이 페이지에서는 Vertex AI Workbench 인스턴스의 특정 버전을 만드는 방법을 설명합니다.
특정 버전을 생성하려는 이유
Vertex AI Workbench 인스턴스에 코드나 애플리케이션과 호환되는 소프트웨어가 있는지 확인하기 위해 특정 버전을 만들 수 있습니다.
Vertex AI Workbench 인스턴스 이미지는 자주 업데이트되며 사전 설치된 소프트웨어와 패키지의 특정 버전은 버전마다 다릅니다.
특정 Vertex AI Workbench 버전에 대한 자세한 내용은 Vertex AI 출시 노트를 참조하세요.
Vertex AI Workbench 인스턴스의 특정 버전을 만든 후에 업그레이드할 수 있습니다.
인스턴스를 업그레이드하면 사전 설치된 소프트웨어 및 패키지가 업데이트됩니다.
자세한 내용은 인스턴스 환경 업그레이드를 참조하세요.
시작하기 전에
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.
METADATA: 이 인스턴스에 적용할 커스텀 메타데이터. 예를 들어 시작 후 스크립트를 지정하려면 post-startup-script 메타데이터 태그를 --metadata=post-startup-script=gs://BUCKET_NAME/hello.sh 형식으로 사용하면 됩니다.
[[["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: 2025-09-04(UTC)"],[],[],null,["# Create a specific version of a Vertex AI Workbench instance\n\nCreate a specific version of an instance\n========================================\n\nThis page describes how to create a specific version of a\nVertex AI Workbench instance.\n\nWhy you might want to create a specific version\n-----------------------------------------------\n\nTo ensure that your Vertex AI Workbench instance has software\nthat is compatible with your code or application, you might want to create\na specific version.\n\nVertex AI Workbench instance images are updated frequently, and\nspecific versions of preinstalled software and packages vary from version\nto version.\n\nTo learn more about specific Vertex AI Workbench versions,\nsee the [Vertex AI release notes](/vertex-ai/docs/release-notes).\n\nAfter you create a specific version of\na Vertex AI Workbench instance, you can upgrade it.\nUpgrading the instance updates the preinstalled software and packages.\nFor more information,\nsee [Upgrade an instance's environment](/vertex-ai/docs/workbench/instances/upgrade).\n\nBefore you begin\n----------------\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\n\u003cbr /\u003e\n\nCreate a specific version\n-------------------------\n\nYou can create a specific version of a Vertex AI Workbench instance\nby using the Google Cloud console or the Google Cloud CLI. \n\n### Console\n\nTo create a specific version of a Vertex AI Workbench instance,\ndo the following:\n\n1. When you [create an instance](/vertex-ai/docs/workbench/instances/create),\n in the **Environment** section, select **Use a previous version**.\n\n2. Click the **Version** list, and select a version. Versions are numbered\n in the form of an `M` followed by the number of the release,\n for example, `M123`.\n\n3. Complete the rest of the instance-creation dialog, and then\n click **Create**.\n\n Vertex AI Workbench creates an instance and automatically starts it.\n When the instance is ready to use, Vertex AI Workbench\n activates an **Open JupyterLab** link.\n\n### gcloud\n\n\nBefore using any of the command data below,\nmake the following replacements:\n\n- \u003cvar translate=\"no\"\u003eINSTANCE_NAME\u003c/var\u003e: the name of your Vertex AI Workbench instance; must start with a letter followed by up to 62 lowercase letters, numbers, or hyphens (-), and cannot end with a hyphen\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: your project ID\n- \u003cvar translate=\"no\"\u003eLOCATION\u003c/var\u003e: the zone where you want your instance to be located\n- \u003cvar translate=\"no\"\u003eVM_IMAGE_NAME\u003c/var\u003e: the image name; to get a list of the available image names, use the [`get-config`\n command](/sdk/gcloud/reference/workbench/instances/get-config)\n- \u003cvar translate=\"no\"\u003eMACHINE_TYPE\u003c/var\u003e: the [machine type](/compute/docs/machine-resource) of your instance's VM\n- \u003cvar translate=\"no\"\u003eMETADATA\u003c/var\u003e: custom metadata to apply to this instance;\n for example, to specify a post-startup-script,\n you can use the `post-startup-script` metadata tag, in the format:\n `--metadata=post-startup-script=gs://`\u003cvar translate=\"no\"\u003eBUCKET_NAME\u003c/var\u003e`/hello.sh`\n\n | To enable the JupyterLab 4 preview, use `--metadata=enable-jupyterlab4-preview=true`. For more information, see [JupyterLab 4 preview](/vertex-ai/docs/workbench/instances/create#jupyterlab-preview).\n\n\nExecute the\n\nfollowing\n\ncommand:\n\n#### Linux, macOS, or Cloud Shell\n\n**Note:** Ensure you have initialized the Google Cloud CLI with authentication and a project by running either [gcloud init](/sdk/gcloud/reference/init); or [gcloud auth login](/sdk/gcloud/reference/auth/login) and [gcloud config set project](/sdk/gcloud/reference/config/set). \n\n```bash\ngcloud workbench instances create INSTANCE_NAME \\\n --project=PROJECT_ID \\\n --location=LOCATION \\\n --vm-image-project=\"cloud-notebooks-managed\" \\\n --vm-image-name=VM_IMAGE_NAME \\\n --machine-type=MACHINE_TYPE \\\n --metadata=METADATA\n```\n\n#### Windows (PowerShell)\n\n**Note:** Ensure you have initialized the Google Cloud CLI with authentication and a project by running either [gcloud init](/sdk/gcloud/reference/init); or [gcloud auth login](/sdk/gcloud/reference/auth/login) and [gcloud config set project](/sdk/gcloud/reference/config/set). \n\n```bash\ngcloud workbench instances create INSTANCE_NAME `\n --project=PROJECT_ID `\n --location=LOCATION `\n --vm-image-project=\"cloud-notebooks-managed\" `\n --vm-image-name=VM_IMAGE_NAME `\n --machine-type=MACHINE_TYPE `\n --metadata=METADATA\n```\n\n#### Windows (cmd.exe)\n\n**Note:** Ensure you have initialized the Google Cloud CLI with authentication and a project by running either [gcloud init](/sdk/gcloud/reference/init); or [gcloud auth login](/sdk/gcloud/reference/auth/login) and [gcloud config set project](/sdk/gcloud/reference/config/set). \n\n```bash\ngcloud workbench instances create INSTANCE_NAME ^\n --project=PROJECT_ID ^\n --location=LOCATION ^\n --vm-image-project=\"cloud-notebooks-managed\" ^\n --vm-image-name=VM_IMAGE_NAME ^\n --machine-type=MACHINE_TYPE ^\n --metadata=METADATA\n```\n\n\u003cbr /\u003e\n\nFor more information about the command for creating an\ninstance from the command line, see the [gcloud CLI\ndocumentation](/sdk/gcloud/reference/workbench/instances/create).\n\nVertex AI Workbench creates an instance and automatically starts it.\nWhen the instance is ready to use, Vertex AI Workbench\nactivates an **Open JupyterLab** link in the Google Cloud console.\n\nWhat's next\n-----------\n\n- Learn more about [upgrading\n Vertex AI Workbench instances](/vertex-ai/docs/workbench/instances/upgrade)\n to ensure that your instance upgrades only when you are ready.\n\n- Learn about [monitoring the health status](/vertex-ai/docs/workbench/instances/monitor-health) of\n your Vertex AI Workbench instance."]]
