ML Model serving cluster tags?

[Deep]

Is there a way to add tags automatically to ML Model serving clusters? I see we can add tags to the model itself which persist but any tags I add to the cluster serving it do not after the endpoint is stopped.

This would be important to track billing in AWS as the clusters are what we need tags on. It is very tedious and impractical to add any number of tags every time we enable serving on a model.

[Kaniz]

Hi @Deep Kalra​ , To customize the serving cluster, use the Cluster Settings tab on the Serving tab.

 

• To add a tag, type the name and value in the Add Tag fields and click Add.
• To edit or delete an existing tag, click one of the icons in the Actions column of the Tags table.

Read the whole doc. Here.

[Deep]

Is there a way to propagate these tags from the Details tab? The Serving tab resets every time the model is stopped and the tags must be reapplied every time.

[Prabakar]

@Deep Kalra​ The cluster tags should help you.

https://docs.databricks.com/applications/mlflow/model-serving.html#customize-the-serving-cluster

[Anonymous]

Hey there @Deep Kalra​ 

Hope all is well!

Just wanted to check in if you were able to resolve your issue and would you be happy to share the solution or mark an answer as best? Else please let us know if you need more help. 

We'd love to hear from you.

Thanks!