Do you have experience working with the Apache Airflow platform for workflow orchestration?

Yes, I have experience working with Apache Airflow. It is a platform for programmatic workflow orchestration that allows creating, scheduling, and monitoring complex task chains.

Airflow uses Directed Acyclic Graphs (DAGs) to describe dependencies between tasks. Each task is a separate operator, such as executing a Python function, running an SQL query, or calling an external service.

Example of a simple DAG in Python:

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

default_args = {'start_date': datetime(2024, 1, 1)}

dag = DAG('example_dag', default_args=default_args, schedule_interval='@daily')

t1 = BashOperator(task_id='print_date', bash_command='date', dag=dag)
t2 = BashOperator(task_id='sleep', bash_command='sleep 5', dag=dag)

t1 >> t2  # t2 will run after t1

Airflow is widely used for automating ETL processes, data processing, and other tasks requiring reliable management of execution sequences.