Cloud computing cluster monitoring method and system based on peak prediction

A monitoring system and cloud computing technology, applied in computing, hardware monitoring, error detection/correction, etc., can solve the problems of complicated codes, inability to fully adapt to server clusters, and many types of interfaces to achieve improved reliability and good user experience , the effect of reducing workload

Inactive Publication Date: 2020-05-22
XI AN JIAOTONG UNIV
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Problems solved by technology

[0004] At present, the commonly used data collection methods mostly use comprehensive and complex collection tools. Due to the shortcomin

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  • Cloud computing cluster monitoring method and system based on peak prediction
  • Cloud computing cluster monitoring method and system based on peak prediction
  • Cloud computing cluster monitoring method and system based on peak prediction

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[0045] In order to detect various important indicators efficiently and conveniently, it is necessary to implement a monitoring platform that integrates three modules of data collection, data sending and receiving, and data storage, and combines indicator prediction algorithms to further improve the reliability of the entire system.

[0046] Among them, the data stored in the data storage module is time series data. Since the situation of time series data is stable and regular, the time series can be reasonably extended. Under normal circumstances, exponential smoothing is used to predict this type of data. The basic idea is: the predicted value is the weighted sum of the previous observations, and different weights are given to different data, new data is given a larger weight, old data Give a smaller weight.

[0047] The exponential smoothing method is divided into three categories according to the number of smoothing: the first exponential smoothing, the second exponential smooth...

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Abstract

The invention discloses a cloud computing cluster monitoring method and system based on peak prediction. The system comprises a data acquistion module, a data sending and receiving end and a data storage end; the data acquisition module is responsible for acquiring performance information and service of each node server system, a Docker container, a Ceph distributed file system and the like; the CPU utilization rate, the memory utilization rate, the disk utilization rate, service state and the log of a current node server, the resource occupation condition of a Docker container, the Ceph running state, the cluster information and the like are periodically and dynamically acquired; the data sending and receiving end is responsible for sending various types of information collected by the data collection end to the management node, and the data sending and receiving end runs on the management node and monitors and receives real-time data sent by each node server; and the data storage endadopts a whisper as a storage rear end, and uses a time sequence database to store the data received by the management node. According to the method, prediction analysis can be accurately carried out, so that possible problems in the cluster are estimated, the maintenance cost is effectively reduced, and the stability and reliability of the cluster server are improved.

Description

technical field [0001] The invention belongs to the technical field of monitoring, and in particular relates to a cloud computing cluster monitoring method and system based on peak value prediction. Background technique [0002] As cloud computing technology is more and more applied to various fields of the information industry, the demand for monitoring and management of server clusters in the cloud computing environment is increasing. The cluster server system under cloud computing is mainly composed of a series of server clusters based on distributed architecture. To manage the cluster server system well and ensure its high-performance operation, an effective cloud computing cluster monitoring system is necessary to monitor and monitor it. regulation. [0003] In order to facilitate users' monitoring and management of server clusters based on embedded hardware and enhance the stability of the entire cluster, an effective and highly reliable cloud resource monitoring syst...

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Application Information

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IPC IPC(8): G06F11/30
CPCG06F11/3006G06F11/3051
Inventor 伍卫国孙岚子康益菲杨晓曦刘钊华李祯华
Owner XI AN JIAOTONG UNIV
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