resume_processes `async` ¶

resume_processes(
    *,
    config_overrides: Optional[AsyncAutoScalingClientConfig] = None,
    auto_scaling_group_name: Optional[XmlStringMaxLen255] = None,
    scaling_processes: Optional[ProcessNames] = None,
) -> None

Resumes the specified suspended auto scaling processes, or all suspended process, for the specified Auto Scaling group.

For more information, see Suspend and resume Amazon EC2 Auto Scaling processes in the Amazon EC2 Auto Scaling User Guide.

Parameters:

auto_scaling_group_name (Optional[XmlStringMaxLen255], default: None ) –

The name of the Auto Scaling group.
scaling_processes (Optional[ProcessNames], default: None ) –
One or more of the following processes:
- Launch
- Terminate
- AddToLoadBalancer
- AlarmNotification
- AZRebalance
- HealthCheck
- InstanceRefresh
- ReplaceUnhealthy
- ScheduledActions
If you omit this property, all processes are specified.

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).
ResourceInUseFault –

The operation can't be performed because the resource is in use.
UnknownServiceError –

The service returned an error code this client does not model.

Examples:

To resume Auto Scaling processes This example resumes the specified suspended scaling process for the specified Auto Scaling group.

>>> await client.resume_processes(auto_scaling_group_name='my-auto-scaling-group', scaling_processes=['AlarmNotification'])

Source code in docs_src/capo_auto_scaling/_services/async_auto_scaling.py

async def resume_processes(
    self,
    *,
    config_overrides: Optional[AsyncAutoScalingClientConfig] = None,
    auto_scaling_group_name: Optional[
        "capo_auto_scaling.types.xml_string_max_len255.XmlStringMaxLen255"
    ] = None,
    scaling_processes: Optional[
        "capo_auto_scaling.types.process_names.ProcessNames"
    ] = None,
) -> None:
    """<p>Resumes the specified suspended auto scaling processes, or all suspended process, for the specified Auto Scaling group.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-suspend-resume-processes.html">Suspend and resume Amazon EC2 Auto Scaling processes</a> in the <i>Amazon EC2 Auto Scaling User Guide</i>.</p>

    Args:
        auto_scaling_group_name: <p>The name of the Auto Scaling group.</p>
        scaling_processes: <p>One or more of the following processes:</p> <ul> <li> <p> <code>Launch</code> </p> </li> <li> <p> <code>Terminate</code> </p> </li> <li> <p> <code>AddToLoadBalancer</code> </p> </li> <li> <p> <code>AlarmNotification</code> </p> </li> <li> <p> <code>AZRebalance</code> </p> </li> <li> <p> <code>HealthCheck</code> </p> </li> <li> <p> <code>InstanceRefresh</code> </p> </li> <li> <p> <code>ReplaceUnhealthy</code> </p> </li> <li> <p> <code>ScheduledActions</code> </p> </li> </ul> <p>If you omit this property, all processes are specified.</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.resource_in_use_fault.ResourceInUseFault: <p>The operation can't be performed because the resource is in use.</p>
        capo_auto_scaling.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        To resume Auto Scaling processes
        This example resumes the specified suspended scaling process for the specified Auto Scaling group.

        >>> await client.resume_processes(auto_scaling_group_name='my-auto-scaling-group', scaling_processes=['AlarmNotification'])
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_auto_scaling.types.scaling_process_query.ScalingProcessQuery]",
    ) -> AsyncOperationResponse[None]:
        import capo_auto_scaling._operations.auto_scaling_2011_01_01.resume_processes

        (
            output,
            http_response,
        ) = await capo_auto_scaling._operations.auto_scaling_2011_01_01.resume_processes.async_resume_processes(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ResumeProcesses")
    )
    input_: capo_auto_scaling.types.scaling_process_query.ScalingProcessQuery = {}
    if auto_scaling_group_name is not None:
        input_["auto_scaling_group_name"] = auto_scaling_group_name
    if scaling_processes is not None:
        input_["scaling_processes"] = scaling_processes

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output

resume_processes async ¶

resume_processes `async` ¶