docker-compose搭建ELK

github已经有人弄好了，直接clone一下，

git clone https://github.com/deviantony/docker-elk.git

进入kibana目录kibana.yml修改密码，注意字符串加引号。

再进入docker-compose.yml修改es密码，注意字符串加引号。

# 启动
docker compose up -d

tips:

1. 拉取docker.elastic.co的镜像贼慢，建议换成阿里云或其他国内镜像。
2. es插件可以下载到elasticsearch/plugins，然后挂载一下，或者构建镜像过程中copy进去。

下面是我修改的docker-compose.yml，可供参考。

version: '3.2'

services:
  elasticsearch:
    build:
      context: elasticsearch/
      args:
        ELK_VERSION: $ELK_VERSION
    volumes:
      - type: bind
        source: ./elasticsearch/config/elasticsearch.yml
        target: /usr/share/elasticsearch/config/elasticsearch.yml
        read_only: true
      - type: volume
        source: elasticsearch
        target: /usr/share/elasticsearch/data
    # 增加 es 插件  
      - type: bind
        source: ./elasticsearch/plugins
        target: /usr/share/elasticsearch/plugins
    ports:
      - "9200:9200"
      - "9300:9300"
    environment:
      ES_JAVA_OPTS: "-Xmx256m -Xms256m"
      ELASTIC_PASSWORD: "123456"
      discovery.type: single-node
    networks:
      - elk

  logstash:
    build:
      context: logstash/
      args:
        ELK_VERSION: $ELK_VERSION
    volumes:
      - type: bind
        source: ./logstash/config/logstash.yml
        target: /usr/share/logstash/config/logstash.yml
        read_only: true
      - type: bind
        source: ./logstash/pipeline
        target: /usr/share/logstash/pipeline
        read_only: true
    ports:
      - "5044:5044"
      - "5000:5000/tcp"
      - "5000:5000/udp"
      - "9600:9600"
    environment:
      LS_JAVA_OPTS: "-Xmx256m -Xms256m"
    networks:
      - elk
    depends_on:
      - elasticsearch

  kibana:
    build:
      context: kibana/
      args:
        ELK_VERSION: $ELK_VERSION
    volumes:
      - type: bind
        source: ./kibana/config/kibana.yml
        target: /usr/share/kibana/config/kibana.yml
        read_only: true
    ports:
      - "5601:5601"
    networks:
      - elk
    depends_on:
      - elasticsearch

networks:
  elk:
    driver: bridge

volumes:
  elasticsearch:

启动成功就可以进kibana玩耍了，es 比较吃机器内存，但相比 gitlab 感觉好一丢丢。