Deploy shadow ML models in Amazon SageMaker

Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. SageMaker accelerates innovation within your organization by providing purpose-built tools for every step of ML development, including labeling, data preparation, feature engineering, statistical bias detection, AutoML, training, tuning, hosting, explainability, monitoring, and workflow automation. You can use a variety of techniques to deploy new ML models to production, so choosing the right strategy is an important decision. You must weigh the options in terms of the impact of change on the system and on the end users. In this post, we show you how to deploy using a shadow deployment strategy.