AmazonMWAA

2024/01/29 - 1 updated api methods

Changes   This release adds MAINTENANCE environment status for Amazon MWAA environments.

2024/01/12 - 1 updated api methods

Changes   This Amazon MWAA feature release includes new fields in CreateWebLoginToken response model. The new fields IamIdentity and AirflowIdentity will let you match identifications, as the Airflow identity length is currently hashed to 64 characters.

2023/11/15 - 2 updated api methods

Changes   This Amazon MWAA release adds support for customer-managed VPC endpoints. This lets you choose whether to create, and manage your environment's VPC endpoints, or to have Amazon MWAA create, and manage them for you.

2023/06/05 - 1 updated api methods

Changes   This release adds ROLLING_BACK and CREATING_SNAPSHOT environment statuses for Amazon MWAA environments.

2023/04/03 - 3 updated api methods

Changes   This Amazon MWAA release adds the ability to customize the Apache Airflow environment by launching a shell script at startup. This shell script is hosted in your environment's Amazon S3 bucket. Amazon MWAA runs the script before installing requirements and initializing the Apache Airflow process.

2022/01/06 - 1 updated api methods

Changes   This release adds a "Source" field that provides the initiator of an update, such as due to an automated patch from AWS or due to modification via Console or API.

2021/05/26 - 3 updated api methods

Changes   Adds scheduler count selection for Environments using Airflow version 2.0.2 or later.

2021/03/16 - 1 updated api methods

Changes   This release adds UPDATE_FAILED and UNAVAILABLE MWAA environment states.

2021/03/04 - 3 updated api methods

Changes   This release introduces a new MinWorker parameter to the CreateEnvironment and UpdateEnvironment APIs. MinWorker allows the users to set a minimum worker count for worker auto-scaling operations.

2020/11/24 - 11 new api methods

Changes   (New Service) Amazon MWAA is a managed service for Apache Airflow that makes it easy for data engineers and data scientists to execute data processing workflows in the cloud.