CreateAutoMLJob - Amazon SageMaker


Creates an Autopilot job.

Find the best-performing model after you run an Autopilot job by calling DescribeAutoMLJob .

For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.

Request Syntax

{ "AutoMLJobConfig": { "CompletionCriteria": { "MaxAutoMLJobRuntimeInSeconds": number, "MaxCandidates": number, "MaxRuntimePerTrainingJobInSeconds": number }, "SecurityConfig": { "EnableInterContainerTrafficEncryption": boolean, "VolumeKmsKeyId": "string", "VpcConfig": { "SecurityGroupIds": [ "string" ], "Subnets": [ "string" ] } } }, "AutoMLJobName": "string", "AutoMLJobObjective": { "MetricName": "string" }, "GenerateCandidateDefinitionsOnly": boolean, "InputDataConfig": [ { "CompressionType": "string", "DataSource": { "S3DataSource": { "S3DataType": "string", "S3Uri": "string" } }, "TargetAttributeName": "string" } ], "ModelDeployConfig": { "AutoGenerateEndpointName": boolean, "EndpointName": "string" }, "OutputDataConfig": { "KmsKeyId": "string", "S3OutputPath": "string" }, "ProblemType": "string", "RoleArn": "string", "Tags": [ { "Key": "string", "Value": "string" } ] }

Request Parameters

For information about the parameters that are common to all actions, see Common Parameters.

The request accepts the following data in JSON format.


Contains CompletionCriteria and SecurityConfig settings for the AutoML job.

Type: AutoMLJobConfig object

Required: No


Identifies an Autopilot job. The name must be unique to your account and is case-insensitive.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 32.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,31}

Required: Yes


Defines the objective metric used to measure the predictive quality of an AutoML job. You provide an AutoMLJobObjective:MetricName and Autopilot infers whether to minimize or maximize it.

Type: AutoMLJobObjective object

Required: No


Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.

Type: Boolean

Required: No


An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition . Format(s) supported: CSV. Minimum of 500 rows.

Type: Array of AutoMLChannel objects

Array Members: Minimum number of 1 item. Maximum number of 20 items.

Required: Yes


Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

Type: ModelDeployConfig object

Required: No


Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.

Type: AutoMLOutputDataConfig object

Required: Yes


Defines the type of supervised learning available for the candidates. Options include: BinaryClassification, MulticlassClassification, and Regression. For more information, see Amazon SageMaker Autopilot problem types and algorithm support.

Type: String

Valid Values: BinaryClassification | MulticlassClassification | Regression

Required: No


The ARN of the role that is used to access the data.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws[a-z\-]*:iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+$

Required: Yes


Each tag consists of a key and an optional value. Tag keys must be unique per resource.

Type: Array of Tag objects

Array Members: Minimum number of 0 items. Maximum number of 50 items.

Required: No

Response Syntax

{ "AutoMLJobArn": "string" }

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.


The unique ARN assigned to the AutoML job when it is created.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 256.

Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:automl-job/.*


For information about the errors that are common to all actions, see Common Errors.


Resource being accessed is in use.

HTTP Status Code: 400


You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.

HTTP Status Code: 400

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: