Orchestrating Apache Airflow ML Workflows at Scale with SageMaker Unified Studio

As organizations increasingly rely on data-driven applications, managing the diverse tools, data, and teams involved can create challenges. Amazon SageMaker Unified Studio addresses this by providing an integrated, governed platform to orchestrate end-to-end data and AI/ML workflows.

In this workshop, we’ll explore how to leverage Amazon SageMaker Unified Studio to build and deploy scalable Apache Airflow workflows that span the data and AI/ML lifecycle. We’ll walk through real-world examples showcasing how this AWS service brings together familiar Airflow capabilities with SageMaker’s data processing, model training, and inference features - all within a unified, collaborative workspace.

Key topics covered:

• Authoring and scheduling Airflow DAGs in SageMaker Unified Studio
• Understanding how Apache Airflow powers workflow orchestration under the hood
• Leveraging SageMaker capabilities like Notebooks, Data Wrangler, and Models
• Implementing centralized governance and workflow monitoring
• Enhancing productivity through unified development environments

Join us to transform your ML workflow experience from complex and fragmented to streamlined and efficient.