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Managed Apache Airflow Hosting

Workflow Automation

Programmatically author and schedule workflows

Apache Airflow is an industry-standard workflow orchestration platform for data pipelines — deployed and fully managed by ManageStacks on AWS, Azure, or GCP with pre-configured Celery workers and Grafana monitoring.

About Apache Airflow

Apache Airflow is a platform to programmatically author, schedule, and monitor workflows. Created at Airbnb, it has become the industry standard for data pipeline orchestration used by thousands of organizations worldwide.

Airflow uses directed acyclic graphs (DAGs) to manage workflow orchestration. Tasks and dependencies are defined in Python, providing a flexible and extensible framework for building ETL pipelines, ML workflows, and general-purpose batch processing jobs.

Key Features

  • Python-based DAG definition for workflows
  • Rich web UI for monitoring and management
  • Extensible with custom operators and hooks
  • Built-in scheduling and dependency management
  • Integration with major cloud services and databases
  • Scalable architecture with Celery or Kubernetes executors

How ManageStacks Helps

ManageStacks provisions Airflow with pre-configured Celery workers, PostgreSQL metadata database, Redis message broker, and Grafana monitoring. We handle scaling, database maintenance, and version upgrades so your data team can focus on building pipelines.

Frequently Asked Questions

How long does it take to deploy Airflow on ManageStacks?+
Under 5 minutes. ManageStacks provisions Airflow with Celery workers, PostgreSQL, Redis, and Grafana monitoring automatically.
Can I use custom Python packages with Airflow on ManageStacks?+
Yes. You can install custom Python packages and configure your DAGs through the ManageStacks deployment. Persistent DAG storage ensures your workflows survive restarts.
Does ManageStacks handle Airflow version upgrades?+
Yes. We test each Airflow release for stability and handle database migrations during upgrades. You can apply updates with one click.