Operation and maintenance alarm system and method

Abstract

The invention provides an operation and maintenance alarm system and method. The system comprises an off-line model training module, an on-line detection module and an alarm module, wherein the off-line model training module is used for updating required parameters of a detection algorithm used by the online detection module on the basis of machine learning and detecting the distribution of index data on the basis of analysis results of historical data, the on-line detection module is used for receiving index data to be detected and detecting the index data by using a preset detection algorithm on the basis of prediction results of the index data distribution, and the alarm module determines whether to give an alarm or not on the basis of preset alarm rules according to a detection result of the on-line detection module. The operation and maintenance alarm system and method can achieve the automatic operation and maintenance alarm.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an operation and maintenance alarm system and method. Background technique [0002] With the rapid development of the network, there have been network systems that need to serve a large number of users. These network systems have a large number of computers (servers) or computing resources distributed in various addresses, and these computers or computing resources are usually constructed as clusters to serve users. As more and more computers or computing resources provide services, it is very important to monitor various indicators of these computers or computing resources and to give timely and accurate alarms when failures occur. [0003] Taking the data center system as an example, it is necessary to monitor various indicators of the computers and computing resources in the data center, so as to discover abnormal conditions in the data center system, so that the operation ...

AI Technical Summary

Problems solved by technology

In addition to requiring a lot of manpower, manually viewing operation and maintenance indicators is also very easy to miss abnormal situations in a large amount of data, and when the amount of data increases to a certain level, it becomes unfeasible to rely on manual viewing

The method of setting a fixed threshold for monitoring requires setting a reasonable threshold for each indicator. When the number of indicators is huge, this method is not feasible

In addition, the method of setting a fixed threshold can only alarm for abnormal conditions that meet simple rules. In a complex actual production environment, it is easy to generate a large number of false alarms.

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