Implement a secure MLOps platform based on Terraform and GitHub

This article provides a comprehensive guide to implementing a secure MLOps platform using Terraform, GitHub, and GitHub Actions, with a focus on Amazon SageMaker Projects.

• Introduces four custom SageMaker Project templates for different ML workflows:
  • LLM training and evaluation
  • Model building and training
  • Model building, training, and deployment
  • Pipeline promotion across environments
• Recommends a multi-account setup with three environments: experimentation, preproduction, and production
• Uses Terraform modules for infrastructure as code, covering areas like networking, security, and SageMaker
• Implements GitHub Actions for automated infrastructure deployment
• Provides detailed steps for bootstrapping AWS accounts, setting up GitHub organization, and deploying infrastructure

The solution offers a structured approach to MLOps, enabling reproducible, secure, and scalable machine learning workflows across different environments.