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

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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

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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

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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:

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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

zooInspector示例
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:

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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。

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注册配置后的界面:


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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:

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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:

image.png

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。

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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