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3 years ago
## 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
```
**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
```
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[![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
```
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**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';
```
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**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
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## 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
```
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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)
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## 03、安装KAFKA
新建搭建kafka环境的`docker-compose.yml`文件,内容如下:
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```
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
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```
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)
```
$KAFKA_HOME/bin/kafka-topics.sh --create --topic austinBusiness --partitions 1 --zookeeper zookeeper:2181 --replication-factor 1
```
查看刚创建的topic信息
```
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$KAFKA_HOME/bin/kafka-topics.sh --zookeeper zookeeper:2181 --describe --topic austinBusiness
```
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## 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`)
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```
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:
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```
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
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```
docker-compose up -d
docker ps
docker exec -it redis redis-cli
auth austin
```
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## 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?)
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**<https://www.apolloconfig.com/#/zh/deployment/quick-start-docker>**
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**<https://github.com/apolloconfig/apollo/tree/master/scripts/docker-quick-start>**
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。
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![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/41b096b379244288a8ab25c67b484c62~tplv-k3u1fbpfcp-zoom-1.image)
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PS我的namespace是`boss.austin`
![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/2101f27fee044a2d86e8d6031c808d95~tplv-k3u1fbpfcp-zoom-1.image)
## 06、安装PROMETHEUS和GRAFANA(可选)
存放`docker-compose.yml`的信息:
```
version: '2'
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networks:
monitor:
driver: bridge
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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
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```
新建prometheus的配置文件`prometheus.yml`
```
global:
scrape_interval: 15s
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evaluation_interval: 15s
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['ip:9090']
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- job_name: 'cadvisor'
static_configs:
- targets: ['ip:8899']
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- job_name: 'node'
static_configs:
- targets: ['ip:9100']
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```
**这里要注意端口,按自己配置的来,ip也要填写为自己的**
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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 <https://grafana.com/grafana/dashboards/> 这里查到。
![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/5836357acce442b480628e06b2e7420a~tplv-k3u1fbpfcp-zoom-1.image)
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服务器的监控直接选用**8919**的就好了
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![](https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/01a19e6370f54c10b096e1c9bd743b59~tplv-k3u1fbpfcp-zoom-1.image)
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![](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
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```
![](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
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networks:
graylog:
driver: bridge
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```
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
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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!
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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
3 years ago
<img align="center" src='https://p3-juejin.byteimg.com/tos-cn-i-k3u1fbpfcp/4e109cdb8d064c1e87541d7b6c17957d~tplv-k3u1fbpfcp-zoom-1.image' width=300px height=300px />