Source code for airflow.providers.amazon.aws.sensors.ssm
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from __future__ import annotations
from collections.abc import Sequence
from typing import TYPE_CHECKING, Any
from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.ssm import SsmHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.triggers.ssm import SsmRunCommandTrigger
from airflow.providers.amazon.aws.utils import validate_execute_complete_event
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]
class SsmRunCommandCompletedSensor(AwsBaseSensor[SsmHook]):
"""
Poll the state of an AWS SSM Run Command until all instance jobs reach a terminal state. Fails if any instance job ends in a failed state.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:SsmRunCommandCompletedSensor`
:param command_id: The ID of the AWS SSM Run Command.
:param deferrable: If True, the sensor will operate in deferrable mode. This mode requires aiobotocore
module to be installed.
(default: False, but can be overridden in config file by setting default_deferrable to True)
:param poke_interval: Polling period in seconds to check for the status of the job. (default: 120)
:param max_retries: Number of times before returning the current state. (default: 75)
:param aws_conn_id: The Airflow connection used for AWS credentials.
If this is ``None`` or empty then the default boto3 behaviour is used. If
running Airflow in a distributed manner and aws_conn_id is None or
empty, then default boto3 configuration would be used (and must be
maintained on each worker node).
:param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
:param verify: Whether or not to verify SSL certificates. See:
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
:param botocore_config: Configuration dictionary (key-values) for botocore client. See:
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
"""
[docs]
FAILURE_STATES: tuple[str, ...] = ("Cancelled", "TimedOut", "Failed")
[docs]
SUCCESS_STATES: tuple[str, ...] = ("Success",)
[docs]
FAILURE_MESSAGE = "SSM run command sensor failed."
[docs]
aws_hook_class = SsmHook
[docs]
template_fields: Sequence[str] = aws_template_fields(
"command_id",
)
def __init__(
self,
*,
command_id,
deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False),
poke_interval: int = 120,
max_retries: int = 75,
**kwargs,
):
super().__init__(**kwargs)
[docs]
self.command_id = command_id
[docs]
self.deferrable = deferrable
[docs]
self.poke_interval = poke_interval
[docs]
self.max_retries = max_retries
[docs]
def poke(self, context: Context):
response = self.hook.conn.list_command_invocations(CommandId=self.command_id)
command_invocations = response.get("CommandInvocations", [])
if not command_invocations:
self.log.info("No command invocations found for command_id=%s yet, waiting...", self.command_id)
return False
for invocation in command_invocations:
state = invocation["Status"]
if state in self.FAILURE_STATES:
raise AirflowException(self.FAILURE_MESSAGE)
if state in self.INTERMEDIATE_STATES:
return False
return True
[docs]
def execute(self, context: Context):
if self.deferrable:
self.defer(
trigger=SsmRunCommandTrigger(
command_id=self.command_id,
waiter_delay=int(self.poke_interval),
waiter_max_attempts=self.max_retries,
aws_conn_id=self.aws_conn_id,
),
method_name="execute_complete",
)
else:
super().execute(context=context)
[docs]
def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> None:
event = validate_execute_complete_event(event)
if event["status"] != "success":
raise AirflowException(f"Error while running run command: {event}")
self.log.info("SSM run command `%s` completed.", event["command_id"])