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://www.cnblogs.com/maxzhang1985/p/9522017.html ).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

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