This is how the planners determine where to place the VM based on
needs like enough capacity(cpu, memory, storage)

Once the available capacity and requested capacity is determined, the
following heuristics are applied to determine the final deployment
plan of the VM:

1. random will choose a random host for the VM (note: random doesn't
imply it won't go to the same host. that may appear as an aberration)

2. firstfit as the name suggests will put the VM in the first suitable
host that is available with enough capacity

3. userdispersing - choose the cluster such that other VMs of the user
(account) are placed as far apart as possible. As far apart being
different clusters - different hosts

4. and 5. are related - concentration basically is the inverse of
dispersion. try and put the VM as packed and close as possible wrt
other VMs of the user(account). So VM1 and VM2 are said to be
concentrated if they belong to the same pod.

The need for 3 arose from providing basic tolerance to failures in
physical resources. And the need for 4. and 5. arose so as to provide
better performance (read, write, network) to VMs in a group.

Apart from all this there are affinity/anti-affinity groups. Host and
Storage tags, HA dedicated hosts, HA tags, etc that can determine the
placement/planning of VMs.

Under what context are you looking to understand this though? That can
help explain the algorithms involved further.

-- 
Prasanna.,

On Thu, Jul 11, 2013 at 09:44:24AM +0000, Sanjeev Neelarapu wrote:
> 
> 
> From: Kiran Koneti
> Sent: Thursday, July 11, 2013 3:13 PM
> To: #Cloud - Engineering
> Subject: Regarding the vm.allocation.algorithm.
> 
> Hi All,
> 
> Where can we find the documentation for the "vm.allocation.algorithm" global 
> setting parameter.
> 
> I just wanted to know the behavior of the different values for this 
> parameter. I see the below values but want to know what is the functionality 
> of each.
> 
> 1)random
> 2)firstfit
> 3)userdispersing
> 4)userconcentratedpod_firstfit
> 5)userconcentratedpod_random
> 
> 
> Regards,
> Kiran.


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