#
# 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.
"""
from __future__ import annotations
import os
from datetime import datetime
from kubernetes.client.rest import ApiException
from airflow.models.dag import DAG
from airflow.providers.cncf.kubernetes.utils.container import container_is_running
from airflow.providers.cncf.kubernetes.utils.pod_manager import PodPhase
from airflow.providers.google.cloud.hooks.kubernetes_engine import GKEHook, GKEKubernetesHook
from airflow.providers.google.cloud.operators.kubernetes_engine import (
GKEClusterAuthDetails,
GKECreateClusterOperator,
GKECreateCustomResourceOperator,
GKEDeleteClusterOperator,
GKEDeleteCustomResourceOperator,
GKEPodExecOperator,
GKEStartPodOperator,
)
from airflow.providers.standard.operators.bash import BashOperator
try:
from airflow.sdk import TriggerRule, task
except ImportError:
# Compatibility for Airflow < 3.1
from airflow.decorators import task # type: ignore[attr-defined,no-redef]
from airflow.utils.trigger_rule import TriggerRule # type: ignore[no-redef,attr-defined]
from system.google import DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
from tests_common.test_utils.version_compat import AIRFLOW_V_3_0_PLUS
[docs]
ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]
DAG_ID = "kubernetes_engine"
[docs]
GCP_PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]
GCP_LOCATION = "europe-west1"
[docs]
CLUSTER_NAME_BASE = f"cluster-{DAG_ID}".replace("_", "-")
[docs]
CLUSTER_NAME_FULL = CLUSTER_NAME_BASE + f"-{ENV_ID}".replace("_", "-")
[docs]
CLUSTER_NAME = CLUSTER_NAME_BASE if len(CLUSTER_NAME_FULL) >= 33 else CLUSTER_NAME_FULL
[docs]
EXEC_POD_NAME = f"existing-pod-{ENV_ID}".replace("_", "-")
[docs]
EXEC_CONTAINER_NAME = "main"
[docs]
EXPECTED_EXEC_OUTPUT = "command executed in existing GKE Pod"
# [START howto_operator_gcp_gke_create_cluster_definition]
[docs]
CLUSTER = {"name": CLUSTER_NAME, "initial_node_count": 1, "autopilot": {"enabled": True}}
# [END howto_operator_gcp_gke_create_cluster_definition]
[docs]
EXEC_POD = f"""
apiVersion: v1
kind: Pod
metadata:
name: {EXEC_POD_NAME}
namespace: default
spec:
restartPolicy: Never
containers:
- name: {EXEC_CONTAINER_NAME}
image: busybox:1.38.0
command: ["sleep", "3600"]
"""
@task.sensor(poke_interval=10, timeout=300, mode="reschedule")
[docs]
def wait_for_running_exec_pod() -> bool:
cluster_hook = GKEHook(location=GCP_LOCATION)
cluster_url, ssl_ca_cert = GKEClusterAuthDetails(
cluster_name=CLUSTER_NAME,
project_id=GCP_PROJECT_ID,
use_internal_ip=False,
use_dns_endpoint=False,
cluster_hook=cluster_hook,
).fetch_cluster_info()
hook = GKEKubernetesHook(
gcp_conn_id="google_cloud_default",
cluster_url=cluster_url,
ssl_ca_cert=ssl_ca_cert,
)
try:
pod = hook.get_pod(name=EXEC_POD_NAME, namespace="default")
except ApiException as error:
if error.status == 404:
return False
raise
return bool(
pod.status and pod.status.phase == PodPhase.RUNNING and container_is_running(pod, EXEC_CONTAINER_NAME)
)
@task
[docs]
def verify_exec_output(output: str) -> None:
if output != EXPECTED_EXEC_OUTPUT:
raise ValueError(f"Unexpected command output: {output!r}")
with DAG(
DAG_ID,
schedule="@once", # Override to match your needs
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example"],
) as dag:
# [START howto_operator_gke_create_cluster]
[docs]
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,
on_finish_action="delete_pod",
)
# [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,
on_finish_action="delete_pod",
)
# [END howto_operator_gke_start_pod_xcom]
create_exec_pod = GKECreateCustomResourceOperator(
task_id="create_exec_pod",
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
cluster_name=CLUSTER_NAME,
yaml_conf=EXEC_POD,
)
exec_pod_is_running = wait_for_running_exec_pod()
# [START howto_operator_gke_pod_exec]
exec_in_existing_pod = GKEPodExecOperator(
task_id="exec_in_existing_pod",
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
cluster_name=CLUSTER_NAME,
pod_name=EXEC_POD_NAME,
namespace="default",
container_name=EXEC_CONTAINER_NAME,
command=["sh", "-c", f"printf '{EXPECTED_EXEC_OUTPUT}'"],
do_xcom_push=True,
)
# [END howto_operator_gke_pod_exec]
exec_output_is_valid = verify_exec_output(exec_in_existing_pod.output)
delete_exec_pod = GKEDeleteCustomResourceOperator(
task_id="delete_exec_pod",
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
cluster_name=CLUSTER_NAME,
yaml_conf=EXEC_POD,
trigger_rule=TriggerRule.ALL_DONE,
)
# [START howto_operator_gke_xcom_result]
pod_task_xcom_result = BashOperator(
task_id="pod_task_xcom_result",
bash_command="""
{% if params.airflow_v3 %}
echo "{{ task_instance.xcom_pull('pod_task_xcom') }}"
{% else %}
echo "{{ task_instance.xcom_pull('pod_task_xcom')[0] }}"
{% endif %}
""",
params={"airflow_v3": AIRFLOW_V_3_0_PLUS},
)
# [END howto_operator_gke_xcom_result]
# [START howto_operator_gke_delete_cluster]
delete_cluster = GKEDeleteClusterOperator(
task_id="delete_cluster",
cluster_name=CLUSTER_NAME,
project_id=GCP_PROJECT_ID,
location=GCP_LOCATION,
)
# [END howto_operator_gke_delete_cluster]
delete_cluster.trigger_rule = TriggerRule.ALL_DONE
create_cluster >> [pod_task, pod_task_xcom] >> delete_cluster
(
create_cluster
>> create_exec_pod
>> exec_pod_is_running
>> exec_in_existing_pod
>> exec_output_is_valid
>> delete_exec_pod
>> delete_cluster
)
pod_task_xcom >> pod_task_xcom_result
from tests_common.test_utils.watcher import watcher
# This test needs watcher in order to properly mark success/failure
# when "teardown" task with trigger rule is part of the DAG
list(dag.tasks) >> watcher()
from tests_common.test_utils.system_tests import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: contributing-docs/testing/system_tests.rst)
[docs]
test_run = get_test_run(dag)