It is as essential as to share and communicate about infrastructure design and elaborated workflows with participants as to actually automate complex operations. Literate Computing for Reproducible Infrastructure is an approach both to describe automated operations as live code and to share predicted and reproducible outcomes among technical and non-technical alike in the form of narrative stories. We utilize Jupyter Notebook for sharing the reproducible experience. Operational engineering and DevOps should be one of the distinctive application areas for Jupyter.

“Automated Operation” [機械化] ≠ “Automation” [自働化]

We want to accomplish traceability and reproducibility in engineering operations. For those primary purposes, we utilize computational narrative tools, i.e., Jupyter Notebook. Every operation is described with no doubt and can be automated. Automated operation is always along with humans in the loop and bound up with a situation. It is something different from distilled automation, which tends to result in an anesthetizing effect (Nicholas InCarr. The Glass Cage). Automated operation is a partnership between humans and machines and augments our ability to learn and expertise.

Collaboration and Communication

For reproducibility and resilience for long-term sustainability, it is crucial not only to share knowledge but also to share reproducible experience participating in both tech and non-tech alike. Narrative stories allow collaborative communication between experts and novices to accumulate infrastructure knowledge and operational experience within an operation team. Moreover, it is efficient to share an understanding of how infrastructure is usable and really works between tech ops and non-tech users. Narrative stories also help communicate with users about how services are delivered and customized, considering reproducibility.

Next: Literate Computing tools