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Cloud economics favor the small workload

Joab Jackson, IDG News Service | June 15, 2011
Cloud computing can cut the cost of running small workloads though may actually be more expensive for larger compute jobs, compared to the costs of running such work in-house, according to researchers from Pennsylvania State University.

The tests assumed that hardware and software would be refreshed every four years. Thanks to Moore's Law, the new hardware would have improved performance, which could help keep costs down for in-house implementations. Cloud computing pricing, on the other hand, may not reflect the lower costs enjoyed by the newer hardware, the researchers observed.

For large workloads, the cost benefits of running in the cloud could run higher than keeping them in-house. Using the same benchmarks, though adjusted to 900 TPC, the researchers estimated that cloud services would quickly become more expensive. An in-house implementation would cost about $400,000 a year to operate, which would increase to $600,000 in 10 years. By contrast, a cloud deployment would start at about $400,000, but would climb to over $1 million a year by the end of the 10-year period.

In addition to comparing cloud prices versus in-house prices, the researchers also examined the costs of hybrid clouds. They found that certain types of hybrid clouds may be more expensive than keeping a system in-house.

Hybrid clouds come in two types, Chul explained. "Vertically partitioned" hybrid clouds are systems in which some of the software (such as application servers) is run in-house, while other programs (such as databases) are run in the cloud. "Horizontally partitioned" clouds are those in which all the software is run in-house, though additional copies could be run in the cloud to meet peak demand.

Overall, vertically partitioned clouds can be expensive to run because of the high data-transfer costs incurred by moving data to and from the cloud, Chul said. Data transfer can account for 30% to 70% of the costs of cloud hosting. However, a hybrid cloud that does not involve a lot of data transfer could be cost-effective, Chul added. And horizontally partitioned clouds can be a money saver as well, as they could be run only for short periods of time, during peak demand, and not require hardware purchases.

Chul cautioned that the study does not take all costs of a cloud migration into account. Many costs can't be quantified, such as the cost of rewriting applications for the cloud, or the cost of retraining IT help to manage the cloud. As a result, the researchers did not factor these costs into their analysis.

At least one audience member, an engineer from Google, criticized the researchers for downplaying these hidden costs, likening the approach to looking for one's lost car keys underneath the street light, "because that's where it's well-lit."

 

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