airflow.providers.google.cloud.operators.kubernetes_engine

This module contains Google Kubernetes Engine operators.

Module Contents

Classes

GKEDeleteClusterOperator

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

GKECreateClusterOperator

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

GKEStartPodOperator

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

Attributes

KUBE_CONFIG_ENV_VAR

airflow.providers.google.cloud.operators.kubernetes_engine.KUBE_CONFIG_ENV_VAR = 'KUBECONFIG'[source]
class airflow.providers.google.cloud.operators.kubernetes_engine.GKEDeleteClusterOperator(*, name, location, project_id=None, gcp_conn_id='google_cloud_default', api_version='v2', impersonation_chain=None, deferrable=conf.getboolean('operators', 'default_deferrable', fallback=False), poll_interval=10, **kwargs)[source]

Bases: airflow.providers.google.cloud.operators.cloud_base.GoogleCloudBaseOperator

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 information on how to use this operator, take a look at the guide: Delete GKE cluster

Parameters
  • project_id (str | None) – 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 Kubernetes Engine zone or region in which the cluster resides.

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

  • api_version (str) – The api version to use

  • impersonation_chain (str | Sequence[str] | None) – Optional 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).

  • deferrable (bool) – Run operator in the deferrable mode.

  • poll_interval (int) – Interval size which defines how often operation status is checked.

template_fields: Sequence[str] = ('project_id', 'gcp_conn_id', 'name', 'location', 'api_version', 'impersonation_chain')[source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

execute_complete(context, event)[source]

Method to be executed after trigger job is done.

class airflow.providers.google.cloud.operators.kubernetes_engine.GKECreateClusterOperator(*, location, body, project_id=None, gcp_conn_id='google_cloud_default', api_version='v2', impersonation_chain=None, poll_interval=10, deferrable=conf.getboolean('operators', 'default_deferrable', fallback=False), **kwargs)[source]

Bases: airflow.providers.google.cloud.operators.cloud_base.GoogleCloudBaseOperator

Create a Google Kubernetes Engine Cluster of specified dimensions and 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

See also

For more information on how to use this operator, take a look at the guide: Create GKE cluster

Parameters
  • project_id (str | None) – The Google Developers Console [project ID or project number]

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

  • body (dict | 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.

  • api_version (str) – The api version to use

  • impersonation_chain (str | Sequence[str] | None) – Optional 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).

  • deferrable (bool) – Run operator in the deferrable mode.

  • poll_interval (int) – Interval size which defines how often operation status is checked.

template_fields: Sequence[str] = ('project_id', 'gcp_conn_id', 'location', 'api_version', 'body', 'impersonation_chain')[source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

execute_complete(context, event)[source]
class airflow.providers.google.cloud.operators.kubernetes_engine.GKEStartPodOperator(*, location, cluster_name, use_internal_ip=False, project_id=None, gcp_conn_id='google_cloud_default', impersonation_chain=None, regional=None, on_finish_action=None, is_delete_operator_pod=None, **kwargs)[source]

Bases: airflow.providers.cncf.kubernetes.operators.pod.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 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

See also

For more detail about Kubernetes Engine authentication have a look at the reference: https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-access-for-kubectl#internal_ip

See also

For more information on how to use this operator, take a look at the guide: Run a Pod on a GKE cluster

Parameters
  • location (str) – The name of the Google Kubernetes Engine zone or region 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

  • use_internal_ip (bool) – Use the internal IP address as the endpoint.

  • project_id (str | None) – The Google Developers Console project id

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

  • impersonation_chain (str | Sequence[str] | None) – Optional service account to impersonate using short-term credentials, or 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).

  • regional (bool | None) – The location param is region name.

  • deferrable – Run operator in the deferrable mode.

  • on_finish_action (str | None) – What to do when the pod reaches its final state, or the execution is interrupted. If “delete_pod”, the pod will be deleted regardless its state; if “delete_succeeded_pod”, only succeeded pod will be deleted. You can set to “keep_pod” to keep the pod. Current default is keep_pod, but this will be changed in the next major release of this provider.

  • is_delete_operator_pod (bool | None) – What to do when the pod reaches its final state, or the execution is interrupted. If True, delete the pod; if False, leave the pod. Current default is False, but this will be changed in the next major release of this provider. Deprecated - use on_finish_action instead.

template_fields: Sequence[str][source]
static get_gke_config_file()[source]
cluster_hook()[source]
hook()[source]
execute(context)[source]

Executes process of creating pod and executing provided command inside it.

fetch_cluster_info()[source]

Fetches cluster info for connecting to it.

invoke_defer_method()[source]

Method to easily redefine triggers which are being used in child classes.

execute_complete(context, event, **kwargs)[source]

Was this entry helpful?