Deploy an Inference Pipeline - Amazon SageMaker
docs.aws.amazon.com › sagemaker › latestRSS. An inference pipeline is a Amazon SageMaker model that is composed of a linear sequence of two to fifteen containers that process requests for inferences on data. You use an inference pipeline to define and deploy any combination of pretrained SageMaker built-in algorithms and your own custom algorithms packaged in Docker containers. You can use an inference pipeline to combine preprocessing, predictions, and post-processing data science tasks.
Deploy Models for Inference - Amazon SageMaker
docs.aws.amazon.com › sagemaker › latestSageMaker provides features to manage resources and optimize inference performance when deploying machine learning models. For guidance on using inference pipelines, compiling and deploying models with Neo, Elastic Inference, and automatic model scaling, see the following topics. To manage data processing and real-time predictions or to process ...