Move ClearML Session (#756)

docs/apps/clearml_session.md

@@ -1,5 +1,5 @@
 ---
-title: ClearML Session
+title: Remote Session
 ---
 
 Machine Learning and Deep Learning development is sometimes more challenging than traditional software development. If 
@@ -11,7 +11,19 @@ in the UI and send it for long-term training on a remote machine.
 
 **If you are not that lucky**, this section is for you :)
 
-## What Does ClearML Session Do?
+ClearML provides tools that allow you to launch remote sessions and to execute code on a remote machine that better 
+meets resource needs:
+* [Clearml Session CLI](#clearml-session-cli) - Launch a JupyterLab and VS Code session on a remote machine
+* [GUI Applications](#gui-applications) (available under ClearML Enterprise Plan)
+  * [JupyterLab](../webapp/applications/apps_jupyter_lab.md) - Launch a JupyterLab session on a remote machine 
+  * [VS Code](../webapp/applications/apps_vscode.md) - Launch a VS Code session on a remote machine 
+
+:::info Remote PyCharm
+You can also work with PyCharm in a remote session over SSH. Use the [PyCharm Plugin](../guides/ide/integration_pycharm.md) 
+to automatically sync local configurations with a remote session.
+:::
+
+## ClearML Session CLI 
 `clearml-session` is a feature that allows to launch a session of JupyterLab and VS Code, and to execute code on a remote 
 machine that better meets resource needs. This feature provides local links to access JupyterLab and VS Code on a 
 remote machine over a secure and encrypted SSH connection. By default, the JupyterLab and 
@@ -31,12 +43,6 @@ VS Code remote sessions use ports 8878 and 8898 respectively.
 
 </Collapsible>
 
-:::info Remote PyCharm
-You can also work with PyCharm in a remote session over SSH. Use the [PyCharm Plugin](../guides/ide/integration_pycharm.md) 
-to automatically sync local configurations with a remote session.
-:::
-
-## How to Run ClearML Session 
 
 ### Prerequisites
 * `clearml` installed and configured. See [Getting Started](../getting_started/ds/ds_first_steps.md) for details.
@@ -120,24 +126,24 @@ To connect to an existing session:
 1. Enter the following command: `clearml-session --attach <session_id>`.
 1. Click on the JupyterLab / VS Code link that is outputted, or connect directly to the SSH session
 
-## Features 
-### Running in Docker
+### Features 
+#### Running in Docker
 To run a session inside a Docker container, use the `--docker` flag and enter the docker image to use in the interactive 
 session.
 
-### Installing Requirements
+#### Installing Requirements
 `clearml-session` can install required Python packages when setting up the remote environment. 
 Specify requirements in one of the following ways: 
 * Attach a `requirement.txt` file to the command using `--requirements </file/location.txt>`.
 * Manually specify packages using `--packages "<package_name>"` 
 (for example `--packages "keras" "clearml"`), and they'll be automatically installed.
 
-### Accessing a Git Repository
+#### Accessing a Git Repository
 To access a git repository remotely, add a `--git-credentials` flag and set it to `true`, so the local `.git-credentials` 
 file is sent to the interactive session. This is helpful if working on private git repositories, and it allows for seamless 
 cloning and tracking of git references, including untracked changes. 
 
-### Starting a Debugging Session 
+#### Starting a Debugging Session 
 You can debug previously executed experiments registered in the ClearML system on a remote interactive session. 
 Input into `clearml-session` the ID of a Task to debug, then `clearml-session` clones the experiment's git repository and 
 replicates the environment on a remote machine. Then the code can be interactively executed and debugged on JupyterLab / VS Code. 
@@ -153,7 +159,7 @@ The Task must be connected to a git repository, since currently single script de
 1. In JupyterLab / VS Code, access the experiment's repository in the `environment/task_repository` folder. 
 
 
-## Command Line Options
+### Command Line Options
 
 <div className="tbl-cmd">
 
@@ -193,4 +199,16 @@ The Task must be connected to a git repository, since currently single script de
 | `--verbose` | Increase verbosity of logging | `none` |
 | `--yes`, `-y`| Automatic yes to prompts; assume "yes" as answer to all prompts and run non-interactively |N/A|
 
-</div>
+</div>
+
+## GUI Applications
+
+:::important Enterprise Feature
+This feature is available under the ClearML Enterprise plan
+:::
+
+The ClearML Enterprise Server provides GUI applications for setting up remote sessions in VS Code and JupyterLab. These
+apps provide local links to access JupyterLab or VS Code on a remote machine over a secure and encrypted SSH connection,
+letting you use the IDE as if you're running on the target machine itself
+
+For more information, see [JupyterLab](../webapp/applications/apps_jupyter_lab.md) and/or [VS Code](../webapp/applications/apps_vscode.md).

sidebars.js

@@ -56,8 +56,9 @@ module.exports = {
         {'ClearML Data': ['clearml_data/clearml_data', 'clearml_data/clearml_data_cli', 'clearml_data/clearml_data_sdk', 'clearml_data/best_practices',
                 {'Workflows': ['clearml_data/data_management_examples/workflows', 'clearml_data/data_management_examples/data_man_simple', 'clearml_data/data_management_examples/data_man_folder_sync', 'clearml_data/data_management_examples/data_man_cifar_classification', 'clearml_data/data_management_examples/data_man_python']},]},
         'model_registry',
+        'apps/clearml_session',
         {'ClearML Serving':['clearml_serving/clearml_serving', 'clearml_serving/clearml_serving_setup', 'clearml_serving/clearml_serving_cli', 'clearml_serving/clearml_serving_tutorial']},
-        {'CLI Tools': ['apps/clearml_session', 'apps/clearml_task', 'apps/clearml_param_search']},
+        {'CLI Tools': ['apps/clearml_task', 'apps/clearml_param_search']},
         {'Integrations': [
                 'integrations/autokeras',
                 'integrations/catboost', 'integrations/click', 'integrations/fastai', 'integrations/transformers',