RStudio Server

Browser-based IDE for R statistical computing and graphics

RStudio Server provides a browser-based development environment for R — with an editor, console, plots, and package management — backed by remote compute. It's served straight to the browser, no desktop or VNC.

Usage

1. Deploy

dxflow workflow create --identity rstudio hub://rstudio

# Start with defaults, or tune per run with --override
dxflow workflow start rstudio
dxflow workflow start rstudio \
    --override env.app.PASSWORD=my-strong-pass

# Publish the web port on an HTTPS link
dxflow workflow start rstudio --link

2. Open the IDE

Open your browser at http://localhost:8787 and sign in as USER (default dxflow) with the password you set in PASSWORD. A start given --link publishes port 8787 at an HTTPS URL printed on the start line, opening the IDE from anywhere.

3. Persist data

The R user's home directory lives under /volume, so your projects, history, and installed packages survive restarts — mount a local directory there to keep them.

Configuration

name: rstudio
tags:
    - analytics
steps:
    - name: app
      runtime: docker
      mode: parallel
      image: ghcr.io/dxflow-ai/rstudio:latest
      volumes:
          - name: volume
            host: ./volume
            container: /volume
      ports:
          - name: web
            host: "8787"
            container: "8787"
      env:
          - USER=dxflow
          - PASSWORD=dxflow
      resources:
          cpu: "4"
          memory: 8G
      link: web

[volume]
app.volume = ./volume

[port]
app.web = 8787

[env]
app.USER = dxflow
app.PASSWORD = dxflow

[resource]
app.cpu = 4
app.memory = 8G

{
    "arch": ["amd64"],
    "image": "ghcr.io/dxflow-ai/rstudio:latest",
    "version": "1.4",
    "minimum": {
        "cpu": 4,
        "memory": "8G",
        "storage": "50G"
    }
}

Notes

Set a strong PASSWORD; it defaults to dxflow, which every reader of this page knows. RStudio authenticates it through PAM against the USER account, so the sign-in page is the only way in.
The home directory is /volume/$USER (default user dxflow) — install R packages with install.packages() and they persist there.

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