Creating an Apache Airflow™ cluster

If you do not have the Yandex Cloud command line interface yet, install and initialize it.

The folder specified in the CLI profile is used by default. You can specify a different folder using the --folder-name or --folder-id parameter.

To create a Managed Service for Apache Airflow™ cluster:

1. View the description of the create cluster CLI command:

   yc managed-airflow cluster create --help
   

2. Specify cluster parameters in the create command (the list of supported parameters in the example is not exhaustive):

   yc managed-airflow cluster create \
      --name <cluster_name> \
      --description <cluster_description> \
      --labels <label_list> \
      --admin-password <administrator_password> \
      --service-account-id <service_account_ID> \
      --subnet-ids <subnet_IDs> \
      --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 \
      --airflow-config <list_of_properties> \
      --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 digit
     • One special character

   • --service-account-id: Service account ID.

   • --subnet-ids: List of subnet IDs.

   • --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 trigger.

     • min-count, max-count: Minimum and maximum number of instances in the cluster for the worker.

     • resource-preset-id: ID of the web server, scheduler, worker, and trigger computing resources. The possible values are:

       • c1-m4: 1 vCPU, 4 GB RAM.
       • c2-m8: 2 vCPUs, 8 GB RAM.
       • c4-m16: 4 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.

     With deletion protection enabled, you will still be able to manually connect to the cluster 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.
     • --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.

Terraform allows you to quickly create a cloud infrastructure in Yandex Cloud and manage it using configuration files. Configuration files store the infrastructure description in the HashiCorp Configuration Language (HCL). Terraform and its providers are distributed under the Business Source License.

For more information about the provider resources, see the documentation on the Terraform website or the mirror.

If you change the configuration files, Terraform automatically detects which part of your configuration is already deployed, and what should be added or removed.

If you don't have Terraform, install it and configure the Yandex Cloud provider.

To create a Managed Service for Apache Airflow™ cluster:

1. In the configuration file, describe the resources you are creating:

   • Managed Service for Apache Airflow™ cluster: Cluster description.

   • Network: Description of the cloud network where a cluster will be located. If you already have a suitable network, you don't have to describe it again.

   • Subnets: Description of the subnets to connect the cluster hosts to. If you already have suitable subnets, you don't have to describe them again.

   Here is an example of the configuration file structure:

   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 digit
     • One special character

   • service_account_id: Service account ID.

   • subnet_ids: List of subnet IDs.

   • 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 trigger.

     • min_count, max_count: Minimum and maximum number of instances in the cluster for the worker.

     • resource_preset_id: ID of the web server, scheduler, worker, and trigger computing resources. The possible values are:

       • c1-m4: 1 vCPU, 4 GB RAM.
       • c2-m8: 2 vCPUs, 8 GB RAM.
       • c4-m16: 4 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. Possible values: true or false.

     With deletion protection enabled, you will still be able to manually connect to the cluster and delete it.

   • lockbox_secrets_backend.enabled: Enables using secrets in Yandex Lockbox to store Apache Airflow™ configuration data, variables, and connection parameters. Possible values: 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. Possible values: 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.
     • 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.

2. Make sure the settings are correct.

   1. Using the command line, navigate to the folder that contains the up-to-date Terraform configuration files with an infrastructure plan.

   2. Run the command:

      terraform validate
      

      If there are errors in the configuration files, Terraform will point to them.

3. Create a Managed Service for Apache Airflow™ cluster.

   1. Run the command to view planned changes:

      terraform plan
      

      If the resource configuration descriptions are correct, the terminal will display a list of the resources to modify and their parameters. This is a test step. No resources are updated.

   2. If you are happy with the planned changes, apply them:

      1. Run the command:

         terraform apply
         

      2. Confirm the update of resources.

      3. Wait for the operation to complete.

   All the resources you need will then be created in the specified folder. You can check the new resources and their settings using the management console.

For more information, see the Terraform provider documentation.

1. Get an IAM token for API authentication and put it into the environment variable:

   export IAM_TOKEN="<IAM_token>"
   

2. Create a file named body.json and add the following contents to it:

   {
     "folderId": "<folder_ID>,
     "name": "<cluster_name>",
     "description": "<cluster_description>",
     "labels": { <label_list> },
     "config": {
       "versionId": "<Apache Airflow™>_version",
       "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": <logging_usage>
       }
     },
     "network": {
       "subnetIds": [ <list_of_subnet_IDs> ],
       "securityGroupIds": [ <list_of_security_group_IDs> ]
     },
     "codeSync": {
       "s3": {
         "bucket": "<bucket_name>"
       }
     },
     "deletionProtection": <deletion_protection>,
     "serviceAccountId": "<service_account_ID>",
     "logging": {
       "enabled": <logging_usage>,
       "minLevel": "<logging_level>",
       // Specify either `folderId` or `logGroupId`.
       "folderId": "<folder_ID>",
       "logGroupId": "<log_group_ID>",
     },
     "adminPassword": "<administrator_password>"
   }
   

   Where:

   • folderId: Folder ID. You can request it with a list of folders in the cloud.

   • name: Cluster name.

   • description: Cluster description.

   • labels: List of labels. Provide labels in "<key>": "<value>" format.

   • config: Cluster configuration:

     • versionId: Apache Airflow™ version.

     • airflow.config: Advanced Apache Airflow™ properties. Provide them in "<configuration_section>.<key>": "<value>" format, such as the following:

       "airflow": {
         "config": {
           "core.load_examples": "False"
         }
       }
       

     • webserver, scheduler, triggerer, and worker: Configuration of Managed Service for Apache Airflow™ components:

       • count: Number of instances in the cluster for the web server, scheduler, and trigger.

       • minCount and maxCount: Minimum and maximum number of instances in the cluster for the worker.

       • resources.resourcePresetId: ID of the web server, scheduler, worker, and trigger computing resources. The possible values are:

         • c1-m4 for 1 vCPU and 4 GB RAM
         • c2-m8 for 2 vCPUs and 8 GB RAM
         • c4-m16 for 4 vCPUs and 16 GB RAM
         • c8-m32 for 8 vCPUs and 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: Network settings:

     • subnetIds: List of subnet IDs.
     • 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.

     With deletion protection enabled, you will still be able to manually connect to the cluster and delete it.

   • serviceAccountId: ID of the previously created service account.

   • 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.

     You can only specify either folderId or logGroupId.

   • adminPassword: Admin user password. The password must be not less than 8 characters long and contain at least:

     • One uppercase letter
     • One lowercase letter
     • One digit
     • One special character

     Note

     Save the password locally or memorize it. The service does not show passwords after the registry is created.

3. Use the Cluster.create method and make a request, e.g., via cURL:

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

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

1. Get an IAM token for API authentication and put it into the environment variable:

   export IAM_TOKEN="<IAM_token>"
   

2. 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.

3. Create a file named body.json and add the following contents to it:

   {
     "folder_id": "<folder_ID>,
     "name": "<cluster_name>",
     "description": "<cluster_description>",
     "labels": { <label_list> },
     "config": {
       "version_id": "<Apache Airflow™>_version",
       "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": <logging_usage>
       }
     },
     "network": {
       "subnet_ids": [ <list_of_subnet_IDs> ],
       "security_group_ids": [ <list_of_security_group_IDs> ]
     },
     "code_sync": {
       "s3": {
         "bucket": "<bucket_name>"
       }
     },
     "deletion_protection": <deletion_protection>,
     "service_account_id": "<service_account_ID>",
     "logging": {
       "enabled": <logging_usage>,
       "min_level": "<logging_level>",
       // Specify either `folder_id` or `log_group_id`.
       "folder_id": "<folder_ID>",
       "log_group_id": "<log_group_ID>",
     },
     "admin_password": "<administrator_password>"
   }
   

   Where:

   • folder_id: Folder ID. You can request it with a list of folders in the cloud.

   • name: Cluster name.

   • description: Cluster description.

   • labels: List of labels. Provide labels in "<key>": "<value>" format.

   • config: Cluster configuration:

     • version_id: Apache Airflow™ version.

     • airflow.config: Advanced Apache Airflow™ properties. Provide them in "<configuration_section>.<key>": "<value>" format, such as the following:

       "airflow": {
         "config": {
           "core.load_examples": "False"
         }
       }
       

     • webserver, scheduler, triggerer, and worker: Configuration of Managed Service for Apache Airflow™ components:

       • count: Number of instances in the cluster for the web server, scheduler, and trigger.

       • min_count and max_count: Minimum and maximum number of instances in the cluster for the worker.

       • resources.resource_preset_id: ID of the web server, scheduler, worker, and trigger computing resources. The possible values are:

         • c1-m4 for 1 vCPU and 4 GB RAM
         • c2-m8 for 2 vCPUs and 8 GB RAM
         • c4-m16 for 4 vCPUs and 16 GB RAM
         • c8-m32 for 8 vCPUs and 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: Network settings:

     • subnet_ids: List of subnet IDs.
     • 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.

     With deletion protection enabled, you will still be able to manually connect to the cluster and delete it.

   • service_account_id: ID of the previously created service account.

   • 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.

     You can only specify either folder_id or log_group_id.

   • 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 digit
     • One special character

     Note

     Save the password locally or memorize it. The service does not show passwords after the registry is created.

4. Use the ClusterService/Create call and make a 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.Create \
       < body.json
   

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