사용자 관리 노트북 인스턴스의 특정 버전을 만든 후 업그레이드할 수 있습니다. 인스턴스를 업그레이드하면 사전 설치된 소프트웨어 및 패키지가 업데이트됩니다. 자세한 내용은 사용자 관리 노트북 인스턴스의 환경 업그레이드를 참조하세요.
시작하기 전에
사용자 관리형 노트북 인스턴스를 만들려면 먼저Google Cloud 프로젝트가 있고 이 프로젝트에 Notebooks API를 사용 설정해야 합니다.
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.
사용자 관리 노트북 인스턴스에 GPU를 사용하려는 경우 Google Cloud 콘솔의 할당량 페이지를 확인하여 프로젝트에 사용 가능한 GPU가 충분히 있는지 확인하세요. GPU가 할당량 페이지에 나와 있지 않거나 추가 GPU 할당량이 필요한 경우 할당량 상향 조정을 요청하세요. Compute Engine 리소스 할당량 페이지의 추가 할당량 요청을 참조하세요.
필요한 역할
프로젝트를 만든 경우 프로젝트에 대한 소유자(roles/owner) IAM 역할이 있으며 이 역할에는 모든 필수 권한이 포함됩니다. 이 섹션을 건너뛰고 사용자 관리형 노트북 인스턴스를 만듭니다. 프로젝트를 직접 만들지 않았으면 이 섹션에서 계속 진행합니다.
Vertex AI Workbench 사용자 관리 노트북 인스턴스를 만드는 데 필요한 권한을 얻으려면 관리자에게 프로젝트에 대한 다음 IAM 역할을 부여해 달라고 요청하세요.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-07-09(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."]]