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If you need a GUI environment to access versions of R other than 4.3.1 an option that provides maximum per-user flexibility is as follows.

Use the RStudio Server web application for R 4.3.1-compatible workflows.

For workflows requiring other R versions, users can install a different their desired version of R on their own desktop/laptop computers along with the RStudio desktop application and the packages they need. Then users can access files on shared storage by mounting their Work area file system via Samba (see Samba remote file system access for more information).

The main drawback to this workflow is that typical personal computers do not have as much RAM as POD compute servers, and some R tasks can be memory intensive. What users can do in such cases is test the code in RStudio on their desktop computer, using smaller data sets if necessary. Then run the "full" workflow from the POD compute server command line using the appropriate desired R version (you can locally install newer R versions yourself)after installing it locally yourself.

Understanding R add-on packages

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• Close all browser windows and restart your computer.
  • Fragmented RAM (computer memory) can sometimes cause problems.
• Make sure the browser software being used is the latest version.
  • Version checks are usually found in the browser's "Help" → "About" dialog, accessible from the options menu in the upper right of a browser's taskbar.
• Try different browsers (e.g. Firefox instead of Chrome, Microsoft Edge, or Safari). 
  • If it is a security issue, a different browser may indicate that there are security risks accessing the website, but give the option to accept the risk and go ahead.
• Try accessing the site from an "Incognito" or "Private" browser window (usually found in an options menu in the upper right of a browser's taskbar.
  • This can bypass browser cache or cookie issues that can interfere with connections.
  Clear the browser's Cookie cache
  • that can interfere with connections.
• Clear the browser's Cookie cache

Try other compute servers

Most PODs have more than one compute server, and RStudio Server is available on all of them. Be sure to try all the compute servers on your POD to see if your issue is specific to only one of them.

If problems persist, please email our rctf-support@utexas.edu support email, including a description of what error or issue you are experiencing.

EDU pod connection issue

An issue on the EDU pod may arise when students use the edupod.cns.utexas.edu virtual host to access RStudio server. The edupod.cns.utexas.edu virtual host acts as a front end load balancer for the request, and forwards it to one of the back-end compute servers. If this occurs, try accessing individual servers specifically:

• https://educcomp01.ccbb.utexas.edu
• https://educcomp02.ccbb.utexas.edu
• https://educcomp04.ccbb.utexas.edu

If accessing a specific server works when using the virtual host does not, please let us know by emailing our rctf-support@utexas.edu support email.

Zombie processes

A "zombie" RStudio process may be preventing you from successfully logging in to an RStudio session. If your POD has more than one compute server, try logging in to one of the others. If that works, the issue is related to something on the compute server you can't login to.

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Sometimes users will get an "Unexpected response from server" error when attempting to upload a file. Here are some troubleshooting tips:

• Try the Browser issues troubleshooting tips, especially:
  • Make sure your browser is up to date with the most current version
  • Try the operation in at least 2 different up-to-date browsers (e.g. Chrome and Firefox)
  • Try the operation in a private/incognito/safe browser session
• Try the upload operation from the JupyterHub web application instead of from RStudio
• Try connecting to a specific back-end compute server as described at EDU pod connection issue

Disk quota exceeded

Another type of problem can arise when a user's 100 GB Home directory quota has been exceeded (not applicable on the EDU pod, which does not have Home directory quotas). This can produce errors when trying to start RStudio Server or R, perform work in R, or even install additional packages. For example, you may see a "Cannot connect to service" message after logging in to RStudio Server. Or, if an R session has been established and saving a new file would exceed the Home directory quota, users will often (but not always) see an error like the following:

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