describe_global_clusters async ¶

async def describe_global_clusters(
    self,
    *,
    config_overrides: Optional[AsyncRDSClientConfig] = None,
    global_cluster_identifier: Optional[
        "capo_rds.types.global_cluster_identifier.GlobalClusterIdentifier"
    ] = None,
    filters: Optional["capo_rds.types.filter_list.FilterList"] = None,
    max_records: Optional["capo_rds.types.integer_optional.IntegerOptional"] = None,
    marker: Optional["capo_rds.types.string.String"] = None,
) -> "capo_rds.types.global_clusters_message.GlobalClustersMessage":
    """<p>Returns information about Aurora global database clusters. This API supports pagination.</p> <p>For more information on Amazon Aurora, see <a href="https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_AuroraOverview.html"> What is Amazon Aurora?</a> in the <i>Amazon Aurora User Guide</i>.</p> <note> <p>This action only applies to Aurora DB clusters.</p> </note>

    Args:
        global_cluster_identifier: <p>The user-supplied DB cluster identifier. If this parameter is specified, information from only the specific DB cluster is returned. This parameter isn't case-sensitive.</p> <p>Constraints:</p> <ul> <li> <p>If supplied, must match an existing DBClusterIdentifier.</p> </li> </ul>
        filters: <p>A filter that specifies one or more global database clusters to describe. This parameter is case-sensitive.</p> <p>Currently, the only supported filter is <code>region</code>.</p> <p>If used, the request returns information about any global cluster with at least one member (primary or secondary) in the specified Amazon Web Services Regions.</p>
        max_records: <p>The maximum number of records to include in the response. If more records exist than the specified <code>MaxRecords</code> value, a pagination token called a marker is included in the response so that you can retrieve the remaining results.</p> <p>Default: 100</p> <p>Constraints: Minimum 20, maximum 100.</p>
        marker: <p>An optional pagination token provided by a previous <code>DescribeGlobalClusters</code> request. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by <code>MaxRecords</code>.</p>

    Raises:
        capo_rds.errors.global_cluster_not_found_fault.GlobalClusterNotFoundFault: <p>The <code>GlobalClusterIdentifier</code> doesn't refer to an existing global database cluster.</p>
        capo_rds.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        To describe global DB clusters
        The following example lists Aurora global DB clusters in the current AWS Region.

        >>> await client.describe_global_clusters()
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_rds.types.describe_global_clusters_message.DescribeGlobalClustersMessage]",
    ) -> AsyncOperationResponse[
        "capo_rds.types.global_clusters_message.GlobalClustersMessage"
    ]:
        import capo_rds._operations.amazon_rd_sv19.describe_global_clusters

        (
            output,
            http_response,
        ) = await capo_rds._operations.amazon_rd_sv19.describe_global_clusters.async_describe_global_clusters(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DescribeGlobalClusters")
    )
    input_: capo_rds.types.describe_global_clusters_message.DescribeGlobalClustersMessage = {}
    if global_cluster_identifier is not None:
        input_["global_cluster_identifier"] = global_cluster_identifier
    if filters is not None:
        input_["filters"] = filters
    if max_records is not None:
        input_["max_records"] = max_records
    if marker is not None:
        input_["marker"] = marker

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output