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Crea una versione specifica di un'istanza di notebook gestiti dall'utente
Questa pagina descrive come creare
un'istanza di notebook gestiti dall'utente basata su una versione specifica di
Deep Learning VM Images.
Perché potresti voler creare una versione specifica
Per assicurarti che l'istanza di notebook gestiti dall'utente disponga di software
compatibile con il tuo codice o la tua applicazione, ti consigliamo di creare
una versione specifica.
Le istanze di blocchi note gestiti dall'utente vengono create utilizzando le immagini Deep Learning VM. Le immagini di Deep Learning VM
vengono aggiornate di frequente e le versioni specifiche di software
e pacchetti preinstallati variano da versione a versione.
Dopo aver creato una versione specifica di un'istanza di blocchi note gestiti dall'utente, puoi eseguirne l'upgrade. L'upgrade dell'istanza aggiorna il software e i pacchetti preinstallati. Per maggiori informazioni, vedi Upgrade dell'ambiente di un'istanza di blocchi note gestiti dall'utente.
Prima di iniziare
Prima di poter creare un'istanza di blocchi note gestiti dall'utente,
devi disporre di un
progettoGoogle Cloud e abilitare l'API Notebooks
per quel progetto.
Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
Se prevedi di utilizzare le GPU con l'istanza di notebook gestiti dall'utente, controlla la pagina Quote nella console Google Cloud per assicurarti di disporre di un numero sufficiente di GPU nel progetto. Se le GPU
non sono elencate nella pagina Quote o se hai bisogno di una quota di GPU aggiuntiva, puoi richiedere un aumento della quota. Consulta la sezione Richiesta di aumento della quota nella pagina Quote delle risorse di Compute Engine.
Ruoli obbligatori
Se hai creato il progetto, disponi del ruolo IAM Proprietario (roles/owner) per il progetto, che include tutte le autorizzazioni richieste. Salta questa sezione e
inizia a creare l'istanza di blocchi note gestiti dall'utente. Se non hai
creato tu il progetto, continua in questa sezione.
Per ottenere le autorizzazioni
necessarie per creare un'istanza di blocchi note gestiti dall'utente di Vertex AI Workbench,
chiedi all'amministratore di concederti i
seguenti ruoli IAM nel progetto:
Per creare un'istanza di notebook gestiti dall'utente basata su una versione specifica di Deep Learning VM, devi conoscere il nome dell'immagine della versione specifica di Deep Learning VM che vuoi utilizzare.
Ogni release di Deep Learning VM include aggiornamenti a
molte immagini diverse e ogni immagine nella release ha il proprio
nome.
Per trovare il nome dell'immagine specifica che ti interessa:
Trova il numero di release di Deep Learning VM
per cui vuoi ottenere i nomi delle immagini.
I numeri di rilascio sono inclusi nelle note di rilascio di Deep Learning VM.
I numeri di rilascio sono nel formato M seguito dal numero di rilascio, ad esempio M79.
Per elencare i nomi delle immagini per una versione specifica di Deep Learning VM, esegui questo comando.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 2025-09-04 UTC."],[],[],null,["# Create a specific version of a Vertex AI Workbench user-managed notebooks instance\n\nCreate a specific version of a user-managed notebooks instance\n==============================================================\n\n\n| Vertex AI Workbench user-managed notebooks is\n| [deprecated](/vertex-ai/docs/deprecations). On\n| April 14, 2025, support for\n| user-managed notebooks will end and the ability to create user-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 user-managed notebooks instances to Vertex AI Workbench instances](/vertex-ai/docs/workbench/user-managed/migrate-to-instances).\n\n\u003cbr /\u003e\n\nThis page describes how you can create\na user-managed notebooks instance based on a specific\n[Deep Learning VM Images](/deep-learning-vm/docs)\nversion.\n\nWhy you might want to create a specific version\n-----------------------------------------------\n\nTo ensure that your user-managed notebooks instance has software\nthat is compatible with your code or application, you might want to create\na specific version.\n\nUser-managed notebooks instances are created by using Deep Learning VM images. Deep Learning VM\nimages are updated frequently, and specific versions of preinstalled software\nand packages vary from version to version.\n\nTo learn more about specific Deep Learning VM versions,\nsee the [Deep Learning VM\nrelease notes](/deep-learning-vm/docs/release-notes).\n\nAfter you create a specific version of a user-managed notebooks instance, you can upgrade it. Upgrading the instance updates the preinstalled software and packages. For more information, see [Upgrade a user-managed\nnotebooks instance's environment](/vertex-ai/docs/workbench/user-managed/upgrade).\n\nBefore you begin\n----------------\n\nBefore you can create a user-managed notebooks instance, you must have a Google Cloud project and enable the Notebooks API for that project.\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Notebooks API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=notebooks.googleapis.com&redirect=https://console.cloud.google.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Notebooks API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=notebooks.googleapis.com&redirect=https://console.cloud.google.com)\n\n1. If you plan to use GPUs with your user-managed notebooks instance, [check the quotas page in the\n Google Cloud console](https://console.cloud.google.com/quotas) to ensure that you have enough GPUs available in your project. If GPUs are not listed on the quotas page, or you require additional GPU quota, you can request a quota increase. See [Requesting an increase in\n quota](/compute/quotas#requesting_additional_quota) on the Compute Engine [Resource quotas](/compute/quotas) page.\n\n\u003cbr /\u003e\n\n### Required roles\n\nIf you created the project, you have the\nOwner (`roles/owner`) IAM role on the project,\nwhich includes all required permissions. Skip this section and\nstart creating your user-managed notebooks instance. If you didn't\ncreate the project yourself, continue in this section.\n\n\nTo get the permissions that\nyou need to create a Vertex AI Workbench user-managed notebooks instance,\n\nask your administrator to grant you the\nfollowing IAM roles on the project:\n\n- Notebooks Admin ([`roles/notebooks.admin`](/vertex-ai/docs/workbench/user-managed/iam#notebooks.admin))\n- Service Account User ([`roles/iam.serviceAccountUser`](/iam/docs/understanding-roles#iam.serviceAccountUser))\n\n\nFor more information about granting roles, see [Manage access to projects, folders, and organizations](/iam/docs/granting-changing-revoking-access).\n\n\nYou might also be able to get\nthe required permissions through [custom\nroles](/iam/docs/creating-custom-roles) or other [predefined\nroles](/iam/docs/roles-overview#predefined).\n\nFind the specific version that you want\n---------------------------------------\n\nTo create a user-managed notebooks instance based on a specific\nDeep Learning VM version, you must know\nthe image name of the specific Deep Learning VM\nversion that you want to use.\n\nEach release of Deep Learning VM includes updates to\nmany different images, and each image in the release has its own\nimage name.\n\nTo find the specific image name that you want:\n\n1. Find the Deep Learning VM release number\n that you want to get image names for.\n Release numbers are included in the [Deep Learning VM\n release notes](/deep-learning-vm/docs/release-notes).\n Release numbers are in the form of an `M` followed by\n the number of the release, for example, `M79`.\n\n2. To list the image names for a specific Deep Learning VM\n release, run the following command.\n\n ```bash\n gcloud compute images list --project=\"deeplearning-platform-release\" \\\n --format=\"value(name)\" \\\n --filter=\"labels.release=\u003cvar translate=\"no\"\u003eRELEASE_NUMBER\u003c/var\u003e\" \\\n --show-deprecated\n ```\n\n Replace \u003cvar translate=\"no\"\u003eRELEASE_NUMBER\u003c/var\u003e with\n a Deep Learning VM release number, such as `M79`.\n3. Find the image name that you want to use.\n\nCreate a specific version from the command line\n-----------------------------------------------\n\nTo create a specific version of\na user-managed notebooks instance from\nthe command line, complete the following steps:\n\n1. Run the following [`gcloud\n notebooks`](/sdk/gcloud/reference/notebooks/instances/create) command:\n\n ```bash\n gcloud notebooks instances create INSTANCE_NAME \\\n --vm-image-project=\"deeplearning-platform-release\" \\\n --vm-image-name=VM_IMAGE_NAME \\\n --machine-type=MACHINE_TYPE \\\n --location=LOCATION\n ```\n\n Replace the following:\n - \u003cvar translate=\"no\"\u003eINSTANCE_NAME\u003c/var\u003e: the name of your new instance\n - \u003cvar translate=\"no\"\u003eVM_IMAGE_NAME\u003c/var\u003e: the image name that you want to use to create your instance\n - \u003cvar translate=\"no\"\u003eMACHINE_TYPE\u003c/var\u003e: the [machine\n type](/compute/docs/machine-resource) of your instance's VM\n - \u003cvar translate=\"no\"\u003eLOCATION\u003c/var\u003e: the Google Cloud [location](/vertex-ai/docs/general/locations#user-managed-notebooks-locations) where you want your new instance to be\n2. Access your instance from the\n [Google Cloud console](https://console.cloud.google.com/vertex-ai/workbench/user-managed).\n\nWhat's next\n-----------\n\n- Learn more about [upgrading\n user-managed notebooks instances](/vertex-ai/docs/workbench/user-managed/upgrade)\n to ensure that your instance upgrades only when you are ready.\n\n- [Install dependencies](/vertex-ai/docs/workbench/user-managed/dependencies) on\n your new user-managed notebooks instance.\n\n- Learn more about Deep Learning VM instances in the\n [Deep Learning VM\n documentation](/deep-learning-vm/docs).\n\n- Learn about [monitoring the health status](/vertex-ai/docs/workbench/user-managed/monitor-health) of\n your user-managed notebooks instance."]]
