CreateEndpointConfig
Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy
models. In
the configuration, you identify one or more models, created using the
CreateModel
API, to deploy and the resources that you want Amazon SageMaker to
provision. Then you call the CreateEndpoint API.
Use this API if you want to use Amazon SageMaker hosting services to deploy models into production.
In the request, you define a ProductionVariant
, for each model that you
want to deploy. Each ProductionVariant
parameter also describes the
resources that you want Amazon SageMaker to provision. This includes the number and
type of ML
compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight
to
specify how much traffic you want to allocate to each model. For example, suppose
that
you want to host two models, A and B, and you assign traffic weight 2 for model A
and 1
for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and
one-third to
model B.
For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).
When you call CreateEndpoint, a load call is made to DynamoDB to
verify that your endpoint configuration exists. When you read data from a DynamoDB
table supporting
Eventually Consistent Reads
, the response might not
reflect the results of a recently completed write operation. The response might
include some stale data. If the dependent entities are not yet in DynamoDB, this
causes a validation error. If you repeat your read request after a short time, the
response should return the latest data. So retry logic is recommended to handle
these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
Request Syntax
{
"DataCaptureConfig": {
"CaptureContentTypeHeader": {
"CsvContentTypes": [ "string
" ],
"JsonContentTypes": [ "string
" ]
},
"CaptureOptions": [
{
"CaptureMode": "string
"
}
],
"DestinationS3Uri": "string
",
"EnableCapture": boolean
,
"InitialSamplingPercentage": number
,
"KmsKeyId": "string
"
},
"EndpointConfigName": "string
",
"KmsKeyId": "string
",
"ProductionVariants": [
{
"AcceleratorType": "string
",
"CoreDumpConfig": {
"DestinationS3Uri": "string
",
"KmsKeyId": "string
"
},
"InitialInstanceCount": number
,
"InitialVariantWeight": number
,
"InstanceType": "string
",
"ModelName": "string
",
"VariantName": "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.
- DataCaptureConfig
-
Type: DataCaptureConfig object
Required: No
- EndpointConfigName
-
The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
Type: String
Length Constraints: Maximum length of 63.
Pattern:
^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}
Required: Yes
- KmsKeyId
-
The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
-
Key ID:
1234abcd-12ab-34cd-56ef-1234567890ab
-
Key ARN:
arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
-
Alias name:
alias/ExampleAlias
-
Alias name ARN:
arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your
CreateEndpoint
,UpdateEndpoint
requests. For more information, refer to the AWS Key Management Service section Using Key Policies in AWS KMSNote Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a
KmsKeyId
when using an instance type with local storage. If any of the models that you specify in theProductionVariants
parameter use nitro-based instances with local storage, do not specify a value for theKmsKeyId
parameter. If you specify a value forKmsKeyId
when using any nitro-based instances with local storage, the call toCreateEndpointConfig
fails.For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
Type: String
Length Constraints: Maximum length of 2048.
Pattern:
.*
Required: No
-
- ProductionVariants
-
An list of
ProductionVariant
objects, one for each model that you want to host at this endpoint.Type: Array of ProductionVariant objects
Array Members: Minimum number of 1 item. Maximum number of 10 items.
Required: Yes
- Tags
-
An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
Type: Array of Tag objects
Array Members: Minimum number of 0 items. Maximum number of 50 items.
Required: No
Response Syntax
{
"EndpointConfigArn": "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.
- EndpointConfigArn
-
The Amazon Resource Name (ARN) of the endpoint configuration.
Type: String
Length Constraints: Minimum length of 20. Maximum length of 2048.
Pattern:
arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:endpoint-config/.*
Errors
For information about the errors that are common to all actions, see Common Errors.
- ResourceLimitExceeded
-
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: