Open Stack

----- Original Message -----
> From: "Adam Lawson" <alawson at aqorn.com>
> To: "Silence Dogood" <matt at nycresistor.com>
> 
> Mathieu,
> 
> Blame it on my scattered brain but I'm now curious. How would this be
> approached practically speaking? I.e. how would ram_weight_multiplier
> enable the scenario I mentioned in my earliest post ?
> 
> //adam

It's specific to the scenario in Silence's post, which Mathiew was replying to directly.

-Steve

> 
> *Adam Lawson*
> 
> On Thu, Mar 3, 2016 at 10:43 AM, Silence Dogood <matt at nycresistor.com>
> wrote:
> 
> > cool!
> >
> > On Thu, Mar 3, 2016 at 1:39 PM, Mathieu Gagné <mgagne at internap.com> wrote:
> >
> >> On 2016-03-03 12:50 PM, Silence Dogood wrote:
> >> > We did some early affinity work and discovered some interesting problems
> >> > with affinity and scheduling. =/  by default openstack used to ( may
> >> > still ) deploy nodes across hosts evenly.
> >> >
> >> > Personally, I think this is a bad approach.  Most cloud providers stack
> >> > across a couple racks at a time filling them then moving to the next.
> >> > This allows older equipment to age out instances more easily for removal
> >> > / replacement.
> >> >
> >> > The problem then is, if you have super large capacity instances they can
> >> > never be deployed once you've got enough tiny instances deployed across
> >> > the environment.  So now you are fighting with the scheduler to ensure
> >> > you have deployment targets for specific instance types ( not very
> >> > elastic / ephemeral ).  goes back to the wave scheduling model being
> >> > superior.
> >> >
> >> > Anyways we had the braindead idea of locking whole physical nodes out
> >> > from the scheduler for a super ( full node ) instance type.  And I
> >> > suppose you could do this with AZs or regions if you really needed to.
> >> > But, it's not a great approach.
> >> >
> >> > I would say that you almost need a wave style scheduler to do this sort
> >> > of affinity work.
> >> >
> >>
> >> You can already do it with the RAMWeigher using the
> >> ram_weight_multiplier config:
> >>
> >>   Multiplier used for weighing ram.  Negative
> >>   numbers mean to stack vs spread.
> >>
> >> Default is 1.0 which means spread.
> >>
> >> --
> >> Mathieu