One Pipeline, Consistent Features: Azure ML Feature Store with Terraform

Feature Store architecture ensures that the same transformation runs in both offline (training) and online (inference) contexts, preventing silent accuracy degradation from training-serving skew. By combining Terraform infrastructure provisioning with Azure ML's feature management capabilities, teams can maintain feature consistency across the entire ML lifecycle while reducing operational overhead.