Yup makes a lot of sense, it is similar to a conversation me and Marco discussed briefly on the final night, where you might want to launch a "development" Big Data quickstart profile where you don't actually launch 5 machines but instead just spin up a bunch of containers over 1 or 2 boxes and then when you're happy you spin up the same setup with a different profile. Of course you then get into LXC/LXD bridge networking issues, but I'll leave that to those who know!
-------------- Director Meteorite.bi - Saiku Analytics Founder Tel: +44(0)5603641316 (Thanks to the Saiku community we reached our Kickstart <http://kickstarter.com/projects/2117053714/saiku-reporting-interactive-report-designer/> goal, but you can always help by sponsoring the project <http://www.meteorite.bi/products/saiku/sponsorship>) On 16 February 2016 at 14:37, Mark Shuttleworth <[email protected]> wrote: > On 15/02/16 12:58, Tom Barber wrote: > > In an alternative world, it would be great to be able to extend these > > locally so when Amazon or whoever launch new instance types we could > have a > > local instance-types.yaml file or something that lets us declare new node > > types without waiting for a new juju release, or perhaps you're stuck on > a > > specific rev it would alleviate that problem... rainy day project > perhaps. > > On a similar note, I would really like to enable bundles to be usable > sanely across multiple different clouds, with detailed expressions of > the best machine instance types for particular roles in the topology. So > what's needed is an effective way to say "on the Azure cloud use this > instance type, on AWS use that, and on Google do the following". > > I think we'd want to be able to say that a bundle has "small, medium and > large" footprint variations, or perhaps "test, dense production and > scale-out production" variations, and then have a mapping inside the > bundle to specific machine types. > > If we have benchmarks for the bundles, then we could even automatically > validate and tweak those machine types, optimising for value. > > Mark > >
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