get_capacity_manager_metric_dimensions ¶

def get_capacity_manager_metric_dimensions(
    self,
    *,
    config_overrides: Optional[EC2ClientConfig] = None,
    group_by: Optional["capo_ec2.types.group_by_set.GroupBySet"] = None,
    filter_by: Optional[
        "capo_ec2.types.capacity_manager_condition_set.CapacityManagerConditionSet"
    ] = None,
    start_time: Optional[
        "capo_ec2.types.millisecond_date_time.MillisecondDateTime"
    ] = None,
    end_time: Optional[
        "capo_ec2.types.millisecond_date_time.MillisecondDateTime"
    ] = None,
    metric_names: Optional["capo_ec2.types.metric_set.MetricSet"] = None,
    max_results: Optional["capo_ec2.types.max_results.MaxResults"] = None,
    next_token: Optional["capo_ec2.types.next_token.NextToken"] = None,
    dry_run: Optional["capo_ec2.types.boolean.Boolean"] = None,
) -> "capo_ec2.types.get_capacity_manager_metric_dimensions_result.GetCapacityManagerMetricDimensionsResult":
    """<p> Retrieves the available dimension values for capacity metrics within a specified time range. This is useful for discovering what accounts, regions, instance families, and other dimensions have data available for filtering and grouping. </p>

    Args:
        group_by: <p> The dimensions to group by when retrieving available dimension values. This determines which dimension combinations are returned. Required parameter. </p>
        filter_by: <p> Conditions to filter which dimension values are returned. Each filter specifies a dimension, comparison operator, and values to match against. </p>
        start_time: <p> The start time for the dimension query, in ISO 8601 format. Only dimensions with data in this time range will be returned. </p>
        end_time: <p> The end time for the dimension query, in ISO 8601 format. Only dimensions with data in this time range will be returned. </p>
        metric_names: <p> The metric names to use as an additional filter when retrieving dimensions. Only dimensions that have data for these metrics will be returned. Required parameter with maximum size of 1 for v1. </p>
        max_results: <p> The maximum number of dimension combinations to return. Valid range is 1 to 1000. Use with NextToken for pagination. </p>
        next_token: <p> The token for the next page of results. Use this value in a subsequent call to retrieve additional dimension values. </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.get_capacity_manager_metric_dimensions_request.GetCapacityManagerMetricDimensionsRequest]",
    ) -> OperationResponse[
        "capo_ec2.types.get_capacity_manager_metric_dimensions_result.GetCapacityManagerMetricDimensionsResult"
    ]:
        import capo_ec2._operations.amazon_ec2.get_capacity_manager_metric_dimensions

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetCapacityManagerMetricDimensions")
    )
    input_: capo_ec2.types.get_capacity_manager_metric_dimensions_request.GetCapacityManagerMetricDimensionsRequest = {}
    if group_by is not None:
        input_["group_by"] = group_by
    if filter_by is not None:
        input_["filter_by"] = filter_by
    if start_time is not None:
        input_["start_time"] = start_time
    if end_time is not None:
        input_["end_time"] = end_time
    if metric_names is not None:
        input_["metric_names"] = metric_names
    if max_results is not None:
        input_["max_results"] = max_results
    if next_token is not None:
        input_["next_token"] = next_token
    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