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This document describes the Cpu/Ram overcommit feature.
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Ideally you shouldn't change the over-provisioning factor in a cluster with vms running. This is because the some of the vms got deployed with the previous factor x.
Lets say you still want to change the factor. On changing it, both used and total capacity are multiplied by this factor to keep a track of available capacity.
Let's understand the capacity calculation below through an example :-
Cluster – c,
cpu over provisioning = 1,
Total cpu = 2GHZ
when we deploy 2VMs of 512Mhz service offering each then
totalCapacity = 2GHz
AvailableCapacity = 1GHz
UsedCapacity = 1GHZ
Now change the cpu over provisioning ratio of cluster c to 2
totalCapacity = 4GHz
AvailableCapacity = 2GHz
UsedCapacity = 2GHZ
Notice the difference in multiplication here. Both used and total capacity are multiplied by this factor. Used Capacity in the new model after changing the factor = (service offering of vm / overcommit it got deployed with) * new overcommit => (.5 GHZ/1)*2 + (.5 GHZ/1)*2 => 2GHz
The reason is want to guarantee (service offering of vm / overcommit it got deployed with) in case of contention. So when a vm is deployed with "x" overprovisioing factor we want to gurantee (service offering of vm / x ) during its lifecycle even though the overprovisioning of cluster is changed. So these vms will get .5Ghz each during contention and therefore available is still 1 Ghz during contention.
The reason to scale the used cpu is to keep track of the "actual" amount of cpu left for further vm allocation. Keep the focus on available capacity. So now available capacity is 2 Ghz when over-provisioning = 2.
Now if we launch 2 VMs with 1Ghz cpu service offering
totalCapacity = 4GHz
AvailableCapacity = 0GHz
UsedCapacity = 4GHZ
Calculation for used capacity for 4vms ((service offering of vm / overcommit it got deployed with) * new overcommit) =
(512Mhz/1)*2 + (512Mhz/1)*2 + (1Ghz/2)*2 + (1Ghz/2)*2 = 4Ghz
In case of contention first 2 vms (512Mhz service offering) get 512Mhz/1 => .5Ghz each and the next 2 vms (1 Ghz service offering and 2 overprovisioning) also get (1Ghz/2) = .5Ghz each. So adding up means 2Ghz which is the actual capacity of the host and so there is no more capacity left to accomodate more vms.
now suppose we change the over provisioning to 3
totalCapacity = 6 GHz
AvailableCapacity = 0 GHz
UsedCapacity = 6 GHZ
Calculation for used capacity for 4vms ((service offering of vm / overcommit it got deployed with) * new overcommit) =
(512Mhz/1)*3 +(512Mhz/1)*3 +(1Ghz/2)*3 + (1Ghz/2)*3 = 6Ghz
Now this is assuming, you haven't stopped and started the vms all this while. Say now you stop and start 1 VM with 512Mhz and another VM with 1Ghz. The over-provisioning factor ratio changes for these vms to 3 each. Note the denominator in the calculation.
totalCapacity = 6 GHz
AvailableCapacity = 1.5 GHz
UsedCapacity = 4.5 GHZ
Calculation for used capacity for 4vms ((service offering of vm / overcommit it got deployed with) * new overcommit) =
(512Mhz/3)*3 +(512Mhz/1)*3 +(1Ghz/3)*3 + (1Ghz/2)*3 = 4.5 Ghz
All this is done to track the available capacity for further vm allocation. If you track the "actual" capacity left on host = .5Ghz (out of 2Ghz). So now you can still create a vm with 1.5 GHz and cluster over-provisioning = 3 and hypervisor will guarantee 1.5/3 = .5 Ghz during contention.
The upside of new model is we are guaranteeing QOS as (service offering of vm / x ) during its lifecycle vs the old model
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Xenserver
Deploy vm with service offering ‘s’ and memory overcommit factor ‘f’ and overcommit factor ‘c’ --
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Same model is followed for cpu.
KVM
TBD
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kvm dose not support automatic adjustment of the guest OS memory dynamically
Note -
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