with DAG(
dag_id='to-publish-manuals-templated',
schedule_interval=None,
start_date=days_ago(2),
max_active_runs=1,
tags=['example', 'templated'],
# render_template_as_native_obj=True is what converts the Jinja to Python objects, instead of a string.
render_template_as_native_obj=True,
) as dag:
# Create an Amazon EKS Cluster control plane without attaching a compute service.
create_cluster = EKSCreateClusterOperator(
task_id='create_eks_cluster',
compute=None,
cluster_name="{{ dag_run.conf['cluster_name'] }}",
cluster_role_arn="{{ dag_run.conf['cluster_role_arn'] }}",
resources_vpc_config="{{ dag_run.conf['resources_vpc_config'] }}",
)
await_create_cluster = EKSClusterStateSensor(
task_id='wait_for_create_cluster',
cluster_name="{{ dag_run.conf['cluster_name'] }}",
target_state=ClusterStates.ACTIVE,
)
create_nodegroup = EKSCreateNodegroupOperator(
task_id='create_eks_nodegroup',
cluster_name="{{ dag_run.conf['cluster_name'] }}",
nodegroup_name="{{ dag_run.conf['nodegroup_name'] }}",
nodegroup_subnets="{{ dag_run.conf['nodegroup_subnets'] }}",
dag_id='example_eks_using_defaults_dag',
default_args={'cluster_name': CLUSTER_NAME},
schedule_interval=None,
start_date=datetime(2021, 1, 1),
max_active_runs=1,
tags=['example'],
) as dag:
# [START howto_operator_eks_create_cluster_with_nodegroup]
# Create an Amazon EKS cluster control plane and an EKS nodegroup compute platform in one step.
create_cluster_and_nodegroup = EKSCreateClusterOperator(
task_id='create_eks_cluster_and_nodegroup',
nodegroup_name=NODEGROUP_NAME,
cluster_role_arn=ROLE_ARN,
nodegroup_role_arn=ROLE_ARN,
# Opting to use the same ARN for the cluster and the nodegroup here,
# but a different ARN could be configured and passed if desired.
resources_vpc_config=VPC_CONFIG,
# Compute defaults to 'nodegroup' but is called out here for the purposed of the example.
compute='nodegroup',
)
# [END howto_operator_eks_create_cluster_with_nodegroup]
await_create_nodegroup = EKSNodegroupStateSensor(
task_id='wait_for_create_nodegroup',
nodegroup_name=NODEGROUP_NAME,
target_state=NodegroupStates.ACTIVE,
)
start_pod = EKSPodOperator(
task_id="run_pod",
with DAG(
dag_id='example_eks_with_fargate_profile_dag',
default_args={'cluster_name': CLUSTER_NAME},
schedule_interval=None,
start_date=datetime(2021, 1, 1),
catchup=False,
max_active_runs=1,
tags=['example'],
) as dag:
# Create an Amazon EKS Cluster control plane without attaching a compute service.
create_cluster = EKSCreateClusterOperator(
task_id='create_eks_cluster',
cluster_role_arn=ROLE_ARN,
resources_vpc_config=VPC_CONFIG,
compute=None,
)
await_create_cluster = EKSClusterStateSensor(
task_id='wait_for_create_cluster',
target_state=ClusterStates.ACTIVE,
)
# [START howto_operator_eks_create_fargate_profile]
create_fargate_profile = EKSCreateFargateProfileOperator(
task_id='create_eks_fargate_profile',
pod_execution_role_arn=ROLE_ARN,
fargate_profile_name=FARGATE_PROFILE_NAME,
selectors=SELECTORS,
)
with DAG(
dag_id='example-create-cluster-and-fargate-all-in-one',
default_args={'cluster_name': CLUSTER_NAME},
schedule_interval=None,
start_date=datetime(2021, 1, 1),
max_active_runs=1,
tags=['example'],
) as dag:
# [START howto_operator_eks_create_cluster_with_fargate_profile]
# Create an Amazon EKS cluster control plane and an AWS Fargate compute platform in one step.
create_cluster_and_fargate_profile = EKSCreateClusterOperator(
task_id='create_eks_cluster_and_fargate_profile',
cluster_role_arn=ROLE_ARN,
resources_vpc_config=VPC_CONFIG,
compute='fargate',
fargate_profile_name=FARGATE_PROFILE_NAME,
# Opting to use the same ARN for the cluster and the pod here,
# but a different ARN could be configured and passed if desired.
fargate_pod_execution_role_arn=ROLE_ARN,
)
# [END howto_operator_eks_create_cluster_with_fargate_profile]
await_create_fargate_profile = EKSFargateProfileStateSensor(
task_id='wait_for_create_fargate_profile',
fargate_profile_name=FARGATE_PROFILE_NAME,
target_state=FargateProfileStates.ACTIVE,
)
start_pod = EKSPodOperator(
task_id="run_pod",
pod_name="run_pod",