# Amazon MWAA now supports Apache Airflow 3.3.1, and tasks can finally hold state!

Hey everyone, Shii-chan here! Today I found an update on the data pipeline side of things.

## What was announced?

According to AWS What's New, Amazon Managed Workflows for Apache Airflow (MWAA) now supports Apache Airflow 3.3.1, the latest release of the framework. MWAA is a managed orchestration service for Apache Airflow that makes it easier to set up and operate end-to-end data pipelines in the cloud.

## Why it matters

Airflow 3.3 brings two standout features: the Task and Asset State Store, and the Language Task SDK. Until now, carrying state across retries and reruns has been a real pain point for data engineers dealing with long-running jobs, or jobs that need to reconnect safely after a crash. This release is aimed squarely at that problem.

## What changes

- **Task and Asset State Store**: tasks can now persist durable state across retries and reruns, enabling cursor tracking and crash-safe reconnection to long-running jobs
- **Language Task SDK (experimental)**: lets you write task logic in Java or Go while keeping orchestration in Python
- Also included: expanded asset partitioning, pluggable retry policies, and bulk actions for DAG runs and task instances

## Dive Deep

On top of these features, Airflow 3.3.1 also delivers stability, security, and UI improvements. To use it, you can launch a new Apache Airflow 3.3.1 environment from the AWS Management Console, or upgrade from 3.2 or later with just a few clicks. It's available in all currently supported Amazon MWAA regions. For the full details, check the Amazon MWAA documentation and the Apache Airflow 3.3.1 change log.

## Wrap-up

- Amazon MWAA now supports Apache Airflow 3.3.1
- The new Task and Asset State Store lets tasks persist state across retries and reruns
- An experimental Language Task SDK lets you write task logic in Java or Go
- Also brings expanded asset partitioning, pluggable retry policies, and bulk actions for DAGs and tasks
- You can launch or upgrade in just a few clicks from the MWAA console — worth trying if you run long jobs or work across multiple languages on your data team!