Spring Boot应用监控实战

ゝ一世哀愁。 2021-09-18 08:06 360阅读 0赞

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## 概述 ##

在前面：[微服务调用链追踪中心搭建][Link 1] 一文中我们利用Zipkin搭建了一个微服务调用链的追踪中心，并且模拟了微服务调用的实验场景。利用Zipkin的库Brave，我们可以收集一个客户端请求从发出到被响应 **经历了哪些组件**、**哪些微服务**、**请求总时长**、**每个组件所花时长** 等信息。

本文将讲述如何利用Zipkin对Mysql数据库的调用进行追踪，这里同样借助OpenZipkin库Brave来完成。

> **注：** 本文首发于 My 公众号 **CodeSheep** ，可 **长按** 或 **扫描** 下面的 **小心心** 来订阅 ↓ ↓ ↓

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## 扩展ZipkinTool组件 ##

ZipkinTool是在[《微服务调用链追踪中心搭建》][Link 1]一文中编写的与Zipkin通信的工具组件，利用其追踪微服务调用链的，现在我们想追踪Mysql数据库调用链的话，可以扩展一下其功能。

*  pom.xml添加依赖：

<dependency>
            <groupId>io.zipkin.brave</groupId>
            <artifactId>brave-mysql</artifactId>
            <version>4.0.6</version>
    </dependency>
    复制代码

*  在ZipkinConfiguration类中添加MySQLStatementInterceptorManagementBean

@Bean
        public MySQLStatementInterceptorManagementBean mySQLStatementInterceptorManagementBean() {
            return new MySQLStatementInterceptorManagementBean(brave().clientTracer());
        }
    复制代码

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## 添加Mysql数据库访问的微服务 ##

依然继承前文：[《微服务调用链追踪中心搭建》][Link 1]，我们改造一下文中的ServiceC这个微服务，在其中添加与Mysql数据库的交互。

*  pom.xml中添加JDBC和Mysql依赖

<dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-starter-jdbc</artifactId>
            </dependency>
            <dependency>
                <groupId>mysql</groupId>
                <artifactId>mysql-connector-java</artifactId>
                <scope>runtime</scope>
            </dependency>
    复制代码

*  application.properties中添加Mysql连接的配置

spring.datasource.driver-class-name=com.mysql.jdbc.Driver
    spring.datasource.url=jdbc:mysql://你的Mysql服务所在IP:3307/test?useSSL=false\
      &statementInterceptors=com.github.kristofa.brave.mysql.MySQLStatementInterceptor\
      &zipkinServiceName=mysqlService
    spring.datasource.username=root
    spring.datasource.password=XXXXXX
    复制代码

*  Controller中添加JdbcTemplate访问数据库的代码

@GetMapping("/mysqltest”) public String mysqlTest() { String name = jdbcTemplate.queryForObject( "SELECT name FROM user WHERE id = 1", String.class ); return "Welcome " + name; } 复制代码

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## 启动Mysql数据库服务 ##

**1. 启动Mysql容器**

docker run -d -p 3307:3306 \
    -v ~/mysql/data:/var/lib/mysql \
    -v ~/mysql/conf:/etc/mysql/conf.d \
    -e MYSQL_ROOT_PASSWORD=XXXXXX \
    --name mysql mysql
    复制代码

**2. 再启动一个Mysql容器，接入其中做一些设置**

*  首先进入mysql命令行

docker run -it --rm \
    --link mysql:mysql mysql \
    mysql -hmysql -u root -p
    复制代码

*  接下来创建数据库zipkin： 用于存放Zipkin所收集的数据

CREATE DATABASE `zipkin`
    
    CREATE TABLE IF NOT EXISTS zipkin_spans (
      `trace_id_high` BIGINT NOT NULL DEFAULT 0 COMMENT 'If non zero, this means the trace uses 128 bit traceIds instead of 64 bit’, `trace_id` BIGINT NOT NULL, `id` BIGINT NOT NULL, `name` VARCHAR(255) NOT NULL, `parent_id` BIGINT, `debug` BIT(1), `start_ts` BIGINT COMMENT 'Span.timestamp(): epoch micros used for endTs query and to implement TTL’,
      `duration` BIGINT COMMENT 'Span.duration(): micros used for minDuration and maxDuration query’ ) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci; ALTER TABLE zipkin_spans ADD UNIQUE KEY(`trace_id_high`, `trace_id`, `id`) COMMENT 'ignore insert on duplicate’;
    ALTER TABLE zipkin_spans ADD INDEX(`trace_id_high`, `trace_id`, `id`) COMMENT 'for joining with zipkin_annotations’; ALTER TABLE zipkin_spans ADD INDEX(`trace_id_high`, `trace_id`) COMMENT 'for getTracesByIds’;
    ALTER TABLE zipkin_spans ADD INDEX(`name`) COMMENT 'for getTraces and getSpanNames’; ALTER TABLE zipkin_spans ADD INDEX(`start_ts`) COMMENT 'for getTraces ordering and range’;
    
    CREATE TABLE IF NOT EXISTS zipkin_annotations (
      `trace_id_high` BIGINT NOT NULL DEFAULT 0 COMMENT 'If non zero, this means the trace uses 128 bit traceIds instead of 64 bit’, `trace_id` BIGINT NOT NULL COMMENT 'coincides with zipkin_spans.trace_id’,
      `span_id` BIGINT NOT NULL COMMENT 'coincides with zipkin_spans.id’, `a_key` VARCHAR(255) NOT NULL COMMENT 'BinaryAnnotation.key or Annotation.value if type == -1’,
      `a_value` BLOB COMMENT 'BinaryAnnotation.value(), which must be smaller than 64KB’, `a_type` INT NOT NULL COMMENT 'BinaryAnnotation.type() or -1 if Annotation’,
      `a_timestamp` BIGINT COMMENT 'Used to implement TTL; Annotation.timestamp or zipkin_spans.timestamp’, `endpoint_ipv4` INT COMMENT 'Null when Binary/Annotation.endpoint is null’,
      `endpoint_ipv6` BINARY(16) COMMENT 'Null when Binary/Annotation.endpoint is null, or no IPv6 address’, `endpoint_port` SMALLINT COMMENT 'Null when Binary/Annotation.endpoint is null’,
      `endpoint_service_name` VARCHAR(255) COMMENT 'Null when Binary/Annotation.endpoint is null’ ) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci; ALTER TABLE zipkin_annotations ADD UNIQUE KEY(`trace_id_high`, `trace_id`, `span_id`, `a_key`, `a_timestamp`) COMMENT 'Ignore insert on duplicate’;
    ALTER TABLE zipkin_annotations ADD INDEX(`trace_id_high`, `trace_id`, `span_id`) COMMENT 'for joining with zipkin_spans’; ALTER TABLE zipkin_annotations ADD INDEX(`trace_id_high`, `trace_id`) COMMENT 'for getTraces/ByIds’;
    ALTER TABLE zipkin_annotations ADD INDEX(`endpoint_service_name`) COMMENT 'for getTraces and getServiceNames’; ALTER TABLE zipkin_annotations ADD INDEX(`a_type`) COMMENT 'for getTraces’;
    ALTER TABLE zipkin_annotations ADD INDEX(`a_key`) COMMENT 'for getTraces’; ALTER TABLE zipkin_annotations ADD INDEX(`trace_id`, `span_id`, `a_key`) COMMENT 'for dependencies job’;
    
    CREATE TABLE IF NOT EXISTS zipkin_dependencies (
      `day` DATE NOT NULL,
      `parent` VARCHAR(255) NOT NULL,
      `child` VARCHAR(255) NOT NULL,
      `call_count` BIGINT,
      `error_count` BIGINT
    ) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;
    
    ALTER TABLE zipkin_dependencies ADD UNIQUE KEY(`day`, `parent`, `child`);
    复制代码

这里创建了三个数据表。

> 该Sql文件可以从以下链接获得：https://github.com/openzipkin/zipkin/blob/master/zipkin-storage/mysql/src/main/resources/mysql.sql

Sql脚本执行完成后，可以看到zipkin相关的三个表已经建成：

*  创建数据库test：用作测试数据库

CREATE DATABASE `test`
    CREATE TABLE `user` (
      `id` int(11) unsigned NOT NULL auto_increment,
      `name` varchar(100) DEFAULT NULL ,
      PRIMARY KEY (`id`)
    ) ENGINE=InnoDB DEFAULT CHARSET = utf8;
    
    insert into user values (1,”hansonwang99”)
    复制代码

这里插入了一条数据用于实验。

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## 启动zipkin服务 ##

docker run -d -p 9411:9411 \
    --link mysql:mysql \
    -e STORAGE_TYPE=mysql \
    -e MYSQL_HOST=mysql \
    -e MYSQL_TCP_PORT=3306 \
    -e MYSQL_DB=zipkin \
    -e MYSQL_USER=root \
    -e MYSQL_PASS=XXXXXX \
     --name zipkin openzipkin/zipkin
    复制代码

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## 启动Mysql数据库访问的微服务（即ServiceC） ##

在浏览器中输入：localhost:8883/mysqltest，如果看到以下输出，就可以证明数据库调用操作已经成功了！

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## Zipkin追踪数据库调用实际实验 ##

*  \*\*浏览器输入：\*\*http://localhost:9411/zipkin/

打开Zipkin Web UI，点击服务名下拉列表能看见已经成功识别了Mysql数据库调用服务

*  **选中mysqlservice后，点击Find Traces**

可以看到 **首次查询** Mysql的调用链追踪信息，有很多

随便点开某一个查看：

*  \*\*接下来浏览器中再次输入：\*\*localhost:8883/mysqltest

目的是再次触发Mysql的调用，然后再次Find Traces，可以看到追踪数据类似下图：包含两次Mysql的query动作：

点开第一个query查看，其实际上是在 **尝试连接Mysql数据库**

点开第二个query查看，发现这里才是 **实际查询业务**

从图形化界面上可以清楚地知道每个阶段的详细步骤与耗时，因此可以用来分析哪个SQL语句执行相对较慢。

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## 后记 ##

本文实验所用源码已经开源，需要的话请 [自取][Link 2]。

*  [作者更多的原创文章在此，欢迎观赏][Link 3]
 *  [My Personal Blog][]

作者更多的SpringBt实践文章在此：

*  [Spring Boot应用监控实战][Spring Boot]
 *  [SpringBoot应用部署于外置Tomcat容器][SpringBoot_Tomcat]
 *  [ElasticSearch搜索引擎在SpringBt中的实践][ElasticSearch_SpringBt]
 *  [初探Kotlin+SpringBoot联合编程][Kotlin_SpringBoot]
 *  [Spring Boot日志框架实践][Spring Boot 1]
 *  [SpringBoot优雅编码之：Lombok加持][SpringBoot_Lombok]

--------------------

如果有兴趣，也可以抽点时间看看作者一些关于容器化、微服务化方面的文章：

*  [利用K8S技术栈打造个人私有云 连载文章][K8S_]
 *  [从一份配置清单详解Nginx服务器配置][Nginx]
 *  [Docker容器可视化监控中心搭建][Docker]
 *  [利用ELK搭建Docker容器化应用日志中心][ELK_Docker]
 *  [RPC框架实践之：Apache Thrift][RPC_Apache Thrift]
 *  [RPC框架实践之：Google gRPC][RPC_Google gRPC]
 *  [微服务调用链追踪中心搭建][Link 4]
 *  [Docker容器跨主机通信][Docker 1]
 *  [Docker Swarm集群初探][Docker Swarm]
 *  [高效编写Dockerfile的几条准则][Dockerfile]

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[Link 1]: https://link.juejin.im?target=https%3A%2F%2Fwww.jianshu.com%2Fp%2Fda80ea881424
[Link 2]: https://link.juejin.im?target=https%3A%2F%2Fgithub.com%2Fhansonwang99%2FZipkin_Traces
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