airflow.contrib.operators.gcp_container_operator

Module Contents

class airflow.contrib.operators.gcp_container_operator.GKEClusterDeleteOperator(project_id, name, location, gcp_conn_id='google_cloud_default', api_version='v2', *args, **kwargs)

Bases:airflow.models.BaseOperator

Deletes the cluster, including the Kubernetes endpoint and all worker nodes.

To delete a certain cluster, you must specify the project_id, the name of the cluster, the location that the cluster is in, and the task_id.

Operator Creation:

operator = GKEClusterDeleteOperator(
            task_id='cluster_delete',
            project_id='my-project',
            location='cluster-location'
            name='cluster-name')

See also

For more detail about deleting clusters have a look at the reference: https://google-cloud-python.readthedocs.io/en/latest/container/gapic/v1/api.html#google.cloud.container_v1.ClusterManagerClient.delete_cluster

Parameters

• project_id (str) – The Google Developers Console [project ID or project number]

• name (str) – The name of the resource to delete, in this case cluster name

• location (str) – The name of the Google Compute Engine zone in which the cluster resides.

• gcp_conn_id (str) – The connection ID to use connecting to Google Cloud Platform.

• api_version (str) – The api version to use

template_fields = ['project_id', 'gcp_conn_id', 'name', 'location', 'api_version']

_check_input(self)

execute(self, context)

class airflow.contrib.operators.gcp_container_operator.GKEClusterCreateOperator(project_id, location, body=None, gcp_conn_id='google_cloud_default', api_version='v2', *args, **kwargs)

Bases:airflow.models.BaseOperator

Create a Google Kubernetes Engine Cluster of specified dimensions The operator will wait until the cluster is created.

The minimum required to define a cluster to create is:

dict() ::

cluster_def = {‘name’: ‘my-cluster-name’,

‘initial_node_count’: 1}

or

Cluster proto ::

from google.cloud.container_v1.types import Cluster

cluster_def = Cluster(name=’my-cluster-name’, initial_node_count=1)

Operator Creation:

operator = GKEClusterCreateOperator(
            task_id='cluster_create',
            project_id='my-project',
            location='my-location'
            body=cluster_def)

See also

For more detail on about creating clusters have a look at the reference: google.cloud.container_v1.types.Cluster

Parameters

• project_id (str) – The Google Developers Console [project ID or project number]

• location (str) – The name of the Google Compute Engine zone in which the cluster resides.

• body (dict or google.cloud.container_v1.types.Cluster) – The Cluster definition to create, can be protobuf or python dict, if dict it must match protobuf message Cluster

• gcp_conn_id (str) – The connection ID to use connecting to Google Cloud Platform.

• api_version (str) – The api version to use

template_fields = ['project_id', 'gcp_conn_id', 'location', 'api_version', 'body']

_check_input(self)

execute(self, context)

airflow.contrib.operators.gcp_container_operator.KUBE_CONFIG_ENV_VAR = KUBECONFIG

airflow.contrib.operators.gcp_container_operator.G_APP_CRED = GOOGLE_APPLICATION_CREDENTIALS

class airflow.contrib.operators.gcp_container_operator.GKEPodOperator(project_id, location, cluster_name, gcp_conn_id='google_cloud_default', *args, **kwargs)

Bases:airflow.contrib.operators.kubernetes_pod_operator.KubernetesPodOperator

Executes a task in a Kubernetes pod in the specified Google Kubernetes Engine cluster

This Operator assumes that the system has gcloud installed and either has working default application credentials or has configured a connection id with a service account.

The minimum required to define a cluster to create are the variables task_id, project_id, location, cluster_name, name, namespace, and image

Operator Creation:

operator = GKEPodOperator(task_id='pod_op',
                          project_id='my-project',
                          location='us-central1-a',
                          cluster_name='my-cluster-name',
                          name='task-name',
                          namespace='default',
                          image='perl')

See also

For more detail about application authentication have a look at the reference: https://cloud.google.com/docs/authentication/production#providing_credentials_to_your_application

Parameters

• project_id (str) – The Google Developers Console project id

• location (str) – The name of the Google Kubernetes Engine zone in which the cluster resides, e.g. ‘us-central1-a’

• cluster_name (str) – The name of the Google Kubernetes Engine cluster the pod should be spawned in

• gcp_conn_id (str) – The google cloud connection id to use. This allows for users to specify a service account.

template_fields

execute(self, context)

_set_env_from_extras(self, extras)

Sets the environment variable GOOGLE_APPLICATION_CREDENTIALS with either:

• The path to the keyfile from the specified connection id

• A generated file’s path if the user specified JSON in the connection id. The

  file is assumed to be deleted after the process dies due to how mkstemp() works.

The environment variable is used inside the gcloud command to determine correct service account to use.

_get_field(self, extras, field, default=None)

Fetches a field from extras, and returns it. This is some Airflow magic. The google_cloud_platform hook type adds custom UI elements to the hook page, which allow admins to specify service_account, key_path, etc. They get formatted as shown below.