exception detection on a suspicious process; and calculating most related system calls in a process with an exception, and performing sorting and output. According to the method, a behavior during software running can be accurately and completely recorded, the automated modeling can be carried out, the exceptional system running process can be detected, and the system call related to the exceptional running process can be positioned more accurately. The invention aims to provide a method for automatically analyzing and positioning related system calls causing performance exception errors when the performance exception errors occur, thereby assisting developers to position and solve potential performance bugs in the software more quickly and efficiently.

Description

technical field [0001] The invention belongs to the field of computer software error diagnosis, and more specifically relates to a method and system for cloud software performance abnormality error diagnosis based on a self-organizing map model. Background technique [0002] In the cloud computing environment, abnormal performance errors have become one of the most concerned issues for users. System performance degradation caused by performance bugs will affect the quality of service to users, and even cause service level agreement violations, resulting in serious economic losses. But many times the diagnosis of performance bugs is very difficult. First of all, the triggering of performance bugs depends on specific inputs or special configurations, and will only appear under specific conditions, making it difficult to reproduce. Then, after a performance bug is triggered, error messages are rarely output, and relevant diagnostic information cannot be directly provided to d...

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Problems solved by technology

[0006] In view of the above shortcomings or improvement needs of the prior art, the present invention provides a cloud software performance abnormality error diagnosis method based on the self-organizing map model. A large amount of manual work cannot be effectively expanded, and it is difficult to locate the location where the exception occurs. Technical problems that cannot effectively help developers find out the cause of the exception

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