Run ensemble ML models on Amazon SageMaker

Model deployment in machine learning (ML) is becoming increasingly complex. You want to deploy not just one ML model but large groups of ML models represented as ensemble workflows. These workflows are comprised of multiple ML models. Productionizing these ML models is challenging because you need to adhere to various performance and latency requirements. Amazon SageMaker supports single-instance ensembles with Triton Inference Server.