create_deployment_strategy ¶

def create_deployment_strategy(
    self,
    name: "capo_appconfig.types.name.Name",
    deployment_duration_in_minutes: "capo_appconfig.types.minutes_between0_and24_hours.MinutesBetween0And24Hours",
    growth_factor: "capo_appconfig.types.growth_factor.GrowthFactor",
    *,
    config_overrides: Optional[AppConfigClientConfig] = None,
    description: Optional["capo_appconfig.types.description.Description"] = None,
    final_bake_time_in_minutes: Optional[
        "capo_appconfig.types.minutes_between0_and24_hours.MinutesBetween0And24Hours"
    ] = None,
    growth_type: Optional["capo_appconfig.types.growth_type.GrowthType"] = None,
    replicate_to: Optional["capo_appconfig.types.replicate_to.ReplicateTo"] = None,
    tags: Optional["capo_appconfig.types.tag_map.TagMap"] = None,
) -> "capo_appconfig.types.deployment_strategy.DeploymentStrategy":
    """<p>Creates a deployment strategy that defines important criteria for rolling out your configuration to the designated targets. A deployment strategy includes the overall duration required, a percentage of targets to receive the deployment during each interval, an algorithm that defines how percentage grows, and bake time.</p>

    Args:
        name: <p>A name for the deployment strategy.</p>
        description: <p>A description of the deployment strategy.</p>
        deployment_duration_in_minutes: <p>Total amount of time for a deployment to last.</p> <note> <p>AppConfig Agent supports deploying feature flag or free-form configuration data to specific segments or individual users during a gradual rollout. Entity-based gradual deployments ensure that once a user or segment receives a configuration version, they continue to receive that same version throughout the deployment period, regardless of which compute resource serves their requests. For more information, see <a href="https://docs.aws.amazon.com/appconfig/latest/userguide/appconfig-agent-how-to-use.html#appconfig-entity-based-gradual-deployments">Using AppConfig Agent for user-based or entity-based gradual deployments</a> </p> </note>
        final_bake_time_in_minutes: <p>Specifies the amount of time AppConfig monitors for Amazon CloudWatch alarms after the configuration has been deployed to 100% of its targets, before considering the deployment to be complete. If an alarm is triggered during this time, AppConfig rolls back the deployment. You must configure permissions for AppConfig to roll back based on CloudWatch alarms. For more information, see <a href="https://docs.aws.amazon.com/appconfig/latest/userguide/getting-started-with-appconfig-cloudwatch-alarms-permissions.html">Configuring permissions for rollback based on Amazon CloudWatch alarms</a> in the <i>AppConfig User Guide</i>.</p>
        growth_factor: <p>The percentage of targets to receive a deployed configuration during each interval.</p>
        growth_type: <p>The algorithm used to define how percentage grows over time. AppConfig supports the following growth types:</p> <p> <b>Linear</b>: For this type, AppConfig processes the deployment by dividing the total number of targets by the value specified for <code>Step percentage</code>. For example, a linear deployment that uses a <code>Step percentage</code> of 10 deploys the configuration to 10 percent of the hosts. After those deployments are complete, the system deploys the configuration to the next 10 percent. This continues until 100% of the targets have successfully received the configuration.</p> <p> <b>Exponential</b>: For this type, AppConfig processes the deployment exponentially using the following formula: <code>G*(2^N)</code>. In this formula, <code>G</code> is the growth factor specified by the user and <code>N</code> is the number of steps until the configuration is deployed to all targets. For example, if you specify a growth factor of 2, then the system rolls out the configuration as follows:</p> <p> <code>2*(2^0)</code> </p> <p> <code>2*(2^1)</code> </p> <p> <code>2*(2^2)</code> </p> <p>Expressed numerically, the deployment rolls out as follows: 2% of the targets, 4% of the targets, 8% of the targets, and continues until the configuration has been deployed to all targets.</p>
        replicate_to: <p>Save the deployment strategy to a Systems Manager (SSM) document.</p>
        tags: <p>Metadata to assign to the deployment strategy. Tags help organize and categorize your AppConfig resources. Each tag consists of a key and an optional value, both of which you define.</p>

    Raises:
        capo_appconfig.errors.bad_request_exception.BadRequestException: <p>The input fails to satisfy the constraints specified by an Amazon Web Services service.</p>
        capo_appconfig.errors.internal_server_exception.InternalServerException: <p>There was an internal failure in the AppConfig service.</p>
        capo_appconfig.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The number of one more AppConfig resources exceeds the maximum allowed. Verify that your environment doesn't exceed the following service quotas:</p> <p>Applications: 100 max</p> <p>To resolve this issue, you can delete one or more resources and try again. Or, you can request a quota increase. For more information about quotas and to request an increase, see <a href="https://docs.aws.amazon.com/general/latest/gr/appconfig.html#limits_appconfig">Service quotas for AppConfig</a> in the Amazon Web Services General Reference.</p>
        capo_appconfig.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        To create a deployment strategy
        The following create-deployment-strategy example creates a deployment strategy called Example-Deployment that takes 15 minutes and deploys the configuration to 25% of the application at a time. The strategy is also copied to an SSM Document.

        >>> client.create_deployment_strategy(name='Example-Deployment', deployment_duration_in_minutes=15, growth_factor=25, replicate_to='SSM_DOCUMENT')
    """

    def _handler(
        req: "OperationRequest[capo_appconfig.types.create_deployment_strategy_request.CreateDeploymentStrategyRequest]",
    ) -> OperationResponse[
        "capo_appconfig.types.deployment_strategy.DeploymentStrategy"
    ]:
        import capo_appconfig._operations.amazon_app_config.create_deployment_strategy

        output, http_response = (
            capo_appconfig._operations.amazon_app_config.create_deployment_strategy.create_deployment_strategy(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateDeploymentStrategy")
    )
    input_: capo_appconfig.types.create_deployment_strategy_request.CreateDeploymentStrategyRequest = {
        "name": name,
        "deployment_duration_in_minutes": deployment_duration_in_minutes,
        "growth_factor": growth_factor,
    }
    if description is not None:
        input_["description"] = description
    if final_bake_time_in_minutes is not None:
        input_["final_bake_time_in_minutes"] = final_bake_time_in_minutes
    if growth_type is not None:
        input_["growth_type"] = growth_type
    if replicate_to is not None:
        input_["replicate_to"] = replicate_to
    if tags is not None:
        input_["tags"] = tags

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