kubernetes吊舱和气流工作人员日志的DNS

时间:2020-07-14 23:00:57

标签: kubernetes airflow airflow-worker kubernetes-dns

➜ k get pods -n edna    
NAME                              READY   STATUS    RESTARTS   AGE
airflow-79d5f59644-dd4k7          1/1     Running   0          16h
airflow-worker-67bcf7844b-rq7r8   1/1     Running   0          22h
backend-65bcb6546-wvvqj           1/1     Running   0          2d16h

因此在 airflow-79d5f59644-dd4k7 窗格中运行的气流试图从气流工作人员(芹菜/ python,它运行一个基于烧瓶的简单web服务器处理日志)中提取日志,并且无法因为域名 airflow-worker-67bcf7844b-rq7r8 airflow-79d5f59644-dd4k7 内部没有解析

*** Log file does not exist: /usr/local/airflow/logs/hello_world/hello_task/2020-07-14T22:05:12.123747+00:00/1.log
*** Fetching from: http://airflow-worker-67bcf7844b-rq7r8:8793/log/hello_world/hello_task/2020-07-14T22:05:12.123747+00:00/1.log
*** Failed to fetch log file from worker. HTTPConnectionPool(host='airflow-worker-67bcf7844b-rq7r8', port=8793): Max retries exceeded with url: /log/hello_world/hello_task/2020-07-14T22:05:12.123747+00:00/1.log (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fd37d6a9790>: Failed to establish a new connection: [Errno -2] Name or service not known'))

我该如何进行这项工作?

我了解Airflow可以将远程日志记录到s3,但是是否可以通过POD随机hasotnames路由请求?

我已经创建了一个NodeType服务,但是airflow不知道该服务的DNS名称,而是试图按airflow worker的主机名访问日志(由Celery报告)。

➜ k get pods -n edna
NAME                              READY   STATUS    RESTARTS   AGE
airflow-79d5f59644-dd4k7          1/1     Running   0          16h
airflow-worker-67bcf7844b-rq7r8   1/1     Running   0          22h
backend-65bcb6546-wvvqj           1/1     Running   0          2d17h

kubectl get pods -n edna -l app=edna-airflow-worker \                                                                        
    -o go-template='{{range .items}}{{.status.podIP}}{{"\n"}}{{end}}'
'Tipz:' kgp -n edna -l app=edna-airflow-worker \ -o go-template='{{range .items}}{{.status.podIP}}{{" "}}{{end}}'
10.0.101.120

进入 airflow-79d5f59644-dd4k7 吊舱

k exec -ti -n edna airflow-79d5f59644-dd4k7 bash  

?  [DEV] airflow-79d5f59644-dd4k7 app # curl -L http://airflow-worker-67bcf7844b-rq7r8:8793/log/hello_world/hello_task/2020-07-14T21:59:01.400678+00:00/1.log

curl: (6) Could not resolve host: airflow-worker-67bcf7844b-rq7r8; Unknown error
?  [DEV] airflow-79d5f59644-dd4k7 app # curl -L http://10.0.101.120:8793/log/hello_world/hello_task/2020-07-14T21:59:01.400678+00:00/1.log
[2020-07-14 21:59:07,257] {{taskinstance.py:669}} INFO - Dependencies all met for <TaskInstance: hello_world.hello_task 2020-07-14T21:59:01.400678+00:00 [queued]>
[2020-07-14 21:59:07,341] {{taskinstance.py:669}} INFO - Dependencies all met for <TaskInstance: hello_world.hello_task 2020-07-14T21:59:01.400678+00:00 [queued]>
[2020-07-14 21:59:07,342] {{taskinstance.py:879}} INFO - 
--------------------------------------------------------------------------------
[2020-07-14 21:59:07,342] {{taskinstance.py:880}} INFO - Starting attempt 1 of 1
[2020-07-14 21:59:07,342] {{taskinstance.py:881}} INFO - 
--------------------------------------------------------------------------------
[2020-07-14 21:59:07,348] {{taskinstance.py:900}} INFO - Executing <Task(PythonOperator): hello_task> on 2020-07-14T21:59:01.400678+00:00
[2020-07-14 21:59:07,351] {{standard_task_runner.py:53}} INFO - Started process 5795 to run task
[2020-07-14 21:59:07,912] {{logging_mixin.py:112}} INFO - Running %s on host %s <TaskInstance: hello_world.hello_task 2020-07-14T21:59:01.400678+00:00 [running]> airflow-worker-67bcf7844b-rq7r8
[2020-07-14 21:59:07,989] {{logging_mixin.py:112}} INFO - Hello world! This is really cool!
[2020-07-14 21:59:07,989] {{python_operator.py:114}} INFO - Done. Returned value was: Hello world! This is really cool!
[2020-07-14 21:59:08,161] {{taskinstance.py:1065}} INFO - Marking task as SUCCESS.dag_id=hello_world, task_id=hello_task, execution_date=20200714T215901, start_date=20200714T215907, end_date=20200714T215908
[2020-07-14 21:59:17,070] {{logging_mixin.py:112}} INFO - [2020-07-14 21:59:17,070] {{local_task_job.py:103}} INFO - Task exited with return code 0
?  [DEV] airflow-79d5f59644-dd4k7 app # 


2 个答案:

答案 0 :(得分:1)

如果 pod A 想要与 pod B 进行通信,则必须为Pod B提供服务 svc-b

>

然后pod A可以与svc-b通信。

这是规则。

对于您的情况,豆荚B是airflow-worker-67bcf7844b-rq7r8:

kubectl -n edna expose airflow-worker-67bcf7844b-rq7r8 \
  --name airflow-worker \
  --port 8793 \
  --target-port 8793

现在可以使用curl -L http://airflow-worker:8793/代替curl -L http://airflow-worker-67bcf7844b-rq7r8:8793/

答案 1 :(得分:1)

解决方案

为工作窗格的deploy.yaml提供以下ENV AIRFLOW__CORE__HOSTNAME_CALLABLE

env:
  - name: AIRFLOW__CORE__HOSTNAME_CALLABLE
    value: 'airflow.utils.net:get_host_ip_address'

或者只是更改airflow.cfg

然后气流尝试通过IP的POD进行访问,如果您的POD暴露了端口 8793

,则说明一切正常