- Install JetBrains Gateway - With the JetBrains Gateway and Gitpod plugin you can create and manage your latest 20 Gitpod workspaces.
- Install the Gitpod plugin - Open JetBrains Gateway and you’ll see the Gitpod logo on the main page. Click “install” to install the Gitpod plugin for JetBrains Gateway.
- Update your Gitpod preferences - Select PyCharm on the Gitpod preferences page which will set PyCharm as your default IDE for future workspace starts.
- Start (or restart) your workspace - Either start a workspace directly from within the JetBrains Gateway via the Gitpod plugin OR open a new workspace directly in Gitpod where on workspace start you will be prompted to open PyCharm for that workspace.
Important: You must restart any started workspaces for your IDE preferences to take effect.
This section relates to plugin management when using JetBrains IDEs in a remote development context. For information on regular plugin management, refer to PyCharm docs.
Unlike with regular development, JetBrains Remote development with PyCharm allows users to install plugins in different locations:
- PyCharm backend plugins - The JetBrains PyCharm backend runs within the remote Gitpod workspace. Backend plugins contribute functionality for IDE experiences relating to the filesystem, tools or languages and frameworks. When installed, a backend plugin only applies to the currently running Gitpod workspace and is not associated with a user. However, a plugin can be preconfigured for all users of a repository so that the plugin is enabled with every workspace start. It is not currently possible to install a backend plugin that applies to all workspaces of a Gitpod user or team.
- JetBrains Client plugins - The JetBrains client runs on the users local machine and can be thought of as the user interface to the remote PyCharm backend. Client plugins are different to backend plugins as they contribute to the user interface aspect of the IDE experience (e.g. keyboard shortcuts and themes). Once installed, a client plugin is enabled for all Gitpod workspaces the user opens (if the workspace is running the exact same version of the PyCharm backend where the plugin was initially installed).
- JetBrains Gateway plugins - The JetBrains Gateway is an application downloaded onto a users local machine which allows users to start JetBrains Clients that are compatible with the PyCharm backend, running in a Gitpod workspace. JetBrains Gateway plugins are installed directly in JetBrains Gateway and contribute to remote development connection experiences (e.g. the Gitpod JetBrains Gateway plugin).
The JetBrains client runs on the users local machine and can be thought of as the user interface to the remote PyCharm backend. Client plugins contribute to the user interface aspect of the IDE experience (e.g. keyboard shortcuts and themes).
Once installed, a client plugin is enabled for all Gitpod workspaces the user opens (if the workspace is running the exact same version of the PyCharm backend where the plugin was initially installed).
To install a plugin on JetBrains Client follow these steps:
- In JetBrains Client open the IDE settings and select Plugins.
- Find the plugin in the Marketplace and click Install.
The JetBrains PyCharm backend runs within the remote Gitpod workspace. Backend plugins contribute functionality requiring access to IDE experiences such as the remote filesystem (e.g. contributing support of languages and frameworks).
When installed, a backend plugin only applies to the currently running Gitpod workspace and is not associated with a user. However, a plugin can be preconfigured for all users of a repository so that the plugin is enabled with every workspace start.
It is not currently possible to install a backend plugin that applies to all workspaces of a Gitpod user or team.
You can install a plugin only for your current workspace following these steps:
- In JetBrains Client open the IDE settings and select Plugins On Host.
- Find the plugin in the Marketplace and click Install.
You can share a plugin on PyCharm backend with everybody working on the repository by adding it to .gitpod.yml and pushing to your Git repository.
Each workspace is preconfigured with plugins from the
gitpod.yml configuration file. For example:
jetbrains: pycharm: plugins: - zielu.gittoolbox - izhangzhihao.rainbow.brackets
You can find the pluginId on the JetBrains Marketplace page:
- Find a page of the required plugin.
- Select the Versions tab.
- Click any version to copy the pluginId (short name such as
org.rust.lang) of the plugin you want to install.
It is not yet possible to install plugins on PyCharm backend for your user to share across all your Gitpod workspaces.
When you open the project PyCharm starts indexing to load modules and enable the core functionality like code completion and navigation. Depending on the size of your project indexing speed can vary significantly.
You can speed up the indexing of a project by applying these general recommendations. Gitpod prebuilds allow you to improve it further by indexing before you start a new workspace.
To leverage it:
- configure prebuilds for your repository, refer to Prebuilds;
- enable indexing for PyCharm in prebuilds by editing .gitpod.yml in your repository:
jetbrains: pycharm: prebuilds: version: stable
- push changes to your Git repository to apply.
version property allows you to control whether to index for
both versions of PyCharm compatible with Gitpod.
Users can switch between
latest versions of PyCharm on the user preferences page.
You can adjust JVM options for PyCharm backend, especially if you want to increase the
-Xmx memory size. For example:
jetbrains: pycharm: vmoptions: "-Xmx4g"
For more detailed information on JVM options, refer to Common JVM Options from JetBrains documentation.
When using a Gitpod workspace you might experience performance issues caused by:
- An application using more resources than expected
- Resource consumption in adjacent containers running on the workspace node.
In your JetBrains IDE within the JetBrains Gateway Backend Control Center you can find two metrics relating to your running workspace:
Workspace CPU and
The remaining metrics you can find in the Backend Control Center regarding the node that your workspace is running on, and not the workspace itself.
Note: Performance information shown in the Backend Control Center is the same as the information that is shown when running the command
gp topin your workspace, see the Command Line Interface documentation for more.
For the questions about supported IDEs and Editors in Gitpod, refer to FAQs.
For the general questions about JetBrains Remote Development, refer to refer to the general IDE PyCharm FAQ.
Debugging performance can be challenging, as performance issues can depend on many factors such as how Gitpod is configured (if you’re operating Gitpod on Self-Hosted). However, there are some ways you can gather performance information and optimise your JetBrains IDE setup with Gitpod:
- Firstly, to gather information on performance, you can view workspace performance metrics from within the IDE in the Backend Control Center, or by using
- You may also want to try adjusting the Max Heap Size allocated to the JetBrains Backend in the Settings tab of the Backend Control Center. If updating this setting helps your performance, you can set the
vmoptionsvalue for your JetBrains IDE in your
Note: If the performance metrics show that your workspace is hitting its resource limits, and you are using Gitpod Self-Hosted, it might make sense to consider changing the resource configuration for your workspaces. This can be done via a config-patch. Configuring workspace resources is not yet available on SaaS.