Getting started with Astro (Managed Apache Airflow)

Explore why using Airflow with Astro improves production workflows by unifying connections across dev, staging, and prod, enabling rollbacks, environment management, and scalable deployment features.

Discover how Astro, a fully managed SaaS for data orchestration with Apache Airflow, uses the Astro CLI, cloud UI, API, and hypervisor to manage clusters and deployments.

Explore three key concepts in Astro: organization, workspace, and deployment—and how they organize airflow deployments and environments within a cluster.

Create your Astro account and set up your organization, workspace, and first project using a template to run Airflow in Astro's managed service, with the Astro ID explained.

Create and configure your first Airflow deployment on Astro by selecting a deployment template, setting work schedules, choosing a provider and cluster, and accessing the Airflow UI.

Remember you have ten days and a limited number of credits; hibernate your deployment until further notice to save credits, then wake it up manually when you resume.

Explore the astro cli, the open source tool that wraps docker or podman to run airflow locally, debug and test dags, and manage workspaces and deployments with best practices.

Install the Astro CLI to set up your local Airflow development environment with the Astro runtime, then start it and access the Airflow UI.

Create a dag that uses the GitHub operator to fetch repository stats, read health thresholds from an Airflow variable, and evaluate whether the repo is healthy or needs attention.

Learn to create and manage airflow connections, variables, and environment variables in astro, compare secrets backend, astro environment manager, and environment variable options for deploying dags.

Discover the Astro Environment Manager and learn to create environment variables, Airflow variables, and connections, link them to deployments, and override values per deployment.

Explore the astro id, an in-browser ide for airflow dag development guided by AI that respects your airflow environment and astro workspace, with built-in checks and versioning.

Import your local project into Astro via the Astro CLI, login, export the project, and create a new GitHub project to access the dag file GitHub repo monitor dot pi.

Configure Astro to test DAGs with an ephemeral asteroid deployment, validating DAGs using real dependencies, linking variables and connections, without a local Airflow environment.

Explore four deployment methods for Astro: project deploys, DAG-only deploys, image-only deploys, and GitHub integration deploy, detailing what gets deployed (DAGs, Docker images) and when to use each.

Wake up the dev deployment, deploy your DAG with the project-based deploy, authenticate via astro login or an API token for CI/CD, then verify the Airflow UI.

Deploy only the dag files with dag-only deploys, the fastest method for astro projects. These deployments avoid restarts, provide no downtime, and are ideal when only dags change.

Compare image-only and dag-only deploys in astro to update the runtime with a Docker image while deploying across airflow components; use dag-only for new dags and image-only for runtime changes.

save credits by hibernating deployments in Astro's managed Apache Airflow, and learn the quick steps to pause a deployment: click here, Hibernate Deployment, then confirm.

Explore airflow metrics in astro, including DAGs and task runs, P90 run durations, deployment analytics, and metrics export to Datadog or Elasticsearch for multi-workspace oversight.

Astro monitors deployments in real time and alerts you to issues through configurable alerts and notification channels, covering incidents from scheduler heartbeat to deprecated runtime versions and capacity challenges.

Explore building and deploying DAGs with the Astro CLI or the Astro ID, setting alerts and monitoring metrics, and previewing features like access management and astro observe.