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# 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.
from __future__ import annotations
from datetime import datetime
from operator import itemgetter
import boto3
from airflow import DAG
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.providers.amazon.aws.operators.ec2 import (
EC2CreateInstanceOperator,
EC2StartInstanceOperator,
EC2StopInstanceOperator,
EC2TerminateInstanceOperator,
)
from airflow.providers.amazon.aws.sensors.ec2 import EC2InstanceStateSensor
from airflow.utils.trigger_rule import TriggerRule
from tests.system.providers.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
[docs]sys_test_context_task = SystemTestContextBuilder().build()
@task
[docs]def get_latest_ami_id():
"""Returns the AMI ID of the most recently-created Amazon Linux image"""
# Amazon is retiring AL2 in 2023 and replacing it with Amazon Linux 2022.
# This image prefix should be futureproof, but may need adjusting depending
# on how they name the new images. This page should have AL2022 info when
# it comes available: https://aws.amazon.com/linux/amazon-linux-2022/faqs/
image_prefix = "Amazon Linux*"
images = boto3.client("ec2").describe_images(
Filters=[
{"Name": "description", "Values": [image_prefix]},
{"Name": "architecture", "Values": ["arm64"]},
],
Owners=["amazon"],
)
# Sort on CreationDate
sorted_images = sorted(images["Images"], key=itemgetter("CreationDate"), reverse=True)
return sorted_images[0]["ImageId"]
@task
[docs]def create_key_pair(key_name: str):
client = boto3.client("ec2")
key_pair_id = client.create_key_pair(KeyName=key_name)["KeyName"]
# Creating the key takes a very short but measurable time, preventing race condition:
client.get_waiter("key_pair_exists").wait(KeyNames=[key_pair_id])
return key_pair_id
@task(trigger_rule=TriggerRule.ALL_DONE)
[docs]def delete_key_pair(key_pair_id: str):
boto3.client("ec2").delete_key_pair(KeyName=key_pair_id)
@task
[docs]def parse_response(instance_ids: list):
return instance_ids[0]
with DAG(
dag_id=DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
tags=["example"],
catchup=False,
) as dag:
[docs] test_context = sys_test_context_task()
env_id = test_context[ENV_ID_KEY]
instance_name = f"{env_id}-instance"
key_name = create_key_pair(key_name=f"{env_id}_key_pair")
image_id = get_latest_ami_id()
config = {
"InstanceType": "t4g.micro",
"KeyName": key_name,
"TagSpecifications": [
{"ResourceType": "instance", "Tags": [{"Key": "Name", "Value": instance_name}]}
],
# Use IMDSv2 for greater security, see the following doc for more details:
# https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/configuring-instance-metadata-service.html
"MetadataOptions": {"HttpEndpoint": "enabled", "HttpTokens": "required"},
}
# EC2CreateInstanceOperator creates and starts the EC2 instances. To test the EC2StartInstanceOperator,
# we will stop the instance, then start them again before terminating them.
# [START howto_operator_ec2_create_instance]
create_instance = EC2CreateInstanceOperator(
task_id="create_instance",
image_id=image_id,
max_count=1,
min_count=1,
config=config,
)
# [END howto_operator_ec2_create_instance]
create_instance.wait_for_completion = True
instance_id = parse_response(create_instance.output)
# [START howto_operator_ec2_stop_instance]
stop_instance = EC2StopInstanceOperator(
task_id="stop_instance",
instance_id=instance_id,
)
# [END howto_operator_ec2_stop_instance]
stop_instance.trigger_rule = TriggerRule.ALL_DONE
# [START howto_operator_ec2_start_instance]
start_instance = EC2StartInstanceOperator(
task_id="start_instance",
instance_id=instance_id,
)
# [END howto_operator_ec2_start_instance]
# [START howto_sensor_ec2_instance_state]
await_instance = EC2InstanceStateSensor(
task_id="await_instance",
instance_id=instance_id,
target_state="running",
)
# [END howto_sensor_ec2_instance_state]
# [START howto_operator_ec2_terminate_instance]
terminate_instance = EC2TerminateInstanceOperator(
task_id="terminate_instance",
instance_ids=instance_id,
wait_for_completion=True,
)
# [END howto_operator_ec2_terminate_instance]
terminate_instance.trigger_rule = TriggerRule.ALL_DONE
chain(
# TEST SETUP
test_context,
key_name,
image_id,
# TEST BODY
create_instance,
instance_id,
stop_instance,
start_instance,
await_instance,
terminate_instance,
# TEST TEARDOWN
delete_key_pair(key_name),
)
from tests.system.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.system.utils import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)
