The mlflow module now supports the scenario 5. This can be achieved by putting the artifact_Proxied_Access variable in the locals file to true.
MLflow pods on GKE now use Workload identity to enable the mlflow-tracking kubernetes service account to use the Terraform GKE SA service account to access the Cloud Storage.
The gcp-minimal and gcp-kubeflow-kservehave reverted to using thegkemodule instead of thegoogle_container_cluster` resource.
artifact_Proxied_Access
variable in the locals file to true.mlflow-tracking
kubernetes service account to use theTerraform GKE SA
service account to access the Cloud Storage.gcp-minimal
and gcp-kubeflow-kservehave reverted to using the
gkemodule instead of the
google_container_cluster` resource.README
is now updated.