开发环境中Docker的使用

一. Ubuntu16.04+Django+Redis+Nginx的Web项目Docker化

1.创建Django项目的image

# 创建项目image 执行 docker build -t ccnu_resource_pub -f docker/app/Dockerfile .
#  把ubuntu:xenial作为基础镜像 如果不存在则pull远程
FROM ubuntu:xenial

#  把docker/common/sources.list 拷贝到镜像里的文件系统中
ADD ./docker/common/sources.list /etc/apt/sources.list

# 运行linux指令
RUN apt-get -y update

# PYTHON环境
WORKDIR /proj
# 把requirements.txt拷贝到/proj文件下
ADD requirements.txt /proj
RUN apt-get install -y python python-dev python3 python3-dev python3-pip
RUN apt-get install -y libmysqlclient-dev
RUN pip3 install --trusted-host pypi.python.org -r requirements.txt
RUN pip3 install uwsgi

#  ES日志目录
RUN mkdir -p /var/log/ccnu_resource
RUN chmod -R 777 /var/log/ccnu_resource

2.创建Nginx的image

# 创建nginx的image  docker build -t ccnu_resource_pub_nginx -f docker/nginx/Dockerfile .

FROM ubuntu:xenial

ADD ./docker/common/sources.list /etc/apt/sources.list

RUN apt-get -y update && apt-get -y update --fix-missing && apt-get -y update

RUN apt-get install -y nginx

3.创建Redis的image

# 创建Redis的image   docker build -t ccnu_resource_pub_redis -f docker/redis/Dockerfile .

FROM ubuntu:xenial

ADD ./docker/common/sources.list /etc/apt/sources.list
RUN apt-get -y update && apt-get -y update --fix-missing && apt-get -y update

RUN apt-get install -y redis-server

4.创建docker-compose.yml

# version表示定义的 docker-compose.yml 文件内容所采用的版本，目前 Docker Compose 的配置文件已经迭代至了第三版
version: "3"

# docker-compose.yml 的核心部分，定义了容器的各项细节
services:
  redis:
#  指定镜像
    image: ccnu_resource_pub_redis:latest
# 端口映射 最好使用引号将端口映射的定义包裹起来,由于 YAML 格式对 xx:yy 这种格式的解析有特殊性，在设置小于 60 的值时，会被当成时间而不是字符串来处理
    ports:
      - "6379:6379"
    command: redis-server --appendonly yes
    logging:
      driver: "json-file"
      options:
        max-size: "200k"
        max-file: "10"

  web:
    image: ccnu_resource_pub:latest
    ports:
      - "8000:8000"
    command: python3 manage.py runserver 0.0.0.0:8000
    logging:
      driver: "json-file"
      options:
        max-size: "200k"
        max-file: "10"
# 以 Compose 配置文件为中心的相对路径作为数据卷挂载到容器
    volumes:
      - .:/proj

# 依赖 表示启动web的compose前需先启动 redis
    depends_on:
      - redis

  celery:
    image: ccnu_resource_pub:latest
    command: celery worker -A ccnu_resource -l info
    logging:
      driver: "json-file"
      options:
        max-size: "200k"
        max-file: "10"
    depends_on:
      - web
    volumes:
      - .:/proj

二. 单机ELK部署Docker化

1. 进入ELK的docker网址(可能要*) https://www.docker.elastic.co/，选择最新稳定版6.54版

使用官方提供的docker-compose.yml创建ES的docker-compose.yml

version: '2.2'
services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4
    container_name: elasticsearch
    environment:
      - cluster.name=docker-cluster
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - esdata1:/usr/share/elasticsearch/data
    ports:
      - 9200:9200
    networks:
      - esnet
  elasticsearch2:
    image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4
    container_name: elasticsearch2
    environment:
      - cluster.name=docker-cluster
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
      - "discovery.zen.ping.unicast.hosts=elasticsearch"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - esdata2:/usr/share/elasticsearch/data
    networks:
      - esnet

volumes:
  esdata1:
    driver: local
  esdata2:
    driver: local

networks:
  esnet:

2. 然后进入配置页面https://www.elastic.co/guide/en/logstash/6.5/docker-config.html， 查看Logstash的docker配置

 logstash:
    image: docker.elastic.co/logstash/logstash:6.5.4
    container_name: logstash
    networks:
      - esnet
    depends_on:
        - elasticsearch
        - elasticsearch2
    environment:
      - "LS_JAVA_OPTS=-Xms512m -Xmx512m"

3. 然后进入配置页面https://www.elastic.co/guide/en/kibana/6.5/docker.html， 查看Kibana的docker配置

 kibana:
    image: docker.elastic.co/kibana/kibana:6.5.4
    container_name: kibana
    ports:
      - "5601:5601"
    networks:
      - esnet
    depends_on:
        - elasticsearch
        - elasticsearch2
  

4. 整合docker-compose.ym

version: '2.2'
services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4
    container_name: elasticsearch
    environment:
      - cluster.name=docker-cluster
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - esdata1:/usr/share/elasticsearch/data
    ports:
      - 9200:9200
    networks:
      - esnet
  elasticsearch2:
    image: docker.elastic.co/elasticsearch/elasticsearch:6.5.4
    container_name: elasticsearch2
    environment:
      - cluster.name=docker-cluster
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
      - "discovery.zen.ping.unicast.hosts=elasticsearch"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - esdata2:/usr/share/elasticsearch/data
    networks:
      - esnet
  logstash:
    image: docker.elastic.co/logstash/logstash:6.5.4
    container_name: logstash
    networks:
      - esnet
    depends_on:
        - elasticsearch
        - elasticsearch2
    environment:
      - "LS_JAVA_OPTS=-Xms512m -Xmx512m"
  kibana:
    image: docker.elastic.co/kibana/kibana:6.5.4
    container_name: kibana
    ports:
      - "5601:5601"
    networks:
      - esnet
    depends_on:
        - elasticsearch
        - elasticsearch2

volumes:
  esdata1:
    driver: local
  esdata2:
    driver: local

networks:
  esnet:

配置好后，执行sudo docker-compose up即可成功启动ELK