diff --git a/pages/index.md b/pages/index.md index 20776790030..cf5db835339 100644 --- a/pages/index.md +++ b/pages/index.md @@ -1107,6 +1107,7 @@ + [Comparative tables - AI Notebooks, AI Training, AI Deploy](public_cloud/ai_machine_learning/gi_00_ai_comparative-table) + [Users - Manage AI users and roles](public_cloud/ai_machine_learning/gi_01_manage_users) + [Data - Concept and best practices](public_cloud/ai_machine_learning/gi_02_concepts_data) + + [AI Tools - Remote SSH Connection](public_cloud/ai_machine_learning/gi_03_remote_connection) + [Data - Compliance between AI Tools and S3 compatible Object Storage](public_cloud/ai_machine_learning/gi_08_s3_compliance) + [FAQ - AI Training](public_cloud/ai_machine_learning/gi_04_training_FAQ) + [ovhai CLI - Cheat Sheet](public_cloud/ai_machine_learning/gi_05_ovhai_cheatsheet) @@ -1164,7 +1165,6 @@ + [Tutorials](public-cloud-ai-and-machine-learning-ai-training-tutorials) + [AI Training - Tutorial - Train your first ML model](public_cloud/ai_machine_learning/training_tuto_01_train_your_first_model) + [AI Training - Tutorial - Build & use custom Docker image](public_cloud/ai_machine_learning/training_tuto_02_build_custom_image) - + [AI Training - Tutorial - Connect to VSCode via remote](public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) + [AI Training - Tutorial - Use tensorboard inside a job](public_cloud/ai_machine_learning/training_tuto_05_tensorboard) + [AI Training - Tutorial - Compare models with W&B for audio classification task](public_cloud/ai_machine_learning/training_tuto_06_models_comparaison_weights_and_biases) + [AI Training - Tutorial - Train a Rasa chatbot with Docker and AI Training](public_cloud/ai_machine_learning/training_tuto_07_train_rasa_chatbot) diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.de-de.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.de-de.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.de-de.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.de-de.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-asia.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-asia.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-asia.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-asia.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-au.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-au.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-au.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-au.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-ca.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-ca.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-ca.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-ca.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-gb.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-gb.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-gb.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-gb.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-ie.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-ie.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-ie.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-ie.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-sg.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-sg.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-sg.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-sg.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-us.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-us.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-us.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.en-us.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.es-es.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.es-es.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.es-es.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.es-es.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.es-us.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.es-us.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.es-us.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.es-us.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.fr-ca.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.fr-ca.md index 2c3d808e0bc..d9645eebfce 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.fr-ca.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.fr-ca.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.fr-fr.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.fr-fr.md index 2c3d808e0bc..d9645eebfce 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.fr-fr.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.fr-fr.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.it-it.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.it-it.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.it-it.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.it-it.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.pl-pl.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.pl-pl.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.pl-pl.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.pl-pl.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.pt-pt.md b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.pt-pt.md index 9d11e042809..a79ecca4ef9 100644 --- a/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.pt-pt.md +++ b/pages/public_cloud/ai_machine_learning/cli_12_howto_run_job_cli/guide.pt-pt.md @@ -180,7 +180,7 @@ A few other options are available for your jobs. - `--timeout` timeout after which the job will stop even if the process in the job did not end, helps you control your consumption - `--label` free labels to help you organize your jobs, labels are also used to scope `app_token`, learn more about `app_token` and how to create them [here](/pages/public_cloud/ai_machine_learning/cli_13_howto_app_token_cli) - `--read-user` you can add a `read-user` to a job, a read user will only have access to the service exposed behind the `job_url`. The read-user must match with the username of an AI Platform user with an `AI Training read` role. -- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote) +- `--ssh-public-keys` allows you to access your job through SSH, it is particularly useful to [setup a VSCode Remote](/pages/public_cloud/ai_machine_learning/gi_03_remote_connection) - `--from` run a job based on the specification of a previous one. All options will override the base job values. The `--image` is the flag used to override the image of the base job. ### Run a job diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.de-de.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.de-de.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.de-de.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-asia.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-asia.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-asia.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-au.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-au.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-au.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-ca.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-ca.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-ca.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-gb.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-gb.md new file mode 100644 index 00000000000..3891cdfae75 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-gb.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) \ No newline at end of file diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-ie.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-ie.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-ie.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-sg.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-sg.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-sg.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-us.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-us.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.en-us.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.es-es.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.es-es.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.es-es.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.es-us.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.es-us.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.es-us.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.fr-ca.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.fr-ca.md new file mode 100644 index 00000000000..8bbc37a86ba --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.fr-ca.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Connexion SSH à distance (EN) +excerpt: Apprenez à configurer une connexion SSH à distance avec AI Notebooks et AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.fr-fr.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.fr-fr.md new file mode 100644 index 00000000000..8bbc37a86ba --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.fr-fr.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Connexion SSH à distance (EN) +excerpt: Apprenez à configurer une connexion SSH à distance avec AI Notebooks et AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.it-it.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.it-it.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.it-it.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.pl-pl.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.pl-pl.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.pl-pl.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.pt-pt.md b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.pt-pt.md new file mode 100644 index 00000000000..b0d4fb456a5 --- /dev/null +++ b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/guide.pt-pt.md @@ -0,0 +1,165 @@ +--- +title: AI Tools - Remote SSH Connection +excerpt: Learn how to configure a remote SSH connection with AI Notebooks and AI Training +updated: 2025-09-09 +--- + +## Objective + +This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. + +## Requirements + +- Access to the [OVHcloud Control Panel](/links/manager) +- An AI Notebook or AI Training Project created inside a [Public Cloud project](/links/public-cloud/public-cloud) in your OVHcloud account +- An [AI user](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) +- [The OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) installed on your computer + +## Instructions + +### Installation + +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. +2. Install [Visual Studio Code](https://code.visualstudio.com/). +3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). + +### Generate an SSH Keypair + +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: + +```bash +ssh-keygen -t ed25519 -C "your_email@example.com" +``` + +> [!primary] +> +> - `-t ed25519` creates a modern, secure key (recommended). +> - `-C` lets you add a label (usually your email) to identify the key. + +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. + +### Specify the SSH Key during AI Notebook or AI Training Job Creation + +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: + +> [!tabs] +> **Using the Control Panel (UI)** +>> +>> First, go to the `Public Cloud`{.action} section of the [OVHcloud Control Panel](/links/manager). +>> +>> 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. +>> +>> From there, click on the `+ Create a notebook`{.action} or `+ Launch a job`{.action} button to configure and create your AI Solution. +>> +>> ![image](images/manager-1.png){.thumbnail} +>> +>> Fill in the various details required until you find the `Advanced configuration`{.action} section. Open it. +>> +>> ![image](images/manager-2.png){.thumbnail} +>> +>> 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: +>> +>> ![image](images/manager-3.png){.thumbnail} +>> +>> This will open a window where you can put the content of your public key file (e.g., `id_ed25519.pub`): +>> +>> ![image](images/manager-4.png){.thumbnail} +>> +>> Click on `Confirm`{.action}. Once your key is added, you can select it from your SSH Keys list: +>> +>> ![image](images/manager-5.png){.thumbnail} +>> +>> 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`. +>> +>> ![image](images/manager-6.png){.thumbnail} +>> +> **Using ovhai CLI** +>> +>> 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. +>> +>> When creating your AI resource using the `ovhai` CLI, specify the SSH public key using the `--ssh-public-keys` option, or `-s` shortcut: +>> +>> ```bash +>> ovhai job run \ +>> --gpu \ +>> --ssh-public-keys ~/.ssh/id_ed25519.pub +>> ``` +>> +>> Once the job is `Running`, you can see the `sshUrl` by getting your job information: +>> +>> ```bash +>> ovhai job get +>> ``` + +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. + +> [!warning] +> In order to work, the deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian). + +### Verify you can connect to the SSH host + +Before continuing, you can verify you can access your job by running the following command from a terminal / PowerShell window, replacing `` with the ID of your job and `` with your resource location (e.g., `gra`, `bhs`): + +```bash +ssh @.ai.cloud.ovh.net +``` + +If the SSH key is well configured, you should see the following: + +``` +Welcome to OVHcloud! +ovh@job-36ed1f18-626b-42f7-b15f-0ed844e65d20:~$ +``` + +### Configure VSCode Remote Connection + +In Visual Studio Code, click on the `Remote Explorer`{.action} icon. + +![image](images/vscode-1.png){.thumbnail} + +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. + +![image](images/vscode-2.png){.thumbnail} + +Add the following section for your new host: + +``` +Host my_ai_training_job +HostName .ai.cloud.ovh.net # Adapt to your resource location (gra, bhs) +User bfa1d77a-9746-4128-9974-f94139937927 # ID of your AI Training Job or AI Notebook +IdentityFile C:\Path\To\id_ed25519 # Path to your private key file (not .pub) +``` + +Save the `config` file. Then refresh remotes by clicking on this icon: + +![image](images/vscode-3.png){.thumbnail} + +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: + +![image](images/vscode-4.png){.thumbnail} + +If the connection is well established, you should see this message in the bottom-left corner of VSCode: + +![image](images/vscode-5.png){.thumbnail} + +### Develop and Run Your Code + +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`. + +![image](images/vscode-6.png){.thumbnail} + +You can also open a terminal and run commands from it. Enjoy! + +![image](images/vscode-7.png){.thumbnail} + +## Go further + +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). + +If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. + +## Feedback + +Please send us your questions, feedback and suggestions to improve the service: + +- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/images/manager-1.png b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/images/manager-1.png new file mode 100644 index 00000000000..be3b7d12ba3 Binary files /dev/null and b/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/images/manager-1.png differ diff --git a/pages/public_cloud/ai_machine_learning/gi_03_remote_connection/images/manager-2.png 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b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.de-de.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.de-de.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-asia.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-asia.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-asia.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-au.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-au.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-au.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-ca.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-ca.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-ca.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-gb.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-gb.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-gb.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-ie.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-ie.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-ie.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-sg.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-sg.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-sg.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-us.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-us.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.en-us.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.es-es.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.es-es.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.es-es.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.es-us.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.es-us.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.es-us.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.fr-ca.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.fr-ca.md deleted file mode 100644 index 21efeed106c..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.fr-ca.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutoriel - Se connecter à VS Code à distance (EN) -excerpt: Comment configurer VS Code pour utiliser AI Training à distance -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.fr-fr.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.fr-fr.md deleted file mode 100644 index 21efeed106c..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.fr-fr.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutoriel - Se connecter à VS Code à distance (EN) -excerpt: Comment configurer VS Code pour utiliser AI Training à distance -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.it-it.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.it-it.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.it-it.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.pl-pl.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.pl-pl.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.pl-pl.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.pt-pt.md b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.pt-pt.md deleted file mode 100644 index dce2991585f..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/guide.pt-pt.md +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: AI Training - Tutorial - Connect to VSCode via remote -excerpt: Tutorial to configure Remote Visual Studio with AI Training -updated: 2022-09-01 ---- - -## Objective - -This tutorial covers the process of starting a job using a Visual Studio Code Remote via SSH. - -## Requirements - -- an **AI Training project** created inside a **Public Cloud** project -- a [user for AI Training](/pages/public_cloud/ai_machine_learning/gi_01_manage_users) -- installing the [OVHcloud AI CLI](/pages/public_cloud/ai_machine_learning/cli_10_howto_install_cli) - -> [!warning] -> The deployed image needs to contain the `bash` binary and a glibc-based Linux (Ubuntu / Debian) - -## Installation - -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. -2. Install [Visual Studio Code](https://code.visualstudio.com/). -3. Install the [Remote Development extension pack](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack). - -## Start a job with the SSH feature - -We will launch a job with the CLI, just choose the number of GPUs (``) to use on your job and use the following command: - -``` {.bash} -ovhai job run --gpu -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-tensorflow:2.3.0 -``` - -Once the job is `Running`, you can see the `sshUrl` with *job get*: - -``` {.bash} -ovhai job get -``` - -## Configure VSCode Remote Development - -Verify you can connect to the SSH host by running the following command from a terminal / PowerShell window replacing user\@hostname accordingly: - -``` {.bash} -ssh @gra.ai.cloud.ovh.net - -Welcome to OVHcloud AI Training Jobs SSH -job-0d916855-1cd4-4b66-8803-b4782bc13902:~$ -``` - -Click on the Remote Explorer Button. - -![image](images/vscode-1.png){.thumbnail} - -Then click on the `+` button to add a SSH server. - -![image](images/vscode-2.png){.thumbnail} - -Then click on the window icon near your server in the list. - -![image](images/vscode-3.png){.thumbnail} - -Enjoy. - -![image](images/vscode-4.png){.thumbnail} - -## Go further - -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). - -If you need training or technical assistance to implement our solutions, contact your sales representative or click on [this link](/links/professional-services) to get a quote and ask our Professional Services experts for a custom analysis of your project. - -## Feedback - -Please send us your questions, feedback and suggestions to improve the service: - -- On the OVHcloud [Discord server](https://discord.gg/ovhcloud) diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-2.png b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-2.png deleted file mode 100644 index d5f6f378d7e..00000000000 Binary files a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-2.png and /dev/null differ diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-3.png b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-3.png deleted file mode 100644 index 37f2bdc3759..00000000000 Binary files a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-3.png and /dev/null differ diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-4.png b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-4.png deleted file mode 100644 index 84600b21268..00000000000 Binary files a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/images/vscode-4.png and /dev/null differ diff --git a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/meta.yaml b/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/meta.yaml deleted file mode 100755 index 7ad946b9bfb..00000000000 --- a/pages/public_cloud/ai_machine_learning/training_tuto_04_vscode_remote/meta.yaml +++ /dev/null @@ -1,3 +0,0 @@ -id: d7ec627e-551a-45b9-90b4-af3b2f304a11 -full_slug: public-cloud-ai-training-vscode-remote-code -reference_category: public-cloud-ai-and-machine-learning-ai-training-tutorials \ No newline at end of file