The cutting edge of scientific research is often accomplished with surprisingly little cutting edge technology. In many cases, the equipment used to make discoveries is quite old, having been operating reliably for many years. Thus many scientists, comfortable with technological status quo, can easily miss small, affordable changes in technology that have the possibility to dramatically increase productivity.
Cloud computing may be one of these changes. While data-reliant researchers often have large, bespoke configurations for storing, retrieving, and working with large data sets, all research fields have had to come to terms with the sheer volume of data that modern, digitized test equipment has made normal. Many have relied on a carefully choreographed dance between mobile drives, email and small, custom-built servers. These solutions do get the job done, but at a cost to reliability and man-hours. Cloud-based solutions allow data to seamlessly be written from one location and accessed by one or many users. The data can be accessed from any location by authorized users, making data available to whole teams immediately upon collection.
Of course, cloud computing is not without its costs. Primarily, the cost. Some potential users balk at the thought of paying to keep data stored in a datacenter. There is certainly fact to this viewpoint, although some of these users may not be factoring the cost of hardware replacement and time, both configuring and using such systems. Many larger organizations have dedicated IT staff to arrange for similar in-house solutions, although most lack the redundancy and 24-hour staff of a dedicated datacenter. In many cases, outsourcing storage capacity can take advantage of such infrastructure at a similar cost.
There is one advantage of cloud-based storage that many have yet to realize: As cloud computing becomes more mature, the same datacenters holding storage resources will have easily accessible computing resources that can be temporarily deployed to help process and analyze the data. When computing power is factored into the cost of data storage and processing, the cost of using cloud-based solutions becomes much more appealing.
While cloud computing does very little to improve lab capabilities, the mixture of storage, accessibility, and computing power has the potential to dramatically streamline post-laboratory processes. Whether in a private cloud setting or a hosted datacenter, many researchers would benefit by looking into whether a cloud-hosting data solution fits into their operational budgets.
Written by Erik Dorthe, a systems engineer at Cari.Net who works with the design and deployment of cloud clusters. His previous background includes an education in biomedical engineering and academic research in biology and materials science.