I'm looking for guidance on deploying machine learning models to Azure. Specifically, I want to know:
- Which Azure service is most cost‑effective for low‑traffic models?
- How to handle versioning and rollback?
- Security best practices for exposing the endpoint.
Any real‑world examples or docs would be appreciated!
I recommend Azure Container Apps for small models. They scale to zero when idle, saving costs.
For versioning, use Azure ML Model Registry. It lets you track model versions and roll back with a single CLI command.
Thanks! Also, make sure to enable Managed Identity on the endpoint and restrict access via Azure AD.