Amazon SageMaker
Developer Guide

The AWS Documentation website is getting a new look!
Try it now and let us know what you think. Switch to the new look >>

You can return to the original look by selecting English in the language selector above.

Create a Pipeline Model

To create a pipeline model that can be deployed to an endpoint or used for a batch transform job, use the Amazon SageMaker console or the CreateModel operation.

To create an inference pipeline (console)

  1. Open the Amazon SageMaker console at


  2. Choose Models, and then choose Create models from the Inference group.

  3. On the Create model page, provide a model name, choose an IAM role, and, if you want to use a private VPC, specify VPC values.

                        The page for creating a model for an Inference Pipeline.
  4. To add information about the containers in the inference pipeline, choose Add container, then choose Next.

  5. Complete the fields for each container in the order that you want to execute them, up to the maximum of five. Complete the Container input options, , Location of inference code image, and, optionally, Location of model artifacts, Container host name, and Environmental variables fields. .

                        Creating a pipeline model with containers.

    The MyInferencePipelineModel page summarizes the settings for the containers that provide input for the model. If you provided the environment variables in a corresponding container definition, Amazon SageMaker shows them in the Environment variables field.

                        The summary of container settings for the pipeline model.