The backlash to the hype over cloud computing is in full swing. I have given a number of talks on cloud computing over the past few months and have been struck by a few things.

First, at an industry event that I attended, although there were quite a few talks on cloud computing (it was one of the tracks), it seems that only a small number of speakers had actually participated in a cloud computing project and I was was one of only a handful that had actually completed several cloud computing projects. Many of the other speakers were simply summarizing second and third hand reports about cloud computing. In my opinion, something was lost in the translation.

Second, I think some of the backlash has gone to far. At one breakfast meeting I attended, there were essentially no acknowledgement of the potential today that clouds offer, simply emphasis on why “real companies” that have to worry about security could never use (public) clouds. Private and condo clouds were not mentioned as alternatives for companies whose security or compliance requirements preclude the use of today’s public clouds. The trade-off, which is always present, that balances potential breaches from performing certain operations in public clouds, from the productivity gains that such clouds can provide was also not mentioned.

Because of this backlash, I think it is a good time to revisit the case for cloud computing. There are three basic reasons for deploying certain operations to clouds:

Cost savings. By employing virtualization and making use of the economies of scale that cloud service providers can take advantage of, deploying certain operations to clouds can lead to improved efficiencies. This advantage seems to be well understood, and is, for example, one of the factors driving the Federal CIO’s push for cloud computing. See for example, the recent RFQ from the GSA for a cloud computing store front.

Productivity. The Elastic, virtualized services that clouds provide lead directly to productivity improvements. As a simple example, I was building an analytic model over the weekend to meet a deadline and the computation took over 4 hours. Since I was using a virtualized resource in a cloud, I was able to use the portal that controlled the various machine images to double the memory in my resource. Five minutes later, I had a new virtualized image and the computation now took less than 5 minutes. (By the way, this is typical of analytic computations. When the data is so large that a computation can no longer be done in memory and requires accessing the disk, the time required increases dramatically.) If, instead, I had gone through a standard procurement process to get a new machine with twice the memory, it would have been quite some time before the model would have been completed.

As another example, I work with a Fortune 500 client in which the analytic models are taking weeks to build instead of days because the modeling environment does not have enough disk space for the entire team to hold all the temporary files and datasets required when building analytic models nor powerful enough computers for models to be computed fast enough to provide timely feedback to the modeler. This is unfortunately fairly typical of modeling environments in Fortune 500 companies (I’ll discuss this situation in a later post). A simple cloud would dramatically improve the situation.

New capabilities. Clouds also provide new capabilities. For example, large data clouds enable the processing and analysis of large datasets that was simply not possible with architectures that manage the data using databases. As a simple example, the type of analytic computations abstracted by the MalStone Benchmark are relatively straightforward, even when there are 100 TB of data, using a Hadoop or Sector based cloud, but in practice not practical using a traditional database when the data is that size.

What’s new. Many of the ideas behind cloud computing are quite old. On the other hand, the combination of: 1) the scale, 2) the utility based pricing, and 3) the simplicity provided by cloud computing make cloud computing a disruptive technology. If you are interested in understanding cloud computing from this point of view, you might find a recent talk I gave for an IEEE Conference on New Technologies called My Other Computer is a Data Center interesting. There is also a written version of a portion of the that recently appeared in the IEEE Bulletin on Data Engineering called On the Varieties of Clouds for Data Intensive Computing.

The image is by John Seb and is available from Flickr under the Creative Commons license.