Verwendung eines geheimen Schlüssels AWS Secrets Manager für eine Apache Airflow-Verbindung

Navigieren Sie in der Befehlszeile zu dem Verzeichnis, in dem Ihr DAG-Code gespeichert ist. Zum Beispiel:

cd dags

Kopieren Sie den Inhalt des folgenden Codebeispiels und speichern Sie ihn lokal untersecrets-manager.py.

"""
Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
 
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
the Software, and to permit persons to whom the Software is furnished to do so.
 
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
"""
from airflow import DAG, settings, secrets
from airflow.operators.python import PythonOperator
from airflow.utils.dates import days_ago
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook

from datetime import timedelta
import os

### The steps to create this secret key can be found at: https://docs.aws.amazon.com/mwaa/latest/userguide/connections-secrets-manager.html
sm_secretId_name = 'airflow/connections/myconn'

default_args = {
    'owner': 'airflow',
    'start_date': days_ago(1),
    'depends_on_past': False
}


### Gets the secret myconn from Secrets Manager
def read_from_aws_sm_fn(**kwargs):
    ### set up Secrets Manager
    hook = AwsBaseHook(client_type='secretsmanager')
    client = hook.get_client_type(region_name='us-east-1')
    response = client.get_secret_value(SecretId=sm_secretId_name)
    myConnSecretString = response["SecretString"]

    return myConnSecretString

### 'os.path.basename(__file__).replace(".py", "")' uses the file name secrets-manager.py for a DAG ID of secrets-manager
with DAG(
        dag_id=os.path.basename(__file__).replace(".py", ""),
        default_args=default_args,
        dagrun_timeout=timedelta(hours=2),
        start_date=days_ago(1),
        schedule_interval=None
) as dag:
    write_all_to_aws_sm = PythonOperator(
        task_id="read_from_aws_sm",
        python_callable=read_from_aws_sm_fn,
        provide_context=True
    )

Navigieren Sie in der Befehlszeile zu dem Verzeichnis, in dem Ihr DAG-Code gespeichert ist. Zum Beispiel:

cd dags

Kopieren Sie den Inhalt des folgenden Codebeispiels und speichern Sie ihn lokal untersecrets-manager.py.

from airflow import DAG, settings, secrets
from airflow.operators.python_operator import PythonOperator
from airflow.utils.dates import days_ago
from airflow.contrib.hooks.aws_hook import AwsHook

from datetime import timedelta
import os

### The steps to create this secret key can be found at: https://docs.aws.amazon.com/mwaa/latest/userguide/connections-secrets-manager.html
sm_secretId_name = 'airflow/connections/myconn'

default_args = {
    'owner': 'airflow',
    'start_date': days_ago(1),
    'depends_on_past': False
}


### Gets the secret myconn from Secrets Manager
def read_from_aws_sm_fn(**kwargs):
    ### set up Secrets Manager
    hook = AwsHook()
    client = hook.get_client_type('secretsmanager')
    response = client.get_secret_value(SecretId=sm_secretId_name)
    myConnSecretString = response["SecretString"]

    return myConnSecretString

### 'os.path.basename(__file__).replace(".py", "")' uses the file name secrets-manager.py for a DAG ID of secrets-manager
with DAG(
        dag_id=os.path.basename(__file__).replace(".py", ""),
        default_args=default_args,
        dagrun_timeout=timedelta(hours=2),
        start_date=days_ago(1),
        schedule_interval=None
) as dag:
    write_all_to_aws_sm = PythonOperator(
        task_id="read_from_aws_sm",
        python_callable=read_from_aws_sm_fn,
        provide_context=True
    )