One of the great things about working for a VAR is that I get to evaluate best of breed solutions in a vendor agnostic manner. Lately, I’ve been spending more and more time speaking with and doing VDI designs for both our EMC and Netapp customers.
I thought I’d take some time to discuss how each of these companies are helping to solve the “VDI IOPS problem.” For those not familiar with this particular problem space, to put it very simply: with physical desktop deployments, each desktop/user has their own hard drive. When moving to a virtual desktop, the storage is consolidated on a SAN/NAS array, and thus there is no longer a 1:1 dekstop to disk drive relationship. This is not to say that you *cannot* have a 1:1 desktop to disk relationship, but doing so would be extremely cost prohibitive and ruin any practical method for justifying VDI regardless of any opex savings. The issue is not one of disk space, but one of performance, namely IOPS. Each disk drive can only support so many IOPS, so the question becomes, how do we design cost effective storage solutions for VDI, while providing the correct amount of performance to not impact user experience.
EMC and Netapp both have different solutions to this problem. To illustrate, lets look at a simple use case:
- 5000 users
- average desktop user IOPS requirement of 10IOPS per user
Simple math gives us 5000 * 10 = 50,000 IOPS required from the storage array. Assuming a standard deployment of 15K fiber channel disks (at 200 random IOPS per disk with decent latency), NOT counting RAID overhead, we would need ~250 spindles to support this workload. This (relatively) massive spindle count will completely skew any TCO when building a business case for VDI, so we must find a way to lower this spindle count, and do it in a cost effective manner WITHOUT sacrificing the performance of the overall system. This is not a $/GB problem, this is s $/IOPS problem. Applying deduplication techniques, and reducing the overall spindle requirement from a CAPACITY perspective will do nothing for solving the $/IOPS problem. Or will it? The storage cost is one of the biggest costs of any VDI deployment. So this is a very important place to look for efficient designs.
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