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describe_global_clusters

describe_global_clusters(
    *,
    config_overrides: Optional[RDSClientConfig] = None,
    global_cluster_identifier: Optional[GlobalClusterIdentifier] = None,
    filters: Optional[FilterList] = None,
    max_records: Optional[IntegerOptional] = None,
    marker: Optional[String] = None,
) -> GlobalClustersMessage

Returns information about Aurora global database clusters. This API supports pagination.

For more information on Amazon Aurora, see What is Amazon Aurora? in the Amazon Aurora User Guide.

This action only applies to Aurora DB clusters.

Parameters:

  • global_cluster_identifier (Optional[GlobalClusterIdentifier], default: None ) –

    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.

    Constraints:

    • If supplied, must match an existing DBClusterIdentifier.

  • filters (Optional[FilterList], default: None ) –

    A filter that specifies one or more global database clusters to describe. This parameter is case-sensitive.

    Currently, the only supported filter is region.

    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.

  • max_records (Optional[IntegerOptional], default: None ) –

    The maximum number of records to include in the response. If more records exist than the specified MaxRecords value, a pagination token called a marker is included in the response so that you can retrieve the remaining results.

    Default: 100

    Constraints: Minimum 20, maximum 100.

  • marker (Optional[String], default: None ) –

    An optional pagination token provided by a previous DescribeGlobalClusters request. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by MaxRecords.

Raises:

Examples:

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

>>> client.describe_global_clusters()
Source code in docs_src/capo_rds/_services/rds.py
def describe_global_clusters(
    self,
    *,
    config_overrides: Optional[RDSClientConfig] = 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.

        >>> client.describe_global_clusters()
    """

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

        output, http_response = (
            capo_rds._operations.amazon_rd_sv19.describe_global_clusters.describe_global_clusters(
                req.options, req.input
            )
        )
        return OperationResponse(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 = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output