Airflow 1.10.10 contains 199 commits since 1.10.9 and includes 11 new features, 43 improvements, 44 bug fixes, and several doc changes.


Some of the noteworthy new features (user-facing) are:

Allow user to chose timezone to use in the RBAC UI

By default the Web UI will show times in UTC. It is possible to change the timezone shown by using the menu in the top right (click on the clock to activate it):

Screenshot: Allow user to chose timezone to use in the RBAC UI


Note: This feature is only available for the RBAC UI (enabled using rbac=True in [webserver] section in your airflow.cfg).

Add Production Docker image support

There are brand new production images (alpha quality) available for Airflow 1.10.10. You can pull them from the Apache Airflow Dockerhub repository and start using it.

More information about using production images can be found in Soon it will be updated with information how to use images using official helm chart.

To pull the images you can run one of the following commands:

  • docker pull apache/airflow:1.10.10-python2.7
  • docker pull apache/airflow:1.10.10-python3.5
  • docker pull apache/airflow:1.10.10-python3.6
  • docker pull apache/airflow:1.10.10-python3.7
  • docker pull apache/airflow:1.10.10 (uses Python 3.6)

Allow Retrieving Airflow Connections & Variables from various Secrets backend

From Airflow 1.10.10, users would be able to get Airflow Variables from Environment Variables.


A new concept of Secrets Backend has been introduced to retrieve Airflow Connections and Variables.

From Airflow 1.10.10, users can retrieve Connections & Variables using the same syntax (no DAG code change is required), from a secret backend defined in airflow.cfg. If no backend is defined, Airflow falls-back to Environment Variables and then Metadata DB.

Check for details on how-to configure Secrets backend.

As of 1.10.10, Airflow supports the following Secret Backends:

  • Hashicorp Vault
  • GCP Secrets Manager
  • AWS Parameters Store


Example configuration to use Hashicorp Vault as the backend:

backend = airflow.contrib.secrets.hashicorp_vault.VaultBackend
backend_kwargs = {"url": "", "connections_path": "connections", "variables_path": "variables", "mount_point": "airflow"}

Stateless Webserver using DAG Serialization

The Webserver can now run without access to DAG Files when DAG Serialization is turned on. The 2 limitations we had in 1.10.7-1.10.9 ( have been resolved.

The main advantage of this would be reduction in Webserver startup time for large number of DAGs. Without DAG Serialization all the DAGs are loaded in the DagBag during the Webserver startup.

With DAG Serialization, an empty DagBag is created and Dags are loaded from DB only when needed (i.e. when a particular DAG is clicked on in the home page)


Tasks using Dummy Operators are no longer sent to executor

The Dummy operators does not actually do any work and are mostly used for organizing/grouping tasks along with BranchPythonOperator.

Previously, when using Kubernetes Executor, the executor would spin up a whole worker pod to execute a dummy task. With Airflow 1.10.10 tasks using Dummy Operators would be scheduled & evaluated by the Scheduler but not sent to the Executor. This should significantly improve execution time and resource usage.

Allow passing DagRun conf when triggering dags via UI

When triggering a DAG from the CLI or the REST API, it s possible to pass configuration for the DAG run as a JSON blob.

From Airflow 1.10.10, when a user clicks on Trigger Dag button, a new screen confirming the trigger request, and allowing the user to pass a JSON configuration blob would be show.

Screenshot: Allow passing DagRun conf when triggering dags via UI


Updating Guide

If you are updating Apache Airflow from a previous version to 1.10.10, please take a note of the following:

  • Run airflow upgradedb after pip install -U apache-airflow==1.10.10 as 1.10.10 contains 3 database migrations.

  • If you have used none_failed trigger rule in your DAG, change it to use the new none_failed_or_skipped trigger rule. As previously implemented, the actual behavior of none_failed trigger rule would skip the current task if all parents of the task had also skipped. This was not in-line with what was documented about that trigger rule. We have changed the implementation to match the documentation, hence if you need the old behavior use none_failed_or_skipped.

    More details in

  • Setting empty string to a Airflow Variable will now return an empty string, it previously returned None.


    >> Variable.set('test_key', '')
    >> Variable.get('test_key')

    The above code returned None previously, now it will return ‘’.

  • When a task is marked as success by a user in Airflow UI, function defined in on_success_callback will be called.

Special Note / Deprecations

Python 2

Python 2 has reached end of its life on Jan 2020. Airflow Master no longer supports Python 2. Airflow 1.10.* would be the last series to support Python 2.

We strongly recommend users to use Python >= 3.6

Use Airflow RBAC UI

Airflow 1.10.10 ships with 2 UIs, the default is non-RBAC Flask-admin based UI and Flask-appbuilder based UI.

The Flask-AppBuilder (FAB) based UI allows Role-based Access Control and has more advanced features compared to the legacy Flask-admin based UI. This UI can be enabled by setting rbac=True in [webserver] section in your airflow.cfg.

Flask-admin based UI is deprecated and new features won’t be ported to it. This UI will still be the default for 1.10.* series but would no longer be available from Airflow 2.0

Running Airflow on MacOS

Run export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES in your scheduler environmentIf you are running Airflow on MacOS and get the following error in the Scheduler logs:

objc[1873]: +[__NSPlaceholderDate initialize] may have been in progress in another thread when fork() was called.
objc[1873]: +[__NSPlaceholderDate initialize] may have been in progress in another thread when fork() was called. We cannot safely call it or ignore it in the fork() child process. Crashing instead. Set a breakpoint on objc_initializeAfterForkError to debug.

This error occurs because of added security to restrict multiprocessing & multithreading in Mac OS High Sierra and above.

We have moved to GitHub Issues

The Airflow Project has moved from JIRA to GitHub for tracking issues.

So if you find any bugs in Airflow 1.10.10 please create a GitHub Issue for it.

List of Contributors

According to git shortlog, the following people contributed to the 1.10.10 release. Thank you to all contributors!

ANiteckiP, Alex Guziel, Alex Lue, Anita Fronczak, Ash Berlin-Taylor, Benji Visser, Bhavika Tekwani, Brad Dettmer, Chris McLennon, Cooper Gillan, Daniel Imberman, Daniel Standish, Felix Uellendall, Jarek Potiuk, Jiajie Zhong, Jithin Sukumar, Kamil Breguła, Kaxil Naik, Kengo Seki, Kris, Kumpan Anton, Lokesh Lal, Louis Guitton, Louis Simoneau, Luyao Yang, Noël Bardelot, Omair Khan, Philipp Großelfinger, Ping Zhang, RasPavel, Ray, Robin Edwards, Ry Walker, Saurabh, Sebastian Brandt, Tomek Kzukowski, Tomek Urbaszek, Van-Duyet Le, Xiaodong Deng, Xinbin Huang, Yu Qian, Zacharya, atrbgithub, cong-zhu, retornam


Read also

Apache Airflow 1.10.12

Kaxil Naik

We are happy to present Apache Airflow 1.10.12

Apache Airflow 1.10.8 & 1.10.9

Kaxil Naik

We are happy to present the new 1.10.8 and 1.10.9 releases of Apache Airflow.