#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""
Example Airflow DAG for Google Kubernetes Engine.
"""
import os
from airflow import models
from airflow.operators.bash import BashOperator
from airflow.providers.google.cloud.operators.kubernetes_engine import (
GKECreateClusterOperator,
GKEDeleteClusterOperator,
GKEStartPodOperator,
)
from airflow.utils.dates import days_ago
GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project")
GCP_LOCATION = os.environ.get("GCP_GKE_LOCATION", "europe-north1-a")
CLUSTER_NAME = os.environ.get("GCP_GKE_CLUSTER_NAME", "cluster-name")
# [START howto_operator_gcp_gke_create_cluster_definition]
CLUSTER = {"name": CLUSTER_NAME, "initial_node_count": 1}
# [END howto_operator_gcp_gke_create_cluster_definition]
with models.DAG(
"example_gcp_gke",
schedule_interval='@once', # Override to match your needs
start_date=days_ago(1),
tags=['example'],
) as dag:
# [START howto_operator_gke_create_cluster]
create_cluster = GKECreateClusterOperator(
task_id="create_cluster",
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
body=CLUSTER,
)
# [END howto_operator_gke_create_cluster]
pod_task = GKEStartPodOperator(
task_id="pod_task",
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
cluster_name=CLUSTER_NAME,
namespace="default",
image="perl",
name="test-pod",
in_cluster=False,
)
# [START howto_operator_gke_start_pod_xcom]
pod_task_xcom = GKEStartPodOperator(
task_id="pod_task_xcom",
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
cluster_name=CLUSTER_NAME,
do_xcom_push=True,
namespace="default",
image="alpine",
cmds=["sh", "-c", 'mkdir -p /airflow/xcom/;echo \'[1,2,3,4]\' > /airflow/xcom/return.json'],
name="test-pod-xcom",
in_cluster=False,
)
# [END howto_operator_gke_start_pod_xcom]
# [START howto_operator_gke_xcom_result]
pod_task_xcom_result = BashOperator(
bash_command="echo \"{{ task_instance.xcom_pull('pod_task_xcom')[0] }}\"",
task_id="pod_task_xcom_result",
)
# [END howto_operator_gke_xcom_result]
# [START howto_operator_gke_delete_cluster]
delete_cluster = GKEDeleteClusterOperator(
task_id="delete_cluster",
name=CLUSTER_NAME,
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
)
# [END howto_operator_gke_delete_cluster]
create_cluster >> pod_task >> delete_cluster
create_cluster >> pod_task_xcom >> delete_cluster
pod_task_xcom >> pod_task_xcom_result