enable_fast_launch ¶

def enable_fast_launch(
    self,
    *,
    config_overrides: Optional[EC2ClientConfig] = None,
    image_id: Optional["capo_ec2.types.image_id.ImageId"] = None,
    resource_type: Optional["capo_ec2.types.string.String"] = None,
    snapshot_configuration: Optional[
        "capo_ec2.types.fast_launch_snapshot_configuration_request.FastLaunchSnapshotConfigurationRequest"
    ] = None,
    launch_template: Optional[
        "capo_ec2.types.fast_launch_launch_template_specification_request.FastLaunchLaunchTemplateSpecificationRequest"
    ] = None,
    max_parallel_launches: Optional["capo_ec2.types.integer.Integer"] = None,
    dry_run: Optional["capo_ec2.types.boolean.Boolean"] = None,
) -> "capo_ec2.types.enable_fast_launch_result.EnableFastLaunchResult":
    """<p>When you enable Windows fast launch for a Windows AMI, images are pre-provisioned, using snapshots to launch instances up to 65% faster. To create the optimized Windows image, Amazon EC2 launches an instance and runs through Sysprep steps, rebooting as required. Then it creates a set of reserved snapshots that are used for subsequent launches. The reserved snapshots are automatically replenished as they are used, depending on your settings for launch frequency.</p> <note> <p>You can only change these settings for Windows AMIs that you own or that have been shared with you.</p> </note>

    Args:
        image_id: <p>Specify the ID of the image for which to enable Windows fast launch.</p>
        resource_type: <p>The type of resource to use for pre-provisioning the AMI for Windows fast launch. Supported values include: <code>snapshot</code>, which is the default value.</p>
        snapshot_configuration: <p>Configuration settings for creating and managing the snapshots that are used for pre-provisioning the AMI for Windows fast launch. The associated <code>ResourceType</code> must be <code>snapshot</code>.</p>
        launch_template: <p>The launch template to use when launching Windows instances from pre-provisioned snapshots. Launch template parameters can include either the name or ID of the launch template, but not both.</p>
        max_parallel_launches: <p>The maximum number of instances that Amazon EC2 can launch at the same time to create pre-provisioned snapshots for Windows fast launch. Value must be <code>6</code> or greater.</p>
        dry_run: <p>Checks whether you have the required permissions for the action, without actually making the request, and provides an error response. If you have the required permissions, the error response is <code>DryRunOperation</code>. Otherwise, it is <code>UnauthorizedOperation</code>.</p>

    Raises:
        capo_ec2.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_ec2.types.enable_fast_launch_request.EnableFastLaunchRequest]",
    ) -> OperationResponse[
        "capo_ec2.types.enable_fast_launch_result.EnableFastLaunchResult"
    ]:
        import capo_ec2._operations.amazon_ec2.enable_fast_launch

        output, http_response = (
            capo_ec2._operations.amazon_ec2.enable_fast_launch.enable_fast_launch(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("EnableFastLaunch")
    )
    input_: capo_ec2.types.enable_fast_launch_request.EnableFastLaunchRequest = {}
    if image_id is not None:
        input_["image_id"] = image_id
    if resource_type is not None:
        input_["resource_type"] = resource_type
    if snapshot_configuration is not None:
        input_["snapshot_configuration"] = snapshot_configuration
    if launch_template is not None:
        input_["launch_template"] = launch_template
    if max_parallel_launches is not None:
        input_["max_parallel_launches"] = max_parallel_launches
    if dry_run is not None:
        input_["dry_run"] = dry_run

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output