Resources for new R admins



I am about to embark on the R admin journey. I'll be managing a small setup with RStudio server pro and RSConnect installed on the same server with no dev/test server. I have looked at the admin guides and have some familiarity with Linux but no prior experience as a Linux admin. I will be working closely with IT for security and authentication but I think I will be managing the software beyond that.

What resources or advice is available for new R admins beyond the admin guides and this forum? I'm interested in getting a sense of what all this role entails for others and what the most difficult parts of the job are.

I really enjoy Nathan's talk from the rstudio conf 2018 (

Looking forward to diving in!


Exciting stuff! Looking forward to hearing how it goes! Some resources that may be helpful:

A bit of an overview:

On learning Linux:

A relatively new Github org focused on this problem and these types of resources:

Nathan's resources from the talk you mention:

More on how we think about R installations in a server environment:

Ultimately, getting familiar with the UNIX terminal will be a huge asset (things like cd, ls, grep, system daemons, config files, vim, and the like). You can also practice building R from source, which is a good skill to have on hand. I think @nathan is doing a webinar on the topic this week, and there is a budding website at .


What I found most helpful for testing and experimentation was downloading and using docker. If you're on Windows, grab docker for windows. If mac, then just install docker. Once you have docker, you can grab the image of your choice (ubuntu, centos) that matches what you're using in production.

This helped me enormously. You can try installing R, installing or upgrading packages, and installing OS dependencies for those packages in your docker container. If you screw it up - who cares! Throw the container away and start a new one.

If you're new to docker as well, I've got a cheat sheet that I put together that should help you get started.


Thanks! I am new to docker. What is the difference between docker and a preconfigured virtual machine? A cheat sheet would be helpful.


Here's some resources to get started:

What is important to know is that it's very easy to pull pre-built container images from

You want an ubuntu container? From your command line (once docker is installed) just run "docker run -it ubuntu bash", and docker will pull an ubuntu image from, and launch you right into the container as root.

You want a centos container? Just run "docker run -it centos bash".

Let me see what I can do about getting you the cheatsheet.


docker has a lot of semantics that make it much more lightweight than a virtual machine. This makes it very nice for the type of throw-away exploration that @snkfischer is talking about (or microservices, etc.). It also does not have its own kernel (it uses the host machine's kernel), which makes images much less resource-intensive, starts up quicker, etc.

On a typical workstation, a few VMs will cripple the host machine's resources because you are running several operating systems concurrently (and lots of overhead with it). With Docker, it's way easier to run a whole bunch of containers concurrently without resource issues, and it pretends to have a separate operating system, so you still have some really helpful isolation. There are some nuances to this, because this does mean it is more tightly coupled to your OS than a VM will be, but that's what the community here, the Docker community, and documentation are for! :slight_smile:


Thanks @cole. That is a helpful explanation. I tried installing Docker on my macbook pro last night and turns out my CPU is not supported. My computer is old but still works well for most applications since I upgraded the hard drive to an SSD. However it seems like Docker is not going to work. I might try using another computer though.


Ah I'm sorry to hear that! You could always try installing an older version of Docker, perhaps? I know very little about CPU compatibility :slight_smile: This is a little funky (and definitely more complex), but you could also try installing docker in a VM on your computer :open_mouth: I'm not sure if that abstracts the CPU enough to trick docker into installing or if you'll just end up at the same road-block.

The other option is something like one of the cloud providers (AWS, GCP, etc.). Most offer a free tier for a year or a free credit or something that you can use to spawn a small linux machine in the cloud. You can install docker on that little machine and then play with it through an SSH session. There are benefits of being forced to use the terminal and learning some more complex networking stuff! Of course, it is a bit more work to do so.


This thread has turned into "How do I run R with Docker?". Kelly O'Briant on the RStudio team recently gave this presentation at UseR! 2018:


There's video of this talk as well: