## 01、安装MYSQL **一**、下载并安装mysql: ``` wget -i -c http://dev.mysql.com/get/mysql57-community-release-el7-10.noarch.rpm yum -y install mysql57-community-release-el7-10.noarch.rpm yum -y install mysql-community-server --nogpgcheck ``` **二**、启动并查看状态MySQL: ``` systemctl start mysqld.service systemctl status mysqld.service ``` **三**、查看MySQL的默认密码: ``` grep "password" /var/log/mysqld.log ``` [![img](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/98b36a9b01de4cc79f3a53245296a19c~tplv-k3u1fbpfcp-zoom-1.image)](https://tva1.sinaimg.cn/large/008i3skNgy1gwg6eiwyqfj313402mgm8.jpg) **四**、登录进MySQL ``` mysql -uroot -p ``` **五**、修改默认密码(设置密码需要有大小写符号组合—安全性),把下面的`my passrod`替换成自己的密码 ``` ALTER USER 'root'@'localhost' IDENTIFIED BY 'my password'; ``` **六**、开启远程访问 (把下面的`my passrod`替换成自己的密码) ``` grant all privileges on *.* to 'root'@'%' identified by 'my password' with grant option; flush privileges; exit ``` **七**、在云服务上增加MySQL的端口 ## 02、安装DOCKER和DOCKER-COMPOSE 首先我们需要安装GCC相关的环境: ``` yum -y install gcc yum -y install gcc-c++ ``` 安装Docker需要的依赖软件包: ``` yum install -y yum-utils device-mapper-persistent-data lvm2 ``` 设置国内的镜像(提高速度) ``` yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo ``` 更新yum软件包索引: ``` yum makecache fast ``` 安装DOCKER CE(注意:Docker分为CE版和EE版,一般我们用CE版就够用了.) ``` yum -y install docker-ce ``` 启动Docker: ``` systemctl start docker ``` 下载回来的Docker版本:: ``` docker version ``` 运行以下命令以下载 Docker Compose 的当前稳定版本: ``` sudo curl -L "https://github.com/docker/compose/releases/download/1.24.1/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose ``` 将可执行权限应用于二进制文件: ``` sudo chmod +x /usr/local/bin/docker-compose ``` 创建软链: ``` sudo ln -s /usr/local/bin/docker-compose /usr/bin/docker-compose ``` 测试是否安装成功: ``` docker-compose --version ``` (Austin项目的中间件使用docker进行部署,文件内容可以参考项目中`docker`文件夹) ## 03、安装KAFKA 新建搭建kafka环境的`docker-compose.yml`文件,内容如下: ``` version: '3' services: zookepper: image: wurstmeister/zookeeper # 原镜像`wurstmeister/zookeeper` container_name: zookeeper # 容器名为'zookeeper' volumes: # 数据卷挂载路径设置,将本机目录映射到容器目录 - "/etc/localtime:/etc/localtime" ports: # 映射端口 - "2181:2181" kafka: image: wurstmeister/kafka # 原镜像`wurstmeister/kafka` container_name: kafka # 容器名为'kafka' volumes: # 数据卷挂载路径设置,将本机目录映射到容器目录 - "/etc/localtime:/etc/localtime" environment: # 设置环境变量,相当于docker run命令中的-e KAFKA_BROKER_ID: 0 # 在kafka集群中,每个kafka都有一个BROKER_ID来区分自己 KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://ip:9092 # TODO 将kafka的地址端口注册给zookeeper KAFKA_LISTENERS: PLAINTEXT://0.0.0.0:9092 # 配置kafka的监听端口 KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181 KAFKA_CREATE_TOPICS: "hello_world" ports: # 映射端口 - "9092:9092" depends_on: # 解决容器依赖启动先后问题 - zookepper kafka-manager: image: sheepkiller/kafka-manager # 原镜像`sheepkiller/kafka-manager` container_name: kafka-manager # 容器名为'kafka-manager' environment: # 设置环境变量,相当于docker run命令中的-e ZK_HOSTS: zookeeper:2181 APPLICATION_SECRET: xxxxx KAFKA_MANAGER_AUTH_ENABLED: "true" # 开启kafka-manager权限校验 KAFKA_MANAGER_USERNAME: admin # 登陆账户 KAFKA_MANAGER_PASSWORD: 123456 # 登陆密码 ports: # 映射端口 - "9000:9000" depends_on: # 解决容器依赖启动先后问题 - kafka ``` 文件内 **// TODO 中的ip**需要改成自己的,并且如果你用的是云服务器,那需要把端口给打开。 在存放`docker-compose.yml`的目录下执行启动命令: ``` docker-compose up -d ``` 可以查看下docker镜像运行的情况: ``` docker ps ``` 进入kafka 的容器: ``` docker exec -it kafka sh ``` 创建一个topic(这里我的**topicName**就叫austinBusiness,你们可以改成自己的) ``` $KAFKA_HOME/bin/kafka-topics.sh --create --topic austinBusiness --partitions 1 --zookeeper zookeeper:2181 --replication-factor 1 ``` 查看刚创建的topic信息: ``` $KAFKA_HOME/bin/kafka-topics.sh --zookeeper zookeeper:2181 --describe --topic austinBusiness ``` ## 04、安装REDIS 首先,我们新建一个文件夹`redis`,然后在该目录下创建出`data`文件夹、`redis.conf`文件和`docker-compose.yaml`文件 `redis.conf`文件的内容如下(后面的配置可在这更改,比如requirepass 我指定的密码为`austin`) ``` protected-mode no port 6379 timeout 0 save 900 1 save 300 10 save 60 10000 rdbcompression yes dbfilename dump.rdb dir /data appendonly yes appendfsync everysec requirepass austin ``` `docker-compose.yaml`的文件内容如下: ``` version: '3' services: redis: image: redis:latest container_name: redis restart: always ports: - 6379:6379 volumes: - ./redis.conf:/usr/local/etc/redis/redis.conf:rw - ./data:/data:rw command: /bin/bash -c "redis-server /usr/local/etc/redis/redis.conf " ``` 配置的工作就完了,如果是云服务器,记得开redis端口**6379** 启动Redis跟之前安装Kafka的时候就差不多啦 ``` docker-compose up -d docker ps docker exec -it redis redis-cli auth austin ``` ## 05、安装APOLLO 部署Apollo跟之前一样直接用`docker-compose`就完事了,在GitHub已经给出了对应的教程和`docker-compose.yml`以及相关的文件,直接复制粘贴就完事咯。 **PS: Apollo 的docker配置文件可以参考:docker/apollo/文件夹, 简单来说,在 docker/apollo/docker-quick-start/文件夹下执行docker-compose up -d 执行即可.** 目录结构最好保持一致: ![](https://p9-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/a532e3221834466a85b6739871694957~tplv-k3u1fbpfcp-watermark.image?) 注:我的配置里更改过端口,所以我的程序`AustinApplication`写的端口为7000 ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/1b3944f3a9e849219c60e673baa5b7ff~tplv-k3u1fbpfcp-watermark.image?) **** **** 部门的创建其实也是一份"配置",输入`organizations`就能把现有的部门给改掉,我新增了`boss`股东部门,大家都是我的股东。 ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/41b096b379244288a8ab25c67b484c62~tplv-k3u1fbpfcp-zoom-1.image) PS:我的namespace是`boss.austin` ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/4c4636a5620a454b931aea8b248e2890~tplv-k3u1fbpfcp-watermark.image?) ## 06、安装PROMETHEUS和GRAFANA(可选) 存放`docker-compose.yml`的信息: ``` version: '2' networks: monitor: driver: bridge services: prometheus: image: prom/prometheus container_name: prometheus hostname: prometheus restart: always volumes: - ./prometheus.yml:/etc/prometheus/prometheus.yml # - ./node_down.yml:/usr/local/etc/node_down.yml:rw ports: - "9090:9090" networks: - monitor alertmanager: image: prom/alertmanager container_name: alertmanager hostname: alertmanager restart: always # volumes: # - ./alertmanager.yml:/usr/local/etc/alertmanager.yml ports: - "9093:9093" networks: - monitor grafana: image: grafana/grafana container_name: grafana hostname: grafana restart: always ports: - "3000:3000" networks: - monitor node-exporter: image: quay.io/prometheus/node-exporter container_name: node-exporter hostname: node-exporter restart: always ports: - "9100:9100" networks: - monitor cadvisor: image: google/cadvisor:latest container_name: cadvisor hostname: cadvisor restart: always volumes: - /:/rootfs:ro - /var/run:/var/run:rw - /sys:/sys:ro - /var/lib/docker/:/var/lib/docker:ro ports: - "8899:8080" networks: - monitor ``` 新建prometheus的配置文件`prometheus.yml` ``` global: scrape_interval: 15s evaluation_interval: 15s scrape_configs: - job_name: 'prometheus' static_configs: - targets: ['ip:9090'] - job_name: 'cadvisor' static_configs: - targets: ['ip:8899'] - job_name: 'node' static_configs: - targets: ['ip:9100'] ``` (**这里要注意端口,按自己配置的来,ip也要填写为自己的**) 把这份`prometheus.yml`的配置往`/etc/prometheus/prometheus.yml` 路径下**复制**一份。随后在目录下`docker-compose up -d`启动,于是我们就可以分别访问: - `http://ip:9100/metrics`( 查看服务器的指标) - `http://ip:8899/metrics`(查看docker容器的指标) - `http://ip:9090/`(prometheus的原生web-ui) - `http://ip:3000/`(Grafana开源的监控可视化组件页面) 进到Grafana首页,配置prometheus作为数据源 ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/76474c290b594d72b8c26f32e6c93753~tplv-k3u1fbpfcp-zoom-1.image) 进到配置页面,写下对应的URL,然后保存就好了。 ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/8a78755f4f30431882878ab08e6855bc~tplv-k3u1fbpfcp-zoom-1.image) 相关监控的模板可以在 这里查到。 ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/5836357acce442b480628e06b2e7420a~tplv-k3u1fbpfcp-zoom-1.image) 服务器的监控直接选用**8919**的就好了 ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/01a19e6370f54c10b096e1c9bd743b59~tplv-k3u1fbpfcp-zoom-1.image) ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/b97faddc55324c2bac2bf13a6e47355e~tplv-k3u1fbpfcp-zoom-1.image) import后就能直接看到高大上的监控页面了: ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/4505d818d2474d8f83d033ad3ad60a64~tplv-k3u1fbpfcp-zoom-1.image) 使用模板**893**来配置监控docker的信息: ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/da69a42ffb984caa99c0beea410dde07~tplv-k3u1fbpfcp-zoom-1.image) ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/14a5c8b4fb5441598ddda816d42d56fd~tplv-k3u1fbpfcp-zoom-1.image) 选用了`4701`模板的JVM监控和`12900`SpringBoot监控(**程序代码已经接入了actuator和prometheus**)。需要在`prometheus.yml`配置下新增暴露的服务地址: ``` - job_name: 'austin' metrics_path: '/actuator/prometheus' # 采集的路径 static_configs: - targets: ['ip:port'] # todo 这里的ip和端口写自己的应用下的 ``` ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/dbd1b8e2b15242a194da0ce8a7c61a80~tplv-k3u1fbpfcp-zoom-1.image) ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/26f4d6d83f4a441d85cb0a396cd0543c~tplv-k3u1fbpfcp-zoom-1.image) ## 07、安装GRAYLOG(可选)-分布式日志收集框架 `docker-compose.yml`文件内容: ``` version: '3' services: mongo: image: mongo:4.2 networks: - graylog elasticsearch: image: docker.elastic.co/elasticsearch/elasticsearch-oss:7.10.2 environment: - http.host=0.0.0.0 - transport.host=localhost - network.host=0.0.0.0 - "ES_JAVA_OPTS=-Dlog4j2.formatMsgNoLookups=true -Xms512m -Xmx512m" ulimits: memlock: soft: -1 hard: -1 deploy: resources: limits: memory: 1g networks: - graylog graylog: image: graylog/graylog:4.2 environment: - GRAYLOG_PASSWORD_SECRET=somepasswordpepper - GRAYLOG_ROOT_PASSWORD_SHA2=8c6976e5b5410415bde908bd4dee15dfb167a9c873fc4bb8a81f6f2ab448a918 - GRAYLOG_HTTP_EXTERNAL_URI=http://ip:9009/ # 这里注意要改ip entrypoint: /usr/bin/tini -- wait-for-it elasticsearch:9200 -- /docker-entrypoint.sh networks: - graylog restart: always depends_on: - mongo - elasticsearch ports: - 9009:9000 - 1514:1514 - 1514:1514/udp - 12201:12201 - 12201:12201/udp networks: graylog: driver: bridge ``` 这个文件里唯一需要改动的就是`ip`(本来的端口是`9000`的,我由于已经占用了`9000`端口了,所以我这里把端口改成了`9009`,你们可以随意) 启动以后,我们就可以通过`ip:port`访问对应的Graylog后台地址了,默认的账号和密码是`admin/admin` ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/c7d068f7bb7445238688a695eab49c8c~tplv-k3u1fbpfcp-zoom-1.image) 配置下`inputs`的配置,找到`GELF UDP`,然后点击`Launch new input`,只需要填写`Title`字段,保存就完事了(其他不用动)。 ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/88878e8e4bb8428c9c6930cb09d5e249~tplv-k3u1fbpfcp-zoom-1.image) 最后配置`austin.grayLogIp`的ip即可实现分布式日志收集 ## 08、XXL-JOB 文档:[https://www.xuxueli.com/xxl-job/#2.1%20%E5%88%9D%E5%A7%8B%E5%8C%96%E2%80%9C%E8%B0%83%E5%BA%A6%E6%95%B0%E6%8D%AE%E5%BA%93%E2%80%9D](https://www.xuxueli.com/xxl-job/#2.1%20%E5%88%9D%E5%A7%8B%E5%8C%96%E2%80%9C%E8%B0%83%E5%BA%A6%E6%95%B0%E6%8D%AE%E5%BA%93%E2%80%9D) xxl-job的部署我这边其实是依赖官网的文档的,步骤可以简单总结为: **1**、把xxl-job的仓库拉下来 **2**、执行`/xxl-job/doc/db/tables_xxl_job.sql`的脚本(创建对应的库、创建表以及插入测试数据记录) **3**、如果是**本地**启动「调度中心」则在`xxl-job-admin`的`application.properties`更改相应的数据库配置,改完启动即可 **4**、如果是**云服务**启动「调度中心」,则可以选择拉取`docker`镜像进行部署,我拉取的是`2.30`版本,随后执行以下命令即可: ```shell docker pull xuxueli/xxl-job-admin:2.3.0 docker run -e PARAMS="--spring.datasource.url=jdbc:mysql://ip:3306/xxl_job?useUnicode=true&characterEncoding=UTF-8&autoReconnect=true&useSSL=false&zeroDateTimeBehavior=convertToNull --spring.datasource.username=root --spring.datasource.password=password " -p 6767:8080 --name xxl-job-admin -d xuxueli/xxl-job-admin:2.3.0 ``` **注意**:第二条命令的**ip**和**password**需要更改为自己的,并且,我开的是**6767**端口 ![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/180eabb4945e475494f3803c69318755~tplv-k3u1fbpfcp-zoom-1.image) ## 09、Flink 部署Flink也是直接上docker-compose就完事了,值得注意的是:我们在部署的时候需要在配置文件里**指定时区** docker-compose.yml配置内容如下: ```yaml version: "2.2" services: jobmanager: image: flink:latest ports: - "8081:8081" command: jobmanager environment: - | FLINK_PROPERTIES= jobmanager.rpc.address: jobmanager - SET_CONTAINER_TIMEZONE=true - CONTAINER_TIMEZONE=Asia/Shanghai - TZ=Asia/Shanghai taskmanager: image: flink:latest depends_on: - jobmanager command: taskmanager scale: 1 environment: - | FLINK_PROPERTIES= jobmanager.rpc.address: jobmanager taskmanager.numberOfTaskSlots: 2 - SET_CONTAINER_TIMEZONE=true - CONTAINER_TIMEZONE=Asia/Shanghai - TZ=Asia/Shanghai ``` ## 10、未完待续 安装更详细的过程以及整个文章系列的更新思路都在公众号**Java3y**连载哟! 如果你需要用这个项目写在简历上,**强烈建议关注公众号看实现细节的思路**。如果⽂档中有任何的不懂的问题,都可以直接来找我询问,我乐意帮助你们!公众号下有我的联系方式