SpringCloud Sleuth 必知必会
- SpringCloud Sleuth 实现的功能是：它会自动为当前应用构建起各通信通道的跟踪机制
  1. 通过诸如 RabbitMQ、Kafka（或者其他任何 SpringCloud Sleuth 绑定器实现的消息中间件）传递的请求
  2. 通过 Zuul、Gateway 代理传递的请求
  3. 通过 RestTemplate 发起的请求
SpringCloud Sleuth 跟踪实现原理
- 为了实现请求跟踪：当请求发送到分布式系统的入口端点时，只需要服务跟踪框架为该请求创建一个唯一的跟踪标识 Trace ID
- 为了统计各处理单元的时间延迟，当请求到达各个服务组件时，或是处理逻辑到达某个状态时，也通过一个唯一标识来标记它的开始、具体过程以及结束，Span ID

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.edge-pattern-dashed{stroke-dasharray:3}#mermaid-svg-01gUNKYLeG2FibyJ .edge-pattern-dotted{stroke-dasharray:2}#mermaid-svg-01gUNKYLeG2FibyJ .marker{fill:#333}#mermaid-svg-01gUNKYLeG2FibyJ .marker.cross{stroke:#333}:root { --mermaid-font-family: "trebuchet ms", verdana, arial;}#mermaid-svg-01gUNKYLeG2FibyJ {color: rgba(0, 0, 0, 0.75);font: ;}

Service A - traceId, spanIdA

Service B - traceId, spanIdA1

Service C - traceId, spanIdA12

Service D - traceId, spanIdA11

Span ID 如果要计算时间延迟，可以通过 spanIdA11 - spanIdA1

8.1.2 Zipkin 是什么

Zipkin 的基础概念
- Zipkin 解决微服务架构中的延迟问题，包括数据的收集、存储、查找和展现
- Zipkin 有四大核心组件构成
  1. Collector：收集器组件
  2. Storge：存储组件
  3. API：RESTFul API，提供外部访问接口
  4. UI：Web UI，提供可视化查询页面

8.2.1 集成 SpringCloud Sleuth 实现微服务通信跟踪

8.2.1.1 集成步骤

保证服务与服务之间存在跨进程通信
Maven 依赖

8.2.1.2 编写测试代码

sca-commerce-gateway 与 sca-commerce-alibaba-nacos-client 添加 Maven 依赖

<!-- 通过 Sleuth 实现链路跟踪 -->
<dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-sleuth</artifactId>
</dependency>

sca-commerce-alibaba-nacos-client 编写测试业务代码与控制层代码

SleuthTraceInfoService

package com.edcode.commerce.service;import brave.Tracer;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.springframework.stereotype.Service;/*** @author eddie.lee* @blog blog.eddilee.cn* @description 使用代码更直观的看到 Sleuth 生成的相关跟踪信息*/
@Slf4j
@Service
@RequiredArgsConstructor
public class SleuthTraceInfoService {/** brave.Tracer 跟踪对象 */private final Tracer tracer;/*** 打印当前的跟踪信息到日志中*/public void logCurrentTraceInfo() {log.info("Sleuth trace id: [{}]", tracer.currentSpan().context().traceId());log.info("Sleuth span id: [{}]", tracer.currentSpan().context().spanId());}
}

SleuthTraceInfoController

package com.edcode.commerce.controller;import com.edcode.commerce.service.SleuthTraceInfoService;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;/*** @author eddie.lee* @blog blog.eddilee.cn* @description 打印跟踪信息*/
@Slf4j
@RestController
@RequestMapping("/sleuth")
@RequiredArgsConstructor
public class SleuthTraceInfoController {private final SleuthTraceInfoService traceInfoService;/*** 打印日志跟踪信息*/@GetMapping("/trace-info")public void logCurrentTraceInfo() {traceInfoService.logCurrentTraceInfo();}
}

8.2.1.2 测试请求与查看控制台日志

发起请求

### 查看 Sleuth 跟踪信息
GET http://127.0.0.1:9001/edcode/scacommerce-nacos-client/sleuth/trace-info
Accept: application/json
sca-commerce-user: eyJhbGciOiJSUzI1NiJ9.eyJzY2EtY29tbWVyY2UtdXNlciI6IntcImlkXCI6MTEsXCJ1c2VybmFtZVwiOlwiZWRkaWVAcXEuY29tXCJ9IiwianRpIjoiZjQ3M2NhZjctY2RjMi00ZmE4LWExNzQtZjZhYmQ5ZDFjMzAzIiwiZXhwIjoxNjM1ODY4ODAwfQ.iTtQE2gHzjPxVP5SEFHrDBkvrzI-yt6oy-w1x--Q3ahhTvYLTiYnvndtIx7IIyYipr_ayZnAQyluPt3oiLaS80r9qByaN3zQF-6gBW_wu_fd0yd89hIjPnQeP1mY2NcchV2FaMUW7Jlq8CUDPurEhW4GUDXOqBXgmxai5UTu4yoXBUfyXUXznKTx697cGo5aoVKTAKvMReJg-77n5sQuafZNDu6pz2D1KMvEucNyZtbXw0JRIl1CsK777Jt3IG1bnOnwRBt8o1tkodZ3zJbfgTGVCHJmfEuUnXwdf4DLAq568pNVvylPLh4_r-UUGGxE6Az9XwOtl1w4vzK1M2ATzw
token: edcode

响应信息

GET http://127.0.0.1:9001/edcode/scacommerce-nacos-client/sleuth/trace-infoHTTP/1.1 200 OK
transfer-encoding: chunked
Content-Type: application/json
Date: Tue, 02 Nov 2021 13:04:55 GMT{"code": 0,"message": "","data": null
}Response code: 200 (OK); Time: 1160ms; Content length: 35 bytes

查看日志

sca-commerce-gateway

2021-11-02 21:04:55.332  INFO [sca-commerce-gateway,353ea734cc43d6ee,353ea734cc43d6ee,true] 1060 --- [ctor-http-nio-2] c.netflix.config.ChainedDynamicProperty  : Flipping property: sca-commerce-nacos-client.ribbon.ActiveConnectionsLimit to use NEXT property: niws.loadbalancer.availabilityFilteringRule.activeConnectionsLimit = 2147483647
2021-11-02 21:04:55.347  INFO [sca-commerce-gateway,353ea734cc43d6ee,353ea734cc43d6ee,true] 1060 --- [ctor-http-nio-2] c.netflix.loadbalancer.BaseLoadBalancer  : Client: sca-commerce-nacos-client instantiated a LoadBalancer: DynamicServerListLoadBalancer:{NFLoadBalancer:name=sca-commerce-nacos-client,current list of Servers=[],Load balancer stats=Zone stats: {},Server stats: []}ServerList:null
2021-11-02 21:04:55.353  INFO [sca-commerce-gateway,353ea734cc43d6ee,353ea734cc43d6ee,true] 1060 --- [ctor-http-nio-2] c.n.l.DynamicServerListLoadBalancer      : Using serverListUpdater PollingServerListUpdater
2021-11-02 21:04:55.372  INFO [sca-commerce-gateway,353ea734cc43d6ee,353ea734cc43d6ee,true] 1060 --- [ctor-http-nio-2] c.netflix.config.ChainedDynamicProperty  : Flipping property: sca-commerce-nacos-client.ribbon.ActiveConnectionsLimit to use NEXT property: niws.loadbalancer.availabilityFilteringRule.activeConnectionsLimit = 2147483647
2021-11-02 21:04:55.374  INFO [sca-commerce-gateway,353ea734cc43d6ee,353ea734cc43d6ee,true] 1060 --- [ctor-http-nio-2] c.n.l.DynamicServerListLoadBalancer      : DynamicServerListLoadBalancer for client sca-commerce-nacos-client initialized: DynamicServerListLoadBalancer:{NFLoadBalancer:name=sca-commerce-nacos-client,current list of Servers=[192.168.3.192:8000],Load balancer stats=Zone stats: {unknown=[Zone:unknown; Instance count:1;   Active connections count: 0;    Circuit breaker tripped count: 0;   Active connections per server: 0.0;]
},Server stats: [[Server:192.168.3.192:8000;    Zone:UNKNOWN;   Total Requests:0;   Successive connection failure:0;    Total blackout seconds:0;   Last connection made:Thu Jan 01 08:00:00 CST 1970;  First connection made: Thu Jan 01 08:00:00 CST 1970;    Active Connections:0;   total failure count in last (1000) msecs:0; average resp time:0.0;  90 percentile resp time:0.0;    95 percentile resp time:0.0;    min resp time:0.0;  max resp time:0.0;  stddev resp time:0.0]
]}ServerList:com.alibaba.cloud.nacos.ribbon.NacosServerList@72186c8f
2021-11-02 21:04:55.592  INFO [sca-commerce-gateway,353ea734cc43d6ee,353ea734cc43d6ee,true] 1060 --- [ctor-http-nio-2] c.e.c.filter.GlobalElapsedLogFilter      : [/edcode/scacommerce-nacos-client/sleuth/trace-info] elapsed: [1034ms]
2021-11-02 21:04:56.358  INFO [sca-commerce-gateway,,,] 1060 --- [erListUpdater-0] c.netflix.config.ChainedDynamicProperty  : Flipping property: sca-commerce-nacos-client.ribbon.ActiveConnectionsLimit to use NEXT property: niws.loadbalancer.availabilityFilteringRule.activeConnectionsLimit = 2147483647

sca-commerce-alibaba-nacos-client

2021-11-02 21:04:55.543  INFO [sca-commerce-nacos-client,353ea734cc43d6ee,c85be2c1bb127558,true] 33740 --- [nio-8000-exec-1] c.e.c.service.SleuthTraceInfoService     : Sleuth trace id: [3836687777773377262]
2021-11-02 21:04:55.543  INFO [sca-commerce-nacos-client,353ea734cc43d6ee,c85be2c1bb127558,true] 33740 --- [nio-8000-exec-1] c.e.c.service.SleuthTraceInfoService     : Sleuth span id: [-4009361721548180136]

解析：[sca-commerce-nacos-client,353ea734cc43d6ee,c85be2c1bb127558,true]
第一行：service name
第二行：trace id
第三行：span id

8.3.1 搭建 Zipkin Server 实现对跟踪信息的收集

8.3.1.1 ZS搭建步骤

Tips：SpringCloud Finchley 版本（包含）之后，官方不建议自己搭建 Zipkin-Server，提供了已经打包好的jar文件（SpringBoot工程），直接下载启动即可
下载地址
- curl -sSL https://zipkin.io/quickstart.sh | bash -s
1. 选择自己需要的版本即可
2. 选择 *.exec.jar 结尾的 jar

8.3.1.2 Linux 终端

[root@localhost opt]# curl -sSL https://zipkin.io/quickstart.sh | bash -s
Thank you for trying Zipkin!
This installer is provided as a quick-start helper, so you can try Zipkin out
without a lengthy installation process.Fetching version number of latest io.zipkin:zipkin-server release...
Latest release of io.zipkin:zipkin-server seems to be 2.23.4Downloading io.zipkin:zipkin-server:2.23.4:exec to zipkin.jar...
> curl -fL -o 'zipkin.jar' 'https://repo1.maven.org/maven2/io/zipkin/zipkin-server/2.23.4/zipkin-server-2.23.4-exec.jar'% Total    % Received % Xferd  Average Speed   Time    Time     Time  CurrentDload  Upload   Total   Spent    Left  Speed
100 59.0M  100 59.0M    0     0  34146      0  0:30:14  0:30:14 --:--:-- 33309Verifying checksum...
> curl -fL -o 'zipkin.jar.md5' 'https://repo1.maven.org/maven2/io/zipkin/zipkin-server/2.23.4/zipkin-server-2.23.4-exec.jar.md5'% Total    % Received % Xferd  Average Speed   Time    Time     Time  CurrentDload  Upload   Total   Spent    Left  Speed
100    32  100    32    0     0     17      0  0:00:01  0:00:01 --:--:--    17
> md5sum -c <<< "$(cat zipkin.jar.md5)  zipkin.jar"
zipkin.jar: OK
Checksum for zipkin.jar passes verificationVerifying GPG signature of zipkin.jar...
> curl -fL -o 'zipkin.jar.asc' 'https://repo1.maven.org/maven2/io/zipkin/zipkin-server/2.23.4/zipkin-server-2.23.4-exec.jar.asc'% Total    % Received % Xferd  Average Speed   Time    Time     Time  CurrentDload  Upload   Total   Spent    Left  Speed
100   833  100   833    0     0     91      0  0:00:09  0:00:09 --:--:--   180GPG signing key is not known, skipping signature verification.
Use the following commands to manually verify the signature of zipkin.jar:gpg --keyserver keyserver.ubuntu.com --recv FF31B515# Optionally trust the key via 'gpg --edit-key FF31B515', then typing 'trust',# choosing a trust level, and exiting the interactive GPG session by 'quit'gpg --verify zipkin.jar.asc zipkin.jarYou can now run the downloaded executable jar:java -jar zipkin.jar[root@localhost opt]# nohup java -jar zipkin.jar &
[1] 30238
[root@localhost opt]# nohup: ignoring input and appending output to ‘nohup.out’

8.3.1.3 Zipkin Web UI

访问：IP:9411

8.3.2 配置 Zipkin Server 实现对跟踪信息的收集

配置 ZS
- 为什么需要对 ZS 做自定义配置？
  1. 默认情况下， ZS 将 跟踪信息存储在内存中（JVM），重启会丢失
  2. ZS 默认使用 HTTP 方式上报跟踪数据，性能较差
- ZS 配置 MySQL 跟踪数据持久化（同时它也支持 ES）
  1. MySQL 中添加数据表：https://github.com/openzipkin/zipkin/blob/master/zipkin-storage/mysql-v1/src/main/resources/mysql.sql
  2. ZS 启动指定 MySQL 路径

8.4.1 SpringCloud Sleuth 整合 Zipkin 实现分布式链路跟踪、收集

SpringCloud Sleuth 整合 Zipkin 步骤
- 简单的两个步骤（Zipkin Server 使用 MySQL 实现跟踪数据持久化）
  - Maven 依赖
  - bootstrap.yml 中增加 Zipkin 的配置
下载、安装 Kafka
- 下载 Kafka：https://kafka.apache.org/quickstart
- 解压、启动 ZK 和 Kafka Server 即可（使用默认配置）

8.4.1.1 下载与解压 Kafka

Downloads

https://kafka.apache.org/downloads

Linux 步骤

[root@localhost opt]# wget https://dlcdn.apache.org/kafka/3.0.0/kafka_2.13-3.0.0.tgz
[root@localhost opt]# tar -zxf kafka_2.13-3.0.0.tgz
[root@localhost opt]# ls -la | grep kafka
drwxr-xr-x.  8 root root       134 Nov  3 01:48 kafka_2.13-3.0.0
-rw-r--r--.  1 root root  86396520 Sep 20 04:46 kafka_2.13-3.0.0.tgz

8.4.1.2 启动 zookeeper 与 Kafka

对外访问需要修改 Kafka 的 server.properties

找到 advertised.listeners 或者自行添加 advertised.listeners 指定 IP 地址

[root@localhost kafka_2.13-3.0.0]# vim /opt/kafka_2.13-3.0.0/config/server.propertiesadvertised.listeners=PLAINTEXT://192.168.3.250:9092

后台启动 zookeeper

[root@localhost kafka_2.13-3.0.0]# nohup /opt/kafka_2.13-3.0.0/bin/zookeeper-server-start.sh config/zookeeper.properties &
[1] 31998
[root@localhost kafka_2.13-3.0.0]# nohup: ignoring input and appending output to ‘nohup.out’

后台启动 kafka

[root@localhost kafka_2.13-3.0.0]# nohup /opt/kafka_2.13-3.0.0/bin/kafka-server-start.sh config/server.properties &
[1] 32574
[root@localhost kafka_2.13-3.0.0]# nohup: ignoring input and appending output to ‘nohup.out’

8.4.1.3 运行 ZipKin 关联 Kafka 与 MySQL

[root@localhost opt]# nohup java -DKAFKA_BOOTSTRAP_SERVERS=127.0.0.1:9092 -jar zipkin.jar --STORAGE_TYPE=mysql --MYSQL_USER=root --MYSQL_PASS=123456 --MYSQL_HOST=127.0.0.1 --MYSQL_TCP_PORT=3306 --MYSQL_DB=zipkin &
[1] 601
[root@localhost opt]# nohup: ignoring input and appending output to ‘nohup.out’

连接kafka：-DKAFKA_BOOTSTRAP_SERVERS=127.0.0.1:9092

连接MySQL：–STORAGE_TYPE=mysql --MYSQL_USER=root --MYSQL_PASS=123456 --MYSQL_HOST=127.0.0.1 --MYSQL_TCP_PORT=3306 --MYSQL_DB=zipkin

8.4.1.4 检查 Linux 服务是否启动

[root@localhost opt]# ps -aux | grep -E 'nacos|zipkin|kafka|zookeeper'
[root@localhost opt]# netstat -ltnp | grep -E '8848|9092|9411|2181'
tcp6       0      0 :::8848                 :::*                    LISTEN      1932/java
tcp6       0      0 :::9411                 :::*                    LISTEN      601/java
tcp6       0      0 :::9092                 :::*                    LISTEN      32574/java
tcp6       0      0 :::2181                 :::*                    LISTEN      31998/java

8.4.1.4 IDEA 启动服务与测试发起请求

Maven 依赖（zipkin 与 kafka）

<!-- 通过 Sleuth 实现链路跟踪 -->
<!--        <dependency>-->
<!--            <groupId>org.springframework.cloud</groupId>-->
<!--            <artifactId>spring-cloud-starter-sleuth</artifactId>-->
<!--        </dependency>-->
<!-- zipkin = spring-cloud-starter-sleuth + spring-cloud-sleuth-zipkin-->
<dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-zipkin</artifactId>
</dependency>
<dependency><groupId>org.springframework.kafka</groupId><artifactId>spring-kafka</artifactId><version>2.5.0.RELEASE</version>
</dependency>

修改 Gateway 与 Nacos-Client 服务的配置文件

spring:kafka:bootstrap-servers: ${KAFKA_SERVER:127.0.0.1}:${KAFKA_PORT:9092}producer:retries: 3consumer:auto-offset-reset: latestzipkin:sender:type: ${ZIPKIN_KAFKA_SENDER:web} # 默认是 webbase-url: http://${ZIPKIN_URL:localhost}:${ZIPKIN_PORT:9411}/

两个服务都需要添加 kafka 与 zipkin 的连接信息

启动服务

启动以下服务
- AuthorityCenterApplication :7000/ # 如果 token 过期，需要重新签发
- NacosClientApplication :8000/
- GatewayApplication :9001/

请求测试

sca-commerce-gateway/src/main/resources/http/nacos-client.http

### 查询服务
GET http://127.0.0.1:9001/edcode/scacommerce-nacos-client/nacos-client/service-instance?serviceId=sca-commerce-gateway
Accept: application/json
sca-commerce-user: eyJhbGciOiJSUzI1NiJ9.eyJzY2EtY29tbWVyY2UtdXNlciI6IntcImlkXCI6MTEsXCJ1c2VybmFtZVwiOlwiZWRkaWVAcXEuY29tXCJ9IiwianRpIjoiMWU1MGI2ZWYtNmUzOS00YmY2LWJlMjktZDc4NWU3NWQyNmY1IiwiZXhwIjoxNjM1OTU1MjAwfQ.P7GxZuMUrgiMUbD4dNYzQiV3A6YkaFpvlzg8cpBdu_hvxqDsVEuuiYODQSzZPQeN3xTQPbJ70zkSY084HV7Vsk929en1lqNiX_dpQEuGSbz2JSPqyJuLZ6v7hRX9GI32sPrZAnaKVXMdeHUXCMMmaS1L3osimSvAlaoDE0n2UukDLgu83xRlL3bddHIJbmFD5BrV6Y-u9d-blqXPOpxFEYkdwS_XrljYiULTH7Olr71TAwODUPdttnmVhHPXB0_dnOG5DZMOC0OxqokHGZJ7CC86paE4TvdNPwqotB6u6zh_d_YCCBWM3t1LmKYB6E_bnz2taL5Q4AYHlRaZZotaAA
token: edcode ## HeaderTokenGatewayFilter###

8.4.1.5 Zipkin Web UI

如何简单的使用

打开 http://192.168.3.250:9411

默认 all，然后直接查找，会显示所有的请求信息，点击其中一条

就会看到该请求的所有经过哪些服务，耗时多少

同样，也可以在终端拿 trace Id：669b59f38adf2c38 去跟踪链路

trace Id 搜索框：669b59f38adf2c38

如何查看服务之间的依赖关系

点击上方的【依赖】

8.5.1 Spring Cloud Sleuth 设置采样率、抽样收集策略

8.5.1.1 Spring Cloud Sleuth 采样收集

收集跟踪信息是一把双刃剑，需要做好权衡
- 收集的跟踪信息越多，越能反映出系统的实际运行情况
- 高并发场景下，大量的请求调用会产生海量的跟踪日志信息，性能开销太大

开发与测试环境可以使用高的采样率，但是生产环境建议不要这么做。

可以自由选择 Zipkin brave 自带的两个抽样策略
- ProbabilityBasedSampler 采样率策略
  - 默认使用的策略，以请求百分比的方式配置和手机跟踪信息：它的默认值为 0.1，代表手机 10% 的请求跟踪信息
  - spring.sleuth.sampler.probability=0.5
- RateLimitingSampler 抽样策略
  - 限速采集，也就是说它可以用来限制每秒追踪请求的最大数量，优先级更高
  - spring.sleuth.sampler.rate=10 ## 一秒最大只有10个跟踪策略给采集

8.5.1.2 bootstrap.yml 配置 Sleuth

sca-commerce-alibaba-nacos-client

spring:sleuth:sampler:# RateLimitingSampler 抽样策略，设置了限速采样，spring.sleuth.sampler.probability 属性值无效rate: 100 # 每秒间隔接受的 trace 量# Probability 抽样策略probability: 1.0 # 采样比例，1.0 表示 100%, 默认：0.1

8.5.1.3 代码配置 Sleuth

package com.edcode.commerce.sampler;import brave.sampler.RateLimitingSampler;
import brave.sampler.Sampler;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;/*** @author eddie.lee* @blog blog.eddilee.cn* @description 使用配置的方式设定抽样率 （二选一）*/
@Configuration
public class SamplerConfig {/*** 限速采集（推荐）*/@Beanpublic Sampler sampler() {return RateLimitingSampler.create(100);}//    /**
//     * 概率采集, 默认的采样策略, 默认值是 0.1
//     */
//    @Bean
//    public Sampler defaultSampler() {//        return ProbabilityBasedSampler.create(0.5f);
//    }
}

代码与Yaml文件配置是二选一，方便简洁肯定是 Yaml配置

限速采集与概率采集无论是代码还是 Yaml文件都是二选一

8.6.1 SpringCloud Sleuth+Zipkin 分布式日志追踪总结

8.6.1.1 SpringCloud Sleuth+Zipkin 逻辑架构图

跟踪、收集所涉及的三个组件（模块）Sleuth、Zipkin、Brave
三个组件之间的关系
- Brave 是一个 tracer 库，提供的是 tracer 接口
- Sleuth 采用了 Brave 作为 tracer 库
- Sleuth 可以不使用 Zipkin

8.6.1.2 Brave 解读

Brave 的两个最基本、也是最核心的概念
- trace：以看作是一个逻辑执行过程中的整个链条（可以看作一棵树）
- span：是 trace 跟踪的基本单位
Brave 中常用的数据结构以及说明
- Tracing：工具类，用于生成 Tracer 类实例
- Tracer：也是工具类，用于生成 Span
- Span：实际记录每个功能块执行信息的类
- TraceContext：记录 trace 的执行过程中的元数据信息类
- Propagation：用于在分布式环境或者跨进程条件下的 trace 跟踪时实现 TraceContext 传递的工具类

8.6.1.2 SpringCloud Sleuth 如何实现跨服务Trace 追踪

SpringCloud Sleuth 实现跨服务 Trace 追踪
- SpringCloud Sleuth 和 Brave 提供了很多不同的分布式框架的支持，例如 gRPC、Kafka、HTTP等