googleComputeEngineR has a lot of integration with
Docker, using it to launch custom pre-made images via the
Get an overview on how to install containers on Google Compute Engine here.
Dockerfiles to create the VM you want to run within, including R packages you want to install. As an example, this is a Dockerfile designed to install R packages for a Shiny app:
FROM rocker/shiny MAINTAINER Mark Edmondson (email@example.com) # install R package dependencies RUN apt-get update && apt-get install -y \ libssl-dev \ ## clean up && apt-get clean \ && rm -rf /var/lib/apt/lists/ \ && rm -rf /tmp/downloaded_packages/ /tmp/*.rds ## Install packages from CRAN RUN install2.r --error \ -r 'http://cran.rstudio.com' \ googleAuthR \ && Rscript -e "devtools::install_github(c('MarkEdmondson1234/googleID')" \ ## clean up && rm -rf /tmp/downloaded_packages/ /tmp/*.rds ## assume shiny app is in build folder /shiny COPY ./shiny/ /srv/shiny-server/myapp/
COPY command copies from a folder in the same location as the
Dockerfile, and then places it within the
/srv/shiny-server/ folder which is the default location for Shiny apps. This location means that the Shiny app will be avialable at
The example Dockerfile above installs
googleAuthR from CRAN,
googleID from GitHub and a Debian dependency for
googleAuthR that is needed,
apt-get. Modify this for your own needs.
Google Cloud comes with a private container registry where you can store public or private docker containers. It is distinct from the more usual Docker hosted hub, where most public Docker images sit.
Container names usually come in the format
You can use this directly or create the correct name for a hosted image via
gce_tag_container() - by default it uses the project you are in, but change the project name if necessary, for example for the public images available in
gcer-public at this URL:
You can use this to save a custom image with your specific dependencies, which can then also be used as a base for other custom images.
Build triggers are a feature of the Google Container Registry, which lets you build the docker image when you push to a public or private Git repository such as GitHub or Bitbucket.
This lets you use version control on your R environments, and provides a useful way to always know exactly what dependencies are running. The VMs built using your dynamic image can be stopped with their Docker versions intact, and you can try out new development versions by launching another VM.
secret. Customise this to your needs, perhaps by creating your own Dockerfile with help from
FROM rocker/tidyverse # Install secret RUN install2.r --error \ secret
Note the image name, folder to build from and that the tag is set to latest.
This should then shown in the build trigger console like this:
This is in the public googleComputeEngineR image project, but should look similar for your own.
library(googleComputeEngineR) ## auto auth messages ## set default project ID to xxxxxx ## set default zone to xxxxx vm <- gce_vm("im-rstudio", predefined_type = "n1-standard-1", template = "rstudio", username = "test", password = "test1234", dynamic_image = gce_tag_container("test-trigger", project = "gcer-public"))
Note I change the project to the public one of the image, as its different from the paid project I put the VM into, but in your case it may be the same.
The Dockerfile name is given by the
You can use this function or pass in the image name directly as listed in the Build trigger console.
FROM field in the
Dockerfile could be a previously made image you or someone else has already created, allowing you to layer on top. The first example above is available via a public Google Continer Registry called
gcer-public, made for this purpose, which you can see here:
One example is
shiny-googleauthrdemo - to construct the correct name we need this and the
gcer-publicproject Id to use within the
This can then be added to to top of your
Dockerfile, and built upon with custom packages:
FROM gcr.io/gcer-public/shiny-googleauthrdemo MAINTAINER Mark Edmondson (firstname.lastname@example.org) # install R package dependencies RUN apt-get update && apt-get install -y \ ##### ADD YOUR DEPENDENCIES ## clean up && apt-get clean \ && rm -rf /var/lib/apt/lists/ \ && rm -rf /tmp/downloaded_packages/ /tmp/*.rds ## Install packages from CRAN RUN install2.r --error \ -r 'http://cran.rstudio.com' \ ##### ADD YOUR CRAN PACKAGES ##### && Rscript -e "devtools::install_github( ## ADD YOUR GITHUB PACKAGES )" \ ## clean up && rm -rf /tmp/downloaded_packages/ /tmp/*.rds ## copy your shiny app folder below COPY ./shiny/ /srv/shiny-server/myapp/
Hopefully more images can be added in the future, along with community contributions. They are rebuilt every commit to the
googleComputeEngineR GitHub repo.
If not building via
Dockerfile (which is preferred), you can save the state of a running container.
For example, you may wish to install some R packages manually to an RStudio instance via its terminal window. Once done, then on your local machine you can save the running container to a new image on Google container registry via
This can take some time (10mins +) if its a new image. You should be able to see the image in the web UI when it is done.
Once saved, the new image can be used to launch new containers just like any other image.
If you want to customise further, the docker commands are triggered upon start up via
These can be used to configured to do more system level commands such as starting the docker service, create users and running start up scripts. These are accessible via the
gce_vm_container function when you supply the
cloud_init file. You can examine the
cloud-config files used in
googleComputeEngineR in this folder:
An example for the RStudio template is shown below. The
%s are replaced with metadata passed via the
#cloud-config users: - name: gcer uid: 2000 write_files: - path: /etc/systemd/system/rstudio.service permissions: 0644 owner: root content: | [Unit] Description=RStudio Server Requires=docker.service After=docker.service [Service] Restart=always Environment="HOME=/home/gcer" ExecStartPre=/usr/share/google/dockercfg_update.sh ExecStart=/usr/bin/docker run -p 80:8787 \ -e "ROOT=TRUE" \ -e "R_LIBS_USER=/library/" \ -e USER=%s -e PASSWORD=%s \ -v /home/gcer/library/:/library/ \ --name=rstudio \ %s ExecStop=/usr/bin/docker stop rstudio ExecStopPost=/usr/bin/docker rm rstudio runcmd: - systemctl daemon-reload - systemctl start rstudio.service