Research And Implementation Of Integrated Maintenance Monitoring And Management System

With the advent of the Internet Plus concept and the rise of big data and cloud computing,numerous traditional industries fully embrace the Internet and gradually carry out information system construction and transformation.Howerver,when people enjoy convenience and benefits of the Internet,how to maintain these complex information systems,especially in the case of large flow,big data and high load,and ensure that the system can run smoothly present a great challenge to policy makers in various industries and maintainers of various information sectors.Therefore,in this thesis,a kind of operation and maintenance monitoring and management system is designed and realized,which can regularly collect information about production servers,database servers and middleware and provide users with data reports,alarm and other functions to reduce the difficulty of user operation and maintenance work.The thesis firstly introduces the research background and significance of this operation and monitoring system and then elaborates the design and implementation detail about this system's core data collecting services.The main contents are as follows:1)Multi-monitoring target data acquisition is achieved.The system uses the combination of pull and push mode to monitor IT infrastructures,databases(My SQL,Oracle,SQL Server),common middlewares(Redis,Docker,Rabbit MQ).What's more,in order to ensure the high availability of collecting services,the registration and backup of these services based on Zoo Keeper is completed.2)High scalable monitoring data storage service is accomplished.Thanks to Rabbit MQ,the data acquisition and storage services are decoupled.Users can improve system throughput based on current load conditions by deploying multiple storage services.3)The efficient historical monitoring data query system is completed.In view of the frequent user queries on recent historical monitoring data,a efficient cache system based on Redis is designed and implemented.4)A data forecasting model is established,which can predict machine resource usage and load.The data prediction module is designed and implemented,which can make a reasonable prediction for the common machine resources and help users prevent and reduce perational risk in advance.Finally,all the above research contents are carried out and the system is completed and tested.Then the results are given.It shows that it is outstanding in ease of use and service stability,which can greatly reduce the workload of operation and maintenance personnel,promote its efficiency and improve the economic efficiency of enterprises.