为了账号安全,请及时绑定邮箱和手机立即绑定
首页 手记 Spring Cloud...

Spring Cloud Sleuth使用ELK收集&分析日志

2019.08.29 11:40 7692浏览

TIPS

本文基于Spring Cloud Greenwich SR2,理论兼容Spring Cloud所有版本。

应用整合

  • 加依赖:

    <dependency>
          <groupId>org.springframework.cloud</groupId>
          <artifactId>spring-cloud-starter-sleuth</artifactId>
        </dependency>
        <dependency>
          <groupId>net.logstash.logback</groupId>
          <artifactId>logstash-logback-encoder</artifactId>
          <version>6.1</version>
        </dependency>
    

    注意, logstash-logback-encoder版本务必和Logback兼容,否则会导致应用启动不起来,而且不会打印任何日志!可前往 https://github.com/logstash/logstash-logback-encoder 查看和Logback的兼容性。

  • resources 目录下创建配置文件:logback-spring.xml ,内容如下:

    <?xml version="1.0" encoding="UTF-8"?>
    <configuration>
        <include resource="org/springframework/boot/logging/logback/defaults.xml"/><springProperty scope="context" name="springAppName" source="spring.application.name"/>
        <!-- Example for logging into the build folder of your project -->
        <property name="LOG_FILE" value="/Users/reno/Desktop/未命名文件夹/elk/logs/${springAppName}"/><!-- You can override this to have a custom pattern -->
        <property name="CONSOLE_LOG_PATTERN"
                  value="%clr(%d{yyyy-MM-dd HH:mm:ss.SSS}){faint} %clr(${LOG_LEVEL_PATTERN:-%5p}) %clr(${PID:- }){magenta} %clr(---){faint} %clr([%15.15t]){faint} %clr(%-40.40logger{39}){cyan} %clr(:){faint} %m%n${LOG_EXCEPTION_CONVERSION_WORD:-%wEx}"/>
    
        <!-- Appender to log to console -->
        <appender name="console" class="ch.qos.logback.core.ConsoleAppender">
            <filter class="ch.qos.logback.classic.filter.ThresholdFilter">
                <!-- Minimum logging level to be presented in the console logs-->
                <level>DEBUG</level>
            </filter>
            <encoder>
                <pattern>${CONSOLE_LOG_PATTERN}</pattern>
                <charset>utf8</charset>
            </encoder>
        </appender>
    
        <!-- Appender to log to file --><appender name="flatfile" class="ch.qos.logback.core.rolling.RollingFileAppender">
            <file>${LOG_FILE}</file>
            <rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">
                <fileNamePattern>${LOG_FILE}.%d{yyyy-MM-dd}.gz</fileNamePattern>
                <maxHistory>7</maxHistory>
            </rollingPolicy>
            <encoder>
                <pattern>${CONSOLE_LOG_PATTERN}</pattern>
                <charset>utf8</charset>
            </encoder>
        </appender><!-- Appender to log to file in a JSON format -->
        <appender name="logstash" class="ch.qos.logback.core.rolling.RollingFileAppender">
            <file>${LOG_FILE}.json</file>
            <rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">
                <fileNamePattern>${LOG_FILE}.json.%d{yyyy-MM-dd}.gz</fileNamePattern>
                <maxHistory>7</maxHistory>
            </rollingPolicy>
            <encoder class="net.logstash.logback.encoder.LoggingEventCompositeJsonEncoder">
                <providers>
                    <timestamp>
                        <timeZone>UTC</timeZone>
                    </timestamp>
                    <pattern>
                        <pattern>
                            {
                            "severity": "%level",
                            "service": "${springAppName:-}",
                            "trace": "%X{X-B3-TraceId:-}",
                            "span": "%X{X-B3-SpanId:-}",
                            "parent": "%X{X-B3-ParentSpanId:-}",
                            "exportable": "%X{X-Span-Export:-}",
                            "pid": "${PID:-}",
                            "thread": "%thread",
                            "class": "%logger{40}",
                            "rest": "%message"
                            }
                        </pattern>
                    </pattern>
                </providers>
            </encoder>
        </appender><root level="INFO">
            <appender-ref ref="console"/>
            <!-- uncomment this to have also JSON logs -->
            <appender-ref ref="logstash"/>
            <!--<appender-ref ref="flatfile"/>-->
        </root>
    </configuration>
    
  • 新建 bootstrap.yml ,并将application.yml 中的以下属性移到bootstrap.yml 中。

    spring:
      application:
        name: user-center
    

    由于上面的 logback-spring.xml 含有变量(例如 springAppName ),故而 spring.application.name 属性必须设置在 bootstrap.yml 文件中,否则,logback-spring.xml 将无法正确读取属性。

测试

  • 启动应用

  • 日志会打印到 /Users/reno/Desktop/未命名文件夹/elk/logs/目录中 ,并且文件名称为 user-center.json ,内容类似如下:

    {"@timestamp":"2019-08-29T02:38:42.468Z","severity":"DEBUG","service":"microservice-provider-user","trace":"5cf9479e966fb5ec","span":"5cf9479e966fb5ec","parent":"","exportable":"false","pid":"13144","thread":"http-nio-8000-exec-1","class":"o.s.w.s.m.m.a.RequestResponseBodyMethodProcessor","rest":"Using 'application/json;q=0.8', given [text/html, application/xhtml+xml, image/webp, image/apng, application/signed-exchange;v=b3, application/xml;q=0.9, */*;q=0.8] and supported [application/json, application/*+json, application/json, application/*+json]"}
    {"@timestamp":"2019-08-29T02:38:42.469Z","severity":"DEBUG","service":"microservice-provider-user","trace":"5cf9479e966fb5ec","span":"5cf9479e966fb5ec","parent":"","exportable":"false","pid":"13144","thread":"http-nio-8000-exec-1","class":"o.s.w.s.m.m.a.RequestResponseBodyMethodProcessor","rest":"Writing [Optional[User(id=1, username=account1, name=张三, age=20, balance=100.00)]]"}
    {"@timestamp":"2019-08-29T02:38:42.491Z","severity":"DEBUG","service":"microservice-provider-user","trace":"5cf9479e966fb5ec","span":"5cf9479e966fb5ec","parent":"","exportable":"false","pid":"13144","thread":"http-nio-8000-exec-1","class":"o.s.o.j.s.OpenEntityManagerInViewInterceptor","rest":"Closing JPA EntityManager in OpenEntityManagerInViewInterceptor"}
    {"@timestamp":"2019-08-29T02:38:42.492Z","severity":"DEBUG","service":"microservice-provider-user","trace":"5cf9479e966fb5ec","span":"5cf9479e966fb5ec","parent":"","exportable":"false","pid":"13144","thread":"http-nio-8000-exec-1","class":"o.s.web.servlet.DispatcherServlet","rest":"Completed 200 OK"}
    {"@timestamp":"2019-08-29T02:38:58.141Z","severity":"ERROR","service":"microservice-provider-user","trace":"","span":"","parent":"","exportable":"","pid":"13144","thread":"ThreadPoolTaskScheduler-1","class":"o.s.c.alibaba.nacos.discovery.NacosWatch","rest":"Error watching Nacos Service change"}
    

    下面,只需要让Logstash收集到这个JSON文件,就可以在Kibana上检索日志啦!

ELK搭建

简单起见,本文使用Docker搭建ELK;其他搭建方式,请看官自行百度,比较简单,但很耗时。

  • 创建 docker-compose.yml 文件,内容如下:

    version: '3'
    services:
      elasticsearch:
        image: elasticsearch:7.3.1
        environment:
          discovery.type: single-node
        ports:
          - "9200:9200"
          - "9300:9300"
      logstash:
        image: logstash:7.3.1
        command: logstash -f /etc/logstash/conf.d/logstash.conf
        volumes:
          # 挂载logstash配置文件
          - ./config:/etc/logstash/conf.d
          - /Users/reno/Desktop/未命名文件夹/elk/logs/:/opt/build/
        ports:
          - "5000:5000"
      kibana:
        image: kibana:7.3.1
        environment:
          - ELASTICSEARCH_URL=http://elasticsearch:9200
        ports:
          - "5601:5601"
    

    需要注意,上面的 /Users/reno/Desktop/未命名文件夹/elk/logs/ 需要改成你应用的打印路径。

  • 在docker-compose.yml文件所在目录创建 config/logstash.conf ,内容如下:

    input {
      file {
        codec => json
        path => "/opt/build/*.json"  # 改成你项目打印的json日志文件。
      }
    }
    filter {
      grok {
        match => { "message" => "%{TIMESTAMP_ISO8601:timestamp}\s+%{LOGLEVEL:severity}\s+\[%{DATA:service},%{DATA:trace},%{DATA:span},%{DATA:exportable}\]\s+%{DATA:pid}\s+---\s+\[%{DATA:thread}\]\s+%{DATA:class}\s+:\s+%{GREEDYDATA:rest}" }
      }
    }
    output {
      elasticsearch {
        hosts => "elasticsearch:9200"  # 改成你的Elasticsearch地址
      }
    }
    
  • 启动ELK

    docker-compose up
    

测试Sleuth & ELK

  • 访问你微服务的API,让它生成一些日志(如果产生日志比较少,可将 org.springframework 包的日志级别设为 debug

  • 访问 http://localhost:5601 (Kibana地址),可看到类似如下的界面,按照如图配置Kibana。

  • 图片描述

  • 图片描述

  • 输入条件,即可分析日志:

    图片描述

原理分析

原理比较简单:

  • 让Sleuth打印JSON格式的日志;
  • 然后在Logstash的配置文件中,配置grok语法,解析并收集JSON格式的日志,并存储到Elasticsearch中去;
  • Kibana可视化分析日志。

···················
欢迎关注课程:
面向未来微服务:Spring Cloud Alibaba从入门到进阶

点击查看更多内容

本文原创发布于慕课网 ,转载请注明出处,谢谢合作

3人点赞

若觉得本文不错,就分享一下吧!

评论

相关文章推荐

正在加载中
意见反馈 帮助中心 APP下载
官方微信

举报

0/150
提交
取消