From Experiment to Production: A Reliable Architecture for Version-Controlled MLOps
Red Hat, Wednesday, August 19th, 2026
Red Hat pairs OpenShift AI with Git-for-data versioning to fix the which-dataset-did-I-use problem in ML pipelines.
Red Hat argues that managing the data behind models is as hard as building the models themselves. The familiar failure is a shift in model performance or inconsistent analysis results, followed by uncertainty about which version of the dataset was used for a given training run or report.
Red Hat's new AI quickstart addresses that problem directly.
It combines the orchestration capability of Red Hat OpenShift AI with Git-for-data style versioning so datasets are tracked alongside code. The result is a reproducible path from experiment to production.