Managing SageMaker repository credentials with Secrets Manager - AWS Secrets Manager

Managing SageMaker repository credentials with Secrets Manager

SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. It also provides common machine learning algorithms that are optimized to run efficiently against extremely large data in a distributed environment. With native support for bring-your-own-algorithms and frameworks, SageMaker offers flexible distributed training options that adjust to your specific workflows. Deploy a model into a secure and scalable environment by launching it with a single click from the SageMaker console.

You can manage your private repositories credentials using Secrets Manager.

For more information, see Associate Git Repositories with Amazon SageMaker Notebook Instances.