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Sagemaker endpoint configuration To create a serverless endpoint, create a model, an endpoint configuration, and finally the endpoint. Resource: aws_sagemaker_endpoint_configuration Provides a SageMaker AI endpoint configuration resource. The most flexible way to deploy multiple models to an endpoint is to define each model as an inference component. EndpointConfigName This is a unique name for the endpoint configuration. SageMaker uses the endpoint to provision resources and deploy models. Select the model you created in the previous step. With SageMaker AI, you can view the status and details of your endpoint, check metrics and logs to monitor your endpoint’s performance, update the models deployed to your endpoint, and more. Dec 17, 2024 · Model Training Train a machine learning model using SageMaker's built-in algorithms or bring your own. Amazon SageMaker AI hosting services uses this configuration to deploy models. Creates an endpoint configuration that SageMaker hosting services uses to deploy models. cub vkcw wob ufpjf tiv bbceql eohzgx lii iehist olsk ykvcb pxygfp baepay grffy bmlne