Azure VMSS Autoscale

Lisa Lownds 66 Reputation points
2020-02-03T19:36:30.3+00:00

Folks,
I'm trying to determine how Autoscale works:

  • If the initial instance count is 5 virtual machines, the minimum is 2 virtual machines and the maximum is 10 virtual machines. When I first deployed my VMSS, I will have 5 virtual machines running. Right?

If I have a rule that says when the CPU reaches 80% it will add an additional virtual machine.

  • How do the increase and decrease rule work? e.g. does the CPU of those initially deployed virtual machines need to operate at or above 80% CPU capacity for 5 minutes before a new instance is started or operate at below 25% CPU capacity before an existing instance is removed?

Lisa.

Azure Virtual Machine Scale Sets
Azure Virtual Machine Scale Sets
Azure compute resources that are used to create and manage groups of heterogeneous load-balanced virtual machines.
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  1. KarishmaTiwari-MSFT 18,667 Reputation points Microsoft Employee
    2020-02-04T00:59:26.827+00:00

    Hi @Lisa Lownds

    1. You are right. If your initial instance count is % VMs, when you first deploy VMSS, you will have 5 VMs running.
    2. Let's say you created a rule that increases the number of VM instances in a scale set when the average CPU load is greater than 80% over a 5-minute period. When the rule triggers, the number of VM instances is increased by 20%, if that's what you selected in the 'Action' section of the autoscale rules. In scale sets with a small number of VM instances, you could set the Operation to Increase count by and then specify 1 or 2 for the Instance count. In scale sets with a large number of VM instances, an increase of 10% or 20% VM instances may be more appropriate.

    2459-repro.png

    I would suggest reading on this example in Azure documentation: https://learn.microsoft.com/en-us/azure/virtual-machine-scale-sets/virtual-machine-scale-sets-autoscale-portal#create-a-rule-to-automatically-scale-out

    Please 'Accept as answer' if this helped you so that it can help others in the community.

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  1. Lisa Lownds 66 Reputation points
    2020-02-04T14:35:46.217+00:00

    Thank you Karishma.