Category: Microsoft

When using any environment that provides virtual desktops at scale, it makes sense to have only the required number of resources running at the right time – rather than all of the resources all of the time. The usual approach to this is to use power management – so unused virtual machines are shut down when not in use.

With Azure we have another potential option designed for large workloads – to use Virtual Machine Scale Sets. This allows us to automatically scale up and down the number of Virtual Machines based on various factors and choices. This effectively allows us to ensure the most economical use of resources – as we never pay for more than we need to use, because the machines are de-allocated when not required. Scale Sets also provide a number of features around image management and VM sizing that could be useful for VDI environments.

In this post I am going to explore the validity and feasibility of VM Scale Sets for a Remote Desktop Services Environment. To start this post – I have the following environment configured, minus the scale set:

Note: if you need an RDS environment – this Azure template is awesome: https://azure.microsoft.com/en-gb/resources/templates/rds-deployment/ – I would advise using multiple infrastructure VMs for each role if this is a production service though.

Next – I configured a single server with the RDS Session Host role and all of the applications I require, as this will become our VM image. I then ran sysprep /generalize as per the Microsoft instructions for Image Capture in Azure. (See here). Once this is done we need to stop and de-allocate the VM, and then we need to turn this into an image we can use with a scale set:

$vmName = "rdsimage01"
$rgName = "eus-rg01"
$location = "EastUS"
$imageName = "rdsworker"
Stop-AzureRmVM -ResourceGroupName $rgName -Name $vmName -Force
Set-AzureRmVm -ResourceGroupName $rgName -Name $vmName -Generalized
$vm = Get-AzureRmVM -Name $vmName -ResourceGroupName $rgName
$image = New-AzureRmImageConfig -Location $location -SourceVirtualMachineId $vm.ID
New-AzureRmImage -Image $image -ImageName $imageName -ResourceGroupName $rgName

Once this is done – we have a VM image saved:

So once we have an image – we can create Virtual Machines from this image, and create a Scale Set that will function as the means to scale up and down the environment. However – we need to do some more work first, as if we just scale up and down with a sysprepped VM, we end up with a VM off domain that won’t be of any use to us…. !

Usually – I just spin up Lab VMs using a JSON Template that creates the VM and joins it to an existing lab domain, using the JoinDomain extension. This saves me lots of time and gives me VMs deployed with minimal input (just a VM name is all I have to enter):

    {
      "apiVersion": "2015-06-15",
      "type": "Microsoft.Compute/virtualMachines/extensions",
      "name": "[concat(parameters('dnsLabelPrefix'),'/joindomain')]",
      "location": "[resourceGroup().location]",
      "dependsOn": [
        "[concat('Microsoft.Compute/virtualMachines/', parameters('dnsLabelPrefix'))]"
      ],
      "properties": {
        "publisher": "Microsoft.Compute",
        "type": "JsonADDomainExtension",
        "typeHandlerVersion": "1.3",
        "autoUpgradeMinorVersion": true,
        "settings": {
          "Name": "[parameters('domainToJoin')]",
          "OUPath": "[parameters('ouPath')]",
          "User": "[concat(parameters('domainToJoin'), '\\', parameters('domainUsername'))]",
          "Restart": "true",
          "Options": "[parameters('domainJoinOptions')]"
        },
        "protectedSettings": {
          "Password": "[parameters('domainPassword')]"
        }

See https://github.com/Azure/azure-quickstart-templates/tree/master/201-vm-domain-join for more details and to use this template.

Now that we have a template – we are ready to go. I’m using Visual Studio to create the JSON for my deployment – and fortunately there is a built in scale set template we can use and modify for this purpose:

With the template up and running, we just need to add some parameters – and we can run a basic test deployment to confirm everything is working. My parameters for the basic template are shown below:

A quick test deployment confirms we are up and running:

However, there are a few issues with the template we need to correct – namely:

• The machines are not joined to the Domain – and we need to place them into the correct OU for GPO settings too
• A new VNET is created – we need to either use peering (prior to creation – or domain join operations will fail), or better an existing VNET already setup
• The load balancer created is not required – we’ll be using the RDS Broker anyway

For this test – all I am concerned about is the domain join and VNET. The load balancer won’t be used so I can just discard this – however, the VNET and Domain Join issues will need to be resolved!

Issue 1 – using an existing VNET

To fix this, I am not going to reinvent the wheel – we just need some minor adjustment to the JSON file, based on this Azure docs article – https://docs.microsoft.com/en-us/azure/virtual-machine-scale-sets/virtual-machine-scale-sets-mvss-existing-vnet. In short, this will achieve the following:

1. Add a subnet ID parameter, and include this in the variables section as well as the parameters.json
2. Remove the Virtual Network resource (because our existing VNET is already in place)
3. Remove the dependsOn from the Scale Set (because the VNET is already created)
4. Change the Network Interfaces of the VMs in the scale set to use the defined subnet in the existing VNET

Issue 2 – joining the Scale Set VMs to an AD Domain

To get the VMs in the scale set joined to an AD Domain we need to make use of JsonADDomainExtension.

"extensionProfile": {
    "extensions": [
        {
            "name": "joindomain",
            "properties": {
                "publisher": "Microsoft.Compute",
                "type": "JsonADDomainExtension",
                "typeHandlerVersion": "1.3",
                "settings": {
                    "Name": "[parameters('domainName')]",
                    "OUPath": "[variables('ouPath')]",
                    "User": "[variables('domainAndUsername')]",
                    "Restart": "true",
                    "Options": "[variables('domainJoinOptions')]"
                },
                "protectedsettings": {
                    "Password": "[parameters('domainJoinPassword')]"
                }
            }
        }
    ]
}

With this added to the JSON template for our deployment, we just need to add the variables and parameters (shown below) and then we are good to go:

Note: the first time I used this I had an issue with the Domain Join – it was caused by specifying only the domain admin username. When specified in the form above (domain\\adminusername) it then worked fine.

Now when we run the template, we get the usual Visual Studio output confirming success – but also a scale set, and, machines joined to the domain:

Because I have previously configured the image used in the Scale Set with the RDS Role, and the Software required – we just need the servers to use an RDS Broker that will manage inbound connections into the RDS Farm. This is where I encounter the first sticking point – these need to be added manually when the Session Collection is created 🙁

This wasn’t a massive issue for this test – so I went ahead and created a Session Collection and added in my VMs:

Next I tested the solution by launching a Desktop via Remote Desktop Web Access:

Bingo – I was then logged into an RDS Session. Note the RDS Connection Name (showing the Broker) and the Computer Name (showing the Session host). This confirms we are running as expected:

I’ve now demonstrated the RDS Farm up and running, utilizing machines created by a Scale Set, and also accessed via a connection broker. But – we aren’t quite done yet, as we have not looked how a scale set could enhance this solution. Below are a few ways we can improve the environment using Scale Sets, and a few limitations when used with RDS:

• We have the option to Manually increase VM instances if we need more Session Hosts:

Note: this will require adding to the RDS Session collection manually (or via PowerShell)

• We can scale the environment automatically using Auto Scale:

Below you can see a default scale rule (5 VMs in the Scale set) and then a rule that runs between 0600 and 1800 daily, and increases the VM Count up to 10 VMs if average CPU usage goes above 80%.

The rule for this Scale operation is shown below:

Note: this will still require machines adding to the Session Collection manually.

• We can increase the size of the VMs

Once a new size has been selected – the existing VMs show as not up to date:

We would then need to upgrade the VMs in the scale set (requiring a reboot), but, does not require the VMs to be re-added to the Session Collection. With this option a drain, upgrade, drain, upgrade option would be available. This allows for a sizing upscale – without lots of reconfiguration or management required.

Overall, it would seem that although scale sets aren’t able to fully integrate with Remote Desktop Services collections, they are still very capable and powerful when it comes to managing RDS Workloads. Scale Sets can be used to size and provision machines, as well as to provide simple options to increase environment capacity and power. Purely using a scale set for the ability to spin up new VMs, or to manage sizing across multiple VMs is a logical step. We also have the option to reimage a VM – taking it back to a clean configuration.

Key Observations from my investigation:

• We can scale an RDS environment very quickly, but RDS Servers can’t be automatically added to a session collection – the GPO settings for this don’t appear to support RDS post 2008R2 (whereby Session Collections and the new configuration method was introduced). This means servers have to be manually added when the Scale Set is scaled up
• Scale sets can be used to increase VM size quickly – without reimaging servers (a reboot is all that is required)
• Scaling can only look at performance metrics – we can’t scale on user count for example
• Reimaging means we can take servers back to a clean build quickly – if a server has an issue we would just prevent logons and then reimage.
• Scaling down can’t take logged on users into consideration – so we’d need a way of draining servers down first
• Scale Sets will also allow us to scale up to very large environments with minimal effort – just increase VM count or size, and add the servers into the RDS Collection. A growing business for example – or one that provides a hosted desktop could scale from 10 servers to a few hundred with minimal effort.

Hope this helps, and congratulations if you have made it to the end of this article! Until next time!

Resources:

• https://docs.microsoft.com/en-us/azure/virtual-machine-scale-sets/overview
• https://docs.microsoft.com/en-us/azure/virtual-machines/windows/capture-image-resource#create-an-image-from-a-snapshot-using-powershell
• https://github.com/Azure/azure-quickstart-templates/tree/master/201-vm-domain-join
• https://docs.microsoft.com/en-us/azure/virtual-machine-scale-sets/virtual-machine-scale-sets-mvss-existing-vnet
• https://docs.microsoft.com/en-us/azure/virtual-machine-scale-sets/virtual-machine-scale-sets-faq#how-do-i-join-a-virtual-machine-scale-set-to-an-active-directory-domain