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Server error diagnosis method based on supervised learning

A technology of supervised learning and error diagnosis, applied in neural learning methods, error detection/correction, instruments, etc., can solve problems such as inflexible and cumbersome methods, and achieve simple and efficient configuration methods, free time and cost, and flexible testing methods

Inactive Publication Date: 2018-10-26
ZHENGZHOU YUNHAI INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] 1. This method of setting a fixed value to detect faults is very inflexible. It is suitable for a variety of devices and must be configured differently for different environments, which is cumbersome.

Method used

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  • Server error diagnosis method based on supervised learning
  • Server error diagnosis method based on supervised learning

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Embodiment 1

[0049] A server error diagnosis method based on supervised learning, by collecting a large amount of existing fault information as the training set of the supervised learning model, training it, and then deploying this model on the server host to be monitored Predictive analysis of faults and errors and automatic reporting.

[0050] Specific steps:

[0051] S1. Collect server failure information;

[0052] S2. Classify the collected fault information, first classify according to the fault type, and then divide each type of fault information into two parts: input group and output group;

[0053] S3, dividing the collected fault information into a training set and a test set;

[0054] S4. Organize the fault information of the input group and the output group into a supervised learning model;

[0055] S5. Use the training set to train the supervised learning model, and use the test set to test the accuracy of the supervised learning model;

[0056] S6. Screening a supervised l...

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Abstract

The invention discloses a server error diagnosis method based on supervised learning. The method specifically includes: utilizing massive fault information to train a supervised-learning model to generate a fault prediction model, and utilizing a fault prediction model for prediction analysis on errors of a server. According to the server error diagnosis method based on supervised learning of theinvention, limitation of traditional methods of setting thresholds to detect faults is broken, a highly efficient algorithm is utilized to automatically analyze and predict log contents, time costs ofmanual server fault diagnosis are released, and fault levels are fully automatically analyzed and predicted.

Description

technical field [0001] The invention relates to the technical field of server fault management, in particular to a method for diagnosing server faults based on supervised learning. Background technique [0002] A running server is carrying countless business traffic all the time and will generate a lot of data. Although the server is a very stable product, with the increase of running time and changes in the surrounding physical environment (such as heat dissipation, etc.), it will inevitably have a certain impact on the server. The risk of downtime, so the ability to predict various failures that may occur on the server has become a very valuable research direction. [0003] At present, the fault analysis of the server generally monitors specific indicators, such as temperature, fan speed, and some other hardware or software indicators, and sets a certain threshold for judgment. After a certain limit is exceeded, the server will automatically report the fault. . [0004]...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/22G06F11/26G06F11/30G06N3/08
CPCG06F11/2263G06F11/26G06F11/3058G06N3/08
Inventor 梁盛楠
Owner ZHENGZHOU YUNHAI INFORMATION TECH CO LTD
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