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
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# 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
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# 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
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# 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
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# 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FQ) 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
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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
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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
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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
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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