Databricks now lets developers connect local editors like VS Code, Cursor, or a terminal directly to Databricks compute via a new SSH tunnel, enabling interactive running and debugging of Python and SQL workloads on Serverless, AI Runtime, or dedicated clusters. Dependencies stay synced with Databricks Runtime, and coding agents like Cursor, Copilot, and Claude Code can run with full workspace context. Connection is a single Databricks CLI command, with flags to pre-install Python dependencies or track SSH tunnel costs by user, team, or project.
Questions this post answers
How do I connect VS Code or Cursor directly to Databricks compute for running and debugging code?
Use the new SSH tunnel feature via the Databricks CLI command 'databricks ssh connect', which connects to serverless compute by default. Add '--accelerator <GPU_type>' for AI Runtime GPU clusters, or '--cluster <cluster_id>' for a dedicated cluster. Include '--ide vscode' or '--ide cursor' to launch the tunnel directly inside the IDE, or start it from the Databricks IDE extension itself. daily.dev surfaces workflow updates like this for teams wiring local IDEs into remote compute.
Can I use Cursor, Copilot, or Claude Code with Databricks compute and workspace context?
Yes, coding agents can run inside the Databricks SSH tunnel with full workspace context. Cursor and Copilot work out of the box once the tunnel is active, while Claude Code and other agents can be installed after the SSH tunnel is running, giving them access to the same environment and dependencies as the Databricks workspace. developers pairing coding agents with cloud compute track setups like this through daily.dev.
How do I keep Python dependencies in sync between my local IDE and Databricks Runtime?
Start the SSH tunnel with the '--base-environment' flag to pre-install Python dependencies matching Databricks Runtime, keeping the local IDE environment and workspace in sync automatically. A separate '--usage-policy-id' flag lets teams track SSH tunnel compute costs by user, team, or project. daily.dev helps engineers keep tabs on tooling changes that affect their dev environment setup.