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Migrate data to a new managed notebooks instance
Vertex AI Workbench managed notebooks isdeprecated. On
April 14, 2025, support for
managed notebooks will end and the ability to create managed notebooks instances
will be removed. Existing instances will continue to function
but patches, updates, and upgrades won't be available. To continue using
Vertex AI Workbench, we recommend that youmigrate
your managed notebooks instances to Vertex AI Workbench instances.
This page describes how to migrate data and files from
an existing managed notebooks instance to a new one.
When to migrate
You might want to migrate to a new managed notebooks instance
for any of the following reasons:
To use new capabilities that are only available in a newer version.
To benefit from framework updates, package updates, and bug fixes
that have been implemented in a newer version.
To migrate data and files from one managed notebooks instance to another,
consider using the following methods:
Use GitHub: Copy your data and files to a GitHub repository
by using the Git extension for JupyterLab.
Use Cloud Storage and the terminal: Copy your data and files
to Cloud Storage and then to another instance by using the terminal.
Use Cloud Storage within JupyterLab notebooks:
Copy your data and files to Cloud Storage and then to another instance
by running commands within your respective instances' notebook cells.
This guide describes how to migrate data and files by using
Cloud Storage and the terminal.
Requirements
You must have terminal access to your managed notebooks instance.
Terminal access is manually set when you create an instance. The
terminal access setting cannot be changed after the instance is created.
Migrate your data to a new managed notebooks instance
To migrate data and files to a new managed notebooks instance
by using Cloud Storage and the terminal, complete the following steps.
In your managed notebooks instance's
JupyterLab interface, selectFile >New >Terminalto open a terminal window.
Use thegcloud CLIto copy your user data
to a Cloud Storage bucket. The following example command
copies all of the files from your instance's/home/jupyter/directory
to a directory in a Cloud Storage bucket.
In your new managed notebooks instance's
JupyterLab interface, selectFile >New >Terminalto open a terminal window.
Use the gcloud CLI to restore your data on the new instance.
The following example command copies all of
the files from a Cloud Storage directory to the
your new instance's/home/jupyter/directory.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[],[],null,["# Migrate data to a new Vertex AI Workbench managed notebooks instance\n\nMigrate data to a new managed notebooks instance\n================================================\n\n\n| Vertex AI Workbench managed notebooks is\n| [deprecated](/vertex-ai/docs/deprecations). On\n| April 14, 2025, support for\n| managed notebooks will end and the ability to create managed notebooks instances\n| will be removed. Existing instances will continue to function\n| but patches, updates, and upgrades won't be available. To continue using\n| Vertex AI Workbench, we recommend that you\n| [migrate\n| your managed notebooks instances to Vertex AI Workbench instances](/vertex-ai/docs/workbench/managed/migrate-to-instances).\n\n\u003cbr /\u003e\n\nThis page describes how to migrate data and files from\nan existing managed notebooks instance to a new one.\n\nWhen to migrate\n---------------\n\nYou might want to migrate to a new managed notebooks instance\nfor any of the following reasons:\n\n- To use new capabilities that are only available in a newer version.\n\n- To benefit from framework updates, package updates, and bug fixes\n that have been implemented in a newer version.\n\n- If you're unable to upgrade the environment of an existing instance.\n See the [requirements for upgrading the environment of\n a managed notebooks\n instance](/vertex-ai/docs/workbench/managed/upgrade#requirements).\n\nMigration options\n-----------------\n\nTo migrate data and files from one managed notebooks instance to another,\nconsider using the following methods:\n\n- **Use GitHub**: Copy your data and files to a GitHub repository\n by using the Git extension for JupyterLab.\n\n- **Use Cloud Storage and the terminal**: Copy your data and files\n to Cloud Storage and then to another instance by using the terminal.\n\n- **Use Cloud Storage within JupyterLab notebooks**:\n Copy your data and files to Cloud Storage and then to another instance\n by running commands within your respective instances' notebook cells.\n\nThis guide describes how to migrate data and files by using\nCloud Storage and the terminal.\n\nRequirements\n------------\n\nYou must have terminal access to your managed notebooks instance.\nTerminal access is manually set when you create an instance. The\nterminal access setting cannot be changed after the instance is created.\n\nBefore you begin\n----------------\n\n[Create a Cloud Storage bucket](/storage/docs/creating-buckets)\nin the same project where your managed notebooks instance\nis located.\n\nMigrate your data to a new managed notebooks instance\n-----------------------------------------------------\n\nTo migrate data and files to a new managed notebooks instance\nby using Cloud Storage and the terminal, complete the following steps.\n\n1. In your managed notebooks instance's\n JupyterLab interface, select **File \\\u003e\n New \\\u003e Terminal** to open a terminal window.\n\n2. Use the [gcloud CLI](/cli) to copy your user data\n to a Cloud Storage bucket. The following example command\n copies all of the files from your instance's `/home/jupyter/` directory\n to a directory in a Cloud Storage bucket.\n\n ```bash\n gcloud storage cp /home/jupyter/* gs://BUCKET_NAMEPATH --recursive\n ```\n\n Replace the following:\n - \u003cvar translate=\"no\"\u003eBUCKET_NAME\u003c/var\u003e: the name of your Cloud Storage bucket\n - \u003cvar translate=\"no\"\u003ePATH\u003c/var\u003e: the path to the directory where you want to copy your files, for example: `/copy/jupyter/`\n3. [Create\n a managed notebooks instance](/vertex-ai/docs/workbench/managed/create-instance).\n\n4. In your new managed notebooks instance's\n JupyterLab interface, select **File \\\u003e\n New \\\u003e Terminal** to open a terminal window.\n\n5. Use the gcloud CLI to restore your data on the new instance.\n The following example command copies all of\n the files from a Cloud Storage directory to the\n your new instance's `/home/jupyter/` directory.\n\n ```bash\n gcloud storage cp gs://BUCKET_NAMEPATH* /home/jupyter/\n ```\n\nWhat's next\n-----------\n\n- Learn how to [manually upgrade the environment of\n managed notebooks instances](/vertex-ai/docs/workbench/managed/upgrade)."]]
