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‎pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.de-de.md‎

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11
---
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title: AI Training - Tutorial - Connect to VSCode via remote
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excerpt: Tutorial to configure Remote Visual Studio with AI Training
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updated: 2022-09-01
2+
title: AI Tools - Remote SSH Connection
3+
excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training
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updated: 2025-09-09
55
---
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77
## Objective
@@ -10,60 +10,148 @@ This tutorial covers the process of starting a job using a Visual Studio Code Re
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## Requirements
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- an **AI Training project** created inside a **Public Cloud** project
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- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users)
15-
- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli)
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- Access to the [OVHcloud Control Panel](/links/manager)
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- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account
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- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users)
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- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer
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> [!warning]
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> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian)
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## Instructions
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## Installation
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### Installation
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1. Install an [OpenSSH compatible SSH client](https://code.visualstudio.com/docs/remote/troubleshooting#_installing-a-supported-ssh-client) if one is not already present.
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2. Install [Visual Studio Code](https://code.visualstudio.com/).
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3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack).
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1. Install an [OpenSSH compatible SSH client](https://code.visualstudio.com/docs/remote/troubleshooting#_installing-a-supported-ssh-client) if one is not already present.
23+
2. Install [Visual Studio Code](https://code.visualstudio.com/).
24+
3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack).
2525

26-
## Start a job with the SSH feature
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### Generate an SSH Keypair
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We will launch a job with the CLI, just choose the number of GPUs (`<nb-gpus>`) to use on your job and use the following command:
28+
If you don’t already have an SSH key, you will need to create one. To do so, open a Terminal / PowerShell, and run the key generation command:
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30-
``` {.bash}
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ovhai job run --gpu <nb-gpus> -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0
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```bash
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ssh-keygen -t ed25519 -C "[email protected]"
3232
```
3333

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Once the job is `Running`, you can see the `sshUrl` with *job get*:
34+
> [!primary]
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>
36+
> - `-t ed25519` creates a modern, secure key (recommended).
37+
> - `-C` lets you add a label (usually your email) to identify the key.
38+
39+
This will create a private key (e.g., `id_ed25519`, not to share) and a public key (e.g., `id_ed25519.pub`) in your `~/.ssh/` directory.
40+
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### Specify the SSH Key during AI Notebook or AI Training Job Creation
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Here is how to add your SSH key to your AI Solution if you are using the [OVHcloud Control Panel](/links/manager) or the `ovhai` CLI:
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> [!tabs]
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> **Using the Control Panel (UI)**
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>>
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>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager).
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>>
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>> Select your Public Cloud project, then go to the `AI & Machine Learning`{.action} category in the left menu and choose `AI Notebooks`{.action} or `AI Training`{.action} section.
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>>
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>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution.
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>>
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>> ![image](images/manager-1.png){.thumbnail}
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>>
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>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it.
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>>
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>> ![image](images/manager-2.png){.thumbnail}
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>>
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>> From there you will find a `SSH Public Keys` sub-section where you can add and configure new SSH keys by clicking on the `+ Configure an SSH Key`{.action} button:
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>>
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>> ![image](images/manager-3.png){.thumbnail}
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>>
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>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`):
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>>
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>> ![image](images/manager-4.png){.thumbnail}
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>>
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>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list:
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>>
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>> ![image](images/manager-5.png){.thumbnail}
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>>
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>> Once selected, make sure to click on the `+`{.action} to confirm the addition of your key. You should see the following message: `1 of 10 SSH key configured`.
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>>
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>> ![image](images/manager-6.png){.thumbnail}
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>>
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> **Using ovhai CLI**
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>>
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>> To follow this part, make sure you have installed the [ovhai CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) on your computer or on an instance.
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>>
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>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut:
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>>
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>> ```bash
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>> ovhai job run <job_image> \
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>> --gpu <nb-gpus> \
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>> --ssh-public-keys ~/.ssh/id_ed25519.pub
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>> ```
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>>
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>> Once the job is `Running`, you can see the `sshUrl` by getting your job information:
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>>
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>> ```bash
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>> ovhai job get <job-id>
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>> ```
93+
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Once your job is created, regardless of the method chosen, you will be able to copy your job id (e.g., `bfa1d77a-9746-4128-9974-f94139937927`), which will be needed in the following steps.
3595
36-
``` {.bash}
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ovhai job get <job-id>
38-
```
96+
> [!warning]
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> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian).
3998
40-
## Configure VSCode Remote Development
99+
### Verify you can connect to the SSH host
41100
42-
Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly:
101+
Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `<job-id>` with the ID of your job and `<region>` with your resource location (e.g., `gra`, `bhs`):
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```bash
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ssh <job-id>@<region>.ai.cloud.ovh.net
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```
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``` {.bash}
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ssh <job-id>@gra.ai.cloud.ovh.net
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If the SSH key is well configured, you should see the following:
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Welcome to OVHcloud AI Training Jobs SSH
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job-0d916855-1cd4-4b66-8803-b4782bc13902:~$
49109
```
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Welcome to OVHcloud!
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ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$
112+
```
113+
114+
### Configure VSCode Remote Connection
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51-
Click on the Remote Explorer Button.
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In Visual Studio Code, click on the `Remote Explorer`{.action} icon.
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![image](images/vscode-1.png){.thumbnail}
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Then click on the `+` button to add a SSH server.
120+
From there, click the gear icon on the SSH feature to access the SSH configuration file for VSCode, typically located at `~/.ssh/config`, and open it.
56121

57122
![image](images/vscode-2.png){.thumbnail}
58123

59-
Then click on the window icon near your server in the list.
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Add the following section for your new host:
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```
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Host my_ai_training_job
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HostName <region>.ai.cloud.ovh.net # Adapt to your resource location (gra, bhs)
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User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook
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IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub)
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```
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Save the `config` file. Then refresh remotes by clicking on this icon:
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![image](images/vscode-3.png){.thumbnail}
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63-
Enjoy.
137+
Your resource should now appear in the SSH menu on the left. Connect to it by clicking the arrow next to your resource. VSCode will restart to connect to your remote resource:
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![image](images/vscode-4.png){.thumbnail}
66140

141+
If the connection is well established, you should see this message in the bottom-left corner of VSCode:
142+
143+
![image](images/vscode-5.png){.thumbnail}
144+
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### Develop and Run Your Code
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Once connected, you can start developing and running your code in the default `/workspace` folder, by clicking on the `Open folder`{.action} blue button, and select `/workspace`.
148+
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![image](images/vscode-6.png){.thumbnail}
150+
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You can also open a terminal and run commands from it. Enjoy!
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153+
![image](images/vscode-7.png){.thumbnail}
154+
67155
## Go further
68156

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You can compare AI models based on resource consumption, accuracy and training time. Refer to this [tutorial](/pages/public_cloud/ai_machine_learning/training_tuto_06_models_comparaison_weights_and_biases).

‎pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-asia.md‎

Lines changed: 118 additions & 30 deletions
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,7 @@
11
---
2-
title: AI Training - Tutorial - Connect to VSCode via remote
3-
excerpt: Tutorial to configure Remote Visual Studio with AI Training
4-
updated: 2022-09-01
2+
title: AI Tools - Remote SSH Connection
3+
excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training
4+
updated: 2025-09-09
55
---
66

77
## Objective
@@ -10,60 +10,148 @@ This tutorial covers the process of starting a job using a Visual Studio Code Re
1010

1111
## Requirements
1212

13-
- an **AI Training project** created inside a **Public Cloud** project
14-
- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users)
15-
- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli)
13+
- Access to the [OVHcloud Control Panel](/links/manager)
14+
- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account
15+
- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users)
16+
- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer
1617

17-
> [!warning]
18-
> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian)
18+
## Instructions
1919

20-
## Installation
20+
### Installation
2121

22-
1. Install an [OpenSSH compatible SSH client](https://code.visualstudio.com/docs/remote/troubleshooting#_installing-a-supported-ssh-client) if one is not already present.
23-
2. Install [Visual Studio Code](https://code.visualstudio.com/).
24-
3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack).
22+
1. Install an [OpenSSH compatible SSH client](https://code.visualstudio.com/docs/remote/troubleshooting#_installing-a-supported-ssh-client) if one is not already present.
23+
2. Install [Visual Studio Code](https://code.visualstudio.com/).
24+
3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack).
2525

26-
## Start a job with the SSH feature
26+
### Generate an SSH Keypair
2727

28-
We will launch a job with the CLI, just choose the number of GPUs (`<nb-gpus>`) to use on your job and use the following command:
28+
If you don’t already have an SSH key, you will need to create one. To do so, open a Terminal / PowerShell, and run the key generation command:
2929

30-
``` {.bash}
31-
ovhai job run --gpu <nb-gpus> -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0
30+
```bash
31+
ssh-keygen -t ed25519 -C "[email protected]"
3232
```
3333

34-
Once the job is `Running`, you can see the `sshUrl` with *job get*:
34+
> [!primary]
35+
>
36+
> - `-t ed25519` creates a modern, secure key (recommended).
37+
> - `-C` lets you add a label (usually your email) to identify the key.
38+
39+
This will create a private key (e.g., `id_ed25519`, not to share) and a public key (e.g., `id_ed25519.pub`) in your `~/.ssh/` directory.
40+
41+
### Specify the SSH Key during AI Notebook or AI Training Job Creation
42+
43+
Here is how to add your SSH key to your AI Solution if you are using the [OVHcloud Control Panel](/links/manager) or the `ovhai` CLI:
44+
45+
> [!tabs]
46+
> **Using the Control Panel (UI)**
47+
>>
48+
>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager).
49+
>>
50+
>> Select your Public Cloud project, then go to the `AI & Machine Learning`{.action} category in the left menu and choose `AI Notebooks`{.action} or `AI Training`{.action} section.
51+
>>
52+
>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution.
53+
>>
54+
>> ![image](images/manager-1.png){.thumbnail}
55+
>>
56+
>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it.
57+
>>
58+
>> ![image](images/manager-2.png){.thumbnail}
59+
>>
60+
>> From there you will find a `SSH Public Keys` sub-section where you can add and configure new SSH keys by clicking on the `+ Configure an SSH Key`{.action} button:
61+
>>
62+
>> ![image](images/manager-3.png){.thumbnail}
63+
>>
64+
>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`):
65+
>>
66+
>> ![image](images/manager-4.png){.thumbnail}
67+
>>
68+
>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list:
69+
>>
70+
>> ![image](images/manager-5.png){.thumbnail}
71+
>>
72+
>> Once selected, make sure to click on the `+`{.action} to confirm the addition of your key. You should see the following message: `1 of 10 SSH key configured`.
73+
>>
74+
>> ![image](images/manager-6.png){.thumbnail}
75+
>>
76+
> **Using ovhai CLI**
77+
>>
78+
>> To follow this part, make sure you have installed the [ovhai CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) on your computer or on an instance.
79+
>>
80+
>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut:
81+
>>
82+
>> ```bash
83+
>> ovhai job run <job_image> \
84+
>> --gpu <nb-gpus> \
85+
>> --ssh-public-keys ~/.ssh/id_ed25519.pub
86+
>> ```
87+
>>
88+
>> Once the job is `Running`, you can see the `sshUrl` by getting your job information:
89+
>>
90+
>> ```bash
91+
>> ovhai job get <job-id>
92+
>> ```
93+
94+
Once your job is created, regardless of the method chosen, you will be able to copy your job id (e.g., `bfa1d77a-9746-4128-9974-f94139937927`), which will be needed in the following steps.
3595
36-
``` {.bash}
37-
ovhai job get <job-id>
38-
```
96+
> [!warning]
97+
> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian).
3998
40-
## Configure VSCode Remote Development
99+
### Verify you can connect to the SSH host
41100
42-
Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly:
101+
Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `<job-id>` with the ID of your job and `<region>` with your resource location (e.g., `gra`, `bhs`):
102+
103+
```bash
104+
ssh <job-id>@<region>.ai.cloud.ovh.net
105+
```
43106
44-
``` {.bash}
45-
ssh <job-id>@gra.ai.cloud.ovh.net
107+
If the SSH key is well configured, you should see the following:
46108

47-
Welcome to OVHcloud AI Training Jobs SSH
48-
job-0d916855-1cd4-4b66-8803-b4782bc13902:~$
49109
```
110+
Welcome to OVHcloud!
111+
ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$
112+
```
113+
114+
### Configure VSCode Remote Connection
50115

51-
Click on the Remote Explorer Button.
116+
In Visual Studio Code, click on the `Remote Explorer`{.action} icon.
52117

53118
![image](images/vscode-1.png){.thumbnail}
54119

55-
Then click on the `+` button to add a SSH server.
120+
From there, click the gear icon on the SSH feature to access the SSH configuration file for VSCode, typically located at `~/.ssh/config`, and open it.
56121

57122
![image](images/vscode-2.png){.thumbnail}
58123

59-
Then click on the window icon near your server in the list.
124+
Add the following section for your new host:
125+
126+
```
127+
Host my_ai_training_job
128+
HostName <region>.ai.cloud.ovh.net # Adapt to your resource location (gra, bhs)
129+
User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook
130+
IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub)
131+
```
132+
133+
Save the `config` file. Then refresh remotes by clicking on this icon:
60134

61135
![image](images/vscode-3.png){.thumbnail}
62136

63-
Enjoy.
137+
Your resource should now appear in the SSH menu on the left. Connect to it by clicking the arrow next to your resource. VSCode will restart to connect to your remote resource:
64138

65139
![image](images/vscode-4.png){.thumbnail}
66140

141+
If the connection is well established, you should see this message in the bottom-left corner of VSCode:
142+
143+
![image](images/vscode-5.png){.thumbnail}
144+
145+
### Develop and Run Your Code
146+
147+
Once connected, you can start developing and running your code in the default `/workspace` folder, by clicking on the `Open folder`{.action} blue button, and select `/workspace`.
148+
149+
![image](images/vscode-6.png){.thumbnail}
150+
151+
You can also open a terminal and run commands from it. Enjoy!
152+
153+
![image](images/vscode-7.png){.thumbnail}
154+
67155
## Go further
68156

69157
You can compare AI models based on resource consumption, accuracy and training time. Refer to this [tutorial](/pages/public_cloud/ai_machine_learning/training_tuto_06_models_comparaison_weights_and_biases).

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