Deployment Considerations

Cloudera Data Science Workbench does not currently support high availability for models. Additionally, there can only be one active deployment per model at any given time. This means you should plan for model downtime if you want to deploy a new build of the model or re-deploy with more/less replicas.

Keep in mind that models that have been developed and trained using Cloudera Data Science Workbench are essentially Python/R code that can easily be persisted and exported to external environments using popular serialization formats such as Pickle, PMML, ONNX, and so on.