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Is DevOps methodologically anyhow different or even applicable in the academia field if used in research and science projects?

closed as unclear what you're asking by Pierre.Vriens, Tensibai Apr 1 at 7:46

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  • so the ops organizations remain to watch identity management, budget and security controls? Otherwise reseachers have to become cost aware of any experiment iteration being it CI job or model training. – Peter Mar 28 at 12:21
  • I've added an answer now, @Peter. – AnoE Mar 28 at 17:09
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    This is such a vague question. Research and science varies from clinical trials and launching satellites down to comsci projects by PhD students. For the question to be a good fit it should be specific and not something that so vague that any answer couldn't be identified as being accurate or not. – simbo1905 Mar 28 at 19:02
  • Still I find Anoe's answer very satisfying. – Peter May 10 at 5:29
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Disclosure - I have not worked in proper ("Academia") research and science projects.

DevOps should be just fine for researchers. As in the commercial world, the interesting bit will be to pick the line where the DevOps teams start and where the lower level base ops begins. This is not a contradiction. You may still have a dedicated ops team which provides the hardware, networking, OS, container management (Kubernetes ect. if you have something like this) and so on.

The most crucial part is that these ops guys now provide the base for the other teams. This means there is not a hand-over of software between the other teams and ops. Ops has the responsibility to provide the DevOps teams with an infrastructure (or platform, whatever you may call it in your case) so they can do their slightly higher-level stuff in a self-sufficient manner. The base ops team would do the hard lifting (i.e., IAM, license stuff, security issues etc.).

There is a plethora of possible ways to structure this. E.g., if you are in a non-techy research field (say, statistics, where people know R but nothing much else), you will have a different structure than if your researchers are hardcore coders/OS experts (say, the VR department where researchers program GPUs etc.).

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