Describes the scaling process types for use with the ResumeProcesses and SuspendProcesses APIs.
Raises:
-
ResourceContentionFault
–
You already have a pending update to an Amazon EC2 Auto Scaling resource (for example, an Auto Scaling group, instance, or load balancer).
-
UnknownServiceError
–
The service returned an error code this client does not model.
Examples:
To describe the Auto Scaling process types
This example describes the Auto Scaling process types.
>>> client.describe_scaling_process_types()
Source code in docs_src/capo_auto_scaling/_services/auto_scaling.py
| def describe_scaling_process_types(
self, *, config_overrides: Optional[AutoScalingClientConfig] = None
) -> "capo_auto_scaling.types.processes_type.ProcessesType":
"""<p>Describes the scaling process types for use with the <a href="https://docs.aws.amazon.com/autoscaling/ec2/APIReference/API_ResumeProcesses.html">ResumeProcesses</a> and <a href="https://docs.aws.amazon.com/autoscaling/ec2/APIReference/API_SuspendProcesses.html">SuspendProcesses</a> APIs.</p>
Raises:
capo_auto_scaling.errors.resource_contention_fault.ResourceContentionFault: <p>You already have a pending update to an Amazon EC2 Auto Scaling resource (for example, an Auto Scaling group, instance, or load balancer).</p>
capo_auto_scaling.errors.UnknownServiceError: The service returned an error code this client does not model.
Examples:
To describe the Auto Scaling process types
This example describes the Auto Scaling process types.
>>> client.describe_scaling_process_types()
"""
def _handler(
req: "OperationRequest[None]",
) -> OperationResponse["capo_auto_scaling.types.processes_type.ProcessesType"]:
import capo_auto_scaling._operations.auto_scaling_2011_01_01.describe_scaling_process_types
output, http_response = (
capo_auto_scaling._operations.auto_scaling_2011_01_01.describe_scaling_process_types.describe_scaling_process_types(
req.options
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("DescribeScalingProcessTypes")
)
response = execute_pipeline(
OperationRequest(input=None, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|