Databricks Serverless Migration

---
name: databricks-serverless-migration
description: "Migrate Databricks workloads from classic compute to serverless compute. Use when migrating notebooks, jobs, pipelines, or Scala JARs (`spark_jar_task`) from classic clusters to serverless, checking if existing code is serverless-compatible, or writing new serverless-compatible code. Provides concrete fixes for the serverless Spark Connect architecture and guides the full migration. Not for classic DBR version upgrades or cluster configuration changes within classic compute."
compatibility: Requires databricks CLI (>= v0.292.0)
metadata:
  version: "0.1.0"
parent: databricks-core
---

# Serverless Compute Migration

**FIRST**: Use the parent `databricks-core` skill for CLI basics, authentication, and profile selection.

Analyze existing Databricks code for serverless compute compatibility and guide migration from classic clusters. The skill follows a 4-step migration lifecycle: **Ingest** the workload → **Analyze** for compatibility → **Test** via A/B comparison → **Validate** and iterate.

## When to Use This Skill

- Migrating notebooks, jobs, or pipelines from classic compute to serverless
- Checking if existing code is serverless-compatible
- Writing new code that targets serverless compute
- Troubleshooting serverless-specific errors after migration
- Choosing between Performance-Optimized and Standard mode

## Where to Run This Skill
… install to load the full skill