[Yandex Cloud documentation](../../index.md) > [Yandex Managed Service for Apache Airflow™](../index.md) > [Concepts](index.md) > Available Apache Airflow™ versions

# Versioning in Managed Service for Apache Airflow™

## Available Apache Airflow™ versions {#available-versions}

Managed Service for Apache Airflow™ supports several Apache Airflow™ versions, each available on one of several Python versions. The following version combinations are supported:

Version Apache Airflow™ | Python version
--- | ---
2.8 | 3.8
2.8 | 3.10
2.10 | 3.10
2.10 | 3.12
3.0 | 3.12
3.1 | 3.12

{% note warning %}

The package contents in Apache Airflow™ may vary in different versions. Some packages available in earlier versions are not included in Apache Airflow™ 3.0 and higher. If required, you can install them when creating or updating a cluster.

{% endnote %}

## Version update {#update}

When updating versions in Managed Service for Apache Airflow™, you can change the following:

* Python version to any supported one for the current Apache Airflow™ version.
* Apache Airflow™ version to the next supported version within the same branch: `2.X` or `3.X`.

    You cannot update Apache Airflow™ from `2.X` to `3.X`. To update to `3.X`, [create a new cluster](../operations/cluster-create.md) and attach the old cluster's DAG storage to it.

Managed Service for Apache Airflow™ does not allow simultaneous updates of Apache Airflow™ and Python versions because user dependencies may stop working on newer Python versions.

For example, to update a cluster from Apache Airflow™ `2.8` and Python `3.8` to Apache Airflow™ `2.10` and Python `3.12`:

1. Update Python to `3.10` and test the cluster with its dependencies.
1. Update Apache Airflow™ to `2.10` and test the cluster after you migrate the database.
1. Update Python to `3.12` and test the dependencies again.

#### Useful links {#see-also}

* [Apache Airflow™](update-policy.md) versioning policy
* [Updating Apache Airflow™ and Python versions](../operations/cluster-version-update.md)