If you're moving Databricks workloads from classic clusters to serverless compute, this walks you through the compatibility minefield. It scans your notebooks for RDD usage, DBFS paths, Hive metastore references, streaming triggers, and other patterns that break on the serverless Spark Connect architecture, then gives you concrete DataFrame API rewrites and config changes. The four-step workflow (ingest, analyze, test, validate) is methodical, and the decision tree separating temporary limitations from actual blockers saves you from debugging things Databricks hasn't implemented yet. Worth noting this is serverless-specific migration, not general DBR version upgrades. If you're still figuring out whether to move at all, the category breakdown helps you estimate effort before committing.
npx skills add https://github.com/databricks/databricks-agent-skills --skill databricks-serverless-migration