A method of dynamically adjusting monitoring frequency suitable for cloud computing

Abstract

The invention relates to the technical field of cloud computing, in particular to a monitoring frequency dynamic adjustment method suitable for cloud computing. The method comprises the steps that monitoring frequency related parameters are set, and a stable variation coefficient is calculated through a stable variation coefficient formula after sampling; the stable variation coefficient is compared with a frequency adjustment threshold value; whether the monitoring frequency is increased or decreased or maintained is determined according to the comparison result. According to the method, the dynamic adjustment problem of the monitoring frequency of all resources of a virtual machine in cloud computing is solved; the method can be used for monitoring the virtual machine.

Description

technical field [0001] The invention relates to the technical field of cloud computing management, in particular to a method for dynamically adjusting monitoring frequency applicable to cloud computing. Background technique [0002] With the development of cloud computing, the scale of a single cloud platform is gradually expanding. In order to facilitate management and operation and maintenance, it is usually developed to monitor various resources of virtual machines, such as CPU utilization, memory utilization, IO utilization, etc. Various resource usage monitoring items; the cloud platform will record each monitoring data to the database or file server for easy reference by operation and maintenance personnel. These historical monitoring data usually allow the operation and maintenance personnel to discover the abnormal situation of the virtual machine in time; however, as the number of virtual machines increases, the historical monitoring data shows an explosive growth; ...

AI Technical Summary

Problems solved by technology

[0004] 2. Individual virtual machines do not monitor data, and applications with relatively low pressure such as individual websites reduce monitoring or even do not monitor performance indicators;

[0007] 1. It is easy to collect useless data by reducing the monitoring frequency. Generally, abnormal performance will have special fluctuations within 60 minutes.

[0008] 2. Individual virtual machines cannot provide operation and maintenance personnel with accurate information on virtual machine performance without collection methods

[0009] 3. Custom monitoring frequency is difficult to control. There is no clear way to judge when and what frequency should be set. Judging purely by the experience of operation and maintenance personnel usually leads to invalid settings

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