enable_enhanced_monitoring ¶

def enable_enhanced_monitoring(
    self,
    shard_level_metrics: "capo_kinesis.types.metrics_name_list.MetricsNameList",
    *,
    config_overrides: Optional[KinesisClientConfig] = None,
    stream_name: Optional["capo_kinesis.types.stream_name.StreamName"] = None,
    stream_arn: Optional["capo_kinesis.types.stream_arn.StreamARN"] = None,
    stream_id: Optional["capo_kinesis.types.stream_id.StreamId"] = None,
) -> "capo_kinesis.types.enhanced_monitoring_output.EnhancedMonitoringOutput":
    """<p>Enables enhanced Kinesis data stream monitoring for shard-level metrics.</p> <note> <p>When invoking this API, you must use either the <code>StreamARN</code> or the <code>StreamName</code> parameter, or both. It is recommended that you use the <code>StreamARN</code> input parameter when you invoke this API.</p> </note>

    Args:
        stream_name: <p>The name of the stream for which to enable enhanced monitoring.</p>
        shard_level_metrics: <p>List of shard-level metrics to enable.</p> <p>The following are the valid shard-level metrics. The value "<code>ALL</code>" enables every metric.</p> <ul> <li> <p> <code>IncomingBytes</code> </p> </li> <li> <p> <code>IncomingRecords</code> </p> </li> <li> <p> <code>OutgoingBytes</code> </p> </li> <li> <p> <code>OutgoingRecords</code> </p> </li> <li> <p> <code>WriteProvisionedThroughputExceeded</code> </p> </li> <li> <p> <code>ReadProvisionedThroughputExceeded</code> </p> </li> <li> <p> <code>IteratorAgeMilliseconds</code> </p> </li> <li> <p> <code>ALL</code> </p> </li> </ul> <p>For more information, see <a href="https://docs.aws.amazon.com/kinesis/latest/dev/monitoring-with-cloudwatch.html">Monitoring the Amazon Kinesis Data Streams Service with Amazon CloudWatch</a> in the <i>Amazon Kinesis Data Streams Developer Guide</i>.</p>
        stream_arn: <p>The ARN of the stream.</p>
        stream_id: <p>Not Implemented. Reserved for future use.</p>

    Raises:
        capo_kinesis.errors.access_denied_exception.AccessDeniedException: <p>Specifies that you do not have the permissions required to perform this operation.</p>
        capo_kinesis.errors.invalid_argument_exception.InvalidArgumentException: <p>A specified parameter exceeds its restrictions, is not supported, or can't be used. For more information, see the returned message.</p>
        capo_kinesis.errors.limit_exceeded_exception.LimitExceededException: <p>The requested resource exceeds the maximum number allowed, or the number of concurrent stream requests exceeds the maximum number allowed. </p>
        capo_kinesis.errors.resource_in_use_exception.ResourceInUseException: <p>The resource is not available for this operation. For successful operation, the resource must be in the <code>ACTIVE</code> state.</p>
        capo_kinesis.errors.resource_not_found_exception.ResourceNotFoundException: <p>The requested resource could not be found. The stream might not be specified correctly.</p>
        capo_kinesis.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_kinesis.types.enable_enhanced_monitoring_input.EnableEnhancedMonitoringInput]",
    ) -> OperationResponse[
        "capo_kinesis.types.enhanced_monitoring_output.EnhancedMonitoringOutput"
    ]:
        import capo_kinesis._operations.kinesis_20131202.enable_enhanced_monitoring

        output, http_response = (
            capo_kinesis._operations.kinesis_20131202.enable_enhanced_monitoring.enable_enhanced_monitoring(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("EnableEnhancedMonitoring")
    )
    input_: capo_kinesis.types.enable_enhanced_monitoring_input.EnableEnhancedMonitoringInput = {
        "shard_level_metrics": shard_level_metrics
    }
    if stream_name is not None:
        input_["stream_name"] = stream_name
    if stream_arn is not None:
        input_["stream_arn"] = stream_arn
    if stream_id is not None:
        input_["stream_id"] = stream_id

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