modify_current_db_cluster_capacity async ¶

async def modify_current_db_cluster_capacity(
    self,
    *,
    config_overrides: Optional[AsyncRDSClientConfig] = None,
    db_cluster_identifier: Optional["capo_rds.types.string.String"] = None,
    capacity: Optional["capo_rds.types.integer_optional.IntegerOptional"] = None,
    seconds_before_timeout: Optional[
        "capo_rds.types.integer_optional.IntegerOptional"
    ] = None,
    timeout_action: Optional["capo_rds.types.string.String"] = None,
) -> "capo_rds.types.db_cluster_capacity_info.DBClusterCapacityInfo":
    """<p>Set the capacity of an Aurora Serverless v1 DB cluster to a specific value.</p> <p>Aurora Serverless v1 scales seamlessly based on the workload on the DB cluster. In some cases, the capacity might not scale fast enough to meet a sudden change in workload, such as a large number of new transactions. Call <code>ModifyCurrentDBClusterCapacity</code> to set the capacity explicitly.</p> <p>After this call sets the DB cluster capacity, Aurora Serverless v1 can automatically scale the DB cluster based on the cooldown period for scaling up and the cooldown period for scaling down.</p> <p>For more information about Aurora Serverless v1, see <a href="https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/aurora-serverless.html">Using Amazon Aurora Serverless v1</a> in the <i>Amazon Aurora User Guide</i>.</p> <important> <p>If you call <code>ModifyCurrentDBClusterCapacity</code> with the default <code>TimeoutAction</code>, connections that prevent Aurora Serverless v1 from finding a scaling point might be dropped. For more information about scaling points, see <a href="https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/aurora-serverless.how-it-works.html#aurora-serverless.how-it-works.auto-scaling"> Autoscaling for Aurora Serverless v1</a> in the <i>Amazon Aurora User Guide</i>.</p> </important> <note> <p>This operation only applies to Aurora Serverless v1 DB clusters.</p> </note>

    Args:
        db_cluster_identifier: <p>The DB cluster identifier for the cluster being modified. This parameter isn't case-sensitive.</p> <p>Constraints:</p> <ul> <li> <p>Must match the identifier of an existing DB cluster.</p> </li> </ul>
        capacity: <p>The DB cluster capacity.</p> <p>When you change the capacity of a paused Aurora Serverless v1 DB cluster, it automatically resumes.</p> <p>Constraints:</p> <ul> <li> <p>For Aurora MySQL, valid capacity values are <code>1</code>, <code>2</code>, <code>4</code>, <code>8</code>, <code>16</code>, <code>32</code>, <code>64</code>, <code>128</code>, and <code>256</code>.</p> </li> <li> <p>For Aurora PostgreSQL, valid capacity values are <code>2</code>, <code>4</code>, <code>8</code>, <code>16</code>, <code>32</code>, <code>64</code>, <code>192</code>, and <code>384</code>.</p> </li> </ul>
        seconds_before_timeout: <p>The amount of time, in seconds, that Aurora Serverless v1 tries to find a scaling point to perform seamless scaling before enforcing the timeout action. The default is 300.</p> <p>Specify a value between 10 and 600 seconds.</p>
        timeout_action: <p>The action to take when the timeout is reached, either <code>ForceApplyCapacityChange</code> or <code>RollbackCapacityChange</code>.</p> <p> <code>ForceApplyCapacityChange</code>, the default, sets the capacity to the specified value as soon as possible.</p> <p> <code>RollbackCapacityChange</code> ignores the capacity change if a scaling point isn't found in the timeout period.</p>

    Raises:
        capo_rds.errors.db_cluster_not_found_fault.DBClusterNotFoundFault: <p> <code>DBClusterIdentifier</code> doesn't refer to an existing DB cluster.</p>
        capo_rds.errors.invalid_db_cluster_capacity_fault.InvalidDBClusterCapacityFault: <p> <code>Capacity</code> isn't a valid Aurora Serverless DB cluster capacity. Valid capacity values are <code>2</code>, <code>4</code>, <code>8</code>, <code>16</code>, <code>32</code>, <code>64</code>, <code>128</code>, and <code>256</code>.</p>
        capo_rds.errors.invalid_db_cluster_state_fault.InvalidDBClusterStateFault: <p>The requested operation can't be performed while the cluster is in this state.</p>
        capo_rds.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        To scale the capacity of an Aurora Serverless DB cluster
        The following example scales the capacity of an Aurora Serverless DB cluster to 8.

        >>> await client.modify_current_db_cluster_capacity(db_cluster_identifier='mydbcluster', capacity=8)
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_rds.types.modify_current_db_cluster_capacity_message.ModifyCurrentDBClusterCapacityMessage]",
    ) -> AsyncOperationResponse[
        "capo_rds.types.db_cluster_capacity_info.DBClusterCapacityInfo"
    ]:
        import capo_rds._operations.amazon_rd_sv19.modify_current_db_cluster_capacity

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ModifyCurrentDBClusterCapacity")
    )
    input_: capo_rds.types.modify_current_db_cluster_capacity_message.ModifyCurrentDBClusterCapacityMessage = {}
    if db_cluster_identifier is not None:
        input_["db_cluster_identifier"] = db_cluster_identifier
    if capacity is not None:
        input_["capacity"] = capacity
    if seconds_before_timeout is not None:
        input_["seconds_before_timeout"] = seconds_before_timeout
    if timeout_action is not None:
        input_["timeout_action"] = timeout_action

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