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"""Tracking the state of Amazon EKS Clusters, Amazon EKS managed node groups, and AWS Fargate profiles."""
from __future__ import annotations
from abc import abstractmethod
from functools import cached_property
from typing import TYPE_CHECKING, Sequence
from airflow.exceptions import AirflowException, AirflowSkipException
from airflow.providers.amazon.aws.hooks.eks import (
ClusterStates,
EksHook,
FargateProfileStates,
NodegroupStates,
)
from airflow.sensors.base import BaseSensorOperator
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]DEFAULT_CONN_ID = "aws_default"
[docs]CLUSTER_TERMINAL_STATES = frozenset({ClusterStates.ACTIVE, ClusterStates.FAILED, ClusterStates.NONEXISTENT})
[docs]FARGATE_TERMINAL_STATES = frozenset(
{
FargateProfileStates.ACTIVE,
FargateProfileStates.CREATE_FAILED,
FargateProfileStates.DELETE_FAILED,
FargateProfileStates.NONEXISTENT,
}
)
[docs]NODEGROUP_TERMINAL_STATES = frozenset(
{
NodegroupStates.ACTIVE,
NodegroupStates.CREATE_FAILED,
NodegroupStates.DELETE_FAILED,
NodegroupStates.NONEXISTENT,
}
)
[docs]class EksBaseSensor(BaseSensorOperator):
"""
Base class to check various EKS states.
Subclasses need to implement get_state and get_terminal_states methods.
:param cluster_name: The name of the Cluster
:param target_state: Will return successfully when that state is reached.
:param target_state_type: The enum containing the states,
will be used to convert the target state if it has to be converted from a string
: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 the default boto3 configuration would be used (and must be
maintained on each worker node).
:param region: Which AWS region the connection should use.
If this is None or empty then the default boto3 behaviour is used.
"""
def __init__(
self,
*,
cluster_name: str,
target_state: ClusterStates | NodegroupStates | FargateProfileStates,
target_state_type: type,
aws_conn_id: str | None = DEFAULT_CONN_ID,
region: str | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.cluster_name = cluster_name
self.aws_conn_id = aws_conn_id
self.region = region
self.target_state = (
target_state
if isinstance(target_state, target_state_type)
else target_state_type(str(target_state).upper())
)
@cached_property
[docs] def hook(self) -> EksHook:
return EksHook(
aws_conn_id=self.aws_conn_id,
region_name=self.region,
)
[docs] def poke(self, context: Context) -> bool:
state = self.get_state()
self.log.info("Current state: %s", state)
if state in (self.get_terminal_states() - {self.target_state}):
# If we reach a terminal state which is not the target state:
# TODO: remove this if check when min_airflow_version is set to higher than 2.7.1
message = f"Terminal state reached. Current state: {state}, Expected state: {self.target_state}"
if self.soft_fail:
raise AirflowSkipException(message)
raise AirflowException(message)
return state == self.target_state
@abstractmethod
[docs] def get_state(self) -> ClusterStates | NodegroupStates | FargateProfileStates:
...
@abstractmethod
[docs] def get_terminal_states(self) -> frozenset:
...
[docs]class EksClusterStateSensor(EksBaseSensor):
"""
Check the state of an Amazon EKS Cluster until it reaches the target state or another terminal state.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:EksClusterStateSensor`
:param cluster_name: The name of the Cluster to watch. (templated)
:param target_state: Target state of the Cluster. (templated)
:param region: Which AWS region the connection should use. (templated)
If this is None or empty then the default boto3 behaviour is used.
:param aws_conn_id: The Airflow connection used for AWS credentials. (templated)
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 the default boto3 configuration would be used (and must be
maintained on each worker node).
"""
[docs] template_fields: Sequence[str] = ("cluster_name", "target_state", "aws_conn_id", "region")
def __init__(
self,
*,
target_state: ClusterStates = ClusterStates.ACTIVE,
**kwargs,
):
super().__init__(target_state=target_state, target_state_type=ClusterStates, **kwargs)
[docs] def get_state(self) -> ClusterStates:
return self.hook.get_cluster_state(clusterName=self.cluster_name)
[docs] def get_terminal_states(self) -> frozenset:
return CLUSTER_TERMINAL_STATES
[docs]class EksFargateProfileStateSensor(EksBaseSensor):
"""
Check the state of an AWS Fargate profile until it reaches the target state or another terminal state.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:EksFargateProfileStateSensor`
:param cluster_name: The name of the Cluster which the AWS Fargate profile is attached to. (templated)
:param fargate_profile_name: The name of the Fargate profile to watch. (templated)
:param target_state: Target state of the Fargate profile. (templated)
:param region: Which AWS region the connection should use. (templated)
If this is None or empty then the default boto3 behaviour is used.
:param aws_conn_id: The Airflow connection used for AWS credentials. (templated)
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 the default boto3 configuration would be used (and must be
maintained on each worker node).
"""
[docs] template_fields: Sequence[str] = (
"cluster_name",
"fargate_profile_name",
"target_state",
"aws_conn_id",
"region",
)
def __init__(
self,
*,
fargate_profile_name: str,
target_state: FargateProfileStates = FargateProfileStates.ACTIVE,
**kwargs,
):
super().__init__(target_state=target_state, target_state_type=FargateProfileStates, **kwargs)
self.fargate_profile_name = fargate_profile_name
[docs] def get_state(self) -> FargateProfileStates:
return self.hook.get_fargate_profile_state(
clusterName=self.cluster_name, fargateProfileName=self.fargate_profile_name
)
[docs] def get_terminal_states(self) -> frozenset:
return FARGATE_TERMINAL_STATES
[docs]class EksNodegroupStateSensor(EksBaseSensor):
"""
Check the state of an EKS managed node group until it reaches the target state or another terminal state.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:EksNodegroupStateSensor`
:param cluster_name: The name of the Cluster which the Nodegroup is attached to. (templated)
:param nodegroup_name: The name of the Nodegroup to watch. (templated)
:param target_state: Target state of the Nodegroup. (templated)
:param region: Which AWS region the connection should use. (templated)
If this is None or empty then the default boto3 behaviour is used.
:param aws_conn_id: The Airflow connection used for AWS credentials. (templated)
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 the default boto3 configuration would be used (and must be
maintained on each worker node).
"""
[docs] template_fields: Sequence[str] = (
"cluster_name",
"nodegroup_name",
"target_state",
"aws_conn_id",
"region",
)
def __init__(
self,
*,
nodegroup_name: str,
target_state: NodegroupStates = NodegroupStates.ACTIVE,
**kwargs,
):
super().__init__(target_state=target_state, target_state_type=NodegroupStates, **kwargs)
self.nodegroup_name = nodegroup_name
[docs] def get_state(self) -> NodegroupStates:
return self.hook.get_nodegroup_state(clusterName=self.cluster_name, nodegroupName=self.nodegroup_name)
[docs] def get_terminal_states(self) -> frozenset:
return NODEGROUP_TERMINAL_STATES
