基于CentOS搭建基于 ZIPKIN 的数据追踪系统

系统要求:CentOS 7.2 64 位操作系统

配置 Java 环境

安装 JDK

Zipkin 使用 Java8

yum install java-1.8.-openjdk* -y

安装完成后,查看是否安装成功:

java -version

安装 Zipkin

新建目录

mkdir -p /data/release/zipkin && cd "$_"

下载 Zipkin

wget -O zipkin.jar 'https://search.maven.org/remote_content?g=io.zipkin.java&a=zipkin-server&v=LATEST&c=exec'

启动 Zipkin

java -jar zipkin.jar

Zipkin 默认监听 9411 端口, 使用浏览器访问 http://118.89.65.22:9411 即可看到 Zipkin 自带的图形化界面(外网:请确认此CVM有外网IP且安全组已开通9411端口)。

配置 MySQL 数据持久化方案

Zipkin 支持的持久化方案很多,如: Cassandra, MySQL, Elasticsearch。本实验使用 MySQL 5.7 作为数据持久化方案。

安装 MySQL 5.7

使用 Ctrl + C 退出上个步骤的 Java 进程并下载 rmp 包

wget http://dev.mysql.com/get/mysql57-community-release-el7-9.noarch.rpm

安装 rpm 包

rpm -Uvh mysql57-community-release-el7-.noarch.rpm

安装 MySQL

yum install mysql-community-server -y

启动 MySQL 服务

systemctl start mysqld.service

设置 MySQL 密码

获取 root 临时密码(下面命令中的密码是教程为您自动生成的,为了方便实验的进行,不建议使用其它密码。如果设置其它密码,请把密码记住,在后续的步骤会使用到)

grep 'temporary password' /var/log/mysqld.log | awk '{print $NF}'

使用上一步的获得的临时密码登入 MySQL

mysql -uroot -p

设置 MySQL 账户 root 密码

ALTER USER 'root'@'localhost' IDENTIFIED BY 'Xx$Zipkin2017';

退出 MySQL, 回到 Bash shell

exit;

初始化 Zipkin 数据库

编写初始化脚本

请在 /data/release/zipkin 目录下创建 zipkin_init.sql,参考下面的内容。

 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
) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci; ALTER TABLE zipkin_dependencies ADD UNIQUE KEY(`day`, `parent`, `child`);

登录 Mysql

mysql -u root --password='Xx$Zipkin2017'

创建 Zipkin 数据库

create database zipkin;

切换数据库

use zipkin;

初始化表及索引

source /data/release/zipkin/zipkin_init.sql

执行以下命令会看到zipkin_annotationszipkin_dependencieszipkin_spans 三张数据表,说明初始化成功了

show tables;

退出 MySQL, 回到 Bash shell

exit

启动 Zipkin

注: 此处默认使用实验生成的密码

cd /data/release/zipkin
STORAGE_TYPE=mysql MYSQL_HOST=localhost MYSQL_TCP_PORT=3306 MYSQL_DB=zipkin MYSQL_USER=root MYSQL_PASS='Xx$Zipkin2017' \
nohup java -jar zipkin.jar &

创建具有数据上报能力的Demo

搭建 NodeJS 环境

curl --silent --location https://rpm.nodesource.com/setup_8.x | sudo bash -
yum install nodejs -y

创建Demo目录

创建/data/release/service_a目录

mkdir -p /data/release/service_a && cd "$_"

使用 NPM 安装相关依赖

请在 /data/release/service_a 目录下创建并编辑 package.json,参考下面的内容。

 {
"name": "service_a",
"version": "1.0.0",
"description": "",
"main": "index.js",
"scripts": {},
"author": "",
"license": "ISC",
"dependencies": {
"express": "^4.15.3",
"zipkin": "^0.7.2",
"zipkin-instrumentation-express": "^0.7.2",
"zipkin-transport-http": "^0.7.2"
}
}

安装相关依赖

npm install

创建并编辑 app.js

请在 /data/release/service_a 目录下创建 app.js,参考下面的内容。

示例代码:/data/release/service_a/app.js

 const express = require('express');
const {Tracer, ExplicitContext, BatchRecorder} = require('zipkin');
const {HttpLogger} = require('zipkin-transport-http');
const zipkinMiddleware = require('zipkin-instrumentation-express').expressMiddleware; const ctxImpl = new ExplicitContext();
const recorder = new BatchRecorder({
logger: new HttpLogger( {
endpoint: 'http://127.0.0.1:9411/api/v1/spans'
})
}); const tracer = new Tracer({ctxImpl, recorder}); const app = express(); app.use(zipkinMiddleware({
tracer,
serviceName: 'service-a'
})); app.use('/', (req, res, next) => {
res.send('hello world');
}); app.listen(3000, () => {
console.log('service-a listening on port 3000!')
});

启动服务

node app.js

该服务监听 3000 端口, 使用浏览器访问 http://118.89.65.22:3000 后,看到“hello world” 的文本字样说明服务已经正常工作。

部署完成

查看采集到的追踪数据

使用浏览器访问 http://118.89.65.22:9411 即可看到刚才访问产生的追踪数据。
至此,本入门教程已结束,而 Zipkin 的学习只是一个开始,如有兴趣,可尝试搭建一个基于 Kafka + Zookeeper + Elasticsearch 的分布式服务。

大功告成

恭喜您已经完成了搭建基于 ZIPKIN 的数据追踪系统的学习。

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