Migrate to Managed Airflow (Gen 3) from Managed Airflow (Legacy Gen 1) (Airflow 2)

Managed Airflow (Gen 3)  |  Managed Airflow (Gen 2)  |  Managed Airflow (Legacy Gen 1)

This page explains how to transfer DAGs, data and configuration from your existing Managed Airflow (Legacy Gen 1), Airflow 2 environments to Managed Airflow (Gen 3), Airflow 2 using snapshots .

Other migration guides

Before you begin

• Managed Airflow supports side-by-side migration from Managed Airflow (Legacy Gen 1) to Managed Airflow (Gen 3). It is not possible to upgrade from Managed Airflow (Legacy Gen 1) to Managed Airflow (Gen 3) in-place.

• Check the list of differences between Managed Airflow (Legacy Gen 1), Managed Airflow (Gen 2), and Managed Airflow (Gen 3).

• The maximum size of the Airflow database that supports snapshots is 20 GB. If your environment's database takes more than 20 GB, reduce the size of the Airflow database .

• The total number of objects in the /dags , /plugins and /data folders in the environment's bucket must be less than 100,000 to create snapshots.

• If you use the XCom mechanism to transfer files, make sure that you use it according to Airflow's guidelines . Transferring big files or a large number of files using XCom impacts Airflow database's performance and can lead to failures when loading snapshots or upgrading your environment. Consider using alternatives such as Cloud Storage to transfer large volumes of data.

Make sure that your DAGs are compatible with Managed Airflow (Gen 3)

Make sure that your DAGs are compatible with Managed Airflow (Gen 3) by following these suggestions:

• The [list of packages][cc-versions] in the Managed Airflow (Gen 3) environment can be different than in your Managed Airflow (Legacy Gen 1) environment. This might affect the compatibility of your DAGs with Managed Airflow (Gen 3).

• Managed Airflow loads configuration overrides, environment variables, and PyPI packages from your Managed Airflow (Legacy Gen 1) environment's snapshot to Managed Airflow (Gen 3) without changing or adjusting them for compatibility. If custom PyPI packages cause dependency conflicts, you can skip their installation when you load the snapshot.

• In Managed Airflow (Gen 3), the environment's cluster is located in the tenant project . Make sure that your DAGs are compatible with this change. In particular, KubernetesPodOperator workloads now scale independently from your environment and it's not possible to use Pod affinity configs.

• In Managed Airflow (Gen 3), the Airflow database can't be accessed directly. Make sure that your DAGs are compatible with this change.

Pause DAGs in your Managed Airflow (Legacy Gen 1) environment

To avoid duplicate DAG runs, pause all DAGs in your Managed Airflow (Legacy Gen 1) environment before saving its snapshot. Skip the liveness monitoring DAG ( airflow_monitoring ), it is used for monitoring purposes and is not included in environment snapshots.

You can use any of the following options:

• In the Airflow web interface , go to DAGsand pause all DAGs manually.

• Use the composer_dags script to pause all DAGs:

   python3  
  composer_dags.py  
  --environment  
   COMPOSER_1_ENV 
    
   \ 
    
  --project  
   PROJECT_ID 
    
   \ 
    
  --location  
   COMPOSER_1_LOCATION 
    
   \ 
    
  --operation  
  pause 
  

  Replace:

  • COMPOSER_1_ENV with the name of your Managed Airflow (Legacy Gen 1) environment.
  • PROJECT_ID with the Project ID .
  • COMPOSER_1_LOCATION with the region where the environment is located.

• (Airflow versions 2.9.1 and later) If there are quota errors while pausing a large number of DAGs, you can use the following Airflow CLI commands to pause all DAGs at once:

   gcloud  
  composer  
  environments  
  run  
   COMPOSER_1_ENV 
    
  dags  
  pause  
   \ 
    
  --project  
   PROJECT_ID 
    
   \ 
    
  --location  
   COMPOSER_1_LOCATION 
    
   \ 
    
  --  
  -y  
  --treat-dag-id-as-regex  
   ".*" 
   
  

• (Airflow versions earlier than 2.9.1) If there are quota errors while pausing a large number of DAGs, it's possible to pause DAGs using the Airflow REST API . Also see Trying the API in the Airflow documentation.

Save the snapshot of your Managed Airflow (Legacy Gen 1) environment

Create a Managed Airflow (Gen 3) environment

Create a Managed Airflow (Gen 3) environment . You can start with an environment preset that matches your expected resource demands, and later scale and optimize your environment further.

You don't need to specify configuration overrides and environment variables because you replace them later when you load the snapshot of your Managed Airflow (Legacy Gen 1) environment.

Load the snapshot to your Managed Airflow (Gen 3) environment

 gcloud  
composer  
environments  
snapshots  
load  
 \ 
  
 COMPOSER_3_ENV 
  
 \ 
  
--location  
 COMPOSER_3_LOCATION 
  
 \ 
  
--snapshot-path  
 " SNAPSHOT_PATH 
" 
 

Unpause DAGs in the Managed Airflow (Gen 3) environment

You can use any of the following options:

• In the Airflow web interface , go to DAGsand unpause all DAGs manually one by one.

• Use the composer_dags script to unpause all DAGs:

   python3  
  composer_dags.py  
  --environment  
   COMPOSER_3_ENV 
    
   \ 
    
  --project  
   PROJECT_ID 
    
   \ 
    
  --location  
   COMPOSER_3_LOCATION 
    
   \ 
    
  --operation  
  unpause 
  

  Replace:

  • COMPOSER_3_ENV with the name of your Managed Airflow (Gen 3) environment.
  • PROJECT_ID with the Project ID .
  • COMPOSER_3_LOCATION with the region where the environment is located.

• (Airflow versions 2.9.1 and later) If there are quota errors while unpausing a large number of DAGs, you can use the following Airflow CLI commands to unpause all DAGs at once:

   gcloud  
  composer  
  environments  
  run  
   COMPOSER_3_ENV 
    
  dags  
  unpause  
   \ 
    
  --project  
   PROJECT_ID 
    
   \ 
    
  --location  
   COMPOSER_3_LOCATION 
    
   \ 
    
  --  
  -y  
  --treat-dag-id-as-regex  
   ".*" 
   
  

• (Airflow versions earlier than 2.9.1) If there are quota errors while unpausing a large number of DAGs, it's possible to unpause DAGs using the Airflow REST API . Also see Trying the API in the Airflow documentation.

Check for DAG errors

1. In the Airflow web interface , go to DAGsand check for reported DAG syntax errors.

2. Check that DAG runs are scheduled at the correct time.

3. Wait for the DAG runs to happen in the Managed Airflow (Gen 3) environment and check if they were successful. If a DAG run was successful, don't unpause it in the Managed Airflow (Legacy Gen 1) environment; if you do so, a DAG run for the same time and date happens in your Managed Airflow (Legacy Gen 1) environment.

4. If a specific DAG runs fails, attempt to troubleshoot the DAG until it successfully runs in Managed Airflow (Gen 3).

Monitor your Managed Airflow (Gen 3) environment

After you transfer all DAGs and configuration to the Managed Airflow (Gen 3) environment, monitor it for potential issues, failed DAG runs, and overall environment health.

If the Managed Airflow (Gen 3) environment runs without problems for a sufficient period of time, consider deleting the Managed Airflow (Legacy Gen 1) environment.

What's next

• Troubleshooting DAGs
• Troubleshooting environment creation
• Troubleshooting environment updates