Understand deployments in MLOps

In H2O MLOps, deployments are created when model version(s) are served for scoring. Models can be deployed to Dev and/or Production environments. Note that admins have the option to create additional environments. Model endpoint security, artifact type, runtime, and Kubernetes options can be configured when deploying a model.

Info

Champion challenger and A/B testing are available through the MLOps Python client. For more information, see Champion/Challenger deployment and A/B testing.

To learn more about deployments in MLOps, refer to the following pages:

• Deploy a model

• View deployments

• Shapley values support