How best to understand what a computer costs. Total cost of acquisition (TCA) is the price you pay to have it land on the loading dock and get it up and running doing real work. That’s the lowest price, but it is not reflective of what a computer actually costs. Total cost of ownership (TCO) takes the cost of acquisition and adds in the cost of maintenance, support, integration, infrastructure, power/cooling and more for three to five years. Needless to say TCO is higher but more realistic.
BottomlineIT generally shifts the platform cost discussion to total cost of ownership (TCO) or Fit for Purpose, an IBM approach that looks at the task to which is being applied, the workload. That puts the cost discussion into the context of not just the cost of the hardware/software or the cost of all the additional requirements but into the context of what you need to achieve what you’re trying to do. Nobody buys computers at this level for the fun of it.
John Shedletsky, IBM VP of competitive technology, has been dissecting the cost of IBM platforms—the zEnterprise, Power Systems, and distributed x86 platforms—in terms of the workloads being run. It makes sense; different workloads have different requirements in terms of response or throughput or availability or security or any other number of attributes and will benefit from different machines and configurations.
Most recently, Shedletsky introduced a new workload benchmark for business analytic reports executed in a typical day, called the BI Day Benchmark. Based on Cognos workloads, it looks at the number of queries generated; characterizes them as simple, intermediate, or complex; and scores them in terms of response time, throughput, or an aggregate measure. You can use the resulting data to calculate a cost per workload.
BottomlineIT, as a matter of policy, steers clear of proprietary benchmarks like BI Day. It is just too difficult to normalize the results across all the variables that can be fudged, making it next to impossible to come up with repeatable results.
A set of cost per workload analyses Shedletsky published back in March here avoids the pitfalls of a proprietary benchmark. In these analyses he pitted a zEnterprise with a zBX against POWER7 and Intel machines all running multi-core blades. One analysis looked at running 500 heavy workloads. The hardware and software cost for a system consisting of 56 Intel Blades (8 cores per blade) for a total of 448 cores came to $11.5 million, which worked out to $23k per workload. On the zEnterprise running 192 total cores, the total hardware/software cost was $7.4 million for a cost per workload of $15k. Click on Shedletsky’s report for all the fine print.
Another interesting workload analysis looked at running 28 front end applications. Here he compared 28 competitive App Server applications on 57 SPARC T3-1B blades with a total of 936 cores at a hardware/software cost of $11.7 million compared to a WebSphere App Server running on 28 POWER7 blades plus 2 Data Power blades in the zBX (zEnterprise) for a total of 224 cores at a hardware/software cost of $4.9 million. Per workload the zEnterprise cost 58% less. Again, click on Shedletsky’s report above for the fine print.
Not all of Shedletsky’s analyses come out in favor of IBM’s zEnterprise or even POWER7 systems. Where they do, however, he makes an interesting observation: since his analyses typically include the full cost of ownership, where z comes out ahead the difference often is not the better platform performance but the cost of labor. He notes that consistent structured zEnterprise management practices consistently combine to lower labor costs.
If fewer people can manage all those blades and cores from a single unified console, the zEnterprise Unified Resource Manager, rather than requiring multiple people learning multiple tools to achieve a comparable level of management, it has to lower the overall cost of operations and the cost per workload. As much as someone may complain that the entry level zEnterprise, the z114, still starts at $75,000, good administrators cost that much or more.
Shedletsky’s BI Day benchmark may never catch on, but he is correct in that to understand a system’s true cost you have to look at the cost per workload. That is almost sure to lead you to hybrid computing and, particularly, the zEnterprise where you can mix platforms for different workloads running concurrently and manage them all in a structured, consistent way.