Production MLOps at GS Caltex with Amazon SageMaker Canvas, part 1

GS Caltex connects models built by process engineers in Amazon SageMaker Canvas to production workflows in Amazon SageMaker Pipelines, with ML engineers handling deployment and scheduled inference. The company automated the handoff so ML engineers now deploy models within a few hours instead of about a week, and it runs batch inference every 30 minutes, which it reports has meaningfully lowered inference costs. The post details the reference architecture, including reusing Data Wrangler preprocessing flows, registering and approving models in Model Registry, and scheduling runs with Amazon EventBridge.