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batch_get_deployment_instances

batch_get_deployment_instances(
    deployment_id: DeploymentId,
    instance_ids: InstancesList,
    *,
    config_overrides: Optional[CodeDeployClientConfig] = None,
) -> BatchGetDeploymentInstancesOutput

This method works, but is deprecated. Use BatchGetDeploymentTargets instead.

Returns an array of one or more instances associated with a deployment. This method works with EC2/On-premises and Lambda compute platforms. The newer BatchGetDeploymentTargets works with all compute platforms. The maximum number of instances that can be returned is 25.

Parameters:

  • deployment_id (DeploymentId) –

    The unique ID of a deployment.

  • instance_ids (InstancesList) –

    The unique IDs of instances used in the deployment. The maximum number of instance IDs you can specify is 25.

Raises:

Source code in docs_src/capo_codedeploy/_services/code_deploy.py
def batch_get_deployment_instances(
    self,
    deployment_id: "capo_codedeploy.types.deployment_id.DeploymentId",
    instance_ids: "capo_codedeploy.types.instances_list.InstancesList",
    *,
    config_overrides: Optional[CodeDeployClientConfig] = None,
) -> "capo_codedeploy.types.batch_get_deployment_instances_output.BatchGetDeploymentInstancesOutput":
    """<note> <p> This method works, but is deprecated. Use <code>BatchGetDeploymentTargets</code> instead. </p> </note> <p> Returns an array of one or more instances associated with a deployment. This method works with EC2/On-premises and Lambda compute platforms. The newer <code>BatchGetDeploymentTargets</code> works with all compute platforms. The maximum number of instances that can be returned is 25.</p>

    Args:
        deployment_id: <p> The unique ID of a deployment. </p>
        instance_ids: <p>The unique IDs of instances used in the deployment. The maximum number of instance IDs you can specify is 25.</p>

    Raises:
        capo_codedeploy.errors.batch_limit_exceeded_exception.BatchLimitExceededException: <p>The maximum number of names or IDs allowed for this request (100) was exceeded.</p>
        capo_codedeploy.errors.deployment_does_not_exist_exception.DeploymentDoesNotExistException: <p>The deployment with the user or Amazon Web Services account does not exist.</p>
        capo_codedeploy.errors.deployment_id_required_exception.DeploymentIdRequiredException: <p>At least one deployment ID must be specified.</p>
        capo_codedeploy.errors.instance_id_required_exception.InstanceIdRequiredException: <p>The instance ID was not specified.</p>
        capo_codedeploy.errors.invalid_compute_platform_exception.InvalidComputePlatformException: <p>The computePlatform is invalid. The computePlatform should be <code>Lambda</code>, <code>Server</code>, or <code>ECS</code>.</p>
        capo_codedeploy.errors.invalid_deployment_id_exception.InvalidDeploymentIdException: <p>At least one of the deployment IDs was specified in an invalid format.</p>
        capo_codedeploy.errors.invalid_instance_name_exception.InvalidInstanceNameException: <p>The on-premises instance name was specified in an invalid format.</p>
        capo_codedeploy.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_codedeploy.types.batch_get_deployment_instances_input.BatchGetDeploymentInstancesInput]",
    ) -> OperationResponse[
        "capo_codedeploy.types.batch_get_deployment_instances_output.BatchGetDeploymentInstancesOutput"
    ]:
        import capo_codedeploy._operations.code_deploy_20141006.batch_get_deployment_instances

        output, http_response = (
            capo_codedeploy._operations.code_deploy_20141006.batch_get_deployment_instances.batch_get_deployment_instances(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("BatchGetDeploymentInstances")
    )
    input_: capo_codedeploy.types.batch_get_deployment_instances_input.BatchGetDeploymentInstancesInput = {
        "deployment_id": deployment_id,
        "instance_ids": instance_ids,
    }

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