Part II: Storage Boon or Bane – VMware View Storage Design Strategy & Methodology

By TJ Vatsa, VMWare EUC Consultant

INTRODUCTION Welcome to Part II of the VMware View Storage Design Strategy and Methodology blog. This blog is in continuation to Part I that can be found here. In the last blog, I had listed some of the most prevalent challenges that impede a predictable VMware View Storage design strategy.. In this blog, I will articulate some of the successful storage design approaches that are employed by VMware End User Computing (EUC) Consulting practice to overcome those challenges.

I’d like to reemphasize the fact that storage is very crucial to a successful VDI deployment. Should the VDI project be made prone to the challenges listed in Part I, Storage, for sure, will seem to be a “bane”. But, if the recommended design strategy listed below is followed, you would be surprised to find VDI Storage being a “boon” for a scalable and predictable VDI deployment.

With that in mind, let’s dive in. Some successful storage design approaches I’ve encountered are the following:

• 1.     PERFORMANCE Versus CAPACITY – Recommendation: “First performance and then capacity”
  Often times, capacity seems more attractive when compared to performance. But, is it really so? Let’s walk through an example.

• a)     Let’s say vendor “A” is selling you a storage appliance, “Appliance A” that has a total capacity of 10TB, being delivered by 10 SATA drives of 1TB capacity each.

• b)     On “Appliance A”, let’s say that each SATA drive delivers approximately 80 IOPS. So, for 10 drives, the total IOPS being delivered by the appliance is 800 IOPS (10 drives * 80 IOPS).

• c)     Now let’s say that vendor “B” is selling you a storage appliance, “Appliance B” that also has a total capacity of 10TB, but it is being delivered by 20 SATA drives of 0.5TB capacity each. [Note: “Appliance B” may be expensive as there is more drives compared to “Appliance A”.]

• d)     Now for “Appliance B”, assuming that the SATA drive specifications are the same as those of “Appliance A”, you should be expecting 1600 IOPS (20 drives * 80 IOPS)

• It’s mathematically clear; “Appliance B” will be delivering twice as much IOPS than “Appliance A”. More storage IOPS invariably turns out to be a boon for a VDI deployment. Another important point to consider, is the fact that employing higher tier storage also ensures high IOPS availability. Case in point, replacing the SATA drives in the example above with SAS drives will certainly provide higher IOPS. SSD drives, while expensive, will provide even higher IOPS.

• 2.     USER SEGMENTATION – Recommendation: Intelligent user segmentation that does not assume “one size fits all approach”.

As was explained in Part I, taking a generic user IOPS, say “X” and then multiplying that with the total number of VDI users in an organization say “Y”, may result in an Oversized or an Undersized Storage Array design. This approach may prove costly, either upfront or at a later date.

The recommended design approach is to intelligently categorize the user’s IOPS as “Small, Medium or High” based on the load a given category of users generate across the organization. As part of the common industry nomenclature for VDI users:

a)     Task Workers: associated with small IOPS.
b)     Knowledge Workers: associated with medium IOPS.
c)     Power Users: associated with high IOPS.

With these guidelines in mind, let me walk you through an example. Let’s say that Customer A’s Silicon Valley campus location has 1000 VDI users. Assuming that the user % split is:

a)     15% Task Workers with an average of 7 IOPS each
b)     70% Knowledge Workers with an average of 15 IOPS each
c)     15% Power Users with an average of 30 IOPS each

The resulting calculation of total estimated IOPS required will look similar to Table 1 below.

Key Takeaways:

1. It is highly recommended to discuss/consult with the customer and to also make use of a desktop assessment tool to determine the user % distribution (split) as well as the average IOPS per user segmentation.
2. Estimated capacity growth and the buffer percentage, is assumed to be 30%. This may vary for your customer based on the industry domain and other factors.
3. This approach to IOPS calculation is more predictable based on user segmentation specific to a given customer’s desktop usage.
4. You can apply this strategy to customers from Healthcare, Financial, Insurance Services, Manufacturing and other industry domains.

I hope you will find this information handy and useful during your VDI architecture design and deployment strategy.

Until next time. Go VMware!