We’re now going to create a custom Docker image based on the rocker/verse image we used above. $ docker stop 487487fc346d Creating a New Container Image The ID in the output from the previous command is used to stop the container. Once you’ve satisfied yourself that the RStudio server is working properly, we’ll shut it down. Login with username rstudio and password rstudio. Now point your browser at You should see a login dialog. Once the downloads are complete we can spin it up. Depending on the speed of your connection it might take a couple of minutes. We’ll install the verse container which contains base R, RStudio, tidyverse, devtools and some packages related to publishing. Share images, automate workflows, and more with a free Docker ID:Ī selection of RStudio Docker containers are hosted by the Rocker project. To try something more ambitious, you can run an Ubuntu container with: The Docker daemon streamed that output to the Docker client, which sent it The Docker daemon created a new container from that image which runs theĮxecutable that produces the output you are currently reading.Ĥ.
The Docker daemon pulled the "hello-world" image from the Docker Hub.ģ. The Docker client contacted the Docker daemon.Ģ. To generate this message, Docker took the following steps:ġ. This message shows that your installation appears to be working correctly. To see further system information about Docker: $ docker infoįinally run a quick test to ensure that Docker is able to download and launch images. This should indicate that Docker is loaded, running and active. $ docker -vĬheck the current status of the Docker service. First it makes sense to validate that Docker is correctly configured and operational. Validate Dockerīeing my first serious foray into the world of Docker I spent some time getting familiar with the tools. I added my user to the docker group and I was ready to roll. On my Linux machine this was a simple procedure. I began by trying things out on my local machine. I provide some additional details about the process. These are some notes about how I got this all set up using a Docker container on DigitalOcean. Setting up a RStudio server which everyone can access (and that requires no individual configuration!) makes a lot of sense. And with multiple operating systems (and versions) these issues can be numerous and pervasive. Since it’s a short course I don’t want to spend a lot of time sorting out technical issues. I’ll be running a training course in a few weeks which will use RStudio as the main computational tool.
0 kommentar(er)
