Build a custom portal with embedded Amazon SageMaker AI MLflow Apps
Quick Answer
This article guides you through building a custom portal using Amazon SageMaker and MLflow Apps, integrating a React front end with a Flask reverse proxy for AWS SigV4 authentication.
Quick Take
This article guides you through building a custom portal using Amazon SageMaker and MLflow Apps, integrating a React front end with a Flask reverse proxy for AWS SigV4 authentication. It covers deployment via AWS CDK, validation, security considerations, and cleanup procedures.
Key Points
- Integrate React front end with Flask for AWS SigV4 authentication.
- Deploy the entire stack using AWS Cloud Development Kit (CDK).
- Validate deployment and review security considerations.
- Includes cleanup procedures for efficient resource management.
Article Excerpt
From source RSS / original summaryIn 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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