get_rds_database_recommendation_projected_metrics ¶

def get_rds_database_recommendation_projected_metrics(
    self,
    resource_arn: "capo_compute_optimizer.types.resource_arn.ResourceArn",
    stat: "capo_compute_optimizer.types.metric_statistic.MetricStatistic",
    period: "capo_compute_optimizer.types.period.Period",
    start_time: "capo_compute_optimizer.types.timestamp.Timestamp",
    end_time: "capo_compute_optimizer.types.timestamp.Timestamp",
    *,
    config_overrides: Optional[ComputeOptimizerClientConfig] = None,
    recommendation_preferences: Optional[
        "capo_compute_optimizer.types.recommendation_preferences.RecommendationPreferences"
    ] = None,
) -> "capo_compute_optimizer.types.get_rds_database_recommendation_projected_metrics_response.GetRDSDatabaseRecommendationProjectedMetricsResponse":
    """<p> Returns the projected metrics of Aurora and RDS database recommendations. </p>

    Args:
        resource_arn: <p> The ARN that identifies the Amazon Aurora or RDS database. </p> <p> The following is the format of the ARN: </p> <p> <code>arn:aws:rds:{region}:{accountId}:db:{resourceName}</code> </p>
        stat: <p> The statistic of the projected metrics. </p>
        period: <p> The granularity, in seconds, of the projected metrics data points. </p>
        start_time: <p> The timestamp of the first projected metrics data point to return. </p>
        end_time: <p> The timestamp of the last projected metrics data point to return. </p>

    Raises:
        capo_compute_optimizer.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_compute_optimizer.errors.internal_server_exception.InternalServerException: <p>An internal error has occurred. Try your call again.</p>
        capo_compute_optimizer.errors.invalid_parameter_value_exception.InvalidParameterValueException: <p>The value supplied for the input parameter is out of range or not valid.</p>
        capo_compute_optimizer.errors.missing_authentication_token.MissingAuthenticationToken: <p>The request must contain either a valid (registered) Amazon Web Services access key ID or X.509 certificate.</p>
        capo_compute_optimizer.errors.opt_in_required_exception.OptInRequiredException: <p>The account is not opted in to Compute Optimizer.</p>
        capo_compute_optimizer.errors.resource_not_found_exception.ResourceNotFoundException: <p>A resource that is required for the action doesn't exist.</p>
        capo_compute_optimizer.errors.service_unavailable_exception.ServiceUnavailableException: <p>The request has failed due to a temporary failure of the server.</p>
        capo_compute_optimizer.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_compute_optimizer.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_compute_optimizer.types.get_rds_database_recommendation_projected_metrics_request.GetRDSDatabaseRecommendationProjectedMetricsRequest]",
    ) -> OperationResponse[
        "capo_compute_optimizer.types.get_rds_database_recommendation_projected_metrics_response.GetRDSDatabaseRecommendationProjectedMetricsResponse"
    ]:
        import capo_compute_optimizer._operations.compute_optimizer_service.get_rds_database_recommendation_projected_metrics

        output, http_response = (
            capo_compute_optimizer._operations.compute_optimizer_service.get_rds_database_recommendation_projected_metrics.get_rds_database_recommendation_projected_metrics(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("GetRDSDatabaseRecommendationProjectedMetrics"),
    )
    input_: capo_compute_optimizer.types.get_rds_database_recommendation_projected_metrics_request.GetRDSDatabaseRecommendationProjectedMetricsRequest = {
        "resource_arn": resource_arn,
        "stat": stat,
        "period": period,
        "start_time": start_time,
        "end_time": end_time,
    }
    if recommendation_preferences is not None:
        input_["recommendation_preferences"] = recommendation_preferences

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