pom.xml

  <dependency>
<groupId>com.github.danielwegener</groupId>
<artifactId>logback-kafka-appender</artifactId>
<version>0.2.0-RC2</version>
</dependency> <dependency>
<groupId>net.logstash.logback</groupId>
<artifactId>logstash-logback-encoder</artifactId>
<version>6.4</version>
</dependency> <dependency>
<groupId>ch.qos.logback</groupId>
<artifactId>logback-classic</artifactId>
<version>1.2.3</version>
</dependency>

logback-spring.xml的文俊

<?xml version="1.0" encoding="UTF-8"?>
<configuration scan="true" scanPeriod="10 seconds" debug="false"> <!--上下文名称-->
<contextName>logback</contextName> <!--日志根目录 -->
<property name="log.path" value="C:/logs" />
<springProperty scope="context" name="servicename" source="spring.application.name" defaultValue="UnknownService"/>
<springProperty scope="context" name="env" source="spring.profiles.active" defaultValue="dev"/>
<springProperty scope="context" name="bootstrapServers" source="spring.kafka.bootstrap-servers" defaultValue="localhost:9092"/>
<springProperty scope="context" name="serviceport" source="server.port" defaultValue="80"/>
<!--获取服务器的IP和名称-->
<conversionRule conversionWord="serviceip" converterClass="com.icar.web.makedata.utils.LogIpConfigUtil" /> <!--以上三行需要和yml对应--> <!--输出日志到控制台 -->
<appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
<filter class="ch.qos.logback.classic.filter.ThresholdFilter">
<level>INFO</level>
</filter>
<encoder>
<pattern>%yellow(%date{yyyy-MM-dd HH:mm:ss}) |%highlight(%-5level) |%blue(%thread) |%green(%file:%line) |%magenta(%logger) |%cyan(%msg%n)</pattern>
<charset>UTF-8</charset>
</encoder>
</appender> <!--①.level=INFO的日志文件 -->
<appender name="INFO_FILE" class="ch.qos.logback.core.rolling.RollingFileAppender">
<rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy">
<fileNamePattern>${log.path}/info/infolevel_makedata.%d{yyyy-MM-dd}.%i.txt</fileNamePattern>
<maxFileSize>100MB</maxFileSize>
<maxHistory>15</maxHistory>
<totalSizeCap>2GB</totalSizeCap>
</rollingPolicy>
<!--日志输出级别-->
<filter class="ch.qos.logback.classic.filter.LevelFilter">
<level>INFO</level>
<onMatch>ACCEPT</onMatch>
<onMismatch>DENY</onMismatch>
</filter>
<!--日志文件输出格式-->
<encoder>
<pattern>[%d{yyyy-MM-dd HH:mm:ss.SSS}] %thread %-5level %logger{50} --- %msg%n</pattern>
<charset>UTF-8</charset>
</encoder>
</appender> <!--②.level=WARN的日志文件 -->
<appender name="WARN_FILE" class="ch.qos.logback.core.rolling.RollingFileAppender">
<!--基本设置-->
<rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy">
<fileNamePattern>${log.path}/warn/warnlevel_makedata.%d{yyyy-MM-dd}.%i.txt</fileNamePattern>
<maxFileSize>100MB</maxFileSize>
<maxHistory>15</maxHistory>
<totalSizeCap>2GB</totalSizeCap>
</rollingPolicy>
<!--日志输出级别-->
<filter class="ch.qos.logback.classic.filter.LevelFilter">
<level>WARN</level>
<onMatch>ACCEPT</onMatch>
<onMismatch>DENY</onMismatch>
</filter>
<!--日志文件输出格式-->
<encoder>
<pattern>[%d{yyyy-MM-dd HH:mm:ss.SSS}] %thread %-5level %logger{50} - %msg%n</pattern>
<charset>UTF-8</charset>
</encoder>
</appender> <!--③.level=ERROR的日志文件 -->
<appender name="ERROR_FILE" class="ch.qos.logback.core.rolling.RollingFileAppender">
<!--基本设置-->
<rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy">
<fileNamePattern>${log.path}/error/errorlever_makedata.%d{yyyy-MM-dd}.%i.txt</fileNamePattern>
<maxFileSize>100MB</maxFileSize>
<maxHistory>15</maxHistory>
<totalSizeCap>2GB</totalSizeCap>
</rollingPolicy>
<!--日志输出级别-->
<filter class="ch.qos.logback.classic.filter.LevelFilter">
<level>ERROR</level>
<onMatch>ACCEPT</onMatch>
<onMismatch>DENY</onMismatch>
</filter>
<!--日志文件输出格式-->
<encoder>
<pattern>[%d{yyyy-MM-dd HH:mm:ss.SSS}] %thread %-5level %logger{50} - %msg%n</pattern>
<charset>UTF-8</charset>
</encoder>
</appender>
<!-- <appender name="KafkaAppender" class="com.github.danielwegener.logback.kafka.KafkaAppender">
<encoder class="com.github.danielwegener.logback.kafka.encoding.LayoutKafkaMessageEncoder">
<layout class="net.logstash.logback.layout.LogstashLayout" >
&lt;!&ndash; 是否包含上下文 &ndash;&gt;
<includeContext>true</includeContext>
&lt;!&ndash; 是否包含日志来源 &ndash;&gt;
<includeCallerData>true</includeCallerData>
&lt;!&ndash; 自定义附加字段 &ndash;&gt;
<customFields>{"system":"test"}</customFields>
&lt;!&ndash; 自定义字段的简称 &ndash;&gt;
<fieldNames class="net.logstash.logback.fieldnames.ShortenedFieldNames"/>
</layout>
<charset>UTF-8</charset>
</encoder>
&lt;!&ndash;kafka topic 需要与配置文件里面的topic一致 否则kafka会沉默并鄙视你&ndash;&gt;
<topic>applog_dev</topic>
<keyingStrategy class="com.github.danielwegener.logback.kafka.keying.HostNameKeyingStrategy" />
<deliveryStrategy class="com.github.danielwegener.logback.kafka.delivery.AsynchronousDeliveryStrategy" />
<producerConfig>bootstrap.servers=124.71.59.186:9092,139.159.249.142:9092,124.71.85.73:9092</producerConfig>
&lt;!&ndash; don't wait for a broker to ack the reception of a batch. &ndash;&gt;
<producerConfig>acks=0</producerConfig>
&lt;!&ndash; wait up to 1000ms and collect log messages before sending them as a batch &ndash;&gt;
<producerConfig>linger.ms=1000</producerConfig>
&lt;!&ndash; even if the producer buffer runs full, do not block the application but start to drop messages &ndash;&gt;
<producerConfig>max.block.ms=0</producerConfig>
&lt;!&ndash; define a client-id that you use to identify yourself against the kafka broker &ndash;&gt;
<producerConfig>client.id=${HOSTNAME}-${CONTEXT_NAME}-logback-relaxed</producerConfig> this is the fallback appender if kafka is not available.
<appender-ref ref="CONSOLE" />
</appender>--> <appender name="KafkaAppender" class="com.github.danielwegener.logback.kafka.KafkaAppender">
<encoder class="net.logstash.logback.encoder.LoggingEventCompositeJsonEncoder">
<providers class="net.logstash.logback.composite.loggingevent.LoggingEventJsonProviders">
<pattern>
<!-- <pattern>
{
"env": "${env}",
"servicename":"${servicename}",
"type":"${servicename}",
"serviceinfo":"%serviceip:${serviceport}",
"date":"%d{yyyy-MM-dd HH:mm:ss.SSS}",
"level":"%level",
"thread": "%thread",
"logger": "%logger{36}",
"msg":"%msg",
"exception":"%exception"
}
</pattern>-->
<pattern>
{
"env": "${env}",
"servicename":"${servicename}",
"type":"${servicename}",
"serviceinfo":"%serviceip:${serviceport}",
"date":"%d{yyyy-MM-dd HH:mm:ss.SSS}",
"level":"%level",
"thread": "%thread",
"msg":"%msg",
"exception":"%exception"
}
</pattern>
</pattern>
</providers>
</encoder>
<topic>appdev</topic>
<keyingStrategy class="com.github.danielwegener.logback.kafka.keying.NoKeyKeyingStrategy"/>
<deliveryStrategy class="com.github.danielwegener.logback.kafka.delivery.AsynchronousDeliveryStrategy"/>
<producerConfig>acks=0</producerConfig>
<producerConfig>linger.ms=1000</producerConfig>
<producerConfig>max.block.ms=0</producerConfig>
<producerConfig>bootstrap.servers=${bootstrapServers}</producerConfig>
</appender> <appender name="ASYNC" class="ch.qos.logback.classic.AsyncAppender">
<appender-ref ref="KafkaAppender"/>
</appender> <root level="INFO">
<appender-ref ref="ASYNC"/>
</root>
<!-- <root>
<appender-ref ref="CONSOLE"/>
<appender-ref ref="INFO_FILE"/>
<appender-ref ref="WARN_FILE"/>
<appender-ref ref="ERROR_FILE"/>
</root>-->
<!--springProfile表示在dev环境下使用 -->
<!-- <springProfile name="dev">
<logger name="com.nick" level="INFO" additivity="true">
<appender-ref ref="KafkaAppender" />
</logger>
</springProfile>--> </configuration>
import ch.qos.logback.classic.pattern.ClassicConverter;
import ch.qos.logback.classic.spi.ILoggingEvent;
import lombok.extern.slf4j.Slf4j; import java.io.Console;
import java.net.Inet4Address;
import java.net.InetAddress;
import java.net.NetworkInterface;
import java.net.UnknownHostException;
import java.util.Enumeration; /**
* 获取服务器IP以及服务器名称
*/
//@Slf4j
public class LogIpConfigUtil extends ClassicConverter { public static String serviceIp; static {
try {
/* Enumeration<NetworkInterface> allNetInterfaces = NetworkInterface.getNetworkInterfaces();
InetAddress ip = null;
while (allNetInterfaces.hasMoreElements()) {
NetworkInterface netInterface = (NetworkInterface) allNetInterfaces.nextElement();
if (netInterface.isLoopback() || netInterface.isVirtual() || !netInterface.isUp()) {
continue;
} else {
Enumeration<InetAddress> addresses = netInterface.getInetAddresses();
while (addresses.hasMoreElements()) {
ip = addresses.nextElement();
if (ip != null && ip instanceof Inet4Address) {
return ip.getHostAddress();
}
}
}
}*/ InetAddress addr = InetAddress.getLocalHost();
serviceIp =addr.getHostName()+"/" +addr.getHostAddress(); } catch (Exception e) {
//log.error("IP地址获取失败" + e.toString());
}
} @Override
public String convert(ILoggingEvent iLoggingEvent) {
return serviceIp;
}
}

logstash-es.conf

input {
kafka {
group_id => "test-consumer-group"
topics => ["appdev"]
bootstrap_servers => "localhost:9092"
codec => "json"
}
}
filter {
}
output {
stdout { codec => rubydebug }
if [type] == "xxxx" {
elasticsearch {
hosts => [ "localhost:9200" ]
index => "xxx"
}
}
}

logback-spring 集成 ELK、kafka的配置的更多相关文章

  1. Spring Boot 自定义kafka 消费者配置 ContainerFactory最佳实践

    Spring Boot 自定义kafka 消费者配置 ContainerFactory最佳实践 本篇博文主要提供一个在 SpringBoot 中自定义 kafka配置的实践,想象这样一个场景:你的系统 ...

  2. spring集成常用技术的配置

    使用spring集成其他技术,最基本的配置都是模板化的,比如配置视图模板引擎.数据库连接池.orm框架.缓存服务.邮件服务.rpc调用等,以spring的xml配置为例,我将这些配置过程整理出来,并不 ...

  3. 【redis】3.Spring 集成注解 redis 项目配置使用

    spring-data-redis  项目,配合 spring 特性并集成 Jedis 的一些命令和方法. 配置redis继承到spring管理项目,使用注解实现redis缓存功能. 参考:http: ...

  4. Spring集成quartz集群配置总结

    1.spring-quartz.xml <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE be ...

  5. 阿里RocketMq试用记录+简单的Spring集成

    CSDN学院招募微信小程序讲师啦 程序猿全指南,让[移动开发]更简单! [观点]移动原生App开发 PK HTML 5开发 云端应用征文大赛,秀绝招,赢无人机! 阿里RocketMq试用记录+简单的S ...

  6. Spring 集成rabbiatmq

    pom 文件 <dependencies> <dependency> <groupId>com.rabbitmq</groupId> <artif ...

  7. ELK+kafka日志收集分析系统

    环境: 服务器IP 软件 版本 192.168.0.156 zookeeper+kafka zk:3.4.14  kafka:2.11-2.2.0 192.168.0.42 zookeeper+kaf ...

  8. 【ELK】5.spring boot日志集成ELK,搭建日志系统

    阅读前必看: ELK在docker下搭建步骤 spring boot集成es,CRUD操作完整版 ============================================== 本章集成 ...

  9. 从零开始学 Java - Spring 集成 ActiveMQ 配置(一)

    你家小区下面有没有快递柜 近两年来,我们收取快递的方式好像变了,变得我们其实并不需要见到快递小哥也能拿到自己的快递了.对,我说的就是类似快递柜.菜鸟驿站这类的代收点的出现,把我们原来快递小哥必须拿着快 ...

  10. Spring Boot 数据访问集成 MyBatis 与事物配置

    对于软件系统而言,持久化数据到数据库是至关重要的一部分.在 Java 领域,有很多的实现了数据持久化层的工具和框架(ORM).ORM 框架的本质是简化编程中操作数据库的繁琐性,比如可以根据对象生成 S ...

随机推荐

  1. junethack使用指南

    本文面向有志于参加Nethack六月衍生大赛,且具有一定英文水平的玩家. 首先,在Junethack服务器页面挑一个在线服务器的网站,个人推荐 hardfought.org,因为访问速度较快. 然后, ...

  2. R树判断点在多边形内-Java版本

    1.什么是RTree 待补充 2.RTree java依赖 rtree的java开源版本在GitHub上:https://github.com/davidmoten/rtree 上面有详细的使用说明 ...

  3. JVM探究

    1.JVM探究 请你谈谈你对JVM的理解?java8虚拟机和之前的变化更新? 什么是OOM,什么是栈溢出StackOverFlowError?怎么分析? JVM的常用调优参数有哪些? 内存快照如何抓取 ...

  4. django-rest-framework 基础三 认证、权限和频率

    django-rest-framework 基础三 认证.权限和频率 目录 django-rest-framework 基础三 认证.权限和频率 1. 认证 1.1 登录接口 1.2 认证 2. 权限 ...

  5. 改善java程序

    1.用偶判断,不用奇判断.因为负数会出错. // 不使用 String str = i + "->" + (i%2 == 1? "奇数": "偶 ...

  6. Nginx的mirror指令能干啥?

    mirror 流量复制 Nginx的 mirror 指令来自于 ngx_http_mirror_module 模块 Nginx Version > 1.13.4 mirror 指令提供的核心功能 ...

  7. OPRF

    在PSI中经常用到OPRF技术,现在系统学习一下. PRF Pseudo Random Function,伪随机函数,主要就是用来产生为伪随机数的. 伪随机数 什么伪随机数? 伪随机数是用确定性的算法 ...

  8. 多线程07:async、future、packaged_task、promise

    async.future.packaged_task.promise 本节内容需要包含头文件:#include <future> 一.std::async. std::future 创建后 ...

  9. 445. Add Two Numbers II - LeetCode

    Question 445. Add Two Numbers II Solution 题目大意:两个列表相加 思路:构造两个栈,两个列表的数依次入栈,再出栈的时候计算其和作为返回链表的一个节点 Java ...

  10. 将汇总结果导出到MySQL

    ①mysql建表test1 ②cd /opt/module/sqoop进入scoop路径 ③ bin/sqoop export \ > --connect jdbc:mysql://master ...