Automating ML Deployments: Terraform Brings Infrastructure as Code to Azure ML

As machine learning models transition to production, deployment complexity becomes a critical operational challenge. This guide shows how Terraform and Azure ML Online Endpoints enable automated model rollouts with traffic splitting and canary deployments, significantly reducing deployment risk. By treating ML infrastructure as code, organizations gain reproducibility, version control, and safer production strategies.