Design And Implementation Of Mass Log Analysis System Based On ELK

In the era of big data,a large amount of log information is generated on enterprise servers every day,which contains a lot of important information related to enterprise products,and log files are scattered on various nodes in a distributed cluster environment,which greatly increases the difficulty of log collection.Therefore,there is an urgent need for a massive log analysis system to solve the above problems.The system can uniformly manage these massive log data scattered on various servers through big data technology,so as to analyze and extract valuable information.By investigating the research status of log analysis systems at home and abroad,combining the architecture of log analysis systems actually used in enterprises,comparing and learning the big data technologies commonly used in log analysis,and finally using the ELK technology stack combined with the current more popular big data technology to design and implement a set of log analysis system was established.The system mainly includes log collection module,log analysis module,data storage module and data visualization module.The log collection module collects and preprocesses the log files on each server in a unified manner;the log analysis module is divided into real-time log analysis and offline log analysis.The real-time log analysis is based on Spark technology to perform streaming analysis on logs,and the analysis results are completed within seconds,Which meets the requirements of real-time dynamic display of data,and offline log analysis also greatly improves the efficiency of log analysis by layering data and reduces the computing pressure of the server;the data storage module provides distributed real-time data storage and search function;the data visualization module uses two visualization methods,one is based on Kibana's original log display,which fits perfectly with Elasticsearch and can quickly filter out log information,and the other is based on ECharts analysis results display,The results can be displayed to users in real time through custom charts.Each module of the log system can run independently,with low coupling and high cohesion.Each module is deployed using a distributed cluster to meet the requirements of high availability and strong scalability.The analysis module of the system is divided into offline log analysis and real-time log analysis can perfectly meet the needs of log analysis in the enterprise.