version: '3' services: postgres: image: postgres:15 environment: POSTGRES_USER: airflow POSTGRES_PASSWORD: airflow POSTGRES_DB: airflow airflow-webserver: image: apache/airflow:2.9.0 ports: - "8080:8080" airflow-scheduler: image: apache/airflow:2.9.0
version: '3' services: postgres: image: postgres:15 environment: POSTGRES_USER: airflow POSTGRES_PASSWORD: airflow POSTGRES_DB: airflow airflow-webserver: image: apache/airflow:2.9.0 ports: - "8080:8080" airflow-scheduler: image: apache/airflow:2.9.0
version: '3' services: postgres: image: postgres:15 environment: POSTGRES_USER: airflow POSTGRES_PASSWORD: airflow POSTGRES_DB: airflow airflow-webserver: image: apache/airflow:2.9.0 ports: - "8080:8080" airflow-scheduler: image: apache/airflow:2.9.0
from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime def extract_data(): print("Running ETL task") with DAG( dag_id="sample_pipeline", start_date=datetime(2025, 1, 1), schedule_interval="@daily", catchup=False
) as dag: task = PythonOperator( task_id="extract_task", python_callable=extract_data )
from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime def extract_data(): print("Running ETL task") with DAG( dag_id="sample_pipeline", start_date=datetime(2025, 1, 1), schedule_interval="@daily", catchup=False
) as dag: task = PythonOperator( task_id="extract_task", python_callable=extract_data )
from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime def extract_data(): print("Running ETL task") with DAG( dag_id="sample_pipeline", start_date=datetime(2025, 1, 1), schedule_interval="@daily", catchup=False
) as dag: task = PythonOperator( task_id="extract_task", python_callable=extract_data ) - Airflow Webserver
- Airflow Scheduler
- Metadata Database
- ETL Scripts and DAGs - Portable workflow orchestration
- Simplified dependency management
- Easy scaling with Kubernetes integration
- Improved development consistency
- Faster testing and deployment
