create_target_group ¶

def create_target_group(
    self,
    name: "capo_vpc_lattice.types.target_group_name.TargetGroupName",
    type: "capo_vpc_lattice.types.target_group_type.TargetGroupType",
    *,
    config_overrides: Optional[VPCLatticeClientConfig] = None,
    config: Optional[
        "capo_vpc_lattice.types.target_group_config.TargetGroupConfig"
    ] = None,
    client_token: Optional[
        "capo_vpc_lattice.types.client_token.ClientToken"
    ] = None,
    tags: Optional["capo_vpc_lattice.types.tag_map.TagMap"] = None,
) -> (
    "capo_vpc_lattice.types.create_target_group_response.CreateTargetGroupResponse"
):
    """<p>Creates a target group. A target group is a collection of targets, or compute resources, that run your application or service. A target group can only be used by a single service.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/vpc-lattice/latest/ug/target-groups.html">Target groups</a> in the <i>Amazon VPC Lattice User Guide</i>.</p>

    Args:
        name: <p>The name of the target group. The name must be unique within the account. The valid characters are a-z, 0-9, and hyphens (-). You can't use a hyphen as the first or last character, or immediately after another hyphen.</p>
        type: <p>The type of target group.</p>
        config: <p>The target group configuration.</p>
        client_token: <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. If you retry a request that completed successfully using the same client token and parameters, the retry succeeds without performing any actions. If the parameters aren't identical, the retry fails.</p>
        tags: <p>The tags for the target group.</p>

    Raises:
        capo_vpc_lattice.errors.access_denied_exception.AccessDeniedException: <p>The user does not have sufficient access to perform this action.</p>
        capo_vpc_lattice.errors.conflict_exception.ConflictException: <p>The request conflicts with the current state of the resource. Updating or deleting a resource can cause an inconsistent state.</p>
        capo_vpc_lattice.errors.internal_server_exception.InternalServerException: <p>An unexpected error occurred while processing the request.</p>
        capo_vpc_lattice.errors.resource_not_found_exception.ResourceNotFoundException: <p>The request references a resource that does not exist.</p>
        capo_vpc_lattice.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The request would cause a service quota to be exceeded.</p>
        capo_vpc_lattice.errors.throttling_exception.ThrottlingException: <p>The limit on the number of requests per second was exceeded.</p>
        capo_vpc_lattice.errors.validation_exception.ValidationException: <p>The input does not satisfy the constraints specified by an Amazon Web Services service.</p>
        capo_vpc_lattice.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_vpc_lattice.types.create_target_group_request.CreateTargetGroupRequest]",
    ) -> OperationResponse[
        "capo_vpc_lattice.types.create_target_group_response.CreateTargetGroupResponse"
    ]:
        import capo_vpc_lattice._operations.mercury_control_plane.create_target_group

        output, http_response = (
            capo_vpc_lattice._operations.mercury_control_plane.create_target_group.create_target_group(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateTargetGroup")
    )
    input_: capo_vpc_lattice.types.create_target_group_request.CreateTargetGroupRequest = {
        "name": name,
        "type": type,
    }
    if config is not None:
        input_["config"] = config
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token
    if tags is not None:
        input_["tags"] = tags

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