August 22, 2011
Cloud computing in any form, whether its delivery of infrastructure as a service or software delivered via a web interface, still faces slower adoption in risk-averse and highly security-conscious industries, according to Anthony O’Donnell, an insurance technology expert who examined the bevy of insurer concerns about clouds in an a recent article.
According to O’Donnell, “While insurance CIOs are warming to a variety of cloud, SaaS and PaaS offerings, concerns about the privacy and security of sensitive customer data have made insurers cautious about when and where they adopt them.”
O’Donnell claims that a number of insurance companies have decided to take the perceived “risk” of possible data breeches using any number of cloud-based services, but that the adoption rate for this sector is not as high as in others. This is in part due to the sensitive nature of insurance data as well as due to issues that include performance and availability.
As Rick Roy, CIO for CUNA Mutual Group told Network World, the availability and security issues hand-in-hand present too many possibilities for problems for some insurance CIOs to be comfortable with.
As Roy stated, “Security for non-public, private information remains a huge concern for insurers, as it is a business issue that spans beyond just a technology issue…And outages like the recent Amazon Web Services incident have also renewed industry concerns around availability and performance of cloud.”
O’Donnell, backed by a series of insurance IT pros who weighed in on the issue, claims that while insurance companies are fine with using cloud-based services to handle many of their customer relations tasks, the mission critical applications that require high availability and inside-the-firewall security are staying put for some.
Full story at Insurance and Technology
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.