Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Membuat versi instance tertentu
Halaman ini menjelaskan cara membuat versi tertentu dari
instance Vertex AI Workbench.
Alasan Anda perlu membuat versi tertentu
Untuk memastikan bahwa instance Vertex AI Workbench memiliki software
yang kompatibel dengan kode atau aplikasi Anda, sebaiknya buat
versi tertentu.
Image instance Vertex AI Workbench sering diupdate, dan
versi tertentu dari software dan paket yang diinstal sebelumnya bervariasi dari satu versi
ke versi lainnya.
Untuk mempelajari lebih lanjut versi Vertex AI Workbench tertentu, lihat catatan rilis Vertex AI.
Setelah membuat versi
instance Vertex AI Workbench tertentu, Anda dapat mengupgradenya.
Dengan mengupgrade instance, paket dan software yang telah diinstal sebelumnya akan diupdate.
Untuk mengetahui informasi selengkapnya,
lihat Mengupgrade lingkungan instance.
Sebelum memulai
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.
Anda dapat membuat versi instance Vertex AI Workbench tertentu
menggunakan Google Cloud konsol atau Google Cloud CLI.
Konsol
Untuk membuat versi instance Vertex AI Workbench tertentu,
lakukan hal berikut:
Saat Anda membuat instance,
di bagian Environment, pilih Use a previous version.
Klik daftar Versi, lalu pilih versi. Versi diberi nomor
dalam bentuk M yang diikuti dengan nomor rilis,
misalnya, M123.
Selesaikan dialog pembuatan instance selanjutnya, lalu
klik Buat.
Vertex AI Workbench membuat sebuah instance dan otomatis memulainya.
Saat instance siap digunakan, Vertex AI Workbench akan mengaktifkan link Open JupyterLab.
gcloud
Sebelum menggunakan salah satu data perintah di bawah, lakukan penggantian berikut:
INSTANCE_NAME: nama instance Vertex AI Workbench Anda;
harus dimulai dengan huruf, diikuti dengan maksimal 62 huruf kecil, angka, atau tanda hubung (-), dan tidak boleh diakhiri dengan tanda hubung
PROJECT_ID: project ID Anda
LOCATION: zona tempat Anda ingin menempatkan instance
VM_IMAGE_NAME: nama image; untuk mendapatkan daftar nama image yang tersedia, gunakan perintah
get-config
METADATA: metadata kustom yang akan diterapkan ke instance ini; misalnya, guna menentukan post-startup-script, Anda dapat menggunakan tag metadata post-startup-script, dalam format: --metadata=post-startup-script=gs://BUCKET_NAME/hello.sh
Untuk mengetahui informasi lebih lanjut tentang perintah untuk membuat instance dari command line, baca dokumentasi gcloud CLI.
Vertex AI Workbench membuat sebuah instance dan otomatis memulainya.
Saat instance siap digunakan, Vertex AI Workbench akan mengaktifkan link Open JupyterLab di konsol Google Cloud .
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-08-19 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."]]