This reads like the writings of climate denialists - constant strawmanning, shifting of goalposts, selection bias in research quoted, and conspiracy theorizing.

Oh @jsignell.github.io too!

I would have suggested Max Jones, Aimee Barciauskas, or Lindsey Nield, but they don't seem to be on BlueSky, so you could instead add @jhamman.bsky.social , @rabernat.bsky.social , or myself.

There should be some @zarr.dev geospatial representation on here.

Evidence:

earthmover.io/blog/zarr-ta...

nice analogy 😉

the fact that I've never once thought about making a range request, and yet make them constantly for extremely targeted data pulls, is absolutely an invisible technical miracle

Of course- I really wrote this article for my past self! I wish someone had explained this cloud science stuff to me earlier.

It’s also important for understanding what problem VirtualiZarr solves.

I’ve given this explanation to many people in the past (including at @cworthy.bsky.social), so I hope that this article can serve as a useful reference the next time someone wonders what @zarr.dev actually is.

5/ Almost all organisations working with scientific array data have this kind of data delivery issue, even if it's just internally.

Whilst the Flux integrations today are established geospatial standards, you also see similar patterns in other fields such as Neuroscience.

4/ Flux's architecture is auto-scaling, so once turned on there is no need to worry about how many users are hitting the data.

As it's not a stateful server like THREDDS, it won't catch fire under pressure.

This is what "Cloud-Native" architectures for scientific data look like.

3/ Your downstream scientists, GIS users, analysts, and external users can all now forget about file formats!

They just keep using the same GUI or tool or script that they prefer, and don't need any other services or copies of the data made bespoke for them - Flux does that on-demand!

2/ Flux bridges this chasm.

It sits in between your data and the consumers, springing up at a moment's notice to provide subsets of data however your users prefer it.