Run JetBrains IDEs remotely with Docker (by JetBrains)


Basic projector-docker repo stats
26 days ago

JetBrains/projector-docker is an open source project licensed under Apache License 2.0 which is an OSI approved license.

Projector-docker Alternatives

Similar projects and alternatives to projector-docker based on common topics and language

  • GitHub repo projector-client

    Common and client-related code for running Swing applications remotely

  • GitHub repo compose-jb

    Jetpack Compose for Desktop, a modern UI framework for Kotlin that makes building performant and beautiful user interfaces easy and enjoyable.

  • GitHub repo projector-server

    Server-side library for running Swing applications remotely

  • GitHub repo projector-installer

    Install, configure and run JetBrains IDEs with Projector Server on Linux or in WSL

  • GitHub repo weblaf

    WebLaF is a fully open-source Look & Feel and component library written in pure Java for cross-platform desktop Swing applications.

  • GitHub repo FlatLaf

    FlatLaf - Flat Look and Feel (with Darcula/IntelliJ themes support)

NOTE: The number of mentions on this list indicates mentions on common posts. Hence, a higher number means a better projector-docker alternative or higher similarity.


Posts where projector-docker has been mentioned. We have used some of these posts to build our list of alternatives and similar projects - the last one was on 2021-03-11.
  • Run JetBrains IDEs Remotely with Docker | 2021-03-12
  • JetBrains Projector released - Access Your IDE Remotely With Projector
    Worked a lot better using one of their Docker images, but feels like it has too many drawbacks compared to my current VcXsrv setup. Cool stuff though, hope it gets developed further.
  • Use docker container as python development environment
    As u/dukea42 mentioned VS Code has an excellent [Remote Development]( extension that allows you to connect the IDE directly to the container. I'm not sure how well this will work with conda, but if you go this route I recommend trying to isolate the container from the host as much as possible (ie: don't try to integrate with the host conda installation and instead load all of the dependencies and runtime directly in the container). This way the container can be reused on any machine without the need for any sort of host dependencies. As for getting PyCharm to work this type of setup, you can look at [JetBrains Projector]( personally have not worked with projector yet, but based on JetBrains track record I'm sure this will work well. The only downside I see of this setup, is that it will make your Container rather large in size, since it will require the Pycharm application to be installed inside the container. But if that's an acceptable trade off for you, this seems like containerization solution that would feel most similar to your current set up.When it comes to managing your environment I recommend taking a look at myceleum, it's a platform we have been working that tries to simplify the process of creating development environments and will also sync your environment accross machines (and team if you are part of one).We are still in Beta, but the application can be downloaded from our website [](Download myceleum). And if you feel like any functionality is missing from the application, you can reach our at [email protected] and we will look into adding it into the platform.When it comes to running the environment, we try to integrate with all IDE's, but we recommend using VS Code with the remote extension as mentioned above, or using the myceleum IDE which will feel very similar to VS Code, but comes bundled into the application.
  • M1 users, how is the 8/16GB memory limit? "I found my best work happens with 8Gb of RAM, [it] enforces discipline"
    /uj Well you see...