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docs/cicd/index.qmd

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+---
+title: CI/CD
+---
+
+Continuous Integration / continous delivery (CI/CD) is a basic tool in todays Data Science toolstack to automate processes and execute repetite tasks on schedule.
+
+Running tasks in CI/CD should be fast and reliable, no matter the language, architecture or computing environment at hand.
+As CI/CD requires installing many packages over and over again, having binaries and optimized distributions helps to reduce runtime.
+
+This page presents snippets for well and lesser known CI/CD engines to help getting started with the R package binaries of this project.
+
+::: {.callout-note}
+The presented snippets rely on external projects and libraries which get updated regurarly.
+There is no guarantee to work out-of-the box at all times.
+If you found an error, please open a pull request in the linked repo.
+:::
+
+## GitHub Actions
+
+### VM
+
+GitHub Actions can be run directly on a VM or in a containered context.
+The available VM images can be found [here](https://github.com/actions/runner-images#available-images).
+The only Linux distribution available is Ubuntu.
+
+For VM workflows, [r-lib/actions](https://github.com/r-lib/actions/blob/v2/examples) provides many examples for different use cases.
+
+To use package binaries from this project, use the following config for `r-lib/actions/setup-r@v2`:
+
+```yaml
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
+          Ncpus: 2
+          cran: 'https://cran.devxy.io/amd64/noble/latest'
+```
+
+(`Ncpus: 2` has been set to allow for parallel installations.)
+
+### Container
+
+An alternative is to run Actions in a containerized context.
+This spins up a container of the selected image in the VM and allows running on other distributions than Ubuntu, e.g. on Alpine.
+To avoid having to install R first and configure a custom repository every time, [specialized images](https://hub.docker.com/r/devxygmbh/r-alpine) are provided which already have everything in place:
+
+```yaml
+jobs:
+  container:
+    runs-on: ubuntu-latest
+    container: devxygmbh:r-alpine
+    steps:
+      - run: |
+          R -q -e 'install.packages("pak", repos = sprintf("https://r-lib.github.io/p/pak/devel/%s/%s/%s", .Platform$pkgType, R.Version()$os, R.Version()$arch))'
+          R -q -e 'getOption("repos")'
+          R -q -e 'options(Ncpus = 2); pak::local_install_dev_deps()'
+```
+
+::: {.callout-note}
+When running in a containerized context, the predefined actions from `r-lib/actions` cannot be used. 
+Shell/R commands must be used directly.
+:::
+
+::: {.callout-note}
+Running containerized in Alpine should be substantially faster than running in a VM context.
+:::
+
+::: {.callout-tip}
+(91 packages)
+
+- Containerized: **1m 21s**
+- VM: 2m 11s
+
+Both runs are based on the assumption that caching is not used. With caching enabled, the performance of both approaches should be roughly comparable.
+
+Source: [pat-s/workflow-compare](https://github.com/pat-s/workflow-compare)
+:::
+
+
+## GitLab Runner
+
+WIP