Implement a secure MLOps platform based on Terraform and GitHub

Machine learning operations (MLOps) is the combination of people, processes, and technology to productionize ML use cases efficiently. To achieve this, enterprise customers must develop MLOps platforms to support reproducibility, robustness, and end-to-end observability of the ML use case’s lifecycle. Those platforms are based on a multi-account setup by adopting strict security constraints, development best practices such as automatic deployment using continuous integration and delivery (CI/CD) technologies, and permitting users to interact only by committing changes to code repositories. For more information about MLOps best practices, refer to the MLOps foundation roadmap for enterprises with Amazon SageMaker.

Terraform by HashiCorp has been embraced by many customers as the main infrastructure as code (IaC) approach to develop, build, deploy, and standardize AWS infrastructure for multi-cloud solutions. Furthermore, development repositories and CI/CD technologies such as GitHub and GitHub Actions, respectively, have been adopted widely by the DevOps and MLOps ...