Airflow

Apache Airflow 3.2.0 is a powerful open-source platform used to programmatically author, schedule, and monitor workflows. It enables developers and data engineers to design complex data pipelines using Python, providing flexibility, scalability, and visibility into workflow execution through a modern web-based interface.

The solution supports common workflow orchestration tasks including task scheduling, dependency management, monitoring, logging, and automation. It is ideal for ETL pipelines, data engineering workflows, machine learning pipelines, and backend job scheduling use cases.

Features of Apache Airflow 3.2.0:

• Python-based workflow definition using Directed Acyclic Graphs (DAGs).
• Web-based UI for monitoring, triggering, and managing workflows.
• Task scheduling with advanced dependency handling.
• Scalable architecture with support for multiple executors.
• Integration with cloud services, databases, and APIs.
• Detailed logging and monitoring for troubleshooting.
• Role-based access control and authentication support.

Usage instructions for Apache Airflow
$ sudo su
$ cd /home/Airflow/airflow-project
$ source venv/bin/activate
$ airflow standalone

Credentials are displayed in the terminal after running standalone mode.

Access the Airflow UI:
Open your browser and navigate to:
http://your-server-ip:8080

Disclaimer: Apache Airflow is provided “as is” under applicable open-source licenses. Users are responsible for proper configuration, workflow design, security settings, and infrastructure management. This solution is best suited for orchestrating, scheduling, and monitoring workflows in development and production environments.