Modern Data Orchestration
Build, run, and observe data pipelines-as-code with Astro, the cloud-native data orchestration platform powered by Apache Airflow™.
Get StartedTrusted By
Focus on your pipelines, not managing Apache Airflow
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Build Faster
Accelerate the development of data pipelines with tools that allow your entire data team to focus on code that impacts your business.
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Run With Confidence
Increase data availability with a reliable and efficient production runtime environment optimized for the cloud.
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See the Whole Picture
Make sense of your data universe with real-time visibility and actionable insights across environments.
27k+
25k+
12m+
2k+Apache Airflow is the de facto standard for expressing data flows as code, with a robust and growing community of data engineers, scientists, and analysts around the world.
Learn more about AirflowUnified Data Flows
Bring order to your distributed data ecosystem with a modern orchestration platform.
Choose Your Deployment
Astro
Fully managed,
deployed in your cloud
Keep orchestration close to your data with a single-tenant data plane in your cloud or ours, no DevOps required. With a common control plane for data pipelines across clouds, you’ll sleep easy knowing your environment is managed by the core developers behind Apache Airflow.
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Software
Self managed, deployed in your private cloud
Launch, manage, and secure Airflow environments with an enterprise-ready software platform built for the most demanding settings.
Learn MoreWork Locally and Control Astro from Your Terminal
Write, test, and run DAGs in a lightweight local development environment.
astro dev init
> Airflow project Initialized!
├── Dockerfile # Base Airflow image
├── README.md
├── airflow_settings.yaml # For local connections
├── dags
│ ├── example-dag-advanced.py
│ └── example-dag-basic.py
├── include # Scripts, helpers, etc.
├── packages.txt # OS packages
├── plugins
└── requirements.txt # Python packages
astro dev start
> Creating containers for Airflow Scheduler, Webserver, and Database...
> Airflow is starting up...
> Your local instance of Airflow is now running on localhost: 8080 🚀
astro dev logs
> Printing logs from Airflow Scheduler, Webserver, and Workers....
================================================================================
DAG File Processing Stats
File Path PID Runtime # DAGs # Errors Last Runtime Last Run
----------------------------------------------- ----- --------- -------- ---------- -------------- -------------------
/usr/local/airflow/dags/example-dag-advanced.py 1 0 0.48s 2022-02-17T16: 32: 14
/usr/local/airflow/dags/example-dag-basic.py 1 0 1.22s 2022-02-17T16: 32: 15
================================================================================
Create, manage, and deploy to production from the comfort of your terminal or CI/CD processes.
astro deployment create my-airflow
NAME Namespace DEPLOYMENT ID TAG AIRFLOW VERSION
my-airflow my-namespace my-uuid 4.0.8 2.2.2
Successfully created deployment. Deployment can be accessed at the following URLs
Airflow Dashboard: https: //my-org.astronomer.run/my-airflow/home
Deployment Dashboard: https: //cloud.astronomer.io/my-workspace/deployments/my-airflow
astro deploy my-airflow
> Deploying: updated DAGs to my-airflow
> Building image...
> Pushing image to Astronomer...
> Deploy Succeeded! Your DAGs are now running at https: //my-org.astronomer.run/my-airflow/home
astro deployment list
> Listing Deployments available to modify...
* Prod Deployment
Stage Deployment
Dev Deployment
Start building your next-generation data platform with Astro.
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