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Build a custom portal with embedded Amazon SageMaker AI MLflow Apps | Amazon Web Services
In this post, you learn how to build a custom portal with embedded SageMaker AI MLflow Apps UI. You walk through the architecture pattern behind a React front end paired with a Flask reverse proxy that handles AWS Signature Version 4 (SigV4) authentication, deploy the entire stack through the AWS Cloud Development Kit (AWS CDK), validate the deployment, and review security considerations and cleanup procedures.
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Streamline external access to Amazon SageMaker MLflow using a REST API proxy | Amazon Web Services
In this post, we demonstrate how to build a secure Flask-based MLflow proxy service that provides HTTPS access to Amazon SageMaker MLflow without requiring the MLflow SDK. This…
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Build a custom portal with embedded Amazon SageMaker AI MLflow Apps | Amazon Web Services
In this post, you learn how to build a custom portal with embedded SageMaker AI MLflow Apps UI. You walk through the architecture pattern behind a React front end paired with a…