diff --git a/workshop-releases.md b/workshop-releases.md index 48695a35..571772ad 100644 --- a/workshop-releases.md +++ b/workshop-releases.md @@ -43,31 +43,32 @@ Once the [Build Docker Image](https://github.com/AlexsLemonade/training-modules/ One important thing to note is that there are a number of symbolic links in the `/etc/skel` directory that point to shared data files in the `/shared` directory on the Data Lab RStudio server. If running the Docker image locally, these links will be broken, but they should work correctly on the RStudio server if the `/shared` directory is mounted. -### Testing on the RStudio server +### Testing on the RStudio Server -To test the Docker image on the Data Lab RStudio server, you will want to log into the server via SSH (not via the RStudio interface). -You can then use the following commands to pull the Docker image and run launch the container interactively with a bash shell: +To test the Docker image on the Data Lab RStudio server, follow the instructions in the `rstudio-server` README: -```bash -docker pull ccdl/training_rstudio:edge -docker run -it --rm \ - --mount type=bind,source=/shared/data,target=/shared/data,readonly \ - ccdl/training_rstudio:edge bash -``` - -Then within the container, you can check that the `/etc/skel` contains the expected contents: `ls -la /etc/skel` should look something like this (skipping the `.` and `..` entries): +Briefly, you will need to create a new user of the `edge` session type, which uses the `ccdl/training_rstudio:edge` Docker image and deploy that change to production. +Then, log in as that user via RStudio server and check that the `home` directory contains the expected contents from the `/etc/skel` directory, which will look something like (assuming the user is `dlab`): -``` --rw-r--r-- 1 root root 220 Jan 6 2022 .bash_logout --rw-r--r-- 1 root root 3771 Jan 6 2022 .bashrc --rw-r--r-- 1 root root 807 Jan 6 2022 .profile -lrwxrwxrwx 1 root root 12 May 23 16:52 shared-data -> /shared/data/ -drwxr-xr-x 4 root root 4096 May 23 16:52 training-modules/ +```bash +$ ls -lah ~ +drwxr-x--- 6 dlab dlab 4.0K Nov 19 20:16 . +drwxr-xr-x 1 root root 4.0K Nov 19 20:13 .. +-rw-r--r-- 1 dlab dlab 220 Jan 6 2022 .bash_logout +-rw-r--r-- 1 dlab dlab 3.7K Jan 6 2022 .bashrc +drwxr-xr-x 3 dlab dlab 4.0K Nov 19 20:16 .config +drwxr-xr-x 3 dlab dlab 4.0K Nov 19 20:16 .local +-rw-r--r-- 1 dlab dlab 807 Jan 6 2022 .profile +drwxr-xr-x 3 dlab dlab 4.0K Nov 19 20:16 R +lrwxrwxrwx 1 dlab dlab 12 Nov 18 22:28 shared-data -> /shared/data +drwxr-xr-x 4 dlab dlab 4.0K Nov 18 22:28 training-modules ``` Within the `training-modules` directory, you should see the modules that you specified in the `current-modules.json` file, and you can check that the files are present as expected. You should also be able to check that the symbolic links to the `/shared/data/` directory are working correctly. -For example, running `ls -la /etc/skel/shared-data/` which should show the contents of the `/shared/data/`, and links within modules' `data/` directories should point to the correct files (usually in `/shared/data/training-modules/`). +For example, links within modules' `data/` directories should point to the correct files (usually in `/shared/data/training-modules/`). + +After verifying that the Docker image is working as expected, you can cleanup the test user as described in the `rstudio-server` README. ### Testing locally