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What's the state of 'traditional' turnkey time sharing for coding + development in 2023? Are always-on, signon-and-go servers or clusters of servers with shared

What's the state of 'traditional' turnkey time sharing for coding + development in 2023? Are always-on, signon-and-go servers or clusters of servers with shared storage and a wealth of pre-installed software used by a community of scores or hundreds or thousands of developers still a common thing? Or has that pretty much gone by the wayside and most development is carried out in more isolated, individualized, single-user oriented environments - be it laptop/desktop or Cloud-based (containers, VMs, EC2, etc.) that are customized/tailored to single individual's needs?

GMoromisato 3y ago
I don't know about "traditional" systems, but I'm trying to create a modern time-share system for building web apps. There's a work in progress at: https://gridwhale.com https://gridwhale.com. (Warning: Still primitive and lots of bugs). My manifesto is here: https://medium.com/@gridwhale/rise-of-the-hyperplatforms-d4a148e608de https://medium.com/@gridwhale/rise-of-the-hyperplatforms-d4a...
packetlost 3y ago
I'm not sure if this is what you're getting at, but the tilde[0] and SDF[1] communities are going pretty strong still. Both of them amount to getting a shell account on a shared box with a bunch of pre-installed/hosted utilities. Much more hobbyist-centric than professional though. [0]: https://tildeverse.org https://tildeverse.org [1]: https://sdf.org https://sdf.org
kedean 3y ago
Supercomputing environments I've encountered are still timesharing-based, because by definition they are too expensive to be single-user. My old university still operates a cluster-based system that you can submit jobs to, with "head nodes" that have ssh access for light work/setup (they aren't suited for heavy jobs). It's operated by the CS dept but available for others to use, the sciences in particular.
- sneed_chucker 3y ago
  From what I've seen at FAANG companies, GPU clusters for ML researchers are similar. Basically a bunch of beefy nodes with 96 CPUs and 8 Nvidia A100 cards each configured in a SLURM cluster. Users get SSH access and can run tmux, jupyter, or whatever else is needed for their workflow.

GMoromisato 3y ago

I don't know about "traditional" systems, but I'm trying to create a modern time-share system for building web apps. There's a work in progress at: https://gridwhale.com https://gridwhale.com. (Warning: Still primitive and lots of bugs). My manifesto is here: https://medium.com/@gridwhale/rise-of-the-hyperplatforms-d4a148e608de https://medium.com/@gridwhale/rise-of-the-hyperplatforms-d4a...

packetlost 3y ago

I'm not sure if this is what you're getting at, but the tilde[0] and SDF[1] communities are going pretty strong still. Both of them amount to getting a shell account on a shared box with a bunch of pre-installed/hosted utilities. Much more hobbyist-centric than professional though. [0]: https://tildeverse.org https://tildeverse.org [1]: https://sdf.org https://sdf.org

kedean 3y ago

Supercomputing environments I've encountered are still timesharing-based, because by definition they are too expensive to be single-user. My old university still operates a cluster-based system that you can submit jobs to, with "head nodes" that have ssh access for light work/setup (they aren't suited for heavy jobs). It's operated by the CS dept but available for others to use, the sciences in particular.

sneed_chucker 3y ago
From what I've seen at FAANG companies, GPU clusters for ML researchers are similar. Basically a bunch of beefy nodes with 96 CPUs and 8 Nvidia A100 cards each configured in a SLURM cluster. Users get SSH access and can run tmux, jupyter, or whatever else is needed for their workflow.