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💡 A solution I see to address this, involves using Airflow to automatically fetch configuration files stored in S3, parse them into a dictionary format, and then pass these dictionaries to the application. This is achieved by using Airflow's S3Hook to access the S3 bucket, retrieve the configuration file (e.g.,
JSON
orYAML
), and then convert this file into a dictionary which the application can use as configuration overrides.
ℹ️ It is recommended to set up proper IAM roles and policies to securely manage access between Airflow and S3, ensuring that the Airflow environment has the necessary permissions to read from the specified S3 bucket.
Airflow DAG Template for Fetching Configuration from S3
from airflow.providers.amazon.aws.hooks.s3 import S3Hook import json def fetch_and_load_config(ti, aws_connection_id, bucket_name, object_key, file_format='json'): # Create an instance of S3Hook s3_hook = S3Hook(aws_connection_id=aws_connection_id) # Read the file content from S3 config_content = s3_hook.read_key(object_key, bucket_name) # Parse the configuration file based on the specified format if file_format == 'json': config_data = json.loads(config_content) elif file_format == 'yaml': import yaml config_data = yaml.safe_load(config_content) else: raise ValueError("Unsupported file format. Only 'json' and 'yaml' are supported.") # Push the configuration data to XCom for other tasks to use ti.xcom_push(key='config_data', value=config_data)
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