add_application_cloud_watch_logging_option ¶

def add_application_cloud_watch_logging_option(
    self,
    application_name: "capo_kinesis_analytics.types.application_name.ApplicationName",
    current_application_version_id: "capo_kinesis_analytics.types.application_version_id.ApplicationVersionId",
    cloud_watch_logging_option: "capo_kinesis_analytics.types.cloud_watch_logging_option.CloudWatchLoggingOption",
    *,
    config_overrides: Optional[KinesisAnalyticsClientConfig] = None,
) -> "capo_kinesis_analytics.types.add_application_cloud_watch_logging_option_response.AddApplicationCloudWatchLoggingOptionResponse":
    """<note> <p>This documentation is for version 1 of the Amazon Kinesis Data Analytics API, which only supports SQL applications. Version 2 of the API supports SQL and Java applications. For more information about version 2, see <a href="/kinesisanalytics/latest/apiv2/Welcome.html">Amazon Kinesis Data Analytics API V2 Documentation</a>.</p> </note> <p>Adds a CloudWatch log stream to monitor application configuration errors. For more information about using CloudWatch log streams with Amazon Kinesis Analytics applications, see <a href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working with Amazon CloudWatch Logs</a>.</p>

    Args:
        application_name: <p>The Kinesis Analytics application name.</p>
        current_application_version_id: <p>The version ID of the Kinesis Analytics application.</p>
        cloud_watch_logging_option: <p>Provides the CloudWatch log stream Amazon Resource Name (ARN) and the IAM role ARN. Note: To write application messages to CloudWatch, the IAM role that is used must have the <code>PutLogEvents</code> policy action enabled.</p>

    Raises:
        capo_kinesis_analytics.errors.concurrent_modification_exception.ConcurrentModificationException: <p>Exception thrown as a result of concurrent modification to an application. For example, two individuals attempting to edit the same application at the same time.</p>
        capo_kinesis_analytics.errors.invalid_argument_exception.InvalidArgumentException: <p>Specified input parameter value is invalid.</p>
        capo_kinesis_analytics.errors.resource_in_use_exception.ResourceInUseException: <p>Application is not available for this operation.</p>
        capo_kinesis_analytics.errors.resource_not_found_exception.ResourceNotFoundException: <p>Specified application can't be found.</p>
        capo_kinesis_analytics.errors.unsupported_operation_exception.UnsupportedOperationException: <p>The request was rejected because a specified parameter is not supported or a specified resource is not valid for this operation. </p>
        capo_kinesis_analytics.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_kinesis_analytics.types.add_application_cloud_watch_logging_option_request.AddApplicationCloudWatchLoggingOptionRequest]",
    ) -> OperationResponse[
        "capo_kinesis_analytics.types.add_application_cloud_watch_logging_option_response.AddApplicationCloudWatchLoggingOptionResponse"
    ]:
        import capo_kinesis_analytics._operations.kinesis_analytics_20150814.add_application_cloud_watch_logging_option

        output, http_response = (
            capo_kinesis_analytics._operations.kinesis_analytics_20150814.add_application_cloud_watch_logging_option.add_application_cloud_watch_logging_option(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("AddApplicationCloudWatchLoggingOption")
    )
    input_: capo_kinesis_analytics.types.add_application_cloud_watch_logging_option_request.AddApplicationCloudWatchLoggingOptionRequest = {
        "application_name": application_name,
        "current_application_version_id": current_application_version_id,
        "cloud_watch_logging_option": cloud_watch_logging_option,
    }

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