Mar 23, 2023

Use AzureML registries to share ML pipelines and models across teams and workspaces​​

  • Train a model in the “dev” workspace and deploy it to “test” and “prod” workspaces, while tracking lineage across the entire lifecycle​
  • Publish environments and components to Registries and use them to submit pipeline jobs to different workspaces (with full reproducibility)​
  • Discover and reuse training tools, data processing utilities, and pretrained models in your organization​

Share models, components, and environments across workspaces with registries (preview) — Azure Machine Learning | Microsoft Learn