이 페이지에서는 Google Cloud Console에서 Google Cloud Marketplace를 사용하여 Deep Learning VM Image 인스턴스를 만드는 방법을 보여줍니다.
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.
시작하기를 클릭합니다. 프로젝트 선택 창이 표시되면 인스턴스를 만들 프로젝트를 선택합니다. Compute Engine VM을 처음 시작하는 경우에는 초기 API 구성 프로세스가 완료될 때까지 기다려야 합니다.
새 Deep Learning VM 배포 페이지에
배포 이름을 입력합니다. 이 이름은 가상 머신 이름의 루트가 됩니다.
Compute Engine은 인스턴스 이름을 지정할 때 이 이름 끝에 -vm을 추가합니다.
영역을 선택하거나 기본값을 유지합니다.
머신 유형에서 VM에 사용할 사양을 선택하거나 기본값을 유지합니다.
GPU에서 GPU 유형 및 GPU 수를 선택하거나 기본값을 유지합니다.
GPU를 사용하지 않으려면 GPU 삭제 버튼을 클릭합니다.
SSH 대신 URL을 통해 JupyterLab에 액세스 사용 설정(베타)을 선택할 수 있습니다. 이 베타 기능을 사용 설정하면 URL을 사용하여 JupyterLab 인스턴스에 액세스할 수 있습니다. Google Cloud 프로젝트의 편집자 또는 소유자 역할이 있는 사용자 누구나 이 URL에 액세스할 수 있습니다. 이 기능은 미국, 유럽연합, 아시아에서만 작동합니다.
머신러닝 프레임워크를 선택하거나 기본값을 유지합니다.
배포를 클릭합니다.
이제 첫 번째 Deep Learning VM 인스턴스가 생성되었습니다.
인스턴스 배포 후 Google Cloud 콘솔에서 Deep Learning VM 인스턴스 및 기타 배포를 관리할 수 있는 Deployment Manager 페이지가 열립니다.
새 인스턴스 액세스
딥 러닝 VM 인스턴스는 생성 후 자동으로 시작됩니다. 액세스하려면 다음 안내를 따르세요.
[[["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)"],[[["\u003cp\u003eThis guide outlines how to create a Deep Learning VM instance using the Google Cloud Marketplace within the Google Cloud console, starting with the "Get started" button.\u003c/p\u003e\n"],["\u003cp\u003eUsers can customize their VM by selecting a deployment name, zone, machine type, GPU type, number of GPUs, and a machine learning framework, or they can opt for default settings.\u003c/p\u003e\n"],["\u003cp\u003eAfter deployment, the VM can be accessed via the VM Instances page, where users can choose between interacting with a graphical user interface or on the command line.\u003c/p\u003e\n"],["\u003cp\u003eThe instance can be manually stopped and started from the VM Instances page, and finally, the deployment can be deleted to avoid incurring unnecessary charges.\u003c/p\u003e\n"],["\u003cp\u003eJupyterLab access via a URL is an available beta feature in select regions, granting access to users in the Editor or Owner role within your Google Cloud project.\u003c/p\u003e\n"]]],[],null,["# Quickstart: Create a Deep Learning VM instance by using the Google Cloud console\n\nCreate a Deep Learning VM instance by using the Google Cloud console\n====================================================================\n\nThis page shows you how to create a Deep Learning VM Images instance\nby using Google Cloud Marketplace in the Google Cloud console.\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- 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| **Note:** This quickstart assumes that all settings will remain at their defaults. For more information about the VM options available to you, see [Choose an\n| Image](/deep-learning-vm/docs/images).\n\nCreate a new instance\n---------------------\n\n1. Go to the Deep Learning VM Cloud Marketplace page in\n the Google Cloud console.\n\n [Go to the Deep Learning VM Cloud Marketplace page](https://console.cloud.google.com/marketplace/details/click-to-deploy-images/deeplearning)\n2. Click **Get started**. If you see a project selection window,\n choose the project in which to create the instance. If this is the first\n time you've launched a Compute Engine VM, you must wait for the initial API\n configuration process to complete.\n\n3. On the **New Deep Learning VM deployment** page, enter a\n **Deployment name** . This will be the root of your virtual machine name.\n Compute Engine appends `-vm` to this name when naming your instance.\n\n4. Select a **Zone**, or keep the default.\n\n5. Under **Machine type**, select the specifications that you\n want for your VM, or keep the default.\n\n6. Under **GPUs** , select the **GPU type** and **Number of GPUs** ,\n or keep the default values.\n If you don't want to use GPUs,\n click the **Delete GPU** button.\n\n7. You have the option to select **Enable access to JupyterLab via URL\n instead of SSH (Beta)**. Enabling this Beta feature lets you\n access your JupyterLab\n instance using a URL. Anyone who is in the Editor or Owner role in your\n Google Cloud project can access this URL. This feature\n only works in the United States, the European Union, and Asia.\n\n8. Select a machine learning **Framework**, or keep the default.\n\n9. Click **Deploy**.\n\nYou've just created your first Deep Learning VM instance.\nAfter the instance is deployed, the Google Cloud console opens\nthe [Deployment Manager page](https://console.cloud.google.com/dm/deployments)\nwhere you can manage your\nDeep Learning VM instances and other deployments.\n\nAccess your new instance\n------------------------\n\nOnce you've created your Deep Learning VM instance, it starts\nautomatically. To access it:\n\n1. Go to the VM Instances page in the Google Cloud console.\n\n [Go to the VM\n Instances page](https://console.cloud.google.com/compute/instances)\n2. Under the **Name** column,\n click the name of your virtual machine instance.\n\n3. In the **Remote Access** section, click the first drop-down list and\n choose how you'd like to access the instance. You can choose to interact\n with a graphical user interface or on the command line.\n\n [](../images/dlvm-qs1.png)\n\n \u003cbr /\u003e\n\nCompute Engine will propagate your SSH keys and create your user. For more\ninformation, see [Connecting to\nInstances](/compute/docs/instances/connecting-to-instance).\n\nStop the instance\n-----------------\n\n1. Go to the VM Instances page in the Google Cloud console.\n\n [Go to the VM\n Instances page](https://console.cloud.google.com/compute/instances)\n2. Select the checkbox next to the Deep Learning VM instance.\n\n3. Click **Stop**.\n\nStart the instance\n------------------\n\nAfter an instance is created, the instance starts automatically. To start the instance\nmanually when it's stopped:\n\n1. Go to the VM Instances page in the Google Cloud console.\n\n [Go to the VM\n Instances page](https://console.cloud.google.com/compute/instances)\n2. Select the checkbox next to the Deep Learning VM instance.\n\n3. Click **Start**.\n\nClean up\n--------\n\n\nTo avoid incurring charges to your Google Cloud account for\nthe resources used on this page, follow these steps.\n\n1. Go to the Deployments page in the Google Cloud console.\n\n [Go to the\n Deployments page](https://console.cloud.google.com/dm/deployments)\n2. Select the checkbox next to the Deep Learning VM deployment.\n\n3. Click **Delete**.\n\nWhat's next\n-----------\n\n- Read a more in-depth description of this process in [Creating a\n Deep Learning VM instance from\n Google Cloud Marketplace](/deep-learning-vm/docs/cloud-marketplace).\n- Learn more about [Images, image families, and\n instances](/deep-learning-vm/docs/concepts-images)."]]
