微服务日志之Spring Boot Kafka实现日志收集

yoyofx

发布于 2018-09-05 11:07:22

2K0

发布于 2018-09-05 11:07:22

文章被收录于专栏：ASP.NETCoreASP.NETCore

前言

承接上文( 微服务日志之.NET Core使用NLog通过Kafka实现日志收集 https://cloud.tencent.com/developer/article/1328903 ).NET/Core的实现,我们的目地是为了让微服务环境中dotnet和java的服务都统一的进行日志收集。

Java体系下Spring Boot + Logback很容易就接入了Kafka实现了日志收集。

Spring Boot集成

Maven 包管理

<dependencyManagement>
  <dependencies>
     <dependency>
    <groupId>ch.qos.logback</groupId>
    <artifactId>logback-core</artifactId>
    <version>1.2.3</version>
    </dependency>
  </dependencies>
</dependencyManagement>

包依赖引用:

<dependency>
    <groupId>com.github.danielwegener</groupId>
    <artifactId>logback-kafka-appender</artifactId>
    <version>0.2.0-RC1</version>
</dependency>
<dependency>
    <groupId>ch.qos.logback</groupId>
    <artifactId>logback-classic</artifactId>
    <version>1.2.3</version>
    <scope>runtime</scope>
</dependency>
<dependency>
    <groupId>net.logstash.logback</groupId>
    <artifactId>logstash-logback-encoder</artifactId>
    <version>5.0</version>
</dependency>

logback-spring.xml

在Spring Boot项目resources目录下添加logback-spring.xml配置文件，注意：一定要修改 {"appname":"webdemo"}，这个值也可以在配置中设置为变量。添加如下配置，STDOUT是在连接失败时，使用的日志输出配置。所以这每个项目要根据自己的情况添加配置。在普通日志输出中使用异步策略提高性能，内容如下:

 <appender name="kafkaAppender" class="com.github.danielwegener.logback.kafka.KafkaAppender">
        <encoder charset="UTF-8" class="net.logstash.logback.encoder.LogstashEncoder" >
            <customFields>{"appname":"webdemo"}</customFields>
            <includeMdc>true</includeMdc>
            <includeContext>true</includeContext>
            <throwableConverter class="net.logstash.logback.stacktrace.ShortenedThrowableConverter">
                <maxDepthPerThrowable>30</maxDepthPerThrowable>
                <rootCauseFirst>true</rootCauseFirst>
            </throwableConverter>
        </encoder>
        <topic>loges</topic>
        <keyingStrategy class="com.github.danielwegener.logback.kafka.keying.HostNameKeyingStrategy" />
        <deliveryStrategy class="com.github.danielwegener.logback.kafka.delivery.AsynchronousDeliveryStrategy" />
        <producerConfig>bootstrap.servers=127.0.0.1:9092</producerConfig>
        <!-- don't wait for a broker to ack the reception of a batch.  -->
        <producerConfig>acks=0</producerConfig>
        <!-- wait up to 1000ms and collect log messages before sending them as a batch -->
        <producerConfig>linger.ms=1000</producerConfig>
        <!-- even if the producer buffer runs full, do not block the application but start to drop messages -->
        <!--<producerConfig>max.block.ms=0</producerConfig>-->
        <producerConfig>block.on.buffer.full=false</producerConfig>
        <!-- kafka连接失败后，使用下面配置进行日志输出 -->
        <appender-ref ref="STDOUT" />
    </appender>

注意：一定要修改 {"appname":"webdemo"} ，这个值也可以在配置中设置为变量。对于第三方框架或库的错误和异常信息如需要写入日志,错误配置如下：

<appender name="kafkaAppenderERROR" class="com.github.danielwegener.logback.kafka.KafkaAppender">
        <encoder charset="UTF-8" class="net.logstash.logback.encoder.LogstashEncoder" >
            <customFields>{"appname":"webdemo"}</customFields>
            <includeMdc>true</includeMdc>
            <includeContext>true</includeContext>
            <throwableConverter class="net.logstash.logback.stacktrace.ShortenedThrowableConverter">
                <maxDepthPerThrowable>30</maxDepthPerThrowable>
                <rootCauseFirst>true</rootCauseFirst>
            </throwableConverter>
        </encoder>
        <topic>ep_component_log</topic>
        <keyingStrategy class="com.github.danielwegener.logback.kafka.keying.HostNameKeyingStrategy" />
        <deliveryStrategy class="com.github.danielwegener.logback.kafka.delivery.AsynchronousDeliveryStrategy" />
        <deliveryStrategy class="com.github.danielwegener.logback.kafka.delivery.BlockingDeliveryStrategy">
            <!-- wait indefinitely until the kafka producer was able to send the message -->
            <timeout>0</timeout>
        </deliveryStrategy>
        <producerConfig>bootstrap.servers=127.0.0.1:9020</producerConfig>
        <!-- don't wait for a broker to ack the reception of a batch.  -->
        <producerConfig>acks=0</producerConfig>
        <!-- wait up to 1000ms and collect log messages before sending them as a batch -->
        <producerConfig>linger.ms=1000</producerConfig>
        <!-- even if the producer buffer runs full, do not block the application but start to drop messages -->
        <producerConfig>max.block.ms=0</producerConfig>
        <appender-ref ref="STDOUT" />
        <filter class="ch.qos.logback.classic.filter.LevelFilter"><!-- 只打印错误日志 -->
            <level>ERROR</level>
            <onMatch>ACCEPT</onMatch>
            <onMismatch>DENY</onMismatch>
        </filter>
    </appender>

在异常日志用使用了同步策略保证，错误日志的有效收集，当然可以根据实际项目情况进行配置。

LOG配置建议：

日志root指定错误即可输出第三方框架异常日志:

 <root level="INFO">
        <appender-ref ref="kafkaAppenderERROR" />
 </root>

建议只输出自己程序里的级别日志配置如下（只供参考）：

<logger name="项目所在包" additivity="false">
    <appender-ref ref="STDOUT" />
    <appender-ref ref="kafkaAppender" />
</logger>

最后

GitHub：https://github.com/maxzhang1985/YOYOFx 如果觉还可以请Star下，欢迎一起交流。

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原始发表：2018-08-28 ，如有侵权请联系 cloudcommunity@tencent.com 删除

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