Design And Implementation Of Intelligent Operation And Maintenance Platform For Bank System Based On ES

With the construction of social informatization,online banking has become the mainstream,and the rate of electronic replacement is getting higher and higher,and there are more and more banking systems to meet customer needs.At the same time,with the continuousexpansion of the bank's customers,businesses and systems,the banking system has accumulated a large amount of log information,which is of great significance to ensure the robustness and stability of the banking system.How to effectively collect,analyze,store and manage the log of the banking system is very important to the development of the bank.The analysis process of the log requires rapidity and timeliness.It requires a lot of time and labor costs to follow up,which brings great trouble to the operation and maintenance of the banking system.After an in-depth investigation of a city commercial bank,this paper designs and implements of intelligent operation and maintenance platform for bank system based on Elasticsearch(ES)technology.This paper takes the mass logs generated by thousands of production servers of a city commercial bank as the basic data,and combines the characteristics of the banking system and the requirements for improved system operation and maintenance capabilities.The main work of this paper includes:(1)Designing and implementing the data collection and analysis platform for the banking system.Based on the business system log data collection of the city commercial bank,the log data collection of middleware,host,load balancer,firewall,database and operating system level is added.Through the real-time analysis and calculation,the original data extraction,cleaning,conversion and integrationare completed.After,unstructured,semi-structured,and mixed-type data is refined and applied to operation and maintenance management,at the same time,the security and integrity of the data are guaranteed.(2)Research the key technologies of real-time collection,analysis,search and storage of massive logs,and use powerful Elasticsearch technology to realize real-time and efficient searchand storage of massive logs.At the same time,these stored large amounts of data will be used for system problem location,search,analysis,intervention,resolution and prediction,thereby improving the efficiency and service level of each system operation and maintenance.(3)The study used Kibana to visualize the real-time monitoring of Elasticsearch stored data,and realize efficient page retrieval Elasticsearch stored data throughKibana visualization page.(4)Realize intelligent shop to assistoperation and maintenance.In this paper,the time series prediction algorithm Prophet is used to analyze the data anomaly,observe the trend of the data,and judge whether it is within the acceptable range under normal conditions.If the actual value exceeds the normal value,the administrator should pay attention to be prepared to respond positively,reduce the abnormal paralysis time of the system and ensure the smooth and safe operation of the system.The abnormal and timely alarm mechanism is completed,which effectively improves the operation and maintenance efficiency and the efficiency of troubleshooting.