Cloud Computing At A Glance

Example of Cloud Computing – Google Docs

Cloud computing fundamentally changes the ways institutions and companies manage their computing needs. Libraries can take advantage of cloud computing to start an IT project with low cost, to manage computing resources cost-effectively, and to explore new computing possibilities.

Customers do not own network resources, such as hardware, software, systems, or services;

network resources are provided through remote data centers on a subscription basis; and

network resources are delivered as services over the Web.

These examples demonstrate that cloud computing providers are offer- ing services on every level, from hardware (e.g., Amazon and Sun), to operating systems (e.g., Google and Microsoft), to software and service (e.g., Google, Microsoft, and Yahoo!). Cloud-computing provid- ers target a variety of end users, from software developers to the general public.

IBM, Sun Yahoo, Microsoft, Google

Digital Library project with lots of databse files and archives

Academic libraries usually run hundreds of PCs for students and staff to fulfill their individual needs (e.g., Microsoft Office, browsers, and image-, audio-, and video-processing applications).

Site employees were set up quickly; systems maintenance is managed by the author’s team, and rebooting now only takes about one minute; and there is no need to buy a new server and put it in a temperature and security controlled environment. The hardware is maintained by the provider.

Nagios, an open-source monitoring system, was tested and configured to identify and report problems for the above library systems. Nagios provides the follow- ing functions: (1) monitoring critical computing components, such as the network, systems, services, and serv- ers; (2) timely alerts delivered via e-mail or cell phone; and (3) report and record logs of outages, events, and alerts. A backup script is also run as a prescheduled job to back up the systems on a regular basis

The annual cost of running two nodes is $480 per year, compared to at least $4,000 dollars if the hardware had been run in the library.

Cost-effectiveness: From the above example and literature review, it is obvious that using cloud computing to run applications, systems, and IT infrastruc- ture saves staff and financial resources. UC Berkeley’s report and Zawodny’s blog provide a detailed analysis of costs for CPU hours and disk storage.

Flexibility: Cloud   computing allows organizations to start a project quickly without worrying about up-front costs. Computing resources such as disk storage, CPU, and RAM can be added when needed. In this case, the author started on a small scale by purchasing one node and added additional resources later.

Data safety: Organizations are able to purchase storage in data centers located thousands of miles away, increasing data safety in case of natural disasters or other factors. This strategy is very difficult to achieve in a      traditional off-site backup.

High availability: Cloud comput- ing providers such as Microsoft, Google, and Amazon have better resources to provide more up-time than almost any other organizations and companies do.

The ability to handle large amounts of data: Cloud computing has a

pay-for-use business model that allows academic institutions to analyze terabytes of data using distributed computing over hundreds of computers for a short-time cost.

On-demand data storage, high availability and data safety are critical features for academic libraries. However, readers should be aware of some technical and business issues.

Availability of a service: In sev- eral widely reported cases, Amazon’s S3 and Google Gmail were inaccessible for a duration of several hours in 2008. The author believes that the com- mercial providers have better technical and financial resources to keep more up-time than most academic institutions. For those wanting no single point of fail- ure (e.g., a provider goes out of business), the author suggests storing duplicate data with a different 
provider or locally.

Data confidentiality: Most aca- demic libraries have open-access data. This issue can be solved by encrypting data before moving to the clouds. In addition, licens- ing terms can be negotiated with providers regarding data safety and confidentiality.

Data transfer bottlenecks: Accessing the digital collections requires considerable network bandwidth, and digital collections are usually optimized for customer access. Moving huge amounts of data (e.g., preservation digital images, audios, videos, and data sets) to data centers can be scheduled during off hours (e.g., 1–5 a.m.), or data can be shipped on hard disks to the data centers.

Legal jurisdiction: Legal jurisdic- tion creates complex issues for both providers and end users. For example, Canadian privacy laws regulate data privacy in public and private sectors. In 2008, the Office of the Privacy Commissioner

of Canada released a finding that “outsourcing of canada .com email services to U.S.-based firm raises questions for subscribers,” and expressed concerns about public sector privacy pro-tection.This brings concerns to both providers and end users, and it was suggested that privacy issues will be very challenging