AWS Big Data Blog
Category: Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
Introducing Amazon MWAA support for the Airflow REST API and web server auto scaling
Apache Airflow is a popular platform for enterprises looking to orchestrate complex data pipelines and workflows. Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed service that streamlines the setup and operation of secure and highly available Airflow environments in the cloud. In this post, we’re excited to introduce two new features that […]
Orchestrate an end-to-end ETL pipeline using Amazon S3, AWS Glue, and Amazon Redshift Serverless with Amazon MWAA
Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate data pipelines in the cloud at scale. Apache Airflow is an open source tool used to programmatically author, schedule, and monitor sequences of processes and tasks, referred to as workflows. […]
Dynamic DAG generation with YAML and DAG Factory in Amazon MWAA
Amazon Managed Workflow for Apache Airflow (Amazon MWAA) is a managed service that allows you to use a familiar Apache Airflow environment with improved scalability, availability, and security to enhance and scale your business workflows without the operational burden of managing the underlying infrastructure. In Airflow, Directed Acyclic Graphs (DAGs) are defined as Python code. […]
Introducing Amazon MWAA larger environment sizes
Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed service for Apache Airflow that streamlines the setup and operation of the infrastructure to orchestrate data pipelines in the cloud. Customers use Amazon MWAA to manage the scalability, availability, and security of their Apache Airflow environments. As they design more intensive, complex, and ever-growing […]
Introducing Amazon MWAA support for Apache Airflow version 2.8.1
Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that makes it straightforward to set up and operate end-to-end data pipelines in the cloud. Organizations use Amazon MWAA to enhance their business workflows. For example, C2i Genomics uses Amazon MWAA in their data platform to orchestrate the validation […]
Disaster recovery strategies for Amazon MWAA – Part 1
In the dynamic world of cloud computing, ensuring the resilience and availability of critical applications is paramount. Disaster recovery (DR) is the process by which an organization anticipates and addresses technology-related disasters. For organizations implementing critical workload orchestration using Amazon Managed Workflows for Apache Airflow (Amazon MWAA), it is crucial to have a DR plan […]
Orchestrate Amazon EMR Serverless Spark jobs with Amazon MWAA, and data validation using Amazon Athena
As data engineering becomes increasingly complex, organizations are looking for new ways to streamline their data processing workflows. Many data engineers today use Apache Airflow to build, schedule, and monitor their data pipelines. However, as the volume of data grows, managing and scaling these pipelines can become a daunting task. Amazon Managed Workflows for Apache […]
Introducing shared VPC support on Amazon MWAA
In this post, we demonstrate automating deployment of Amazon Managed Workflows for Apache Airflow (Amazon MWAA) using customer-managed endpoints in a VPC, providing compatibility with shared, or otherwise restricted, VPCs. Data scientists and engineers have made Apache Airflow a leading open source tool to create data pipelines due to its active open source community, familiar […]
Introducing Amazon MWAA support for Apache Airflow version 2.7.2 and deferrable operators
Today, we are announcing the availability of Apache Airflow version 2.7.2 environments and support for deferrable operators on Amazon MWAA. In this post, we provide an overview of deferrable operators and triggers, including a walkthrough of an example showcasing how to use them. We also delve into some of the new features and capabilities of Apache Airflow, and how you can set up or upgrade your Amazon MWAA environment to version 2.7.2.
Use Snowflake with Amazon MWAA to orchestrate data pipelines
This blog post is co-written with James Sun from Snowflake. Customers rely on data from different sources such as mobile applications, clickstream events from websites, historical data, and more to deduce meaningful patterns to optimize their products, services, and processes. With a data pipeline, which is a set of tasks used to automate the movement […]