Accessing Unity Catalog's MLFlow model registry from outside Databricks

[rahuja]

Hello Everyone

We are integrating Unity Catalog in our Organisation's Databricks. In our case we are planning to move our inference from Databricks to Kubernetes. In order to make the inference code use the latest registered model we need to query the model registry from outside Databricks. So I wanted to ask:
1. Is the model registry exposed via a public api?

2. If not how can we do this?

Thanks in advance for your time.

[mhiltner]

Hey @rahuja, 

If you register your models in Unity Catalog (and they effectively appear on your Catalog Explorer) you could use Delta sharing for your models. https://docs.databricks.com/en/data-sharing/index.html 

Also, curious about the decision. Databricks serving capabilities are quite good, what are the benefits that you are looking for with this migration? 

[rahuja]

Hello @mhiltner 

Currently we are contemplating whether to do this or not. In my organisation this decision is based due to cost. We already have a managed Kubernetes cluster that we are paying for.

[p4pratikjain]

I have used glue in the past to score models that are registered in Databricks mlflow registry. You need to configure MLFlow on Kubernetes to access your model registry.
You can use something like this - 
https://docs.databricks.com/en/mlflow/access-hosted-tracking-server.html

[bajdwobaht]

You can use the MLflow client (in various language specific SDKs) to download model artifacts. For example, see here: https://docs.databricks.com/en/mlflow/models.html#download-model-artifacts

We leverage this pattern to serve models in our K8s stack for similar reasons to what you stated (existing clusters, cost / performance, network latency benefits, etc.). I've also used Databricks Model Serving extensively, including in the original "CPU only on Spark clusters" version, and I much prefer the self-managed route if it's something your team has capacity to support.