Airflow可以存储在云端，例如使用AWS S3或Google Cloud Storage。具体实现方法如下：

1. 在Airflow配置文件中配置S3或GCS连接信息：

S3例子：

[conn_id]
aws_conn_id=s3_conn

[s3_conn]
aws_access_key_id = ACCESS_KEY
aws_secret_access_key = SECRET_KEY

GCS例子：

[conn_id]
google_cloud_conn_id=gcs_conn

[gcs_conn]
google_cloud_storage_conn_id = gcs_conn

2. 在DAG中指定存储在云端的文件路径和存储类型（s3或gcs）：

S3例子：

from airflow.models import DAG
from airflow.operators import BashOperator

dag = DAG(
    'example_s3',
    schedule_interval='0 0 * * *',
    catchup=False
)

S3_BUCKET = 'my-airflow-bucket'
S3_KEY = 'example_s3.txt'

t1 = BashOperator(
    task_id='upload_to_s3',
    bash_command=f'aws s3 cp {local_file_path} s3://{S3_BUCKET}/{S3_KEY}',
    dag=dag
)

t2 = BashOperator(
    task_id='download_from_s3',
    bash_command=f'aws s3 cp s3://{S3_BUCKET}/{S3_KEY} {local_download_path}',
    dag=dag
)

GCS例子：

from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from datetime import datetime

dag = DAG(
    'example_gcs',
    description='Example DAG to upload and download files from GCS',
    schedule_interval='@daily',
    start_date=datetime(2022, 3, 1),
    catchup=False
)

GCS_BUCKET = 'my-airflow-bucket'
GCS_KEY = 'example_gcs.txt'

t1 = BashOperator(
    task_id='upload_to_gcs',
    bash_command=f'gsutil cp {local_file_path} gs://{GCS_BUCKET}/{GCS_KEY}',
    dag=dag
)

t2 = BashOperator(
    task_id='download_from_gcs',
    bash_command=f