Server performance detection method, device and system and medium
A detection method and server technology, which is applied in the fields of information security and artificial intelligence, can solve the problems of inability to correctly judge abnormalities, consume manpower, positive and negative sample deviations, etc., and achieve the goal of avoiding incomplete coverage of time series models, high timeliness, and accurate judgment results Effect
Pending Publication Date: 2020-11-13
INDUSTRIAL AND COMMERCIAL BANK OF CHINA +1
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[0003] In the process of realizing the concept of the present disclosure, the inventors found that at least the following problems exist in the prior art: the first type of solution manually sets thresholds for various performance indicators, which is inaccurate and labor-intensive; the timing model in the second type of solution The data is required to have a certain regularity. In some special scenarios, such as various promotions such as Double 11, Double 12, and June 18, when the system load increases significantly, it is impossible to correctly judge the abnormality; the third type of solution is passed When the supervised machine learning model judges the abnormality, the negative samples of the time node where the system abnormality occurs are far less than the normal positive samples of the system, there is a serious positive and negative sample deviation problem, which will lead to overfitting and the failure to find the abnormal problem
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[0028] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. It should be understood, however, that these descriptions are exemplary only, and are not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present disclosure.
[0029] The terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting of the present disclosure. The terms "comprising", "comprising", etc. used herein indicate the presence of stated features, ...
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The invention provides a server performance detection method, device and system and a medium, and relates to the technical field of information safety and artificial intelligence. The method comprisesthe following steps: collecting real-time service load data of a server and corresponding real-time performance data; inputting the real-time service load data into an exception detection model, wherein the exception detection model is a data model obtained by training based on the service load data of the server under the condition of normal operation and corresponding performance data; collecting real-time prediction performance data output by the anomaly detection model based on the real-time service load data; and determining an operation state of the server based on comparison between the real-time performance data and the real-time prediction performance data.
Description
technical field [0001] The present disclosure relates to the technical fields of information security and artificial intelligence, and more specifically, to a server performance detection method, device, system and medium. Background technique [0002] During the operation of the server, the service capability will be reduced due to hardware failures such as CPU and disk, and its availability will also be affected due to program problems running on it and unreasonable resource allocation. When the server is abnormal, the business carried on it will be affected, thereby reducing the service level. The solutions for server anomaly detection in the prior art mainly include three categories: the first category mainly sets security thresholds for regularly collected server performance indicators, and implements server anomaly detection by alarming when the threshold is exceeded. The second type is an anomaly detection method based on a time series model; when the server is runni...
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IPC IPC(8): G06F11/34G06N20/00
CPCG06F11/3447G06N20/00
Inventor 祝萍
Owner INDUSTRIAL AND COMMERCIAL BANK OF CHINA