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The upgrade documentation says existing feature and model serving workloads continue "with no action required" and the create_online_store and update_online_store interfaces need no changes. It doesn't tie Failed to fetch database instance with ID ....

Really like this approach. The shift from just “data → model” to thinking about ingestion, replayability, and model lifecycle is what makes this feel like a real-world ML project.

@airbotsThe underlying issue is generally a metadata reconciliation lag where the Vector Search index status remains stuck displaying Syncing in Catalog Explorer even after the sync pipeline has completed. The metadata status reporting mechanism gene...

Yeah, I’d start simple with XGBoost or LightGBM and use AutoML for a quick baseline. Then just focus on the features that actually improve the results.

Hi, Could you provide a workspaceID and endpointID and any other details such as screenshots? Will check to see what I can find based on those details, ~Mo.

Hi @LPBigot, Since Serverless CPU is working but Serverless GPU is failing when the notebook tries to attach compute, could you confirm a couple of things so we can narrow this down? Is this a paid/Premium+ workspace, or is it a free/trial-style setu...

What you are encountering is an expected behavior on Databricks serverless. Because CrossValidator (along with other Spark ML tuning estimators) relies heavily on internal DataFrame caching to optimize iterative model training, Databricks enforces st...

The dynamic conda.yaml generation trick doesn't actually fix this, and you already found that out yourself. Whatever ends up in the final logged conda.yaml is what gets read at environment build time, so if a plaintext credential has to be in that fi...

Databricks AutoML is still around and actively used as of mid-2026, so nothing's wrong on that front, but there's a nuance worth knowing: starting with Databricks Runtime 18.0 ML, AutoML was removed as a built-in library on classic compute. It's stil...

Hi @ShaRKS, If you are taking the Associate ML pathway, the notebooks are typically available through the course's lab environment rather than as separate downloadable assets. Databricks course pages for the ML curriculum note that lecture notebooks ...