Community documentation on setting up a local OSF instance

I think it would be very useful to have a document with the best practices of people setting up a local OSF instance at their home institute. In the issue list I noticed several people have worked on this in the past (https://github.com/CenterForOpenScience/osf.io/issues/6248, https://github.com/CenterForOpenScience/osf.io/issues/7219, https://github.com/CenterForOpenScience/osf.io/issues/6255, https://github.com/CenterForOpenScience/osf.io/issues/7347, https://github.com/CenterForOpenScience/osf.io/issues/7805, https://github.com/CenterForOpenScience/osf.io/issues/8493). The Docker Compose document is a good starting point for a local installation. However, my experience is that it does not cover specific application configurations, like when to create a local.py and what values to change.

For me it is also not clear how to setup working with files on a local installation. I guess this goes via Waterbutler, but any input or best practices on this topic would be highly appreciated. Also which storage option is used as default (Amazon S3, or any other object storage system like Swift, Ceph or Minio)

@umardraz, @mfraezz, @yacchin1205, @sloria, @mattvw, @antonwats, @jpkeith4, @HiroyukiNaito, I would appreciate it if you can share you experiences with setting up a local OSF installation. Did you succeed to setup an instance? What was the most difficult part? Is it still in use?

[pdurbin]

I have a half baked dream of spinning up software related to Dataverse (you can deposit data from OSF into Dataverse) using the Kubernetes config in https://github.com/IQSS/dataverse-kubernetes . I’m coming at the from the Dataverse developer perspective of wanting to ensure that integrations are tested regularly. Right now I think we rely on users to tell us if we broke something. 😄

I got this idea of spinning up related software in our ecosystem in Kubernetes from @craig-willis who created https://www.workbench.nationaldataservice.org which is described at http://www.nationaldataservice.org/platform/workbench.html and has “specs” various software (including Dataverse, CKAN, Globus, Jupyter, etc.) at https://github.com/nds-org/ndslabs-specs

I have no idea if anyone has any time to work on any of this though. It’s just a thought.

I agree that docs are crucial. Maybe someone from the OSF community could apply for https://developers.google.com/season-of-docs/

Hi, @RightInTwo !!! 👋

[Johnetordoff]

@CaptainSifff if your organization is interested in using a personal OSF instance, I suggest they look at the implementation for RDM-osf.io. That’s essentially the only large group that has forked our project that is being actively used and is open source. If you’d like to use just a portion of our functionality I’d recommend integrating with our services as is, such as WaterButler and modular-file-renderer, or forking one of those services. I’d also strongly recommend using our new Oauth2 capabilities to utilize our file storage and REST API.

We are somewhat cagey about writing precise instructions for setting up osf.io because the data model and external integrations we are writing change frequently and we simply don’t have the resources to walk people through the process individually, but if you are representing an institution and want more details please contact us at [e-mail] and we and talk about what is best for your use case. Mention that you had a conversation with John Tordoff and name the organization you represent and will answer your questions to the best of our ability.