apache-airflow-providers-microsoft-azure

What it is and what it does

This is an Apache Airflow provider package that bridges Airflow's workflow orchestration engine to Microsoft Azure's cloud services. It exposes Azure resources—storage accounts, data lakes, Cosmos DB, Synapse, Batch, Container Instances, and more—as Airflow operators, hooks, and sensors, allowing you to define, schedule, and monitor Azure-based data pipelines and infrastructure tasks as DAGs.

The package wraps the official Azure SDK libraries (33 runtime dependencies covering storage, compute, identity, and data services) and integrates them into Airflow's task execution model. You install it on top of an existing Airflow deployment, define tasks using Azure operators, and Airflow handles scheduling, retry logic, and monitoring. It supports Python 3.10 through 3.14 and is actively maintained by the Apache Airflow project.

Use it for:

• Schedule and monitor Azure Data Lake or Blob Storage data ingestion and transformation jobs within Airflow DAGs.
• Orchestrate Azure Synapse Spark jobs, Batch compute tasks, or Container Instance deployments as part of multi-step workflows.
• Automate Azure resource provisioning, scaling, and lifecycle management (compute, storage, container registry) via Airflow.
• Build hybrid cloud pipelines that coordinate Azure services with AWS, GCP, or on-premises systems using Airflow's cross-provider support.
• Manage secrets and authentication to Azure services through Azure Key Vault integration within Airflow task execution.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Integrates Apache Airflow with Microsoft Azure services, providing operators, hooks, and sensors to orchestrate Azure resources and data workflows.

Yes, if you run Apache Airflow and need to orchestrate Azure workloads. The package is production-stable, actively maintained, and permissively licensed. The 33 dependencies are substantial but expected for comprehensive Azure SDK coverage. Verify that your Airflow deployment meets the >=2.11.0 requirement and that your environment can accommodate the Azure SDK footprint; no known vulnerabilities as of the query date.

Install

apache-airflow-providers-microsoft-azure on PyPI

pip install apache-airflow-providers-microsoft-azure

uv add apache-airflow-providers-microsoft-azure

poetry add apache-airflow-providers-microsoft-azure

Installing apache-airflow-providers-microsoft-azure

Before you install

Low friction installation with a pure-Python wheel. Actively maintained—released 6 days ago with 46490 repository stars. Requires Apache Airflow >=2.11.0 and pulls in 33 runtime dependencies, all Azure SDK packages; evaluate whether your environment can accommodate this dependency footprint.

License in practice

Licensed under Apache-2.0 (permissive), allowing use in commercial and proprietary projects with minimal restrictions; include a copy of the license and note any material modifications.

Quickstart

pip install apache-airflow-providers-microsoft-azure

from airflow.providers.microsoft.azure.operators.adls import ADLSDeleteOperator
from airflow.models import DAG

with DAG('azure_example') as dag:
    delete_task = ADLSDeleteOperator(task_id='delete_adls', path='/data')

Requires Apache Airflow >=2.11.0 and Python 3.10 or later; Azure credentials and connectivity to Azure services must be configured outside the package.

Verify before relying

• Specific operators, sensors, and hooks available in version 14.1.0 beyond the Azure SDK services listed.
• Whether all 33 dependencies are always required or if some are optional for specific Azure services.
• Performance characteristics and scalability limits for large-scale Azure resource orchestration.

Package facts

Evidence: apache_airflow_providers_microsoft_azure-14.1.0-py3-none-any.whl

Keywords: airflow-provider, microsoft.azure, airflow, integration

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