Secure multi-account model deployment with Amazon SageMaker: Part 1

Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. Although Studio provides all the tools you need to take your models from experimentation to production, you need a robust and secure model deployment process. This process must fulfill your organization's operational and security requirements. Amazon SageMaker and Studio provide a wide range of specialized functionality for building highly secure, scalable, and flexible MLOps platforms to cover your model deployment use cases and requirements. Three SageMaker services, SageMaker Pipelines, SageMaker Projects, and SageMaker Model Registry, build a foundation to implement enterprise-grade secure multi-account model deployment workflow.