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Amazon MWAA
Secure and highly available managed workflow orchestration for Apache Airflow
Amazon MWAA
Secure and highly available managed workflow orchestration for Apache Airflow
Features
Features
Deploy Apache Airflow at scale without the operational burden of managing underlying infrastructure.
Run Apache Airflow workloads in your own isolated and secure cloud environment.
Monitor environments through Amazon CloudWatch integration to reduce operating costs and engineering overhead.
Connect to cloud or on-premises resources through Apache Airflow providers or custom plugins.
How It Works
Amazon Managed Workflows for Apache Airflow (MWAA) orchestrates your workflows using Directed Acyclic Graphs (DAGs) written in Python. You provide MWAA an Amazon Simple Storage Service (S3) bucket where your DAGs, plugins, and Python requirements reside. Then run and monitor your DAGs from the Management Console, a command line interface (CLI), a software development kit (SDK), or the Apache Airflow user interface (UI).
How It Works
Amazon Managed Workflows for Apache Airflow (MWAA) orchestrates your workflows using Directed Acyclic Graphs (DAGs) written in Python. You provide MWAA an Amazon Simple Storage Service (S3) bucket where your DAGs, plugins, and Python requirements reside. Then run and monitor your DAGs from the Management Console, a command line interface (CLI), a software development kit (SDK), or the Apache Airflow user interface (UI).
Use Cases
Support Complex Workflows
Coordinate Extract, Transform, and Load (ETL) Jobs
Prepare ML Data
Use Cases
Support Complex Workflows
Coordinate Extract, Transform, and Load (ETL) Jobs
Prepare ML Data
Automate your pipeline to help machine learning (ML) modeling systems ingest and then train on data.
