First, to review the definitions from Wikipedia.

DevOps - DevOps is a software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). The main characteristic of the DevOps movement is to strongly advocate automation and monitoring at all steps of software construction [..]. DevOps aims at shorter development cycles, increased deployment frequency, and more dependable releases, in close alignment with business objectives.

Data Science - Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured [..].

Now let's consider two cases.

A. DevOps for Data Science: use DevOps knowledge base to deliver shorter cycles in data science experiments, more automation and scalability as well as reproducible experiments. Business case: "works on my machine" is a known problem also in data science teams and transition from first experiments to production is not always easy.

B. Data Science for DevOps: use Data Science knowledge base to define and implement the vague "Measure" in DevOps principles. Using Industry 4.0 approach, you could evaluate data from the whole toolchain. Of course companies collect and analyse time series data, but afaik this is much more focused on production, or limited to the scope of separate tools. Business case: holistic data driven insights - not replacing but augmenting human interaction - in large scales environments (think of dozens of scrum teams and hundreds, even thousands of [micro]services).

Now my questions (please try to judge in terms of Q&A community strategy):

  • Are A, B both more or less offtopic here or only one of them?
  • Would you recommend proposing a separate community for either A,B or both?
  • 1
    $\begingroup$ A is DevOps, not on topic. B is Data Science, on-topic. In both cases I do not think the problem the discipline is being applied to is relevant to the issue of whether on-topic or not. $\endgroup$
    – Stephen Rauch Mod
    May 5, 2018 at 0:00

1 Answer 1


Both categories sound like they could be on topic; B more than A. It depends. I suppose it depends on what type of person is most likely to give a good answer. Readers here are more data science than devops. If the question hinges more on understanding of data science than devops, it's probably a fit here.


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