zipkin的工作原理

基本思想：在服务调用的请求和响应中加入trace ID，标明上下游请求的关系。利用这些信息，可视化地分析服务调用链路和服务间的依赖关系，保存下来进行展示。

时序图：

首先是User code，表示的是我们的应用程序代码。

当我们的应用程序接收到请求/foo时，并不会立即执行，而是交由跟踪仪器来处理。

然后是Trace Instrumentation，跟踪仪器，它负责记录标签、添加跟踪头、记录时间戳，此时会产生新的请求，该请求会交给http客户端。

然后是http client，这里用requests，http client会发起新的请求，请求结束后，结果会返回给追踪仪器，然后由追踪仪器分析请求耗费的时间。

追踪仪器在返回结果给user code的同时，会异步将刚才的请求信息以span的形式报告给zipkin server。

以上就是zipkin在应用程序中扮演的角色。

以代码形式表现zipkin的作用：

1、首先运行zipkin，以docker形式

docker run -d -p 9411:9411 openzipkin/zipkin

访问zipkin

http://192.168.0.105:9411

2、然后编写简单flask应用

这里的python版本为3.9

先安装要使用的包

pip install flask py_zipkin pymysql requests

程序如下：

首先编写文件app.py，内容为：

import time
import requests
from flask import Flask
from py_zipkin.zipkin import zipkin_span, create_http_headers_for_new_span

app = Flask(__name__)

app.config.update({
    "ZIPKIN_HOST": "192.168.0.105",
    "ZIPKIN_PORT": 9411,
    "APP_PORT": 5000
})


def do_stuff():
    time.sleep(2)
    headers = create_http_headers_for_new_span()
    requests.get("http://localhost:6000/service1/", headers=headers)
    return "OK"


def http_transport(encoded_span):
    body = encoded_span
    zipkin_url = "http://192.168.0.105:9411/api/v1/spans"
    headers = {"Content-Type": "application/x-thrift"}

    r = requests.post(
        zipkin_url, data=body, headers=headers
    )
    print(type(encoded_span), encoded_span, body, r, r.content)


@app.route('/')
def index():
    with zipkin_span(service_name='webapp', span_name='index', transport_handler=http_transport, port=5000, sample_rate=100):
        with zipkin_span(service_name='webapp', span_name='do_stuff'):
            do_stuff()

        time.sleep(1)

    return 'OK', 200


if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000, debug=True)

然后是文件server1.py，内容为：

from flask import request
import requests
from flask import Flask
from py_zipkin.zipkin import zipkin_span, ZipkinAttrs
import time
import pymysql

app = Flask(__name__)
app.config.update({
    "ZIPKIN_HOST": "192.168.0.105",
    "ZIPKIN_PORT": "9411",
    "APP_PORT": 5000,
})


def do_stuff():
    time.sleep(2)
    with zipkin_span(service_name='service1', span_name='service1_db_search'):
        db_search()
    return 'OK'


def db_search():
    # 打开数据库连接
    db = pymysql.connect(host="127.0.0.1", user="root", password="123456", database="mysql", charset='utf8')
    # 使用cursor()方法获取操作游标
    cursor = db.cursor()
    # 使用execute方法执行SQL语句
    cursor.execute("SELECT VERSION()")
    # 使用 fetchone() 方法获取一条数据
    data = cursor.fetchone()
    print("Database version : %s " % data)
    # 关闭数据库连接
    db.close()


def http_transport(encoded_span):
    body = encoded_span
    zipkin_url = "http://192.168.0.105:9411/api/v1/spans"
    headers = {"Content-Type": "application/x-thrift"}
    requests.post(zipkin_url, data=body, headers=headers)


@app.route('/service1/')
def index():
    with zipkin_span(
        service_name='service1',
        zipkin_attrs=ZipkinAttrs(
            trace_id=request.headers['X-B3-TraceID'],
            span_id=request.headers['X-B3-SpanID'],
            parent_span_id=request.headers['X-B3-ParentSpanID'],
            flags=request.headers['X-B3-Flags'],
            is_sampled=request.headers['X-B3-Sampled'],
        ),
        span_name='index_service1',
        transport_handler=http_transport,
        port=6000,
        sample_rate=100,
    ):
        with zipkin_span(service_name='service1', span_name='service1_do_stuff'):
            do_stuff()
    return 'OK', 200


if __name__ == '__main__':
    app.run(host="0.0.0.0", port=6000, debug=True)