英文:
GCP DL Image instance automatically starts Jupyter server but I cant find login Token
问题
我刚刚使用GCP提供的deep-learning-vm镜像创建了一个VM实例。我正在尝试远程访问笔记本服务器。但是我意识到，一旦我启动VM，jupyter笔记本服务器就会启动。我可以使用external_ip:8888连接到VM的jupyter笔记本服务器。
有一个问题。通常情况下，当我们手动启动jupyter笔记本服务器时，它会提供给我们一个登录令牌。在这种情况下，我不知道令牌是什么。
第二个问题是，当我运行jupyter notebook list来查看正在运行的服务器时，什么也看不到。我也尝试使用sudo用户。没有任何正在运行的服务器的迹象。但是无论如何，我可以连接到jupyter服务器的登录页面。而且当我使用lsof -i来检查端口时，我可以看到jupyter正在监听，即使我没有手动启动它。
我尝试关闭端口，但它们在几秒后又重新启动。我不明白如何在没有令牌信息的情况下使用jupyter服务器。我尝试设置密码，但没有成功。
我尝试更改用户，关闭端口，手动运行jupyter-lab服务器。但这些都没有帮助我。
英文:
I just created a VM instance with deep-learning-vm image provided by GCP. I am trying remote access to notebook server. However I realized jupyter notebook server starts the moment I start the VM. I can use the external_ip:8888 to connect the VM's jupyter notebook server.
There is 1 issue with his. Normally when we start jupyter notebook server manually it provides us a login token. In this case I do not know what the token is.
Second issue is when i do jupyter notebook list to see running servers, i see nothing. I tried with sudo user as well. There is no trace of a running server. However I can connect to login page of jupyter server regardless. Also when i check the ports using lsof -i, I can see jupyter is listening even tho I did not started it manually.
i tried to to kill the ports but they start again after seconds. I dont understand how I am suppose to use the jupyter server without token information. I tried to setup a password but it did not worked.
I tried changing the user, killing the ports, manually running the server using jupyter-lab. However these did not help me
答案1
得分: 1
有一些需要澄清的假设。
- 当您使用深度学习平台时，Jupyter 是一个专用的
systemctl服务。Jupyter 服务在此处定义：/lib/systemd/system/jupyter.service
您可以通过谷歌提供的代理 URL 访问 JupyterLab。
Jupyter 服务绑定到本地 IP 地址 (127.0.0.1) 和端口 (8080)，不使用令牌。
要跟踪 Jupyter 状态，请使用：systemctl status jupyter.service
示例：
/lib/systemd/system/jupyter.service
[Unit]
Description=Jupyter 笔记本服务
[Service]
Type=simple
MemoryHigh=15348914432
MemoryMax=15398914432
ExecStartPost=/usr/bin/timeout 60 sh -c 'while ! ss -t -l -n sport = :8080 | grep -q "^LISTEN.*:8080"; do sleep 1; done'
ExecStart=/bin/bash --login -c '/opt/conda/bin/jupyter lab --config=/home/jupyter/.jupyter/jupyter_notebook_config.py'
User=jupyter
Group=jupyter
WorkingDirectory=/home/jupyter
Restart=always
[Install]
WantedBy=multi-user.target
-
启动 JupyterLab 并使用外部 IP 地址不是一个好的安全实践。这就是为什么我们提供代理 URL 或推荐使用 SSH 访问的原因。
-
您可以探索用户管理的笔记本，它们使用与深度学习 VM 映像相同的底层操作系统：
https://cloud.google.com/vertex-ai/docs/workbench/user-managed/create-new
https://cloud.google.com/deep-learning-vm/docs/cli
英文:
There is some assumptions that need clarification.
- When you use Deep Learning Platform, Jupyter is a dedicated
systemctlservice. The Jupyter service is defined here:/lib/systemd/system/jupyter.service
You can access JupyterLab through a Proxy URL provided by Google.
Jupyter Service binds to local IP address (127.0.0.1) and port (8080) and does not use a token.
To track Jupyter status use: systemctl status jupyter.service
Example:
/lib/systemd/system/jupyter.service
[Unit]
Description=Jupyter Notebook Service
[Service]
Type=simple
MemoryHigh=15348914432
MemoryMax=15398914432
ExecStartPost=/usr/bin/timeout 60 sh -c 'while ! ss -t -l -n sport = :8080 | grep -q "^LISTEN.*:8080"; do sleep 1; done'
ExecStart=/bin/bash --login -c '/opt/conda/bin/jupyter lab --config=/home/jupyter/.jupyter/jupyter_notebook_config.py'
User=jupyter
Group=jupyter
WorkingDirectory=/home/jupyter
Restart=always
[Install]
WantedBy=multi-user.target
-
Is a not a good security practice to start JupyterLab manually and use an external IP address. This is why we provide a Proxy URL or recommend SSH access.
-
You can explore User Managed Notebooks which uses the same underlying OS as the Deep Learning VM image:
https://cloud.google.com/vertex-ai/docs/workbench/user-managed/create-new
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