istio环境集成zipkin

   在非istio的环境中，如果我们选择了zipkin作为链路追踪的解决方案，那么我们需要业务代码里对每次调用生成span/trace id,虽然大部分流行语言zipkin都提供了对应的sdk帮我们做了这些集成工作，但是我们还是要在发出请求时手动调用sdk提供的方法生成并携带相应header到业务下游，相当于要对每一种语言都要去手动做一次 request的封装，如果公司使用的语言多了那么会是一种很繁琐的工作。那么有没有一种工具能帮我们自动生成每次调用所需的信息呢? 答案当然是有的，在istio环境中，这一切都变成了可能、当envoy收到调用请求时，会自动帮我们注入所需的headers，在业务代码中我们只需做少量改动，只需要调用下游服务时传递header 就可以了。参考地址：https://istio.io/latest/zh/docs/tasks/observability/distributed-tracing/overview/

 

下面是一个python flask 应用在istio中接入zipkin的例子：

1.拓扑：

有三个应用，分别是 zipkin-a ， zipkin-b， zipkin-c

调用关系是: zipkin-a  ----->  zipkin-b ----> zipkin-c

案例代码：

zipkin-a:

from flask import Flask,request
import requests

app = Flask(__name__)


@app.route('/')
def hello_worlda():
    tmp_headers = {}
    b3_headers = ["x-request-id","x-b3-traceid","x-b3-spanid","x-b3-parentspanid","x-b3-sampled","x-b3-flags","x-ot-span-context"]
    for header in b3_headers:
        if request.headers.get(header):
            tmp_headers.update({header:request.headers.get(header)})
    requests.get('http://zipkin-b:5001',headers=tmp_headers)
    return 'zipkin-a!'


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

zipkin-b:

from flask import Flask,request
import requests

app = Flask(__name__)


@app.route('/')
def hello_worlda():
    tmp_headers = {}
    b3_headers = ["x-request-id","x-b3-traceid","x-b3-spanid","x-b3-parentspanid","x-b3-sampled","x-b3-flags","x-ot-span-context"]
    for header in b3_headers:
        if request.headers.get(header):
            tmp_headers.update({header:request.headers.get(header)})
    requests.get('http://zipkin-c:5002', headers=tmp_headers)
    return 'zipkin-b'


if __name__ == '__main__':
    app.run(host="0.0.0.0",port=5001)

zipkin-c:

from flask import Flask,request

app = Flask(__name__)


@app.route('/')
def hello_world():
    print(' ------------- ^^^ -----------')
    print(request.headers)
    return 'Hello World!'


if __name__ == '__main__':
    app.run(host="0.0.0.0",port=5002)

 

对应k8s manifest:

zipkin-a:

kind: Deployment
metadata:
 name: zipkin-a
spec:
 selector:
  matchLabels:
    app: zipkin-a
    version: "v1"
 replicas: 1
 template:
  metadata:
   labels:
    app: zipkin-a
    version: "v1"
  spec:
   containers:
   - name: zipkin-a
     image: reg.xthklocal.cn/xthk-library/zipkin_a
     command: ["python","/tmp/a.py"]
     ports:
     - containerPort: 5000
       name: http
       protocol: TCP
---
apiVersion: v1
kind: Service
metadata:
  name: zipkin-a
spec:
  ports:
  - name: http-5000
    port: 5000
    protocol: TCP
    targetPort: 5000
  selector:
    app: zipkin-a
  type: ClusterIP

 

zipkin-b:

apiVersion: apps/v1
kind: Deployment
metadata:
 name: zipkin-b
spec:
 selector:
  matchLabels:
    app: zipkin-b
    version: "v1"
 replicas: 1
 template:
  metadata:
   labels:
    app: zipkin-b
    version: "v1"
  spec:
   containers:
   - name: zipkin-b
     image: reg.xthklocal.cn/xthk-library/zipkin_b
     command: ["python","/tmp/b.py"]
     ports:
     - containerPort: 5001
       name: http
       protocol: TCP
---
apiVersion: v1
kind: Service
metadata:
  name: zipkin-b
spec:
  ports:
  - name: http-5000
    port: 5001
    protocol: TCP
    targetPort: 5001
  selector:
    app: zipkin-b
  type: ClusterIP

zipkin-c:

apiVersion: apps/v1
kind: Deployment
metadata:
 name: zipkin-c
spec:
 selector:
  matchLabels:
    app: zipkin-c
    version: "v1"
 replicas: 1
 template:
  metadata:
   labels:
    app: zipkin-c
    version: "v1"
  spec:
   containers:
   - name: zipkin-c
     image: reg.xthklocal.cn/xthk-library/zipkin_c
     command: ["python","/tmp/c.py"]
     ports:
     - containerPort: 5002
       name: http
       protocol: TCP
---
apiVersion: v1
kind: Service
metadata:
  name: zipkin-c
spec:
  ports:
  - name: http-5000
    port: 5002
    protocol: TCP
    targetPort: 5002
  selector:
    app: zipkin-c
  type: ClusterIP

 

istio 增加以下zipkin 配置：

data:
  mesh: |-
    defaultConfig:
      tracing:
        zipkin:
          address: 192.168.3.100:31377   #改成zipkin server的实际地址

 

进入任意能与zipkin-a 容器通信的容器调用zipkin-a 服务触发链路上报 （如果采样率未设置未全部采样，需要多次调用才能看到效果）

 

 

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