Apache Airflow is an open-source platform for creating, running and monitoring workflows. Users develop Python language scripts that define Directed Acyclic Graphs (DAGs). These DAGs specify dependencies and a sequence of steps (or tasks) to run either on a defined schedule or based on external event triggers. Airflow is popular among developers that need to monitor and manage data pipelines.
Our adapter for Airflow provides seamless integration and automation of Airflow DAG executions into your Tidal-managed processes. With more robust scheduling functionality than the basic features in Airflow, Tidal Automation enables you to include complex DAGs as Airflow jobs within your enterprise workflows and schedule those jobs based on other dependencies and resources. Centralized management frees up developers from monitoring and scheduling tasks so they can focus on higher value activities.
The Tidal adapter for Airflow enables you to:
Airflow DAGs can be seen directly in Tidal through a built-in DAG viewer.
Tidal’s enterprise-wide automation platform transcends the inherent limitations associated with standalone point products or native cloud schedulers. We can automate and orchestrate cross-application workloads and enterprise-wide business processes that traverse multiple clouds and hybrid environments – all from a single-pane-of-glass view.
Tidal helps you optimize the value and performance of your legacy infrastructure while opening new opportunities to leverage next-gen applications and workflows. From pure on-prem to hybrid on-prem and cloud engagements – the answer is Tidal.