基于Docker的大规模日志采集与分析系统

传统日志分析技术在处理大规模日志时存在效率低、功能简单、实际应用扩展性弱等问题.为解决这些问题，设计了基于Docker的大规模日志采集与分析系统.系统分为数据采集、数据缓存、数据转发、数据存储、数据检索和展示五层，支持从不同数据源采集各种类型的日志，通过Kafka消息队列提供可靠数据传输，利用Elasticsearch实现数据分布式存储和检索，并以可视化方式分析日志.同时采用Docker容器技术实现系统的快速部署和版本控制.该系统具有实时性、可扩展性、易部署等特点.实验结果表明了该系统可行有效，具有良好的实用价值.

Large-Scale Log Collection and Analysis System Based on Docker

The traditional log analysis technology has low efficiency, simple function, poor scalability in practice in processing the large-scale log. To solve these problems, a large-scale log collection and analysis system based on Docker is designed. There are five layers including data collection, data cache, data forwarding, data storage, data retrieval and display in the system. And the system can take in any type of log files from different data sources, provide reliable data transmission through Kafka message queue, utilize Elasticsearch to realize distributed storage and retrieval of data, and analyze log by means of visualization. Meanwhile, the use of docker container technology can realize rapid deployment and version control of the system. The system has the characteristics of real-time, scalability, easy deployment and so on. The experimental results show that the system is feasible and effective with good practical value.