Updating an Apache Airflow™ cluster

Written by

Yandex Cloud

Updated at May 5, 2025

After creating a cluster, you can edit its basic and advanced settings.

Management console

CLI

Terraform

REST API

gRPC API

To change the cluster settings:

Navigate to the folder dashboard and select Managed Service for Apache Airflow™.
Select the cluster and click Edit in the top panel.
Under Basic parameters, edit the cluster name and description, delete labels, or add new ones.
Under Access settings, select a service account or create a new one with the managed-airflow.integrationProvider role. The cluster will thus get the permissions it needs to work with user resources. For more information, see Impersonation.

To update a service account in a Managed Service for Apache Airflow™ cluster, assign the iam.serviceAccounts.user role or higher to your Yandex Cloud account.

Warning

If the cluster already uses a service account to access objects from Object Storage, then changing it to a different service account may make these objects unavailable and interrupt the cluster operation. Before changing the service account settings, make sure that the cluster doesn't use the objects in question.
Under Network settings, select a security group for cluster network traffic or create a new group.

Security group settings do not affect access to the Apache Airflow™ web interface.
In the settings sections of Managed Service for Apache Airflow™ components, i.e., Web server configuration, Scheduler configuration, and Worker configuration, specify the number of instances and computing resource configuration.
Under Triggerer configuration, enable or disable the Triggerer service. If it is enabled, specify the number of instances and resources.
Under Dependencies, delete or add names of pip and deb packages.
Under DAG file storage, select an existing bucket to store DAG files or create a new one. Make sure to grant the READ permission for this bucket to the cluster service account.
Under Advanced settings, enable or disable deletion protection.
Under Airflow configuration:
- Add, edit, or delete Apache Airflow™ additional properties, e.g., the api.maximum_page_limit key with 150 for its value.
  
  Populate the fields manually or import a configuration from a file (see sample configuration file).
- Enable or disable the Use Lockbox Secret Backend option allowing you to use secrets in Yandex Lockbox to store Apache Airflow™ configuration data, variables, and connection parameters.
  
  To extract the required information from the secret, the cluster service account must have the lockbox.payloadViewer role.
  
  You can assign this role either at whole folder level or individual secret level.
Under Logging, enable or disable logging. If logging is enabled, specify the log group to write logs to and the minimum logging level. Logs generated by Apache Airflow™ will be sent to Yandex Cloud Logging.
Click Save changes.

If you do not have the Yandex Cloud CLI yet, install and initialize it.

The folder specified when creating the CLI profile is used by default. To change the default folder, use the yc config set folder-id <folder_ID> command. You can specify a different folder using the --folder-name or --folder-id parameter.

To change the cluster settings:

View the description of the CLI command to update the cluster:
```
yc managed-airflow cluster update --help
```
Provide a list of settings to update in the update cluster command:
```
yc managed-airflow cluster update <cluster_name_or_ID> \
   --new-name <new_cluster_name> \
   --description <cluster_description> \
   --labels <label_list> \
   --service-account-id <service_account_ID> \
   --security-group-ids <security_group_IDs> \
   --webserver count=<number_of_instances>,`
              `resource-preset-id=<resource_ID> \
   --scheduler count=<number_of_instances>,`
              `resource-preset-id=<resource_ID> \
   --worker min-count=<minimum_number_of_instances>,`
           `max-count=<maximum_number_of_instances>,`
           `resource-preset-id=<resource_ID> \
   --triggerer count=<number_of_instances>,`
              `resource-preset-id=<resource_ID> \
   --deb-packages <list_of_deb_packages> \
   --pip-packages <list_of_pip_packages> \
   --dags-bucket <bucket_name> \
   --deletion-protection \
   --lockbox-secrets-backend \
   --log-enabled \
   --log-folder-id <folder_ID> \
   --log-min-level <logging_level>
```
Where:
- --name: Cluster name.
- --description: Cluster description.
- --labels: List of labels. Provide labels in <key>=<value> format.
- --admin-password: Admin user password. The password must be not less than 8 characters long and contain at least:
  - One uppercase letter
  - One lowercase letter
  - One number
  - One special character
- --service-account-id: Service account ID.
- --security-group-ids: List of security group IDs.
- --webserver, --scheduler, --worker, --triggerer: Managed Service for Apache Airflow™ component configuration:
  - count: Number of instances in the cluster for the web server, scheduler, and Triggerer.
  - min-count, max-count: Minimum and maximum number of instances in the cluster for the worker.
  - resource-preset-id: ID of the computing resources of the web server, scheduler, worker, and Triggerer. The possible values are:
    - c1-m2: 1 vCPU, 2 GB RAM
    - c1-m4: 1 vCPU, 4 GB RAM
    - c2-m4: 2 vCPUs, 4 GB RAM
    - c2-m8: 2 vCPUs, 8 GB RAM
    - c4-m8: 4 vCPUs, 8 GB RAM
    - c4-m16: 4 vCPUs, 16 GB RAM
    - c8-m16: 8 vCPUs, 16 GB RAM
    - c8-m32: 8 vCPUs, 32 GB RAM
- --deb-packages, --pip-packages: Lists of deb and pip packages enabling you to install additional libraries and applications in the cluster for running DAG files:
  
  If required, you can set version restrictions for the installed packages, for example:
```
--pip-packages "pandas==2.0.2,scikit-learn>=1.0.0,clickhouse-driver~=0.2.0"
```
  The package name format and version are defined by the install command: pip install for pip packages and apt install for deb packages.
- --dags-bucket: Name of the bucket to store DAG files in.
- --deletion-protection: Enables cluster protection against accidental deletion.
  
  Even if it is enabled, one can still connect to the cluster manually and delete it.
- --lockbox-secrets-backend: Enables using secrets in Yandex Lockbox to store Apache Airflow™ configuration data, variables, and connection parameters.
- --airflow-config: Apache Airflow™ additional properties. Provide them in <configuration_section>.<key>=<value> format, such as the following:
```
--airflow-config core.load_examples=False
```
- Logging parameters:
  - --log-enabled: Enables logging. Logs generated by Apache Airflow™ will be sent to Yandex Cloud Logging.
  - --log-folder-id: Folder ID. Logs will be written to the default log group for this folder.
  - --log-group-id: Custom log group ID. Logs will be written to this group.
    
    Specify one of the two parameters: --log-folder-id or --log-group-id.
  - --log-min-level: Minimum logging level. Possible values: TRACE, DEBUG, INFO (default), WARN, ERROR, and FATAL.
  You can specify only one of the parameters: --log-folder-id or --log-group-id.
You can request the cluster ID and name with the list of clusters in the folder.

To change the cluster settings:

Open the current Terraform configuration file that defines your infrastructure.

For more information about creating this file, see Creating clusters.
To change cluster settings, change the required fields' values in the configuration file.

Alert

Do not change the cluster name and password using Terraform. This will delete the existing cluster and create a new one.

Here is the configuration file example:
```
resource "yandex_airflow_cluster" "<cluster_name>" {
  name        = "<cluster_name>"
  description = "<cluster_description>"

  labels = { <label_list> }

  admin_password     = "<administrator_password>"
  service_account_id = "<service_account_ID>"
  subnet_ids         = ["<list_of_subnet_IDs>"]
  security_group_ids = ["<list_of_security_group_IDs>"]

  webserver = {
    count              = <number_of_instances>
    resource_preset_id = "<resource_ID>"
  }

  scheduler = {
    count              = <number_of_instances>
    resource_preset_id = "<resource_ID>"
  }

  worker = {
    min_count          = <minimum_number_of_instances>
    max_count          = <maximum_number_of_instances>
    resource_preset_id = "<resource_ID>"
  }

  triggerer = {
    count              = <number_of_instances>
    resource_preset_id = "<resource_ID>"
  }

  pip_packages = ["list_of_pip_packages"]
  deb_packages = ["list_of_deb_packages"]

  code_sync = {
    s3 = {
      bucket = "<bucket_name>"
    }
  }

  deletion_protection = <deletion_protection>

  lockbox_secrets_backend = {
    enabled = <usage_of_secrets>
  }

  airflow_config = {
    <configuration_section> = {
      <key> = "<value>"
    }
  }

  logging = {
    enabled   = <use_of_logging>
    folder_id = "<folder_ID>"
    min_level = "<logging_level>"
  }
}

resource "yandex_vpc_network" "<network_name>" { name = "<network_name>" }

resource "yandex_vpc_subnet" "<subnet_name>" {
  name           = "<subnet_name>"
  zone           = "<availability_zone>"
  network_id     = "<network_ID>"
  v4_cidr_blocks = ["<range>"]
}
```
Where:
- name: Cluster name.
- description: Cluster description.
- labels: List of labels. Provide labels in <key> = "<value>" format.
- admin_password: Admin user password. The password must be not less than 8 characters long and contain at least:
  - One uppercase letter
  - One lowercase letter
  - One number
  - One special character
- service_account_id: Service account ID.
- subnet_ids: Subnet IDs list.
  
  Note
  
  Once a cluster is created, you cannot change its subnets.
- security_group_ids: List of security group IDs.
- webserver, scheduler, worker, triggerer: Managed Service for Apache Airflow™ component configuration:
  - count: Number of instances in the cluster for the web server, scheduler, and Triggerer.
  - min_count, max_count: Minimum and maximum number of instances in the cluster for the worker.
  - resource_preset_id: ID of the computing resources of the web server, scheduler, worker, and Triggerer. The possible values are:
    - c1-m2: 1 vCPU, 2 GB RAM
    - c1-m4: 1 vCPU, 4 GB RAM
    - c2-m4: 2 vCPUs, 4 GB RAM
    - c2-m8: 2 vCPUs, 8 GB RAM
    - c4-m8: 4 vCPUs, 8 GB RAM
    - c4-m16: 4 vCPUs, 16 GB RAM
    - c8-m16: 8 vCPUs, 16 GB RAM
    - c8-m32: 8 vCPUs, 32 GB RAM
- deb_packages, pip_packages: Lists of deb and pip packages enabling you to install additional libraries and applications in the cluster for running DAG files:
  
  If required, you can set version restrictions for the installed packages, for example:
```
pip_packages = ["pandas==2.0.2","scikit-learn>=1.0.0","clickhouse-driver~=0.2.0"]
```
  The package name format and version are defined by the install command: pip install for pip packages and apt install for deb packages.
- code_sync.s3.bucket: Name of the bucket to store DAG files in.
- deletion_protection: Enables cluster protection against accidental deletion. The possible values are true or false.
  
  Even if it is enabled, one can still connect to the cluster manually and delete it.
- lockbox_secrets_backend.enabled: Enables using secrets in Yandex Lockbox to store Apache Airflow™ configuration data, variables, and connection parameters. The possible values are true or false.
- airflow_config: Apache Airflow™ additional properties, e.g., core for configuration section, load_examples for key, and False for value.
- logging: Logging parameters:
  - enabled: Enables logging. Logs generated by Apache Airflow™ components will be sent to Yandex Cloud Logging. The possible values are true or false.
  - folder_id: Folder ID. Logs will be written to the default log group for this folder.
  - log_group_id: Custom log group ID. Logs will be written to this group.
    
    Specify one of the two parameters: folder_id or log_group_id.
  - min_level: Minimum logging level. Possible values: TRACE, DEBUG, INFO (default), WARN, ERROR, and FATAL.
  You can specify only one of the parameters: folder_id or log_group_id.
Make sure the settings are correct.
1. In the command line, navigate to the directory that contains the current Terraform configuration files defining the infrastructure.
2. Run this command:
```
terraform validate
```
  Terraform will show any errors found in your configuration files.
Confirm updating the resources.
1. Run this command to view the planned changes:
```
terraform plan
```
  If you described the configuration correctly, the terminal will display a list of the resources to update and their parameters. This is a verification step that does not apply changes to your resources.
2. If everything looks correct, apply the changes:
  1. Run this command:
```
terraform apply
```
  2. Confirm updating the resources.
  3. Wait for the operation to complete.

For more information, see the Terraform provider documentation.

To change the cluster settings:

Get an IAM token for API authentication and put it into the environment variable:
```
export IAM_TOKEN="<IAM_token>"
```
Create a file named body.json and add the following contents to it:
```
{
  "updateMask": "<list_of_parameters_to_update>",
  "name": "<cluster_name>",
  "description": "<cluster_description>",
  "labels": { <label_list> },
  "configSpec": {
    "airflow": {
      "config": { <list_of_properties> }
    },
    "webserver": {
      "count": "<number_of_instances>",
      "resources": {
        "resourcePresetId": "<resource_ID>"
      }
    },
    "scheduler": {
      "count": "<number_of_instances>",
      "resources": {
        "resourcePresetId": "<resource_ID>"
      }
    },
    "triggerer": {
      "count": "<number_of_instances>",
      "resources": {
        "resourcePresetId": "<resource_ID>"
      }
    },
    "worker": {
      "minCount": "<minimum_number_of_instances>",
      "maxCount": "<maximum_number_of_instances>",
      "resources": {
        "resourcePresetId": "<resource_ID>"
      }
    },
    "dependencies": {
      "pipPackages": [ <list_of_pip_packages> ],
      "debPackages": [ <list_of_deb_packages> ]
    },
    "lockbox": {
      "enabled": <use_of_logging>
    }
  },
  "codeSync": {
    "s3": {
      "bucket": "<bucket_name>"
    }
  },
  "networkSpec": {
    "securityGroupIds": [ <list_of_security_group_IDs> ]
  },
  "deletionProtection": <deletion_protection>,
  "serviceAccountId": "<service_account_ID>",
  "logging": {
    "enabled": <use_of_logging>,
    "minLevel": "<logging_level>",
    "folderId": "<folder_ID>"
  }
}
```
Where:
- updateMask: List of parameters to update as a single string, separated by commas.
  
  Warning
  
  When you update a cluster, all parameters of the object you are changing that were not explicitly provided in the request will be overriden by their defaults. To avoid this, list the settings you want to change in the updateMask parameter.
- name: Cluster name.
- description: Cluster description.
- labels: List of labels. Provide labels in "<key>": "<value>" format.
- config: Cluster configuration:
  - airflow.config: Apache Airflow™ additional properties. Provide them in "<configuration_section>.<key>": "<value>" format, for example:
```
"airflow": {
  "config": {
    "core.load_examples": "False"
  }
}
```
  - webserver, scheduler, triggerer, worker: Managed Service for Apache Airflow™ component configuration:
    - count: Number of instances in the cluster for the web server, scheduler, and Triggerer.
    - minCount, maxCount: Minimum and maximum number of instances in the cluster for the worker.
    - resources.resourcePresetId: ID of the computing resources of the web server, scheduler, worker, and Triggerer. The possible values are:
      - c1-m2: 1 vCPU, 2 GB RAM
      - c1-m4: 1 vCPU, 4 GB RAM
      - c2-m4: 2 vCPUs, 4 GB RAM
      - c2-m8: 2 vCPUs, 8 GB RAM
      - c4-m8: 4 vCPUs, 8 GB RAM
      - c4-m16: 4 vCPUs, 16 GB RAM
      - c8-m16: 8 vCPUs, 16 GB RAM
      - c8-m32: 8 vCPUs, 32 GB RAM
  - dependencies: Lists of packages enabling you to install additional libraries and applications for running DAG files in the cluster:
    - pipPackages: List of pip packages.
    - debPackages: List of deb packages.
    If required, you can set version restrictions for the installed packages, for example:
```
"dependencies": {
  "pipPackages": [
    "pandas==2.0.2",
    "scikit-learn>=1.0.0",
    "clickhouse-driver~=0.2.0"
  ]
}
```
    The package name format and version are defined by the install command: pip install for pip packages and apt install for deb packages.
  - lockbox.enabled: Enables using secrets in Yandex Lockbox to store Apache Airflow™ configuration data, variables, and connection parameters. The possible values are true or false.
- network.securityGroupIds: List of security group IDs.
- codeSync.s3.bucket: Name of the bucket to store DAG files in.
- deletionProtection: Enables cluster protection against accidental deletion. The possible values are true or false.
  
  Even if it is enabled, one can still connect to the cluster manually and delete it.
- serviceAccountId: ID of the service account with the managed-airflow.integrationProvider role. The cluster will thus get the permissions it needs to work with user resources. For more information, see Impersonation.
  
  To update a service account in a Managed Service for Apache Airflow™ cluster, assign the iam.serviceAccounts.user role or higher to your Yandex Cloud account.
  
  Warning
  
  If the cluster already uses a service account to access objects from Object Storage, then changing it to a different service account may make these objects unavailable and interrupt the cluster operation. Before changing the service account settings, make sure that the cluster doesn't use the objects in question.
- logging: Logging parameters:
  - enabled: Enables logging. Logs generated by Apache Airflow™ components will be sent to Yandex Cloud Logging. The possible values are true or false.
  - minLevel: Minimum logging level. Possible values: TRACE, DEBUG, INFO, WARN, ERROR, and FATAL.
  - folderId: Folder ID. Logs will be written to the default log group for this folder.
  - logGroupId: Custom log group ID. Logs will be written to this group.
    
    Specify one of the two parameters: folderId or logGroupId.

Use the Cluster.update method and send the following request, e.g., via cURL:

curl \
    --request PATCH \
    --header "Authorization: Bearer $IAM_TOKEN" \
    --url 'https://airflow.api.cloud.yandex.net/managed-airflow/v1/clusters/<cluster_ID>'
    --data '@body.json'

You can request the cluster ID with the list of clusters in the folder.

View the server response to make sure the request was successful.

To change the cluster settings:

Get an IAM token for API authentication and put it into the environment variable:
```
export IAM_TOKEN="<IAM_token>"
```
Clone the cloudapi repository:
```
cd ~/ && git clone --depth=1 https://github.com/yandex-cloud/cloudapi
```
Below, we assume the repository contents are stored in the ~/cloudapi/ directory.
Create a file named body.json and add the following contents to it:
```
{
  "cluster_id": "<cluster_ID>",
  "update_mask": "<list_of_parameters_to_update>",
  "name": "<cluster_name>",
  "description": "<cluster_description>",
  "labels": { <label_list> },
  "config_spec": {
    "airflow": {
      "config": { <list_of_properties> }
    },
    "webserver": {
      "count": "<number_of_instances>",
      "resources": {
        "resource_preset_id": "<resource_ID>"
      }
    },
    "scheduler": {
      "count": "<number_of_instances>",
      "resources": {
        "resource_preset_id": "<resource_ID>"
      }
    },
    "triggerer": {
      "count": "<number_of_instances>",
      "resources": {
        "resource_preset_id": "<resource_ID>"
      }
    },
    "worker": {
      "min_count": "<minimum_number_of_instances>",
      "max_count": "<maximum_number_of_instances>",
      "resources": {
        "resource_preset_id": "<resource_ID>"
      }
    },
    "dependencies": {
      "pip_packages": [ <list_of_pip_packages> ],
      "deb_packages": [ <list_of_deb_packages> ]
    },
    "lockbox": {
      "enabled": <use_of_logging>
    }
  },
  "code_sync": {
    "s3": {
      "bucket": "<bucket_name>"
    }
  },
  "network_spec": {
    "security_group_ids": [ <list_of_security_group_IDs> ]
  },
  "deletion_protection": <deletion_protection>,
  "service_account_id": "<service_account_ID>",
  "logging": {
    "enabled": <use_of_logging>,
    "min_level": "<logging_level>",
    "folder_id": "<folder_ID>"
  }
}
```
Where:
- cluster_id: Cluster ID. You can request it with the list of clusters in a folder.
- update_mask: List of parameters to update as an array of paths[] strings.
  Format for listing settings
  "update_mask": { "paths": [ "<setting_1>", "<setting_2>", ... "<setting_N>" ] }
  Warning
  
  When you update a cluster, all parameters of the object you are changing that were not explicitly provided in the request will be overriden by their defaults. To avoid this, list the settings you want to change in the update_mask parameter.
- name: Cluster name.
- description: Cluster description.
- labels: List of labels. Provide labels in "<key>": "<value>" format.
- config_spec: Cluster configuration:
  - airflow.config: Apache Airflow™ additional properties. Provide them in "<configuration_section>.<key>": "<value>" format, for example:
```
"airflow": {
  "config": {
    "core.load_examples": "False"
  }
}
```
  - webserver, scheduler, triggerer, worker: Managed Service for Apache Airflow™ component configuration:
    - count: Number of instances in the cluster for the web server, scheduler, and Triggerer.
    - min_count, max_count: Minimum and maximum number of instances in the cluster for the worker.
    - resources.resource_preset_id: ID of the computing resources of the web server, scheduler, worker, and Triggerer. The possible values are:
      - c1-m2: 1 vCPU, 2 GB RAM
      - c1-m4: 1 vCPU, 4 GB RAM
      - c2-m4: 2 vCPUs, 4 GB RAM
      - c2-m8: 2 vCPUs, 8 GB RAM
      - c4-m8: 4 vCPUs, 8 GB RAM
      - c4-m16: 4 vCPUs, 16 GB RAM
      - c8-m16: 8 vCPUs, 16 GB RAM
      - c8-m32: 8 vCPUs, 32 GB RAM
  - dependencies: Lists of packages enabling you to install additional libraries and applications for running DAG files in the cluster:
    - pip_packages: List of pip packages.
    - deb_packages: List of deb packages.
    If required, you can set version restrictions for the installed packages, for example:
```
"dependencies": {
  "pip_packages": [
    "pandas==2.0.2",
    "scikit-learn>=1.0.0",
    "clickhouse-driver~=0.2.0"
  ]
}
```
    The package name format and version are defined by the install command: pip install for pip packages and apt install for deb packages.
  - lockbox.enabled: Enables using secrets in Yandex Lockbox to store Apache Airflow™ configuration data, variables, and connection parameters. The possible values are true or false.
- network_spec.security_group_ids: List of security group IDs.
- code_sync.s3.bucket: Name of the bucket to store DAG files in.
- deletion_protection: Enables cluster protection against accidental deletion. The possible values are true or false.
  
  Even if it is enabled, one can still connect to the cluster manually and delete it.
- service_account_id: ID of the service account with the managed-airflow.integrationProvider role. The cluster will thus get the permissions it needs to work with user resources. For more information, see Impersonation.
  
  To update a service account in a Managed Service for Apache Airflow™ cluster, assign the iam.serviceAccounts.user role or higher to your Yandex Cloud account.
  
  Warning
  
  If the cluster already uses a service account to access objects from Object Storage, then changing it to a different service account may make these objects unavailable and interrupt the cluster operation. Before changing the service account settings, make sure that the cluster doesn't use the objects in question.
- logging: Logging parameters:
  - enabled: Enables logging. Logs generated by Apache Airflow™ components will be sent to Yandex Cloud Logging. The possible values are true or false.
  - min_level: Minimum logging level. Possible values: TRACE, DEBUG, INFO, WARN, ERROR, and FATAL.
  - folder_id: Folder ID. Logs will be written to the default log group for this folder.
  - log_group_id: Custom log group ID. Logs will be written to this group.
    
    Specify either folder_id or log_group_id.

Use the ClusterService/Update call and send the following request, e.g., via gRPCurl:

grpcurl \
    -format json \
    -import-path ~/cloudapi/ \
    -import-path ~/cloudapi/third_party/googleapis/ \
    -proto ~/cloudapi/yandex/cloud/airflow/v1/cluster_service.proto \
    -rpc-header "Authorization: Bearer $IAM_TOKEN" \
    -d @ \
    airflow.api.cloud.yandex.net:443 \
    yandex.cloud.airflow.v1.ClusterService.Update \
    < body.json

View the server response to make sure the request was successful.

Updating an Apache Airflow™ cluster

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