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MLflow Model Serving on Azure Databricks

jhonw901227
New Contributor II

I know that in the documentation about model serving says.

  • The cluster is maintained as long as serving is enabled, even if no active model version exists. To terminate the serving cluster, disable model serving for the registered model.
  • The cluster is considered an all-purpose cluster, subject to all-purpose workload pricing.
  • Global init scripts are not run on serving clusters.

In order to try to save cost, I want to ask if someone know or has checked a way to start/stop those Job clusters via Scheduling feature in ADB?

Can we use same cluster for different model?

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