Question

我目前正在Google Cloud GCP的Kubernetes上运行Airflow。我的项目基于docker-airflow。我能够启动UI，但是当我尝试为Google Cloud创建连接并提交连接时，出现以下错误。

ValueError: Fernet key must be 32 url-safe base64-encoded bytes.

[2018-09-21 19:45:13,345] AirflowException: Could not create Fernet object: Fernet key must be 32 url-safe base64-encoded bytes.

文档推荐的第一个问题是确保您已安装密码，我确实这样做。我安装了两种类型，一种带有气流，一种来自PyPi。

pip3 install apache-airflow[kubernetes,crypto] and also tried
pip install cryptography

我尝试运行用于生成和存储环境变量的命令，如文档here中所述。（如下所示）

1）要么手动生成一个Fernet密钥，然后添加到airflow.cfg

2）设置环境变量并重新启动服务器。

python -c "from cryptography.fernet import Fernet; 
print(Fernet.generate_key().decode())"

示例键：81HqDtbqAywKSOumSha3BhWNOdQ26slT6K0YaZeZyPs=

使用kubernetes我无法使用关闭进程ID的典型方法来重启服务器，因为它与容器绑定了。我还尝试将生成的密钥（上方）放在kubernetes集群的configmaps.yaml文件中（部署时等于airflow.cfg）。

我尝试通过DAG，通过UI和使用airflow命令行客户端手动运行GCP连接。这三种方法均返回相同的错误。我在此处包括UI提交的图片以及完整的堆栈跟踪。

问题

为什么会这样？是否未生成Fernet密钥？可能不会保存在基础卷上吗？*

感谢您的帮助。

-RR

Traceback (most recent call last):

File "/usr/local/lib/python3.6/site-packages/airflow/models.py", line 159, in get_fernet
_fernet = Fernet(configuration.conf.get('core', 'FERNET_KEY').encode('utf-8'))
File "/usr/local/lib/python3.6/site-packages/cryptography/fernet.py", line 37, in __init__
"Fernet key must be 32 url-safe base64-encoded bytes."
ValueError: Fernet key must be 32 url-safe base64-encoded bytes.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1982, in wsgi_app
  response = self.full_dispatch_request()
File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1614, in full_dispatch_request
  rv = self.handle_user_exception(e)
    File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1517, in handle_user_exception
  reraise(exc_type, exc_value, tb)
File "/usr/local/lib/python3.6/site-packages/flask/_compat.py", line 33, in reraise
  raise value
File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1612, in full_dispatch_request
  rv = self.dispatch_request()
File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1598, in dispatch_request
  return self.view_functions[rule.endpoint](**req.view_args)
File "/usr/local/lib/python3.6/site-packages/flask_appbuilder/security/decorators.py", line 26, in wraps
  return f(self, *args, **kwargs)
File "/usr/local/lib/python3.6/site-packages/flask_appbuilder/views.py", line 524, in edit
  widgets = self._edit(pk)
File "/usr/local/lib/python3.6/site-packages/flask_appbuilder/baseviews.py", line 965, in _edit
  form.populate_obj(item)
File "/usr/local/lib/python3.6/site-packages/wtforms/form.py", line 96, in populate_obj
  field.populate_obj(obj, name)
File "/usr/local/lib/python3.6/site-packages/wtforms/fields/core.py", line 330, in populate_obj
  setattr(obj, name, self.data)
File "<string>", line 1, in __set__
File "/usr/local/lib/python3.6/site-packages/airflow/models.py", line 731, in set_extra
  fernet = get_fernet()
File "/usr/local/lib/python3.6/site-packages/airflow/models.py", line 163, in get_fernet
raise AirflowException("Could not create Fernet object: {}".format(ve))
airflow.exceptions.AirflowException: Could not create Fernet object: 
Fernet key must be 32 url-safe base64-encoded bytes.

这是基础持久卷的YAML。

kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: airflow-dags
  namespace: data
spec:
  accessModes:
    - ReadOnlyMany
  storageClassName: standard    
  resources:
    requests:
      storage: 8Gi
---
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: airflow-logs
  namespace: data
spec:
  accessModes:
    - ReadOnlyMany
  storageClassName: standard    
  resources:
    requests:
      storage: 8Gi

这是气流配置YAML。

apiVersion: apps/v1
kind: Deployment
metadata:
  name: airflow
  namespace: data
  labels:
    name: airflow
spec:
  replicas: 1
  selector:
    matchLabels:
      name: airflow
  template:
    metadata:
      labels:
        name: airflow
    spec:
      serviceAccountName: spark-service-account
      automountServiceAccountToken: true
      initContainers:
      - name: "init"
        image: <image_name>
        imagePullPolicy: Always
        volumeMounts:
        - name: airflow-configmap
          mountPath: /root/airflow/airflow.cfg
          subPath: airflow.cfg
        - name: airflow-dags
          mountPath: /root/airflow/dags
        # - name: test-volume
        #   mountPath: /root/test_volume
        env:
        - name: SQL_ALCHEMY_CONN
          valueFrom:
            secretKeyRef:
              name: airflow-secrets
              key: sql_alchemy_conn
        command:
          - "bash"
        args:
          - "-cx"
          - "airflow initdb || true && airflow create_user -u airflow -l airflow -f jon -e airflow@apache.org -r Admin -p airflow || true"
      containers:
      - name: webserver
        image: <image_name>
        imagePullPolicy: IfNotPresent
        ports:
        - name: webserver
          containerPort: 8080
        env:
        - name: <namespace_name>
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
        - name: SQL_ALCHEMY_CONN
          valueFrom:
            secretKeyRef:
              name: airflow-secrets
              key: sql_alchemy_conn
        command: ["/bin/sh", "-c"]
        args: ["airflow webserver"]
        volumeMounts:
        - name: airflow-configmap
          mountPath: /root/airflow/airflow.cfg
          subPath: airflow.cfg
        - name: airflow-dags
          mountPath: /root/airflow/dags
        - name: airflow-logs
          mountPath: /root/airflow/logs
        # readinessProbe:
        #   initialDelaySeconds: 5
        #   timeoutSeconds: 5
        #   periodSeconds: 5
        #   httpGet:
        #     path: /login
        #     port: 8080
        # livenessProbe:
        #   initialDelaySeconds: 5
        #   timeoutSeconds: 5
        #   failureThreshold: 5
        #   httpGet:
        #     path: /login
        #     port: 8080
      - name: scheduler
        image: image-name
        imagePullPolicy: IfNotPresent
        env:
        - name: namespace_name
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
        - name: SQL_ALCHEMY_CONN
          valueFrom:
            secretKeyRef:
              name: airflow-secrets
              key: sql_alchemy_conn
        command: ["/bin/sh", "-c"]
        args: ["cp ./dags/* /root/airflow/dags/; airflow scheduler"]
        volumeMounts:
        - name: airflow-configmap
          mountPath: /root/airflow/airflow.cfg
          subPath: airflow.cfg
        - name: airflow-dags
          mountPath: /root/airflow/dags
        - name: airflow-logs
          mountPath: /root/airflow/logs
      volumes:
      - name: airflow-configmap
        configMap:
          name: airflow-configmap
      - name: airflow-dags
        persistentVolumeClaim:
          claimName: airflow-dags
      - name: airflow-logs
        persistentVolumeClaim:
          claimName: airflow-logs
---
apiVersion: v1
kind: Service
metadata:
  name: airflow
  namespace: data
spec:
  type: NodePort
  ports:
    - port: 8080
      nodePort: 30809
  selector:
    name: airflow

Answer 1

重新启动工作服务器和Web服务器。

您的工作人员和Web服务器正在使用旧的Fernet密钥。您在配置中更改了密钥，因此所有新存储或修改的Connections都将使用新密钥，但是Web服务器/工作人员仍在使用旧密钥进行操作。它们将永远不会匹配，并继续给出此错误，直到重新启动为止。

Kubernetes的气流GCP连接问题-Fernet密钥必须是32个URL安全的base64编码字节

问题

1 个答案: