1. Brief introduction
ELK is a set of log collection tools. As the name suggests, ELK includes three open source tools, namely elasticsearch, logstash, and kibana. Among them, elasticsearch is a search and data analysis engine, and Logstash is a free and open server-side data processing pipeline. Capable of ingesting data from multiple sources, Kibana is a free and open user interface for visualizing Elasticsearch data.
ELK has a variety of architectures for deployment. Different architectures can be selected according to the size of the data volume and server requirements. Some architectures also need to use message queue middleware, such as kafka or redis, for data persistence and to prevent log data loss. This situation.
2. Elasticsearch cluster
2.1 Pull the image
Install elasticsearch, the current selection is version 7.2.0
docker pull elasticsearch:7.2.0
2.2 Create a cluster directory
Create es1, es2, es3 cluster directories:
[root@localhost ~]# mkdir -p /data/elk/es1/data
[root@localhost ~]# chmod -R 777 /data/elk/es1/data
[root@localhost ~]# mkdir -p /data/elk/es2/data
[root@localhost ~]# chmod -R 777 /data/el