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It's fascinating to see the descendants of the original AMP Lab (https://amplab.cs.berkeley.edu/) are still generating value long after it ended. For reference, Spark and Mesos are two other projects that came out of the same effort.

This blog post from the authors https://medium.com/@zongheng_yang/skypilot-ml-and-data-scien...

I believe autostop (simply stopping idle clusters) alone can masively (X times) costs for many organizations.




(SkyPilot dev) Can't agree more on autostop / autodown. Subjective to measure but save our own costs massively.


I believe the Ray suite of ML + distributed computing tools is also from AMP descendants:

https://docs.ray.io/




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