DeleteMLEndpoint - Neptune Data API
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

DeleteMLEndpoint

Cancels the creation of a Neptune ML inference endpoint. See Managing inference endpoints using the endpoints command.

When invoking this operation in a Neptune cluster that has IAM authentication enabled, the IAM user or role making the request must have a policy attached that allows the neptune-db:DeleteMLEndpoint IAM action in that cluster.

Request Syntax

DELETE /ml/endpoints/id?clean=clean&neptuneIamRoleArn=neptuneIamRoleArn HTTP/1.1

URI Request Parameters

The request uses the following URI parameters.

clean

If this flag is set to TRUE, all Neptune ML S3 artifacts should be deleted when the job is stopped. The default is FALSE.

id

The unique identifier of the inference endpoint.

Required: Yes

neptuneIamRoleArn

The ARN of an IAM role providing Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will be thrown.

Request Body

The request does not have a request body.

Response Syntax

HTTP/1.1 200 Content-type: application/json { "status": "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.

status

The status of the cancellation.

Type: String

Errors

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

BadRequestException

Raised when a request is submitted that cannot be processed.

HTTP Status Code: 400

ClientTimeoutException

Raised when a request timed out in the client.

HTTP Status Code: 408

ConstraintViolationException

Raised when a value in a request field did not satisfy required constraints.

HTTP Status Code: 400

IllegalArgumentException

Raised when an argument in a request is not supported.

HTTP Status Code: 400

InvalidArgumentException

Raised when an argument in a request has an invalid value.

HTTP Status Code: 400

InvalidParameterException

Raised when a parameter value is not valid.

HTTP Status Code: 400

MissingParameterException

Raised when a required parameter is missing.

HTTP Status Code: 400

MLResourceNotFoundException

Raised when a specified machine-learning resource could not be found.

HTTP Status Code: 404

PreconditionsFailedException

Raised when a precondition for processing a request is not satisfied.

HTTP Status Code: 400

TooManyRequestsException

Raised when the number of requests being processed exceeds the limit.

HTTP Status Code: 429

UnsupportedOperationException

Raised when a request attempts to initiate an operation that is not supported.

HTTP Status Code: 400

See Also

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