XenDesktop 7.7 and Windows 10


The other day, I was able to share the latest single server density results when running Windows 7 on XenDesktop 7.7. We looked at a range of parameters like:

      • PVS vs MCS
      • PVS Disk Cache vs RAM Cache
      • Citrix Policies: Very High Definition vs High Server Scalability vs Optimized for WAN
      • Windows 7 optimizations

Once that testing was complete, we moved onto the next version… Windows 10. An again, looking at the exact same parameters.

First, we look at Microsoft Hyper-V 2012R2

HVwin10

Second, we look at Citrix XenServer 6.5 SP1

xswin10

What do you notice?

Between XenServer & Hyper-V… Not much

Between MCS and PVS… Not much as the 5-6% gains in MCS would be offset by increased storage costs due to lack of RAM Caching capabilities

Between the different policies… Around a 7-8% improvement

Between OS optimizations… Around a 7% improvement

The last part I find very interesting.

If you recall, I recently posted a blog (Windows 10 Optimization: The Results) showing that the Optimized OS config, based on the numerous Windows 10 optimizations, showed a 20% improvement in density. As we look at this expanded series of tests, what I now see is something rather interesting. Simply utilizing the Citrix policy templates, we achieve 1/2 of that density gain.

And I can tell you from experience that implementing the Citrix policies are much easier than working through all of those Windows 10 optimizations

So my advice, definitely use the Citrix policy templates as your starting point. If you want to know more about them, I suggest the following:

Server Specs:

      • Processors: Dual Intel Xeon E5-2697 (12 cores each)
      • RAM: 384 GB
      • Workload: Knowledge Worker
      • VM Specs: 2vCPU, 4 GB RAM

 

Daniel (Follow @djfeller)

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One thought on “XenDesktop 7.7 and Windows 10”

  1. Very nice to see this collection of comparisons! Windows 10 is a different beast and it’s always good to not assume that all OS versions are going to exhibit the same behavior.

    Like

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