[ aws . sagemaker ]

describe-endpoint-config

Description

Returns the description of an endpoint configuration created using the CreateEndpointConfig API.

See also: AWS API Documentation

See ‘aws help’ for descriptions of global parameters.

Synopsis

  describe-endpoint-config
--endpoint-config-name <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--cli-auto-prompt <value>]

Options

--endpoint-config-name (string)

The name of the endpoint configuration.

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

--cli-auto-prompt (boolean) Automatically prompt for CLI input parameters.

See ‘aws help’ for descriptions of global parameters.

Output

EndpointConfigName -> (string)

Name of the Amazon SageMaker endpoint configuration.

EndpointConfigArn -> (string)

The Amazon Resource Name (ARN) of the endpoint configuration.

ProductionVariants -> (list)

An array of ProductionVariant objects, one for each model that you want to host at this endpoint.

(structure)

Identifies a model that you want to host and the resources to deploy for hosting it. If you are deploying multiple models, tell Amazon SageMaker how to distribute traffic among the models by specifying variant weights.

VariantName -> (string)

The name of the production variant.

ModelName -> (string)

The name of the model that you want to host. This is the name that you specified when creating the model.

InitialInstanceCount -> (integer)

Number of instances to launch initially.

InstanceType -> (string)

The ML compute instance type.

InitialVariantWeight -> (float)

Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.

AcceleratorType -> (string)

The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker .

DataCaptureConfig -> (structure)

EnableCapture -> (boolean)

InitialSamplingPercentage -> (integer)

DestinationS3Uri -> (string)

KmsKeyId -> (string)

CaptureOptions -> (list)

(structure)

CaptureMode -> (string)

CaptureContentTypeHeader -> (structure)

CsvContentTypes -> (list)

(string)

JsonContentTypes -> (list)

(string)

KmsKeyId -> (string)

AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.

CreationTime -> (timestamp)

A timestamp that shows when the endpoint configuration was created.