Popular orchestration libraries such as Airflow require altering Python code to use their features, which makes the codebase more complex and harder to maintain.
To separate data science code from orchestration logic, use Kestra.
With this approach, data scientists can prioritize model processing and training, while data engineers can focus on building workflows.
Article on how to build a data drift detection pipeline with Kestra.
