Deferrable mode for ECS operators

airflow/providers/amazon/aws/operators/ecs.py

@@ -35,6 +35,11 @@
  EcsHook,
  should_retry_eni,
 )
+from airflow.providers.amazon.aws.hooks.logs import AwsLogsHook
+from airflow.providers.amazon.aws.triggers.ecs import (
+ ClusterWaiterTrigger,
+ TaskDoneTrigger,
+)
 from airflow.providers.amazon.aws.utils.task_log_fetcher import AwsTaskLogFetcher
 from airflow.utils.helpers import prune_dict
 from airflow.utils.session import provide_session
@@ -67,6 +72,15 @@ def execute(self, context: Context):
  """Must overwrite in child classes."""
  raise NotImplementedError("Please implement execute() in subclass")
 
+ def _complete_exec_with_cluster_desc(self, context, event=None):
+ """To be used as trigger callback for operators that return the cluster description."""
+ if event["status"] != "success":
+ raise AirflowException(f"Error while waiting for operation on cluster to complete: {event}")
+ cluster_arn = event.get("arn")
+ # We cannot get the cluster definition from the waiter on success, so we have to query it here.
+ details = self.hook.conn.describe_clusters(clusters=[cluster_arn])["clusters"][0]
+ return details
+
 
 class EcsCreateClusterOperator(EcsBaseOperator):
  """
@@ -84,18 +98,27 @@ class EcsCreateClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
+ template_fields: Sequence[str] = (
+ "cluster_name",
+ "create_cluster_kwargs",
+ "wait_for_completion",
+ "deferrable",
+ )
 
  def __init__(
  self,
  *,
  cluster_name: str,
  create_cluster_kwargs: dict | None = None,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
@@ -104,6 +127,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info(
@@ -119,6 +143,21 @@ def execute(self, context: Context):
  # In some circumstances the ECS Cluster is created immediately,
  # and there is no reason to wait for completion.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_active",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_active")
  waiter.wait(
@@ -148,24 +187,29 @@ class EcsDeleteClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
+ template_fields: Sequence[str] = ("cluster_name", "wait_for_completion", "deferrable")
 
  def __init__(
  self,
  *,
  cluster_name: str,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
  self.cluster_name = cluster_name
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info("Deleting cluster %r.", self.cluster_name)
@@ -174,9 +218,24 @@ def execute(self, context: Context):
  cluster_state = cluster_details.get("status")
 
  if cluster_state == EcsClusterStates.INACTIVE:
- # In some circumstances the ECS Cluster is deleted immediately,
- # so there is no reason to wait for completion.
+ # if the cluster doesn't have capacity providers that are associated with it,
+ # the deletion is instantaneous, and we don't need to wait for it.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_inactive",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_inactive")
  waiter.wait(
@@ -347,6 +406,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  finished.
  :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait
  in between each Cloudwatch logs fetches.
+ If deferrable is set to True, that parameter is ignored and waiter_delay is used instead.
  :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
  transient errors.
  :param reattach: If set to True, will check if the task previously launched by the task_instance
@@ -361,6 +421,9 @@ class EcsRunTaskOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
  ui_color = "#f0ede4"
@@ -384,6 +447,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  "reattach",
  "number_logs_exception",
  "wait_for_completion",
+ "deferrable",
  )
  template_fields_renderers = {
  "overrides": "json",
@@ -416,8 +480,9 @@ def __init__(
  reattach: bool = False,
  number_logs_exception: int = 10,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 6,
+ waiter_max_attempts: int = 100,
+ deferrable: bool = False,
  **kwargs,
  ):
  super().__init__(**kwargs)
@@ -451,6 +516,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  if self._aws_logs_enabled() and not self.wait_for_completion:
  self.log.warning(
@@ -473,7 +539,35 @@ def execute(self, context, session=None):
  if self.reattach:
  self._try_reattach_task(context)
 
- self._start_wait_check_task(context)
+ self._start_wait_task(context)
+
+ self._after_execution(session)
+
+ if self.do_xcom_push and self.task_log_fetcher:
+ return self.task_log_fetcher.get_last_log_message()
+ else:
+ return None
+
+ def execute_complete(self, context, event=None):
+ if event["status"] != "success":
+ raise AirflowException(f"Error in task execution: {event}")
+ self.arn = event["task_arn"] # restore arn to its updated value, needed for next steps
+ self._after_execution()
+ if self._aws_logs_enabled():
+ # same behavior as non-deferrable mode, return last line of logs of the task.
+ logs_client = AwsLogsHook(aws_conn_id=self.aws_conn_id, region_name=self.region).conn
+ one_log = logs_client.get_log_events(
+ logGroupName=self.awslogs_group,
+ logStreamName=self._get_logs_stream_name(),
+ startFromHead=False,
+ limit=1,
+ )
+ if len(one_log["events"]) > 0:
+ return one_log["events"][0]["message"]
+
+ @provide_session
+ def _after_execution(self, session=None):
+ self._check_success_task()
 
  self.log.info("ECS Task has been successfully executed")
 
@@ -482,16 +576,29 @@ def execute(self, context, session=None):
  # as we can't reattach it anymore
  self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id))
 
- if self.do_xcom_push and self.task_log_fetcher:
- return self.task_log_fetcher.get_last_log_message()
-
- return None
-
  @AwsBaseHook.retry(should_retry_eni)
- def _start_wait_check_task(self, context):
+ def _start_wait_task(self, context):
  if not self.arn:
  self._start_task(context)
 
+ if self.deferrable:
+ self.defer(
+ trigger=TaskDoneTrigger(
+ cluster=self.cluster,
+ task_arn=self.arn,
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ log_group=self.awslogs_group,
+ log_stream=self._get_logs_stream_name(),
+ ),
+ method_name="execute_complete",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
+
  if not self.wait_for_completion:
  return
 
@@ -508,8 +615,6 @@ def _start_wait_check_task(self, context):
  else:
  self._wait_for_task_ended()
 
- self._check_success_task()
-
  def _xcom_del(self, session, task_id):
  session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete()
 
@@ -584,33 +689,34 @@ def _wait_for_task_ended(self) -> None:
  waiter.wait(
  cluster=self.cluster,
  tasks=[self.arn],
- WaiterConfig=prune_dict(
- {
- "Delay": self.waiter_delay,
- "MaxAttempts": self.waiter_max_attempts,
- }
- ),
+ WaiterConfig={
+ "Delay": self.waiter_delay,
+ "MaxAttempts": self.waiter_max_attempts,
+ },
  )
 
  return
 
  def _aws_logs_enabled(self):
  return self.awslogs_group and self.awslogs_stream_prefix
 
+ def _get_logs_stream_name(self) -> str:
+ return f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
+
  def _get_task_log_fetcher(self) -> AwsTaskLogFetcher:
  if not self.awslogs_group:
  raise ValueError("must specify awslogs_group to fetch task logs")
- log_stream_name = f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
 
  return AwsTaskLogFetcher(
  aws_conn_id=self.aws_conn_id,
  region_name=self.awslogs_region,
  log_group=self.awslogs_group,
- log_stream_name=log_stream_name,
+ log_stream_name=self._get_logs_stream_name(),
  fetch_interval=self.awslogs_fetch_interval,
  logger=self.log,
  )
 
+ @AwsBaseHook.retry(should_retry_eni)
  def _check_success_task(self) -> None:
  if not self.client or not self.arn:
  return

airflow/providers/amazon/aws/operators/ecs.py

@@ -35,6 +35,11 @@
  EcsHook,
  should_retry_eni,
 )
+from airflow.providers.amazon.aws.hooks.logs import AwsLogsHook
+from airflow.providers.amazon.aws.triggers.ecs import (
+ ClusterWaiterTrigger,
+ TaskDoneTrigger,
+)
 from airflow.providers.amazon.aws.utils.task_log_fetcher import AwsTaskLogFetcher
 from airflow.utils.helpers import prune_dict
 from airflow.utils.session import provide_session
@@ -67,6 +72,15 @@ def execute(self, context: Context):
  """Must overwrite in child classes."""
  raise NotImplementedError("Please implement execute() in subclass")
 
+ def _complete_exec_with_cluster_desc(self, context, event=None):
+ """To be used as trigger callback for operators that return the cluster description."""
+ if event["status"] != "success":
+ raise AirflowException(f"Error while waiting for operation on cluster to complete: {event}")
+ cluster_arn = event.get("arn")
+ # We cannot get the cluster definition from the waiter on success, so we have to query it here.
+ details = self.hook.conn.describe_clusters(clusters=[cluster_arn])["clusters"][0]
+ return details
+
 
 class EcsCreateClusterOperator(EcsBaseOperator):
  """
@@ -84,18 +98,27 @@ class EcsCreateClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
+ template_fields: Sequence[str] = (
+ "cluster_name",
+ "create_cluster_kwargs",
+ "wait_for_completion",
+ "deferrable",
+ )
 
  def __init__(
  self,
  *,
  cluster_name: str,
  create_cluster_kwargs: dict | None = None,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
@@ -104,6 +127,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info(
@@ -119,6 +143,21 @@ def execute(self, context: Context):
  # In some circumstances the ECS Cluster is created immediately,
  # and there is no reason to wait for completion.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_active",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_active")
  waiter.wait(
@@ -148,24 +187,29 @@ class EcsDeleteClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
+ template_fields: Sequence[str] = ("cluster_name", "wait_for_completion", "deferrable")
 
  def __init__(
  self,
  *,
  cluster_name: str,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
  self.cluster_name = cluster_name
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info("Deleting cluster %r.", self.cluster_name)
@@ -174,9 +218,24 @@ def execute(self, context: Context):
  cluster_state = cluster_details.get("status")
 
  if cluster_state == EcsClusterStates.INACTIVE:
- # In some circumstances the ECS Cluster is deleted immediately,
- # so there is no reason to wait for completion.
+ # if the cluster doesn't have capacity providers that are associated with it,
+ # the deletion is instantaneous, and we don't need to wait for it.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_inactive",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_inactive")
  waiter.wait(
@@ -347,6 +406,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  finished.
  :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait
  in between each Cloudwatch logs fetches.
+ If deferrable is set to True, that parameter is ignored and waiter_delay is used instead.
  :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
  transient errors.
  :param reattach: If set to True, will check if the task previously launched by the task_instance
@@ -361,6 +421,9 @@ class EcsRunTaskOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
  ui_color = "#f0ede4"
@@ -384,6 +447,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  "reattach",
  "number_logs_exception",
  "wait_for_completion",
+ "deferrable",
  )
  template_fields_renderers = {
  "overrides": "json",
@@ -416,8 +480,9 @@ def __init__(
  reattach: bool = False,
  number_logs_exception: int = 10,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 6,
+ waiter_max_attempts: int = 100,
+ deferrable: bool = False,
  **kwargs,
  ):
  super().__init__(**kwargs)
@@ -451,6 +516,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  if self._aws_logs_enabled() and not self.wait_for_completion:
  self.log.warning(
@@ -473,7 +539,35 @@ def execute(self, context, session=None):
  if self.reattach:
  self._try_reattach_task(context)
 
- self._start_wait_check_task(context)
+ self._start_wait_task(context)
+
+ self._after_execution(session)
+
+ if self.do_xcom_push and self.task_log_fetcher:
+ return self.task_log_fetcher.get_last_log_message()
+ else:
+ return None
+
+ def execute_complete(self, context, event=None):
+ if event["status"] != "success":
+ raise AirflowException(f"Error in task execution: {event}")
+ self.arn = event["task_arn"] # restore arn to its updated value, needed for next steps
+ self._after_execution()
+ if self._aws_logs_enabled():
+ # same behavior as non-deferrable mode, return last line of logs of the task.
+ logs_client = AwsLogsHook(aws_conn_id=self.aws_conn_id, region_name=self.region).conn
+ one_log = logs_client.get_log_events(
+ logGroupName=self.awslogs_group,
+ logStreamName=self._get_logs_stream_name(),
+ startFromHead=False,
+ limit=1,
+ )
+ if len(one_log["events"]) > 0:
+ return one_log["events"][0]["message"]
+
+ @provide_session
+ def _after_execution(self, session=None):
+ self._check_success_task()
 
  self.log.info("ECS Task has been successfully executed")
 
@@ -482,16 +576,29 @@ def execute(self, context, session=None):
  # as we can't reattach it anymore
  self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id))
 
- if self.do_xcom_push and self.task_log_fetcher:
- return self.task_log_fetcher.get_last_log_message()
-
- return None
-
  @AwsBaseHook.retry(should_retry_eni)
- def _start_wait_check_task(self, context):
+ def _start_wait_task(self, context):
  if not self.arn:
  self._start_task(context)
 
+ if self.deferrable:
+ self.defer(
+ trigger=TaskDoneTrigger(
+ cluster=self.cluster,
+ task_arn=self.arn,
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ log_group=self.awslogs_group,
+ log_stream=self._get_logs_stream_name(),
+ ),
+ method_name="execute_complete",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
+
  if not self.wait_for_completion:
  return
 
@@ -508,8 +615,6 @@ def _start_wait_check_task(self, context):
  else:
  self._wait_for_task_ended()
 
- self._check_success_task()
-
  def _xcom_del(self, session, task_id):
  session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete()
 
@@ -584,33 +689,34 @@ def _wait_for_task_ended(self) -> None:
  waiter.wait(
  cluster=self.cluster,
  tasks=[self.arn],
- WaiterConfig=prune_dict(
- {
- "Delay": self.waiter_delay,
- "MaxAttempts": self.waiter_max_attempts,
- }
- ),
+ WaiterConfig={
+ "Delay": self.waiter_delay,
+ "MaxAttempts": self.waiter_max_attempts,
+ },
  )
 
  return
 
  def _aws_logs_enabled(self):
  return self.awslogs_group and self.awslogs_stream_prefix
 
+ def _get_logs_stream_name(self) -> str:
+ return f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
+
  def _get_task_log_fetcher(self) -> AwsTaskLogFetcher:
  if not self.awslogs_group:
  raise ValueError("must specify awslogs_group to fetch task logs")
- log_stream_name = f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
 
  return AwsTaskLogFetcher(
  aws_conn_id=self.aws_conn_id,
  region_name=self.awslogs_region,
  log_group=self.awslogs_group,
- log_stream_name=log_stream_name,
+ log_stream_name=self._get_logs_stream_name(),
  fetch_interval=self.awslogs_fetch_interval,
  logger=self.log,
  )
 
+ @AwsBaseHook.retry(should_retry_eni)
  def _check_success_task(self) -> None:
  if not self.client or not self.arn:
  return

airflow/providers/amazon/aws/operators/ecs.py

@@ -35,6 +35,11 @@
  EcsHook,
  should_retry_eni,
 )
+from airflow.providers.amazon.aws.hooks.logs import AwsLogsHook
+from airflow.providers.amazon.aws.triggers.ecs import (
+ ClusterWaiterTrigger,
+ TaskDoneTrigger,
+)
 from airflow.providers.amazon.aws.utils.task_log_fetcher import AwsTaskLogFetcher
 from airflow.utils.helpers import prune_dict
 from airflow.utils.session import provide_session
@@ -67,6 +72,15 @@ def execute(self, context: Context):
  """Must overwrite in child classes."""
  raise NotImplementedError("Please implement execute() in subclass")
 
+ def _complete_exec_with_cluster_desc(self, context, event=None):
+ """To be used as trigger callback for operators that return the cluster description."""
+ if event["status"] != "success":
+ raise AirflowException(f"Error while waiting for operation on cluster to complete: {event}")
+ cluster_arn = event.get("arn")
+ # We cannot get the cluster definition from the waiter on success, so we have to query it here.
+ details = self.hook.conn.describe_clusters(clusters=[cluster_arn])["clusters"][0]
+ return details
+
 
 class EcsCreateClusterOperator(EcsBaseOperator):
  """
@@ -84,18 +98,27 @@ class EcsCreateClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
+ template_fields: Sequence[str] = (
+ "cluster_name",
+ "create_cluster_kwargs",
+ "wait_for_completion",
+ "deferrable",
+ )
 
  def __init__(
  self,
  *,
  cluster_name: str,
  create_cluster_kwargs: dict | None = None,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
@@ -104,6 +127,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info(
@@ -119,6 +143,21 @@ def execute(self, context: Context):
  # In some circumstances the ECS Cluster is created immediately,
  # and there is no reason to wait for completion.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_active",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_active")
  waiter.wait(
@@ -148,24 +187,29 @@ class EcsDeleteClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
+ template_fields: Sequence[str] = ("cluster_name", "wait_for_completion", "deferrable")
 
  def __init__(
  self,
  *,
  cluster_name: str,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
  self.cluster_name = cluster_name
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info("Deleting cluster %r.", self.cluster_name)
@@ -174,9 +218,24 @@ def execute(self, context: Context):
  cluster_state = cluster_details.get("status")
 
  if cluster_state == EcsClusterStates.INACTIVE:
- # In some circumstances the ECS Cluster is deleted immediately,
- # so there is no reason to wait for completion.
+ # if the cluster doesn't have capacity providers that are associated with it,
+ # the deletion is instantaneous, and we don't need to wait for it.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_inactive",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_inactive")
  waiter.wait(
@@ -347,6 +406,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  finished.
  :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait
  in between each Cloudwatch logs fetches.
+ If deferrable is set to True, that parameter is ignored and waiter_delay is used instead.
  :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
  transient errors.
  :param reattach: If set to True, will check if the task previously launched by the task_instance
@@ -361,6 +421,9 @@ class EcsRunTaskOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
  ui_color = "#f0ede4"
@@ -384,6 +447,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  "reattach",
  "number_logs_exception",
  "wait_for_completion",
+ "deferrable",
  )
  template_fields_renderers = {
  "overrides": "json",
@@ -416,8 +480,9 @@ def __init__(
  reattach: bool = False,
  number_logs_exception: int = 10,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 6,
+ waiter_max_attempts: int = 100,
+ deferrable: bool = False,
  **kwargs,
  ):
  super().__init__(**kwargs)
@@ -451,6 +516,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  if self._aws_logs_enabled() and not self.wait_for_completion:
  self.log.warning(
@@ -473,7 +539,35 @@ def execute(self, context, session=None):
  if self.reattach:
  self._try_reattach_task(context)
 
- self._start_wait_check_task(context)
+ self._start_wait_task(context)
+
+ self._after_execution(session)
+
+ if self.do_xcom_push and self.task_log_fetcher:
+ return self.task_log_fetcher.get_last_log_message()
+ else:
+ return None
+
+ def execute_complete(self, context, event=None):
+ if event["status"] != "success":
+ raise AirflowException(f"Error in task execution: {event}")
+ self.arn = event["task_arn"] # restore arn to its updated value, needed for next steps
+ self._after_execution()
+ if self._aws_logs_enabled():
+ # same behavior as non-deferrable mode, return last line of logs of the task.
+ logs_client = AwsLogsHook(aws_conn_id=self.aws_conn_id, region_name=self.region).conn
+ one_log = logs_client.get_log_events(
+ logGroupName=self.awslogs_group,
+ logStreamName=self._get_logs_stream_name(),
+ startFromHead=False,
+ limit=1,
+ )
+ if len(one_log["events"]) > 0:
+ return one_log["events"][0]["message"]
+
+ @provide_session
+ def _after_execution(self, session=None):
+ self._check_success_task()
 
  self.log.info("ECS Task has been successfully executed")
 
@@ -482,16 +576,29 @@ def execute(self, context, session=None):
  # as we can't reattach it anymore
  self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id))
 
- if self.do_xcom_push and self.task_log_fetcher:
- return self.task_log_fetcher.get_last_log_message()
-
- return None
-
  @AwsBaseHook.retry(should_retry_eni)
- def _start_wait_check_task(self, context):
+ def _start_wait_task(self, context):
  if not self.arn:
  self._start_task(context)
 
+ if self.deferrable:
+ self.defer(
+ trigger=TaskDoneTrigger(
+ cluster=self.cluster,
+ task_arn=self.arn,
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ log_group=self.awslogs_group,
+ log_stream=self._get_logs_stream_name(),
+ ),
+ method_name="execute_complete",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
+
  if not self.wait_for_completion:
  return
 
@@ -508,8 +615,6 @@ def _start_wait_check_task(self, context):
  else:
  self._wait_for_task_ended()
 
- self._check_success_task()
-
  def _xcom_del(self, session, task_id):
  session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete()
 
@@ -584,33 +689,34 @@ def _wait_for_task_ended(self) -> None:
  waiter.wait(
  cluster=self.cluster,
  tasks=[self.arn],
- WaiterConfig=prune_dict(
- {
- "Delay": self.waiter_delay,
- "MaxAttempts": self.waiter_max_attempts,
- }
- ),
+ WaiterConfig={
+ "Delay": self.waiter_delay,
+ "MaxAttempts": self.waiter_max_attempts,
+ },
  )
 
  return
 
  def _aws_logs_enabled(self):
  return self.awslogs_group and self.awslogs_stream_prefix
 
+ def _get_logs_stream_name(self) -> str:
+ return f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
+
  def _get_task_log_fetcher(self) -> AwsTaskLogFetcher:
  if not self.awslogs_group:
  raise ValueError("must specify awslogs_group to fetch task logs")
- log_stream_name = f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
 
  return AwsTaskLogFetcher(
  aws_conn_id=self.aws_conn_id,
  region_name=self.awslogs_region,
  log_group=self.awslogs_group,
- log_stream_name=log_stream_name,
+ log_stream_name=self._get_logs_stream_name(),
  fetch_interval=self.awslogs_fetch_interval,
  logger=self.log,
  )
 
+ @AwsBaseHook.retry(should_retry_eni)
  def _check_success_task(self) -> None:
  if not self.client or not self.arn:
  return

airflow/providers/amazon/aws/operators/ecs.py

@@ -35,6 +35,11 @@
  EcsHook,
  should_retry_eni,
 )
+from airflow.providers.amazon.aws.hooks.logs import AwsLogsHook
+from airflow.providers.amazon.aws.triggers.ecs import (
+ ClusterWaiterTrigger,
+ TaskDoneTrigger,
+)
 from airflow.providers.amazon.aws.utils.task_log_fetcher import AwsTaskLogFetcher
 from airflow.utils.helpers import prune_dict
 from airflow.utils.session import provide_session
@@ -67,6 +72,15 @@ def execute(self, context: Context):
  """Must overwrite in child classes."""
  raise NotImplementedError("Please implement execute() in subclass")
 
+ def _complete_exec_with_cluster_desc(self, context, event=None):
+ """To be used as trigger callback for operators that return the cluster description."""
+ if event["status"] != "success":
+ raise AirflowException(f"Error while waiting for operation on cluster to complete: {event}")
+ cluster_arn = event.get("arn")
+ # We cannot get the cluster definition from the waiter on success, so we have to query it here.
+ details = self.hook.conn.describe_clusters(clusters=[cluster_arn])["clusters"][0]
+ return details
+
 
 class EcsCreateClusterOperator(EcsBaseOperator):
  """
@@ -84,18 +98,27 @@ class EcsCreateClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
+ template_fields: Sequence[str] = (
+ "cluster_name",
+ "create_cluster_kwargs",
+ "wait_for_completion",
+ "deferrable",
+ )
 
  def __init__(
  self,
  *,
  cluster_name: str,
  create_cluster_kwargs: dict | None = None,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
@@ -104,6 +127,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info(
@@ -119,6 +143,21 @@ def execute(self, context: Context):
  # In some circumstances the ECS Cluster is created immediately,
  # and there is no reason to wait for completion.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_active",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_active")
  waiter.wait(
@@ -148,24 +187,29 @@ class EcsDeleteClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
+ template_fields: Sequence[str] = ("cluster_name", "wait_for_completion", "deferrable")
 
  def __init__(
  self,
  *,
  cluster_name: str,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
  self.cluster_name = cluster_name
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info("Deleting cluster %r.", self.cluster_name)
@@ -174,9 +218,24 @@ def execute(self, context: Context):
  cluster_state = cluster_details.get("status")
 
  if cluster_state == EcsClusterStates.INACTIVE:
- # In some circumstances the ECS Cluster is deleted immediately,
- # so there is no reason to wait for completion.
+ # if the cluster doesn't have capacity providers that are associated with it,
+ # the deletion is instantaneous, and we don't need to wait for it.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_inactive",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_inactive")
  waiter.wait(
@@ -347,6 +406,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  finished.
  :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait
  in between each Cloudwatch logs fetches.
+ If deferrable is set to True, that parameter is ignored and waiter_delay is used instead.
  :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
  transient errors.
  :param reattach: If set to True, will check if the task previously launched by the task_instance
@@ -361,6 +421,9 @@ class EcsRunTaskOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
  ui_color = "#f0ede4"
@@ -384,6 +447,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  "reattach",
  "number_logs_exception",
  "wait_for_completion",
+ "deferrable",
  )
  template_fields_renderers = {
  "overrides": "json",
@@ -416,8 +480,9 @@ def __init__(
  reattach: bool = False,
  number_logs_exception: int = 10,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 6,
+ waiter_max_attempts: int = 100,
+ deferrable: bool = False,
  **kwargs,
  ):
  super().__init__(**kwargs)
@@ -451,6 +516,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  if self._aws_logs_enabled() and not self.wait_for_completion:
  self.log.warning(
@@ -473,7 +539,35 @@ def execute(self, context, session=None):
  if self.reattach:
  self._try_reattach_task(context)
 
- self._start_wait_check_task(context)
+ self._start_wait_task(context)
+
+ self._after_execution(session)
+
+ if self.do_xcom_push and self.task_log_fetcher:
+ return self.task_log_fetcher.get_last_log_message()
+ else:
+ return None
+
+ def execute_complete(self, context, event=None):
+ if event["status"] != "success":
+ raise AirflowException(f"Error in task execution: {event}")
+ self.arn = event["task_arn"] # restore arn to its updated value, needed for next steps
+ self._after_execution()
+ if self._aws_logs_enabled():
+ # same behavior as non-deferrable mode, return last line of logs of the task.
+ logs_client = AwsLogsHook(aws_conn_id=self.aws_conn_id, region_name=self.region).conn
+ one_log = logs_client.get_log_events(
+ logGroupName=self.awslogs_group,
+ logStreamName=self._get_logs_stream_name(),
+ startFromHead=False,
+ limit=1,
+ )
+ if len(one_log["events"]) > 0:
+ return one_log["events"][0]["message"]
+
+ @provide_session
+ def _after_execution(self, session=None):
+ self._check_success_task()
 
  self.log.info("ECS Task has been successfully executed")
 
@@ -482,16 +576,29 @@ def execute(self, context, session=None):
  # as we can't reattach it anymore
  self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id))
 
- if self.do_xcom_push and self.task_log_fetcher:
- return self.task_log_fetcher.get_last_log_message()
-
- return None
-
  @AwsBaseHook.retry(should_retry_eni)
- def _start_wait_check_task(self, context):
+ def _start_wait_task(self, context):
  if not self.arn:
  self._start_task(context)
 
+ if self.deferrable:
+ self.defer(
+ trigger=TaskDoneTrigger(
+ cluster=self.cluster,
+ task_arn=self.arn,
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ log_group=self.awslogs_group,
+ log_stream=self._get_logs_stream_name(),
+ ),
+ method_name="execute_complete",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
+
  if not self.wait_for_completion:
  return
 
@@ -508,8 +615,6 @@ def _start_wait_check_task(self, context):
  else:
  self._wait_for_task_ended()
 
- self._check_success_task()
-
  def _xcom_del(self, session, task_id):
  session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete()
 
@@ -584,33 +689,34 @@ def _wait_for_task_ended(self) -> None:
  waiter.wait(
  cluster=self.cluster,
  tasks=[self.arn],
- WaiterConfig=prune_dict(
- {
- "Delay": self.waiter_delay,
- "MaxAttempts": self.waiter_max_attempts,
- }
- ),
+ WaiterConfig={
+ "Delay": self.waiter_delay,
+ "MaxAttempts": self.waiter_max_attempts,
+ },
  )
 
  return
 
  def _aws_logs_enabled(self):
  return self.awslogs_group and self.awslogs_stream_prefix
 
+ def _get_logs_stream_name(self) -> str:
+ return f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
+
  def _get_task_log_fetcher(self) -> AwsTaskLogFetcher:
  if not self.awslogs_group:
  raise ValueError("must specify awslogs_group to fetch task logs")
- log_stream_name = f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
 
  return AwsTaskLogFetcher(
  aws_conn_id=self.aws_conn_id,
  region_name=self.awslogs_region,
  log_group=self.awslogs_group,
- log_stream_name=log_stream_name,
+ log_stream_name=self._get_logs_stream_name(),
  fetch_interval=self.awslogs_fetch_interval,
  logger=self.log,
  )
 
+ @AwsBaseHook.retry(should_retry_eni)
  def _check_success_task(self) -> None:
  if not self.client or not self.arn:
  return

airflow/providers/amazon/aws/operators/ecs.py

@@ -35,6 +35,11 @@
  EcsHook,
  should_retry_eni,
 )
+from airflow.providers.amazon.aws.hooks.logs import AwsLogsHook
+from airflow.providers.amazon.aws.triggers.ecs import (
+ ClusterWaiterTrigger,
+ TaskDoneTrigger,
+)
 from airflow.providers.amazon.aws.utils.task_log_fetcher import AwsTaskLogFetcher
 from airflow.utils.helpers import prune_dict
 from airflow.utils.session import provide_session
@@ -67,6 +72,15 @@ def execute(self, context: Context):
  """Must overwrite in child classes."""
  raise NotImplementedError("Please implement execute() in subclass")
 
+ def _complete_exec_with_cluster_desc(self, context, event=None):
+ """To be used as trigger callback for operators that return the cluster description."""
+ if event["status"] != "success":
+ raise AirflowException(f"Error while waiting for operation on cluster to complete: {event}")
+ cluster_arn = event.get("arn")
+ # We cannot get the cluster definition from the waiter on success, so we have to query it here.
+ details = self.hook.conn.describe_clusters(clusters=[cluster_arn])["clusters"][0]
+ return details
+
 
 class EcsCreateClusterOperator(EcsBaseOperator):
  """
@@ -84,18 +98,27 @@ class EcsCreateClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
+ template_fields: Sequence[str] = (
+ "cluster_name",
+ "create_cluster_kwargs",
+ "wait_for_completion",
+ "deferrable",
+ )
 
  def __init__(
  self,
  *,
  cluster_name: str,
  create_cluster_kwargs: dict | None = None,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
@@ -104,6 +127,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info(
@@ -119,6 +143,21 @@ def execute(self, context: Context):
  # In some circumstances the ECS Cluster is created immediately,
  # and there is no reason to wait for completion.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_active",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_active")
  waiter.wait(
@@ -148,24 +187,29 @@ class EcsDeleteClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
+ template_fields: Sequence[str] = ("cluster_name", "wait_for_completion", "deferrable")
 
  def __init__(
  self,
  *,
  cluster_name: str,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
  self.cluster_name = cluster_name
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info("Deleting cluster %r.", self.cluster_name)
@@ -174,9 +218,24 @@ def execute(self, context: Context):
  cluster_state = cluster_details.get("status")
 
  if cluster_state == EcsClusterStates.INACTIVE:
- # In some circumstances the ECS Cluster is deleted immediately,
- # so there is no reason to wait for completion.
+ # if the cluster doesn't have capacity providers that are associated with it,
+ # the deletion is instantaneous, and we don't need to wait for it.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_inactive",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_inactive")
  waiter.wait(
@@ -347,6 +406,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  finished.
  :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait
  in between each Cloudwatch logs fetches.
+ If deferrable is set to True, that parameter is ignored and waiter_delay is used instead.
  :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
  transient errors.
  :param reattach: If set to True, will check if the task previously launched by the task_instance
@@ -361,6 +421,9 @@ class EcsRunTaskOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
  ui_color = "#f0ede4"
@@ -384,6 +447,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  "reattach",
  "number_logs_exception",
  "wait_for_completion",
+ "deferrable",
  )
  template_fields_renderers = {
  "overrides": "json",
@@ -416,8 +480,9 @@ def __init__(
  reattach: bool = False,
  number_logs_exception: int = 10,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 6,
+ waiter_max_attempts: int = 100,
+ deferrable: bool = False,
  **kwargs,
  ):
  super().__init__(**kwargs)
@@ -451,6 +516,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  if self._aws_logs_enabled() and not self.wait_for_completion:
  self.log.warning(
@@ -473,7 +539,35 @@ def execute(self, context, session=None):
  if self.reattach:
  self._try_reattach_task(context)
 
- self._start_wait_check_task(context)
+ self._start_wait_task(context)
+
+ self._after_execution(session)
+
+ if self.do_xcom_push and self.task_log_fetcher:
+ return self.task_log_fetcher.get_last_log_message()
+ else:
+ return None
+
+ def execute_complete(self, context, event=None):
+ if event["status"] != "success":
+ raise AirflowException(f"Error in task execution: {event}")
+ self.arn = event["task_arn"] # restore arn to its updated value, needed for next steps
+ self._after_execution()
+ if self._aws_logs_enabled():
+ # same behavior as non-deferrable mode, return last line of logs of the task.
+ logs_client = AwsLogsHook(aws_conn_id=self.aws_conn_id, region_name=self.region).conn
+ one_log = logs_client.get_log_events(
+ logGroupName=self.awslogs_group,
+ logStreamName=self._get_logs_stream_name(),
+ startFromHead=False,
+ limit=1,
+ )
+ if len(one_log["events"]) > 0:
+ return one_log["events"][0]["message"]
+
+ @provide_session
+ def _after_execution(self, session=None):
+ self._check_success_task()
 
  self.log.info("ECS Task has been successfully executed")
 
@@ -482,16 +576,29 @@ def execute(self, context, session=None):
  # as we can't reattach it anymore
  self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id))
 
- if self.do_xcom_push and self.task_log_fetcher:
- return self.task_log_fetcher.get_last_log_message()
-
- return None
-
  @AwsBaseHook.retry(should_retry_eni)
- def _start_wait_check_task(self, context):
+ def _start_wait_task(self, context):
  if not self.arn:
  self._start_task(context)
 
+ if self.deferrable:
+ self.defer(
+ trigger=TaskDoneTrigger(
+ cluster=self.cluster,
+ task_arn=self.arn,
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ log_group=self.awslogs_group,
+ log_stream=self._get_logs_stream_name(),
+ ),
+ method_name="execute_complete",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
+
  if not self.wait_for_completion:
  return
 
@@ -508,8 +615,6 @@ def _start_wait_check_task(self, context):
  else:
  self._wait_for_task_ended()
 
- self._check_success_task()
-
  def _xcom_del(self, session, task_id):
  session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete()
 
@@ -584,33 +689,34 @@ def _wait_for_task_ended(self) -> None:
  waiter.wait(
  cluster=self.cluster,
  tasks=[self.arn],
- WaiterConfig=prune_dict(
- {
- "Delay": self.waiter_delay,
- "MaxAttempts": self.waiter_max_attempts,
- }
- ),
+ WaiterConfig={
+ "Delay": self.waiter_delay,
+ "MaxAttempts": self.waiter_max_attempts,
+ },
  )
 
  return
 
  def _aws_logs_enabled(self):
  return self.awslogs_group and self.awslogs_stream_prefix
 
+ def _get_logs_stream_name(self) -> str:
+ return f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
+
  def _get_task_log_fetcher(self) -> AwsTaskLogFetcher:
  if not self.awslogs_group:
  raise ValueError("must specify awslogs_group to fetch task logs")
- log_stream_name = f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
 
  return AwsTaskLogFetcher(
  aws_conn_id=self.aws_conn_id,
  region_name=self.awslogs_region,
  log_group=self.awslogs_group,
- log_stream_name=log_stream_name,
+ log_stream_name=self._get_logs_stream_name(),
  fetch_interval=self.awslogs_fetch_interval,
  logger=self.log,
  )
 
+ @AwsBaseHook.retry(should_retry_eni)
  def _check_success_task(self) -> None:
  if not self.client or not self.arn:
  return

airflow/providers/amazon/aws/operators/ecs.py

@@ -35,6 +35,11 @@
  EcsHook,
  should_retry_eni,
 )
+from airflow.providers.amazon.aws.hooks.logs import AwsLogsHook
+from airflow.providers.amazon.aws.triggers.ecs import (
+ ClusterWaiterTrigger,
+ TaskDoneTrigger,
+)
 from airflow.providers.amazon.aws.utils.task_log_fetcher import AwsTaskLogFetcher
 from airflow.utils.helpers import prune_dict
 from airflow.utils.session import provide_session
@@ -67,6 +72,15 @@ def execute(self, context: Context):
  """Must overwrite in child classes."""
  raise NotImplementedError("Please implement execute() in subclass")
 
+ def _complete_exec_with_cluster_desc(self, context, event=None):
+ """To be used as trigger callback for operators that return the cluster description."""
+ if event["status"] != "success":
+ raise AirflowException(f"Error while waiting for operation on cluster to complete: {event}")
+ cluster_arn = event.get("arn")
+ # We cannot get the cluster definition from the waiter on success, so we have to query it here.
+ details = self.hook.conn.describe_clusters(clusters=[cluster_arn])["clusters"][0]
+ return details
+
 
 class EcsCreateClusterOperator(EcsBaseOperator):
  """
@@ -84,18 +98,27 @@ class EcsCreateClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
+ template_fields: Sequence[str] = (
+ "cluster_name",
+ "create_cluster_kwargs",
+ "wait_for_completion",
+ "deferrable",
+ )
 
  def __init__(
  self,
  *,
  cluster_name: str,
  create_cluster_kwargs: dict | None = None,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
@@ -104,6 +127,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info(
@@ -119,6 +143,21 @@ def execute(self, context: Context):
  # In some circumstances the ECS Cluster is created immediately,
  # and there is no reason to wait for completion.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_active",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_active")
  waiter.wait(
@@ -148,24 +187,29 @@ class EcsDeleteClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
+ template_fields: Sequence[str] = ("cluster_name", "wait_for_completion", "deferrable")
 
  def __init__(
  self,
  *,
  cluster_name: str,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
  self.cluster_name = cluster_name
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info("Deleting cluster %r.", self.cluster_name)
@@ -174,9 +218,24 @@ def execute(self, context: Context):
  cluster_state = cluster_details.get("status")
 
  if cluster_state == EcsClusterStates.INACTIVE:
- # In some circumstances the ECS Cluster is deleted immediately,
- # so there is no reason to wait for completion.
+ # if the cluster doesn't have capacity providers that are associated with it,
+ # the deletion is instantaneous, and we don't need to wait for it.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_inactive",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_inactive")
  waiter.wait(
@@ -347,6 +406,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  finished.
  :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait
  in between each Cloudwatch logs fetches.
+ If deferrable is set to True, that parameter is ignored and waiter_delay is used instead.
  :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
  transient errors.
  :param reattach: If set to True, will check if the task previously launched by the task_instance
@@ -361,6 +421,9 @@ class EcsRunTaskOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
  ui_color = "#f0ede4"
@@ -384,6 +447,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  "reattach",
  "number_logs_exception",
  "wait_for_completion",
+ "deferrable",
  )
  template_fields_renderers = {
  "overrides": "json",
@@ -416,8 +480,9 @@ def __init__(
  reattach: bool = False,
  number_logs_exception: int = 10,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 6,
+ waiter_max_attempts: int = 100,
+ deferrable: bool = False,
  **kwargs,
  ):
  super().__init__(**kwargs)
@@ -451,6 +516,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  if self._aws_logs_enabled() and not self.wait_for_completion:
  self.log.warning(
@@ -473,7 +539,35 @@ def execute(self, context, session=None):
  if self.reattach:
  self._try_reattach_task(context)
 
- self._start_wait_check_task(context)
+ self._start_wait_task(context)
+
+ self._after_execution(session)
+
+ if self.do_xcom_push and self.task_log_fetcher:
+ return self.task_log_fetcher.get_last_log_message()
+ else:
+ return None
+
+ def execute_complete(self, context, event=None):
+ if event["status"] != "success":
+ raise AirflowException(f"Error in task execution: {event}")
+ self.arn = event["task_arn"] # restore arn to its updated value, needed for next steps
+ self._after_execution()
+ if self._aws_logs_enabled():
+ # same behavior as non-deferrable mode, return last line of logs of the task.
+ logs_client = AwsLogsHook(aws_conn_id=self.aws_conn_id, region_name=self.region).conn
+ one_log = logs_client.get_log_events(
+ logGroupName=self.awslogs_group,
+ logStreamName=self._get_logs_stream_name(),
+ startFromHead=False,
+ limit=1,
+ )
+ if len(one_log["events"]) > 0:
+ return one_log["events"][0]["message"]
+
+ @provide_session
+ def _after_execution(self, session=None):
+ self._check_success_task()
 
  self.log.info("ECS Task has been successfully executed")
 
@@ -482,16 +576,29 @@ def execute(self, context, session=None):
  # as we can't reattach it anymore
  self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id))
 
- if self.do_xcom_push and self.task_log_fetcher:
- return self.task_log_fetcher.get_last_log_message()
-
- return None
-
  @AwsBaseHook.retry(should_retry_eni)
- def _start_wait_check_task(self, context):
+ def _start_wait_task(self, context):
  if not self.arn:
  self._start_task(context)
 
+ if self.deferrable:
+ self.defer(
+ trigger=TaskDoneTrigger(
+ cluster=self.cluster,
+ task_arn=self.arn,
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ log_group=self.awslogs_group,
+ log_stream=self._get_logs_stream_name(),
+ ),
+ method_name="execute_complete",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
+
  if not self.wait_for_completion:
  return
 
@@ -508,8 +615,6 @@ def _start_wait_check_task(self, context):
  else:
  self._wait_for_task_ended()
 
- self._check_success_task()
-
  def _xcom_del(self, session, task_id):
  session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete()
 
@@ -584,33 +689,34 @@ def _wait_for_task_ended(self) -> None:
  waiter.wait(
  cluster=self.cluster,
  tasks=[self.arn],
- WaiterConfig=prune_dict(
- {
- "Delay": self.waiter_delay,
- "MaxAttempts": self.waiter_max_attempts,
- }
- ),
+ WaiterConfig={
+ "Delay": self.waiter_delay,
+ "MaxAttempts": self.waiter_max_attempts,
+ },
  )
 
  return
 
  def _aws_logs_enabled(self):
  return self.awslogs_group and self.awslogs_stream_prefix
 
+ def _get_logs_stream_name(self) -> str:
+ return f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
+
  def _get_task_log_fetcher(self) -> AwsTaskLogFetcher:
  if not self.awslogs_group:
  raise ValueError("must specify awslogs_group to fetch task logs")
- log_stream_name = f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
 
  return AwsTaskLogFetcher(
  aws_conn_id=self.aws_conn_id,
  region_name=self.awslogs_region,
  log_group=self.awslogs_group,
- log_stream_name=log_stream_name,
+ log_stream_name=self._get_logs_stream_name(),
  fetch_interval=self.awslogs_fetch_interval,
  logger=self.log,
  )
 
+ @AwsBaseHook.retry(should_retry_eni)
  def _check_success_task(self) -> None:
  if not self.client or not self.arn:
  return

airflow/providers/amazon/aws/operators/ecs.py

@@ -35,6 +35,11 @@
  EcsHook,
  should_retry_eni,
 )
+from airflow.providers.amazon.aws.hooks.logs import AwsLogsHook
+from airflow.providers.amazon.aws.triggers.ecs import (
+ ClusterWaiterTrigger,
+ TaskDoneTrigger,
+)
 from airflow.providers.amazon.aws.utils.task_log_fetcher import AwsTaskLogFetcher
 from airflow.utils.helpers import prune_dict
 from airflow.utils.session import provide_session
@@ -67,6 +72,15 @@ def execute(self, context: Context):
  """Must overwrite in child classes."""
  raise NotImplementedError("Please implement execute() in subclass")
 
+ def _complete_exec_with_cluster_desc(self, context, event=None):
+ """To be used as trigger callback for operators that return the cluster description."""
+ if event["status"] != "success":
+ raise AirflowException(f"Error while waiting for operation on cluster to complete: {event}")
+ cluster_arn = event.get("arn")
+ # We cannot get the cluster definition from the waiter on success, so we have to query it here.
+ details = self.hook.conn.describe_clusters(clusters=[cluster_arn])["clusters"][0]
+ return details
+
 
 class EcsCreateClusterOperator(EcsBaseOperator):
  """
@@ -84,18 +98,27 @@ class EcsCreateClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
+ template_fields: Sequence[str] = (
+ "cluster_name",
+ "create_cluster_kwargs",
+ "wait_for_completion",
+ "deferrable",
+ )
 
  def __init__(
  self,
  *,
  cluster_name: str,
  create_cluster_kwargs: dict | None = None,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
@@ -104,6 +127,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info(
@@ -119,6 +143,21 @@ def execute(self, context: Context):
  # In some circumstances the ECS Cluster is created immediately,
  # and there is no reason to wait for completion.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_active",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_active")
  waiter.wait(
@@ -148,24 +187,29 @@ class EcsDeleteClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
+ template_fields: Sequence[str] = ("cluster_name", "wait_for_completion", "deferrable")
 
  def __init__(
  self,
  *,
  cluster_name: str,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
  self.cluster_name = cluster_name
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info("Deleting cluster %r.", self.cluster_name)
@@ -174,9 +218,24 @@ def execute(self, context: Context):
  cluster_state = cluster_details.get("status")
 
  if cluster_state == EcsClusterStates.INACTIVE:
- # In some circumstances the ECS Cluster is deleted immediately,
- # so there is no reason to wait for completion.
+ # if the cluster doesn't have capacity providers that are associated with it,
+ # the deletion is instantaneous, and we don't need to wait for it.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_inactive",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_inactive")
  waiter.wait(
@@ -347,6 +406,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  finished.
  :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait
  in between each Cloudwatch logs fetches.
+ If deferrable is set to True, that parameter is ignored and waiter_delay is used instead.
  :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
  transient errors.
  :param reattach: If set to True, will check if the task previously launched by the task_instance
@@ -361,6 +421,9 @@ class EcsRunTaskOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
  ui_color = "#f0ede4"
@@ -384,6 +447,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  "reattach",
  "number_logs_exception",
  "wait_for_completion",
+ "deferrable",
  )
  template_fields_renderers = {
  "overrides": "json",
@@ -416,8 +480,9 @@ def __init__(
  reattach: bool = False,
  number_logs_exception: int = 10,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 6,
+ waiter_max_attempts: int = 100,
+ deferrable: bool = False,
  **kwargs,
  ):
  super().__init__(**kwargs)
@@ -451,6 +516,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  if self._aws_logs_enabled() and not self.wait_for_completion:
  self.log.warning(
@@ -473,7 +539,35 @@ def execute(self, context, session=None):
  if self.reattach:
  self._try_reattach_task(context)
 
- self._start_wait_check_task(context)
+ self._start_wait_task(context)
+
+ self._after_execution(session)
+
+ if self.do_xcom_push and self.task_log_fetcher:
+ return self.task_log_fetcher.get_last_log_message()
+ else:
+ return None
+
+ def execute_complete(self, context, event=None):
+ if event["status"] != "success":
+ raise AirflowException(f"Error in task execution: {event}")
+ self.arn = event["task_arn"] # restore arn to its updated value, needed for next steps
+ self._after_execution()
+ if self._aws_logs_enabled():
+ # same behavior as non-deferrable mode, return last line of logs of the task.
+ logs_client = AwsLogsHook(aws_conn_id=self.aws_conn_id, region_name=self.region).conn
+ one_log = logs_client.get_log_events(
+ logGroupName=self.awslogs_group,
+ logStreamName=self._get_logs_stream_name(),
+ startFromHead=False,
+ limit=1,
+ )
+ if len(one_log["events"]) > 0:
+ return one_log["events"][0]["message"]
+
+ @provide_session
+ def _after_execution(self, session=None):
+ self._check_success_task()
 
  self.log.info("ECS Task has been successfully executed")
 
@@ -482,16 +576,29 @@ def execute(self, context, session=None):
  # as we can't reattach it anymore
  self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id))
 
- if self.do_xcom_push and self.task_log_fetcher:
- return self.task_log_fetcher.get_last_log_message()
-
- return None
-
  @AwsBaseHook.retry(should_retry_eni)
- def _start_wait_check_task(self, context):
+ def _start_wait_task(self, context):
  if not self.arn:
  self._start_task(context)
 
+ if self.deferrable:
+ self.defer(
+ trigger=TaskDoneTrigger(
+ cluster=self.cluster,
+ task_arn=self.arn,
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ log_group=self.awslogs_group,
+ log_stream=self._get_logs_stream_name(),
+ ),
+ method_name="execute_complete",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
+
  if not self.wait_for_completion:
  return
 
@@ -508,8 +615,6 @@ def _start_wait_check_task(self, context):
  else:
  self._wait_for_task_ended()
 
- self._check_success_task()
-
  def _xcom_del(self, session, task_id):
  session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete()
 
@@ -584,33 +689,34 @@ def _wait_for_task_ended(self) -> None:
  waiter.wait(
  cluster=self.cluster,
  tasks=[self.arn],
- WaiterConfig=prune_dict(
- {
- "Delay": self.waiter_delay,
- "MaxAttempts": self.waiter_max_attempts,
- }
- ),
+ WaiterConfig={
+ "Delay": self.waiter_delay,
+ "MaxAttempts": self.waiter_max_attempts,
+ },
  )
 
  return
 
  def _aws_logs_enabled(self):
  return self.awslogs_group and self.awslogs_stream_prefix
 
+ def _get_logs_stream_name(self) -> str:
+ return f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
+
  def _get_task_log_fetcher(self) -> AwsTaskLogFetcher:
  if not self.awslogs_group:
  raise ValueError("must specify awslogs_group to fetch task logs")
- log_stream_name = f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
 
  return AwsTaskLogFetcher(
  aws_conn_id=self.aws_conn_id,
  region_name=self.awslogs_region,
  log_group=self.awslogs_group,
- log_stream_name=log_stream_name,
+ log_stream_name=self._get_logs_stream_name(),
  fetch_interval=self.awslogs_fetch_interval,
  logger=self.log,
  )
 
+ @AwsBaseHook.retry(should_retry_eni)
  def _check_success_task(self) -> None:
  if not self.client or not self.arn:
  return

airflow/providers/amazon/aws/operators/ecs.py

@@ -35,6 +35,11 @@
  EcsHook,
  should_retry_eni,
 )
+from airflow.providers.amazon.aws.hooks.logs import AwsLogsHook
+from airflow.providers.amazon.aws.triggers.ecs import (
+ ClusterWaiterTrigger,
+ TaskDoneTrigger,
+)
 from airflow.providers.amazon.aws.utils.task_log_fetcher import AwsTaskLogFetcher
 from airflow.utils.helpers import prune_dict
 from airflow.utils.session import provide_session
@@ -67,6 +72,15 @@ def execute(self, context: Context):
  """Must overwrite in child classes."""
  raise NotImplementedError("Please implement execute() in subclass")
 
+ def _complete_exec_with_cluster_desc(self, context, event=None):
+ """To be used as trigger callback for operators that return the cluster description."""
+ if event["status"] != "success":
+ raise AirflowException(f"Error while waiting for operation on cluster to complete: {event}")
+ cluster_arn = event.get("arn")
+ # We cannot get the cluster definition from the waiter on success, so we have to query it here.
+ details = self.hook.conn.describe_clusters(clusters=[cluster_arn])["clusters"][0]
+ return details
+
 
 class EcsCreateClusterOperator(EcsBaseOperator):
  """
@@ -84,18 +98,27 @@ class EcsCreateClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "create_cluster_kwargs", "wait_for_completion")
+ template_fields: Sequence[str] = (
+ "cluster_name",
+ "create_cluster_kwargs",
+ "wait_for_completion",
+ "deferrable",
+ )
 
  def __init__(
  self,
  *,
  cluster_name: str,
  create_cluster_kwargs: dict | None = None,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
@@ -104,6 +127,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info(
@@ -119,6 +143,21 @@ def execute(self, context: Context):
  # In some circumstances the ECS Cluster is created immediately,
  # and there is no reason to wait for completion.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_active",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_active")
  waiter.wait(
@@ -148,24 +187,29 @@ class EcsDeleteClusterOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
- template_fields: Sequence[str] = ("cluster_name", "wait_for_completion")
+ template_fields: Sequence[str] = ("cluster_name", "wait_for_completion", "deferrable")
 
  def __init__(
  self,
  *,
  cluster_name: str,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 15,
+ waiter_max_attempts: int = 60,
+ deferrable: bool = False,
  **kwargs,
  ) -> None:
  super().__init__(**kwargs)
  self.cluster_name = cluster_name
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  def execute(self, context: Context):
  self.log.info("Deleting cluster %r.", self.cluster_name)
@@ -174,9 +218,24 @@ def execute(self, context: Context):
  cluster_state = cluster_details.get("status")
 
  if cluster_state == EcsClusterStates.INACTIVE:
- # In some circumstances the ECS Cluster is deleted immediately,
- # so there is no reason to wait for completion.
+ # if the cluster doesn't have capacity providers that are associated with it,
+ # the deletion is instantaneous, and we don't need to wait for it.
  self.log.info("Cluster %r in state: %r.", self.cluster_name, cluster_state)
+ elif self.deferrable:
+ self.defer(
+ trigger=ClusterWaiterTrigger(
+ waiter_name="cluster_inactive",
+ cluster_arn=cluster_details["clusterArn"],
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ ),
+ method_name="_complete_exec_with_cluster_desc",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
  elif self.wait_for_completion:
  waiter = self.hook.get_waiter("cluster_inactive")
  waiter.wait(
@@ -347,6 +406,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  finished.
  :param awslogs_fetch_interval: the interval that the ECS task log fetcher should wait
  in between each Cloudwatch logs fetches.
+ If deferrable is set to True, that parameter is ignored and waiter_delay is used instead.
  :param quota_retry: Config if and how to retry the launch of a new ECS task, to handle
  transient errors.
  :param reattach: If set to True, will check if the task previously launched by the task_instance
@@ -361,6 +421,9 @@ class EcsRunTaskOperator(EcsBaseOperator):
  if not set then the default waiter value will be used.
  :param waiter_max_attempts: The maximum number of attempts to be made,
  if not set then the default waiter value will be used.
+ :param deferrable: If True, the operator will wait asynchronously for the job to complete.
+ This implies waiting for completion. This mode requires aiobotocore module to be installed.
+ (default: False)
  """
 
  ui_color = "#f0ede4"
@@ -384,6 +447,7 @@ class EcsRunTaskOperator(EcsBaseOperator):
  "reattach",
  "number_logs_exception",
  "wait_for_completion",
+ "deferrable",
  )
  template_fields_renderers = {
  "overrides": "json",
@@ -416,8 +480,9 @@ def __init__(
  reattach: bool = False,
  number_logs_exception: int = 10,
  wait_for_completion: bool = True,
- waiter_delay: int | None = None,
- waiter_max_attempts: int | None = None,
+ waiter_delay: int = 6,
+ waiter_max_attempts: int = 100,
+ deferrable: bool = False,
  **kwargs,
  ):
  super().__init__(**kwargs)
@@ -451,6 +516,7 @@ def __init__(
  self.wait_for_completion = wait_for_completion
  self.waiter_delay = waiter_delay
  self.waiter_max_attempts = waiter_max_attempts
+ self.deferrable = deferrable
 
  if self._aws_logs_enabled() and not self.wait_for_completion:
  self.log.warning(
@@ -473,7 +539,35 @@ def execute(self, context, session=None):
  if self.reattach:
  self._try_reattach_task(context)
 
- self._start_wait_check_task(context)
+ self._start_wait_task(context)
+
+ self._after_execution(session)
+
+ if self.do_xcom_push and self.task_log_fetcher:
+ return self.task_log_fetcher.get_last_log_message()
+ else:
+ return None
+
+ def execute_complete(self, context, event=None):
+ if event["status"] != "success":
+ raise AirflowException(f"Error in task execution: {event}")
+ self.arn = event["task_arn"] # restore arn to its updated value, needed for next steps
+ self._after_execution()
+ if self._aws_logs_enabled():
+ # same behavior as non-deferrable mode, return last line of logs of the task.
+ logs_client = AwsLogsHook(aws_conn_id=self.aws_conn_id, region_name=self.region).conn
+ one_log = logs_client.get_log_events(
+ logGroupName=self.awslogs_group,
+ logStreamName=self._get_logs_stream_name(),
+ startFromHead=False,
+ limit=1,
+ )
+ if len(one_log["events"]) > 0:
+ return one_log["events"][0]["message"]
+
+ @provide_session
+ def _after_execution(self, session=None):
+ self._check_success_task()
 
  self.log.info("ECS Task has been successfully executed")
 
@@ -482,16 +576,29 @@ def execute(self, context, session=None):
  # as we can't reattach it anymore
  self._xcom_del(session, self.REATTACH_XCOM_TASK_ID_TEMPLATE.format(task_id=self.task_id))
 
- if self.do_xcom_push and self.task_log_fetcher:
- return self.task_log_fetcher.get_last_log_message()
-
- return None
-
  @AwsBaseHook.retry(should_retry_eni)
- def _start_wait_check_task(self, context):
+ def _start_wait_task(self, context):
  if not self.arn:
  self._start_task(context)
 
+ if self.deferrable:
+ self.defer(
+ trigger=TaskDoneTrigger(
+ cluster=self.cluster,
+ task_arn=self.arn,
+ waiter_delay=self.waiter_delay,
+ waiter_max_attempts=self.waiter_max_attempts,
+ aws_conn_id=self.aws_conn_id,
+ region=self.region,
+ log_group=self.awslogs_group,
+ log_stream=self._get_logs_stream_name(),
+ ),
+ method_name="execute_complete",
+ # timeout is set to ensure that if a trigger dies, the timeout does not restart
+ # 60 seconds is added to allow the trigger to exit gracefully (i.e. yield TriggerEvent)
+ timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
+ )
+
  if not self.wait_for_completion:
  return
 
@@ -508,8 +615,6 @@ def _start_wait_check_task(self, context):
  else:
  self._wait_for_task_ended()
 
- self._check_success_task()
-
  def _xcom_del(self, session, task_id):
  session.query(XCom).filter(XCom.dag_id == self.dag_id, XCom.task_id == task_id).delete()
 
@@ -584,33 +689,34 @@ def _wait_for_task_ended(self) -> None:
  waiter.wait(
  cluster=self.cluster,
  tasks=[self.arn],
- WaiterConfig=prune_dict(
- {
- "Delay": self.waiter_delay,
- "MaxAttempts": self.waiter_max_attempts,
- }
- ),
+ WaiterConfig={
+ "Delay": self.waiter_delay,
+ "MaxAttempts": self.waiter_max_attempts,
+ },
  )
 
  return
 
  def _aws_logs_enabled(self):
  return self.awslogs_group and self.awslogs_stream_prefix
 
+ def _get_logs_stream_name(self) -> str:
+ return f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
+
  def _get_task_log_fetcher(self) -> AwsTaskLogFetcher:
  if not self.awslogs_group:
  raise ValueError("must specify awslogs_group to fetch task logs")
- log_stream_name = f"{self.awslogs_stream_prefix}/{self._get_ecs_task_id(self.arn)}"
 
  return AwsTaskLogFetcher(
  aws_conn_id=self.aws_conn_id,
  region_name=self.awslogs_region,
  log_group=self.awslogs_group,
- log_stream_name=log_stream_name,
+ log_stream_name=self._get_logs_stream_name(),
  fetch_interval=self.awslogs_fetch_interval,
  logger=self.log,
  )
 
+ @AwsBaseHook.retry(should_retry_eni)
  def _check_success_task(self) -> None:
  if not self.client or not self.arn:
  return