David Merrill

Cloud Economics Revisited (parts 2 and 3)

Blog Post created by David Merrill on Nov 1, 2016

Cloud Storage Economics – Part 2 - Original Posts November and December 2010

 

My previous entry introduced some of the cost and architecture parameters that I have been investigating relative to cloud storage architectures. I have shown that looking at cost of acquisition only, it is easy to see that DAS is the winner. Both TCO and TCDO measurements counts only the CAPEX costs associated with storage ownership. But price is only a fraction of costs. Over the life of storage, the OPEX costs can reach 3-5X the purchase price, so it is worthwhile to tool at TCO for Cloud Storage Architectures and determine if there is a cross-over point between DAS and Enterprise arrays.

 

First, lets take a look at how I break down the types of money between these 4 cost modeling methods:

 

 

In the previous blog models we saw that there was not a cross-over point or cost parity between DAS and Enterprise when we look only at total raw capacity. There was a cross over point for TCDO at 900 units, when we look at the costs to storage data (not just present capacity). When we add Hard and Soft costs to the TCDO view, we see that enterprise architectures can become economically better at a certain point of scale, total size, data types, data value, transaction workload, and processing value.

 

First, the TCO plus (traditionally) hard costs of CAPEX. We can see a cross-over point at around 500 units.

 

 

Next, when we consider adding soft costs to the mix, the cross-over point is around 100 units.

 

 

Don’t forget that both the X and Y axis are logarithmic. The differences in real dollars is much more significant than what is presented in the graph.

 

 

 

Cloud Storage Economics – Part 3

  1. My previous 2 blogs have shown how price ¹ cost applies to standard SAN and NAS storage architectures, but also to cloud storage architectures. What we have concluded:

 

  • If you look only at total cost of acquisition (TCA) on a raw TB basis, DAS will always win in your economics models
  • If we expand TCA to and only count primary data store, usable or written-to space, we start to see TCO parity at roughly 1,000 units (nodes, TB, etc)
  • When we apply hard costs such as power and labor to the models, the cross over point is around 500 units
  • And finally, if we consider other soft cost – benefits that are qualitative but not necessarily showing up in a budget report (like carbon footprint, performance), then the cross over point occurs in a few hundred units.

So therefore what?

    1. Don’t be seduced by price alone, even with small to medium cloud installations
    2. Visit with your storage vendor and solution architects to understand the node and storage scale-out, and where barriers exist with scale, availability and manageability.
    3. Understand all the costs that are important to your IT department; this has to be more than just capital costs. Apply all these costs to the cloud design at various scale points. Model the hard costs first. Secondary models that show other problem areas should be considered as well.
    4. Usually there are several cost centers that bear the cost burden for different costs. Don’t be myopic in your cost analysis, look at the total costs for the company and not just your own cost center impact.
    5. Cross over points do exist for enterprise-class and modular storage architectures
      • At scale
      • At performance levels
      • For availability
      • For total environmental costs and carbon emissions

 

There are economic cross over points that can be defined and modeled for your own IT installation. Not everyone will have the same cost co-efficients, but models and predictions (like the following) can be developed to calculate cross-over points for your cloud initiatives.

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