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"""
Example Airflow DAG for Google Cloud Managed Service for Apache Kafka testing Cluster operations.
"""
from __future__ import annotations
import os
from datetime import datetime
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.managed_kafka import (
ManagedKafkaCreateClusterOperator,
ManagedKafkaDeleteClusterOperator,
ManagedKafkaGetClusterOperator,
ManagedKafkaListClustersOperator,
ManagedKafkaUpdateClusterOperator,
)
try:
from airflow.sdk import TriggerRule
except ImportError:
# Compatibility for Airflow < 3.1
from airflow.utils.trigger_rule import TriggerRule # type: ignore[no-redef,attr-defined]
ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "default")
DAG_ID = "managed_kafka_cluster_operations"
LOCATION = "us-central1"
CLUSTER_ID = f"cluster-kafka-cluster-{ENV_ID}".replace("_", "-")
CLUSTER_CONF = {
"gcp_config": {
"access_config": {
"network_configs": [
{"subnet": f"projects/{PROJECT_ID}/regions/{LOCATION}/subnetworks/default"},
],
},
},
"capacity_config": {
"vcpu_count": 3,
"memory_bytes": 3221225472,
},
}
CLUSTER_TO_UPDATE = {
"capacity_config": {
"vcpu_count": 3,
"memory_bytes": 8589934592,
}
}
CLUSTER_UPDATE_MASK = {"paths": ["capacity_config"]}
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "managed_kafka", "cluster"],
) as dag:
# [START how_to_cloud_managed_kafka_create_cluster_operator]
create_cluster = ManagedKafkaCreateClusterOperator(
task_id="create_cluster",
project_id=PROJECT_ID,
location=LOCATION,
cluster=CLUSTER_CONF,
cluster_id=CLUSTER_ID,
)
# [END how_to_cloud_managed_kafka_create_cluster_operator]
# [START how_to_cloud_managed_kafka_update_cluster_operator]
update_cluster = ManagedKafkaUpdateClusterOperator(
task_id="update_cluster",
project_id=PROJECT_ID,
location=LOCATION,
cluster_id=CLUSTER_ID,
cluster=CLUSTER_TO_UPDATE,
update_mask=CLUSTER_UPDATE_MASK,
)
# [END how_to_cloud_managed_kafka_update_cluster_operator]
# [START how_to_cloud_managed_kafka_get_cluster_operator]
get_cluster = ManagedKafkaGetClusterOperator(
task_id="get_cluster",
project_id=PROJECT_ID,
location=LOCATION,
cluster_id=CLUSTER_ID,
)
# [END how_to_cloud_managed_kafka_get_cluster_operator]
# [START how_to_cloud_managed_kafka_delete_cluster_operator]
delete_cluster = ManagedKafkaDeleteClusterOperator(
task_id="delete_cluster",
project_id=PROJECT_ID,
location=LOCATION,
cluster_id=CLUSTER_ID,
trigger_rule=TriggerRule.ALL_DONE,
)
# [END how_to_cloud_managed_kafka_delete_cluster_operator]
# [START how_to_cloud_managed_kafka_list_cluster_operator]
list_clusters = ManagedKafkaListClustersOperator(
task_id="list_clusters",
project_id=PROJECT_ID,
location=LOCATION,
)
# [END how_to_cloud_managed_kafka_list_cluster_operator]
(
[
create_cluster >> update_cluster >> get_cluster >> delete_cluster,
list_clusters,
]
)
# ### Everything below this line is not part of example ###
# ### Just for system tests purpose ###
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)
test_run = get_test_run(dag)