https://community.databricks.com/t5/get-started-discussions/simple-notebook-sync/m-p/115422#M9341 <P>Hi <a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/158811">@Kabi</a>, as of my knowledge databricks doesn’t support directly connecting to Databricks kernel. However, here are practical ways to sync your local notebook with Databricks:</P><UL><LI>You can use Git to version control your notebooks. Clone your repo into Databricks via Repos, edit locally or in Databricks, and push changes to keep both environments in sync.</LI><LI>Install databricks-connect to execute local code on a Databricks cluster. Ensure your local Python version matches the cluster’s runtime.</LI><LI>Use the Databricks VSCode extension to sync files between your local machine and Databricks workspace. It's easy to develop locally while using Databricks clusters for execution.</LI></UL><P>And as you mentioned, for MLflow, set up your DATABRICKS_TOKEN to securely connect to tracking servers hosted on Databricks.</P><P>From my experience, first two ways are simplest way to sync notebooks.</P> Mon, 14 Apr 2025 15:15:46 GMT Renu_ 2025-04-14T15:15:46Z https://community.databricks.com/t5/get-started-discussions/simple-notebook-sync/m-p/115392#M9340 <P class="">Hi, is there a simple way to sync a local notebook with a Databricks notebook? For example, is it possible to just connect to the Databricks kernel or something similar?</P><P class="">I know there are IDE extensions for this, but unfortunately, they use the local development environment to interact with Databricks. As a result, I sometimes have to install additional libraries or adjust settings — for instance, I need to use a token to interact with MLflow.</P> Mon, 14 Apr 2025 09:29:53 GMT https://community.databricks.com/t5/get-started-discussions/simple-notebook-sync/m-p/115392#M9340 Kabi 2025-04-14T09:29:53Z https://community.databricks.com/t5/get-started-discussions/simple-notebook-sync/m-p/115422#M9341 <P>Hi <a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/158811">@Kabi</a>, as of my knowledge databricks doesn’t support directly connecting to Databricks kernel. However, here are practical ways to sync your local notebook with Databricks:</P><UL><LI>You can use Git to version control your notebooks. Clone your repo into Databricks via Repos, edit locally or in Databricks, and push changes to keep both environments in sync.</LI><LI>Install databricks-connect to execute local code on a Databricks cluster. Ensure your local Python version matches the cluster’s runtime.</LI><LI>Use the Databricks VSCode extension to sync files between your local machine and Databricks workspace. It's easy to develop locally while using Databricks clusters for execution.</LI></UL><P>And as you mentioned, for MLflow, set up your DATABRICKS_TOKEN to securely connect to tracking servers hosted on Databricks.</P><P>From my experience, first two ways are simplest way to sync notebooks.</P> Mon, 14 Apr 2025 15:15:46 GMT https://community.databricks.com/t5/get-started-discussions/simple-notebook-sync/m-p/115422#M9341 Renu_ 2025-04-14T15:15:46Z