Operator for managing a Google Cloud ML Engine model.

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Last Updated: Feb. 25, 2023

Access Instructions

Install the Google provider package into your Airflow environment.

Import the module into your DAG file and instantiate it with your desired params.


modelRequiredA dictionary containing the information about the model. If the operation is create, then the model parameter should contain all the information about this model such as name. If the operation is get, the model parameter should contain the name of the model.
operationThe operation to perform. Available operations are: create: Creates a new model as provided by the model parameter. get: Gets a particular model where the name is specified in model.
project_idThe Google Cloud project name to which MLEngine model belongs. If set to None or missing, the default project_id from the Google Cloud connection is used. (templated)
gcp_conn_idThe connection ID to use when fetching connection info.
delegate_toThe account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled.
impersonation_chainOptional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated).


Operator for managing a Google Cloud ML Engine model.


This operator is deprecated. Consider using operators for specific operations: MLEngineCreateModelOperator, MLEngineGetModelOperator.

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