With the release of `dagster-airflow` 1.1.17, data engineering teams can now easily transition Airflow DAGs to Dagster, providing a radically better developer experience. This tooling makes it possible for organizations to migrate away from legacy imperative approaches and adopt a modern declarative framework that offers excellent developer ergonomics. The `dagster-airflow` library enables users to lift-and-shift their existing Airflow DAGs into Dagster, or orchestrate Dagster job runs from Airflow, providing a seamless transition for data teams looking for an Airflow alternative. By using the `dagster-airflow` library, organizations can boost their team's ability to rapidly develop, deploy, and maintain high-quality pipelines, delivering more effectively against stakeholder expectations.