Reproducibility & DevOps

Reproducible environments, DevContainers, Docker, CI/CD, deployment, and engineering standards.

Running ShinyProxy Well: Docker, Operations, and Packaged Shiny Apps

What actually matters when deploying packaged Shiny apps behind ShinyProxy: Docker images, persistence, observability, and the boring operational details that decide whether…

March 14, 2026

Engineering Standards for Scientific Software

4 min

How I approach architecture, tests, documentation, CI/CD, handover, and technical training when building internal tools for scientific teams.

March 14, 2026

Reproducible Environments for Everyone: DevContainers for Data Science Teams

13 min

How to use devcontainers and a pre-built personal image to give every team member — including non-developers — an identical, low-setup R + Python environment.

November 28, 2025

The Reproducibility Quest: Modern Tools for R and Python Data Science

20 min

A comprehensive guide to achieving reproducible data science workflows — environment setup, package management, containerization, and what reproducibility actually means in…

June 10, 2025

rv: The Modern R Package Manager for Reproducible Workflows

8 min

Discover rv, the new declarative R package manager written in Rust. Learn how it compares to renv, draws inspiration from Python’s uv, and pairs with rig for a modern R…

January 20, 2025

Staying Current in a Fast-Moving Field: Why I Built a Resources Catalog

7 min

In data science, machine learning, and AI, the pace of change is relentless. Here’s why I maintain a curated collection of resources — and why you might want to do the same.

December 13, 2024