Intelligent monitoring method for data center system

Abstract

The invention relates to an intelligent monitoring method for a data center system, which comprises the following steps of: acquiring information of an application cluster to be monitored, and initializing an association table of the application cluster to be monitored; constructing a multi-process pool; acquiring historical information data of the to-be-monitored equipment according to a plurality of sub-processes established in the multi-process pool; preprocessing the obtained historical information data of the to-be-monitored equipment; constructing a time sequence prediction model, and performing real-time prediction on the system basic information in combination with the preprocessed historical information data of the to-be-monitored equipment to obtain a system basic information prediction curve; establishing a dynamic security baseline band of the system basic information, and combining the system basic information prediction curve to obtain abnormal data; and returning the abnormal data to the user. Compared with the prior art, the method has the advantages that the operation efficiency can be effectively improved, the human resource cost can be reduced, and abnormal data can be accurately and quickly monitored and obtained on the premise of meeting the alarm timeliness requirement.

Description

technical field [0001] The invention relates to the technical field of system operation and maintenance, in particular to an intelligent monitoring method for a data center system. Background technique [0002] The IT center of an enterprise is usually a huge data center, and a large number of devices are purchased to support business systems. As the cornerstone of various services, the data center not only needs to manage a wide range of business systems, but also is responsible for the operation and maintenance of all equipment, and is also responsible for the operation and monitoring of hundreds of billions of business every year. There are many system platforms and equipment, and tens of thousands of equipment. The volume poses a higher challenge to the monitoring mechanism. [0003] In the research of intelligent operation and maintenance, in order to ensure that users can be informed of abnormal situations in a timely manner, it is particularly important to monitor th...

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Problems solved by technology

[0004] However, in the process of engineering implementation of complex scenarios, the above-mentioned method is likely to change in timeliness, and the expected alarm effect cannot be achieved.

This is because there are tens of thousands of servers monitored in the data center, and about a thousand of them need to be focused on. When using the time series model to predict system performance indicators, as the number o

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