Active monitoring data pushing method of server

Abstract

The invention provides an active monitoring data pushing method of a server. The active monitoring data pushing method of the server is characterized in that a data active pushing agent system is installed on an operation system of the server so as to combine monitoring methods of various servers, unify monitoring data formats and send completed and readable monitoring data to a monitoring service end, the data active pushing agent system structurally comprises a data monitoring control center (1), a knowledge expansion module (2), a monitoring data management module (3), a monitoring data knowledge module (4) and a monitoring data memory module (5), the data active pushing agent system performs modularization processing on collection, collation, analysis and transmission of the monitoring data and performs expansion of monitoring modes, and the whole collection process of the monitoring data is completed by being globally controlled through the data monitoring control center. Furthermore, a user can install an agent program of the data active pushing agent system on the operation system of the server, and then collection, collation, analysis and display of complex monitoring data can be achieved.

Description

Technical field [0001] The present invention relates to the technical field of servers, in particular to a method for servers to actively push monitoring data. Background technique [0002] At present, with the development and application of cloud computing, the demand for hardware server equipment has evolved from the initial single or small demand method to the large-scale and large-volume demand method so far. [0003] For small-scale server clusters, in the process of collecting monitoring data in a traditional way, the complexity of the same type of monitoring data and the difficulty of analyzing the difference of different monitoring data are still acceptable, but if you are facing a large-scale server cluster, plus With the ever-changing monitoring methods and methods, traditional monitoring methods have encountered bottlenecks in the scalability and analytical difficulty. [0004] In order to solve the problems encountered by various servers in the process of collecting, sor...

AI Technical Summary

Problems solved by technology

[0003] For small-scale server clusters, in the process of collecting monitoring data in the traditional way, the complexity of similar monitoring data and the difficulty of parsing the differences of different monitoring data are still acceptable, but if faced with large-scale server clusters, coupled with With the ever-changing monitoring methods and methods, the traditional monitoring methods have encountered bottlenecks in terms of scalability and analysis difficulty

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