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使用Docker(Mac)搭建 Nginx/Openresty - Kafka - kafkaManager

日期:2018-05-25点击:389

本文默认读者已经对Docker有一定了解,且清楚使用Docker进行部署的优势。

1.安装Docker(Mac)

官网:https://docs.docker.com/docker-for-mac/install/

1.1 下载 Docker for Mac

地址:https://store.docker.com/editions/community/docker-ce-desktop-mac

1.2 下载完成以后,双击打开文件Docker.dmg

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1.3双击Docker.app启动

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Mac顶部状态栏会出现鲸鱼图标


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1.4点击鲸鱼图标可以进行设置

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1.5 Check versions

$ docker --version Docker version 18.03, build c97c6d6 $ docker-compose --version docker-compose version 1.21.2, build 8dd22a9 $ docker-machine --version docker-machine version 0.14.0, build 9ba6da9 

1.6 Hello Word

1.6.1 打开命令行终端,通过运行简单的Docker映像测试您的安装工作。

$ docker run hello-world Unable to find image 'hello-world:latest' locally latest: Pulling from library/hello-world ca4f61b1923c: Pull complete Digest: sha256:ca0eeb6fb05351dfc8759c20733c91def84cb8007aa89a5bf606bc8b315b9fc7 Status: Downloaded newer image for hello-world:latest Hello from Docker! This message shows that your installation appears to be working correctly. ... 

1.6.2 启动Dockerized web server

$ docker run -d -p 80:80 --name webserver nginx 

1.6.3 打开浏览器,输入http://localhost/

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常用命令:

docker ps 查看正在运行的容器 docker stop停止正在运行的容器 docker start启动容器 docker ps -a查看终止状态的容器 docker rm -f webserver命令来移除正在运行的容器 docker list 列出本地镜像 docker rmi 删除的镜像 

2.使用Docker安装Nginx

Docker Store 地址:https://store.docker.com/images/nginx

其实在上文中Hello World即已经安装了nginx。

2.1 拉取 image

docker pull nginx 

3.2 创建Nginx容器

docker run --name mynginx -p 80:80 -v /Users/gaoguangchao/Work/opt/local/nginx/logs:/var/log/nginx -v /Users/gaoguangchao/Work/opt/local/nginx/conf.d:/etc/nginx/conf.d -v /Users/gaoguangchao/Work/opt/local/nginx/nginx.conf:/etc/nginx/nginx.conf:ro -v /Users/gaoguangchao/Work/opt/local/nginx/html:/etc/nginx/html -d nginx 

-d 以守护进程运行(运行在后台)
--name nginx 容器名称;
-p 80:80 端口映射
-v 配置挂载路径 宿主机路径:容器内的路径

关于挂载

    1. 为了能直接修改配置文件,以实现对Nginx的定制化,需要进行Docker的相关目录挂在宿主机上。
    1. 需要挂载的目录/文件:/etc/nginx/conf.d /etc/nginx/nginx.conf /etc/nginx/html
    1. 有一点尤其需要注意,当挂载的为文件而非目录时,需要注意以下两点:
    • a. 挂载文件命令: -v 宿主机路径:容器内的路径:ro
    • b.宿主机需要先创建后文件,无法自动创建,反之将报错

nginx.conf 示例

#user nobody; worker_processes 1; #error_log logs/error.log; #error_log logs/error.log notice; #error_log logs/error.log info; #pid logs/nginx.pid; events { worker_connections 1024; } http { include mime.types; default_type application/octet-stream; #access_log logs/access.log main; sendfile on; #tcp_nopush on; #keepalive_timeout 0; keepalive_timeout 65; #gzip on; upstream demo { server 127.0.0.1:8080; } server { listen 80; server_name request_log; location / { root html; #index index.html index.htm; proxy_connect_timeout 3; proxy_send_timeout 30; proxy_read_timeout 30; proxy_pass http://demo; } #error_page 404 /404.html; # redirect server error pages to the static page /50x.html # error_page 500 502 503 504 /50x.html; location = /50x.html { root html; } } } 

2.3 浏览器访问

img_dbf4ee99cc15a59f92d2afa9b02d5dcb.png
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在调试过程中往往不会很顺利,这里的技巧是通过阅读error.log中的异常日志进行

2.4 配置反向代理

此处是本机启动一个 SpringBoot web server,端口为:8080,浏览器访问:http://localhost:8080/index/hello

img_9c86e848403b9f7e89f968fb8c01cb02.png
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按照上节中nginx.conf示例中的配置方式,增加upstreamserverproxy_pass相关配置,对80端口进行监听,重启nginx容器。

docker restart mynginx 

浏览器访问:http://localhost/index/hello,可以看到正常访问。

3.使用Docker安装Openresty

Openresty是在Nginx基础上做了大量的定制扩展,其安装过程和Nginx基本一致。

Docker Store 地址:https://store.docker.com/community/images/openresty/openresty

3.1 拉取 image

docker pull openresty/openresty 

3.2 创建Openresty容器

docker run -d --name="openresty" -p 80:80 -v /Users/gaoguangchao/Work/opt/local/openresty/nginx.conf:/usr/local/openresty/nginx/conf/nginx.conf:ro -v /Users/gaoguangchao/Work/opt/local/openresty/logs:/usr/local/openresty/nginx/logs -v /Users/gaoguangchao/Work/opt/local/openresty/conf.d:/etc/nginx/conf.d -v /Users/gaoguangchao/Work/opt/local/openresty/html:/etc/nginx/html openresty/openresty 

注意事项和安装Nginx基本一致,在此不再赘述。

4.使用Docker安装Kafka

Docker Store 地址:https://store.docker.com/community/images/spotify/kafka

4.1 拉取 image

docker pull spotify/kafka 

4.2 创建Kafka容器

运行命令:

docker run -p 2181:2181 -p 9092:9092 --env ADVERTISED_HOST=`127.0.0.1` --env ADVERTISED_PORT=9092 spotify/kafka 

2181为zookeeper端口,9092为kafka端口

输出启动日志:

img_4f9fef47d79fc29734fd6f4b04809457.png
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4.3 Check zookeeper是否启动

可以使用一些可视化客户端连接端口,进行监控,如zooInspector、Idea Zookeeper Plugin等

img_173dd2c80514ab6817600915addc1e4a.png
zooInspector示例
img_c3e977185bfafaad3eb4537352d95b25.png
Idea Zookeeper Plugin

5.使用Docker安装Kafka Manager

Kafka Manager 是Yahoo开源的kafka监控和配置的web系统,可以进行kafka的日常监控和配置的动态修改。

Docker Store 地址:https://store.docker.com/community/images/sheepkiller/kafka-manager

5.1 拉取 image

docker pull sheepkiller/kafka-manager 

5.2 创建Kafka Manager容器

运行命令:

docker run -it --rm -p 9000:9000 -e ZK_HOSTS="127.0.0.1:2181" -e APPLICATION_SECRET=letmein sheepkiller/kafka-manager 

2181为上节中部署的zookeeper端口,9000为kafka-manager的web端口

输出启动日志:

img_577d9b8f0118d3390e4cdb6a5615ed9b.png
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5.3 访问Kafka Manager

浏览器访问:http://localhost:9000
按照页面上的操作按钮进行kafka集群的注册,具体使用方式再次不做详细介绍。

img_b9cfc35b7c2d696bbbfdcb1e42944956.png
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注册配置后的界面:


img_3e144af5658bb951576acf2d23d6444a.png
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6.Kafka消息生产与消费

6.1创建maven项目

** pom依赖**

 <dependencies> <dependency> <groupId>org.slf4j</groupId> <artifactId>jcl-over-slf4j</artifactId> <version>${org.slf4j-version}</version> <scope>runtime</scope> </dependency> <dependency> <groupId>org.apache.logging.log4j</groupId> <artifactId>log4j-1.2-api</artifactId> <version>${log4j2-version}</version> </dependency> <dependency> <groupId>org.apache.logging.log4j</groupId> <artifactId>log4j-slf4j-impl</artifactId> <version>${log4j2-version}</version> </dependency> <dependency> <groupId>org.apache.logging.log4j</groupId> <artifactId>log4j-api</artifactId> <version>${log4j2-version}</version> </dependency> <dependency> <groupId>org.apache.logging.log4j</groupId> <artifactId>log4j-core</artifactId> <version>${log4j2-version}</version> </dependency> <dependency> <groupId>com.lmax</groupId> <artifactId>disruptor</artifactId> <version>3.2.0</version> </dependency> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka-clients</artifactId> <version>0.10.1.0</version> </dependency> </dependencies> 

6.2 增加log4j2配置

配置log4j2为能正常打印debug日志,方便进行异常排查 (重要)
resources目录下增加log4j2.xml文件

<?xml version="1.0" encoding="UTF-8"?> <configuration status="WARN"> <Properties> <Property name="pattern_layout">%d %-5p (%F:%L) - %m%n</Property> <Property name="LOG_HOME">/logs</Property> </Properties> <appenders> <Console name="CONSOLE" target="SYSTEM_OUT"> <PatternLayout pattern="%d %-5p (%F:%L) - %m%n"/> </Console> </appenders> <loggers> <root level="debug" includeLocation="true"> <appender-ref ref="CONSOLE"/> </root> </loggers> </configuration> 

关于log4j2的使用,有兴趣的可以了解:Log4j1升级Log4j2实战

6.3 创建生产者示例

package com.moko.kafka; import org.apache.kafka.clients.producer.*; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.util.Properties; public class MokoProducer extends Thread { private static final Logger LOGGER = LoggerFactory.getLogger(MokoProducer.class); private final KafkaProducer<String, String> producer; private final String topic; private final boolean isAsync; public MokoProducer(String topic, boolean isAsync) { Properties properties = new Properties(); properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "78c4f4a0f989:9092");//broker 集群地址 properties.put(ProducerConfig.CLIENT_ID_CONFIG, "MokoProducer");//自定义客户端id properties.put(ProducerConfig.ACKS_CONFIG, "all"); properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringSerializer");//key 序列号方式 properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringSerializer");//value 序列号方式 this.producer = new KafkaProducer<String, String>(properties); this.topic = topic; this.isAsync = isAsync; } @Override public void run() { int seq = 0; while (true) { String msg = "Msg: " + seq; if (isAsync) {//异步 producer.send(new ProducerRecord<String, String>(this.topic, msg)); } else {//同步 producer.send(new ProducerRecord<String, String>(this.topic, msg), new MsgProducerCallback(msg)); } seq++; try { Thread.sleep(1000); } catch (InterruptedException e) { e.printStackTrace(); } } } /** * 消息发送后的回调函数 */ class MsgProducerCallback implements Callback { private final String msg; public MsgProducerCallback(String msg) { this.msg = msg; } public void onCompletion(RecordMetadata recordMetadata, Exception e) { if (recordMetadata != null) { LOGGER.info(msg + " be sended to partition no : " + recordMetadata.partition()); } else { LOGGER.info("recordMetadata is null"); } if (e != null) e.printStackTrace(); } } public static void main(String args[]) { new MokoProducer("access-log", false).start();//开始发送消息 } } 

简单运行后,打印日志如下:

img_e38ecdb6af5c4dc13f6cef1c6acd1a61.png
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6.4 创建消费者示例

package com.moko.kafka; import org.apache.kafka.clients.consumer.ConsumerRecord; import org.apache.kafka.clients.consumer.ConsumerRecords; import org.apache.kafka.clients.consumer.KafkaConsumer; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.util.Arrays; import java.util.Properties; public class MokoCustomer { private static final Logger LOGGER = LoggerFactory.getLogger(MokoCustomer.class); public static void main(String args[]) throws Exception { String topicName = "access-log"; Properties props = new Properties(); KafkaConsumer<String, String> consumer = getKafkaConsumer(props); consumer.subscribe(Arrays.asList(topicName)); while (true) { ConsumerRecords<String, String> records = consumer.poll(100); if (!records.isEmpty()) { LOGGER.info("========================="); } for (ConsumerRecord<String, String> record : records) { LOGGER.info(record.value()); } } } private static KafkaConsumer<String, String> getKafkaConsumer(Properties props) { props.put("bootstrap.servers", "172.18.153.41:9092"); props.put("group.id", "group-1"); props.put("enable.auto.commit", "true"); props.put("auto.commit.interval.ms", "1000"); props.put("session.timeout.ms", "30000"); props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer"); props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer"); return new KafkaConsumer<String, String>(props); } } 

简单运行后,打印日志如下:

img_0cc06713934c43c5dfff0219df0ca752.png
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6.5 注意事项

由于是在本机使用Docker搭建的环境,遇到最多的问题就是网络问题,如host等的配置,但是只要意识到这点,通过注意分析各种异常日志,便不难排查解决。

img_405b6eb120d6edcb8a5bea1c3c049ed1.png
项目目录结构

7.结语

致此,本文就介绍完了如何使用Docker搭建 Nginx/Openresty - Kafka - kafkaManager。

后续将会继续介绍如何使用Docker搭建一套 nginx+lua+kafka实现的日志收集的教程,敬请期待。


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