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Amazon Managed Workflows for Apache Airflow

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Amazon Managed Workflows for Apache Airflow

Last updated on November 22, 2025

Amazon Managed Workflows for Apache Airflow (MWAA) Cheat Sheet

  • Amazon MWAA is a service that helps you manage and automate your data workflows using Apache Airflow.
  • Workflows are designed as Directed Acyclic Graphs (DAGs) using Python.

Use Cases

  • Complex Data Workflows: Handles complex data processing tasks.
  • ETL Jobs: Coordinates Extract, Transform, Load (ETL) processes.
  • Machine Learning: Prepares datasets for machine learning models.
  • Data Orchestration Across AWS Services: Easily integrates with S3, Redshift, Lambda, and RDS for orchestrated workflows.
  • Event-Driven Workflows: Can trigger DAGs based on events from EventBridge or S3.
  • Data Quality Checks: Automate validation and monitoring of datasets as part of pipelines.
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Key Features

  • Deployment: Easy setup and operation.
  • Scaling: Automatically adjusts to match workload demands.
  • Security: Built-in measures for data protection.
  • Monitoring: Comprehensive tracking of workflows.
  • Cost-Effectiveness: Reduces operational costs due to its managed nature.
  • Plugin Support: Extend Airflow capabilities with custom operators, hooks, and sensors.
  • Version Management: Supports multiple Airflow versions with minimal disruption.
  • Integration with AWS IAM: Fine-grained access control for DAGs and resources.
  • Logging and Auditing: Centralized logs stored in CloudWatch for auditing and troubleshooting.

Security

  • Network Isolation: Operates within Amazon’s Virtual Private Cloud (VPC).
  • Data Encryption: Uses AWS Key Management Service for automatic data encryption.
  • IAM Roles for Tasks: Each task can assume a role to securely access AWS resources.
  • Secrets Management: Integrates with AWS Secrets Manager for secure credential handling.
  • Audit Trails: Logs all Airflow actions for compliance and auditing purposes.

Pricing

  • Environment Pricing: Billed hourly based on environment size.
  • Additional Worker Instance Pricing: Billed hourly based on task load.
  • Additional Scheduler Instance Pricing: Billed hourly based on availability.
  • Database Storage: Billed per GB-month for storage consumed.
  • Data Transfer Costs: Charges may apply for data transferred between VPC and other AWS regions.
  • Log Storage Costs: CloudWatch log storage and retrieval are billed separately.
  • DAG Runs: Indirect cost based on the number of tasks executed and compute resources consumed.

Amazon Managed Workflows for Apache Airflow References:

https://aws.amazon.com/managed-workflows-for-apache-airflow/

https://aws.amazon.com/managed-workflows-for-apache-airflow/features/

https://aws.amazon.com/managed-workflows-for-apache-airflow/pricing/

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Written by: Nestor Mayagma Jr.

Nestor is a cloud engineer and content creator at Tutorials Dojo. He's been an active AWS Community Builder since 2022, with a growing interest in multi-cloud technologies across AWS, Azure, and Google Cloud. In his leisure time, he indulges in playing FPS games.

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