OK so I hope this is not a too vague question, but can you tell me, what may be the benefits of still using clearML in this mode?

@<1523701070390366208:profile|CostlyOstrich36> , After talking to my manager about this, can someone from marketing contact me about Enterprise ClearML pricing?

First of all experiment management?

Don't think so. Consider that agent doesn't know who executed the pipeline or even on which machine.

OK, thank you. I think the only real limitation is that the GUI will probably not be useful for our users, but they can do everything (create projects, tasks, queues etc.) from the command line, right?

Which mode? It is indeed vague 🙂

@<1577468638728818688:profile|DelightfulArcticwolf22> , in addition to @<1523701087100473344:profile|SuccessfulKoala55> ’s answer, you have data management, orchestration (Integration with SLURM), pipelines, reports and much more.

As I mentioned, provisioning resources according to different groups - i.e. role based access controls are an enterprise feature.

I suggest you watch the onboarding videos on the ClearML Youtube channel - None

There are no role based access controls in the open source version. This feature exists only in the Scale/Enterprise licenses.

Hi @<1577468638728818688:profile|DelightfulArcticwolf22> - you can contact me directly on Slack or via email at noamb@clearml.ai

Thank you John, I suspected so...

So when using the open source clearML server, what are my options as far as multi-tenancy is concerned? I mean if I users simply run cleaml-init, with the credentials of a specifc project, and then clearml-agent with queue names, etc, How do I enable user/groups separation?

@<1523701087100473344:profile|SuccessfulKoala55> Yes, kind of, except that they do use SLURM. I am really trying to understand what are the benefits of using open source clearML in this case

@<1577468638728818688:profile|DelightfulArcticwolf22> I'm not sure what "normal" python means in this context? You mean as opposed to everyone just running python scripts and SSHing into machine to run processes manually?

OK sorry about that... Let me explain. We have researchers that sometimes work alone and sometimes in teams and our compute resources are in a SLURM based cluster. So basically, with the open source version all they can do is to open projects and run tasks while relaying on the system services to enable access separation, etc. So how is this better than just keep using "normal" python?