AWS Amazon SageMaker Endpoint Configuration
This page shows how to write Terraform and CloudFormation for Amazon SageMaker Endpoint Configuration and write them securely.
aws_sagemaker_endpoint_configuration (Terraform)
The Endpoint Configuration in Amazon SageMaker can be configured in Terraform with the resource name aws_sagemaker_endpoint_configuration. The following sections describe 5 examples of how to use the resource and its parameters.
Example Usage from GitHub
resource "aws_sagemaker_endpoint_configuration" "invalid" {
name = "my-endpoint-config"
production_variants {
variant_name = "variant-1"
model_name = "name"
resource "aws_sagemaker_endpoint_configuration" "kms_key_arn_is_set" {
kms_key_arn = aws_kms_key.test_key.arn
production_variants {
model_name = aws_sagemaker_model.test_model.name
initial_instance_count = 1
resource "aws_sagemaker_endpoint_configuration" "kms_key_arn_is_set" {
kms_key_arn = aws_kms_key.test_key.arn
production_variants {
model_name = aws_sagemaker_model.test_model.name
initial_instance_count = 1
resource "aws_sagemaker_endpoint_configuration" "examplea" {
name = "my-endpoint-config"
kms_key_arn = aws_kms_key.examplea.arn
production_variants {
variant_name = "variant-1"
resource "aws_sagemaker_endpoint_configuration" "this" {
name = "rs-model-a-Staging"
production_variants {
model_name = aws_sagemaker_model.this.name
initial_instance_count = 1
Parameters
-
arnoptional computed - string -
idoptional computed - string -
kms_key_arnoptional - string -
nameoptional computed - string -
tagsoptional - map from string to string -
data_capture_configlist block-
destination_s3_urirequired - string -
enable_captureoptional - bool -
initial_sampling_percentagerequired - number -
kms_key_idoptional - string -
capture_content_type_headerlist block-
csv_content_typesoptional - set of string -
json_content_typesoptional - set of string
-
-
capture_optionslist block-
capture_moderequired - string
-
-
-
production_variantslist block-
accelerator_typeoptional - string -
initial_instance_countrequired - number -
initial_variant_weightoptional - number -
instance_typerequired - string -
model_namerequired - string -
variant_nameoptional computed - string
-
Explanation in Terraform Registry
Provides a SageMaker endpoint configuration resource.
AWS::SageMaker::EndpointConfig (CloudFormation)
The EndpointConfig in SageMaker can be configured in CloudFormation with the resource name AWS::SageMaker::EndpointConfig. The following sections describe how to use the resource and its parameters.
Example Usage from GitHub
An example could not be found in GitHub.
Parameters
-
DataCaptureConfigoptional - DataCaptureConfig -
ProductionVariantsrequired - List of ProductionVariant -
KmsKeyIdoptional - String -
AsyncInferenceConfigoptional - AsyncInferenceConfig -
EndpointConfigNameoptional - String -
Tagsoptional - List of Tag
Explanation in CloudFormation Registry
The
AWS::SageMaker::EndpointConfigresource creates a configuration for an Amazon SageMaker endpoint. For more information, see CreateEndpointConfig in the SageMaker Developer Guide.
Frequently asked questions
What is AWS Amazon SageMaker Endpoint Configuration?
AWS Amazon SageMaker Endpoint Configuration is a resource for Amazon SageMaker of Amazon Web Service. Settings can be wrote in Terraform and CloudFormation.
Where can I find the example code for the AWS Amazon SageMaker Endpoint Configuration?
For Terraform, the Cigna/confectionery, ffsclyh/config-lint and stelligent/config-lint source code examples are useful. See the Terraform Example section for further details.
