As grid technology gets absorbed into enterprise fabrics, it could become inseparable from technologies such as virtualization and service-oriented architectures (SOA) and the creation of enterprise utilities, according to 451 Group analysts Steve Wallage and William Fellows. One consequence for grid computing, the analysts said in their 2007 grid computing outlook, is that the term […]
Datamation content and product recommendations are
editorially independent. We may make money when you click on links
to our partners.
Learn More
As grid technology gets absorbed into enterprise fabrics, it could become inseparable from technologies such as virtualization and service-oriented architectures (SOA) and the creation of enterprise utilities, according to 451 Group analysts Steve Wallage and William Fellows.
One consequence for grid computing, the analysts said in their 2007 grid computing outlook, is that the term grid computing “will become both more relevant and less used in 2007. It will be more relevant as grids are used to support far more than HPC tasks, but less used as vendors seek to be associated with far more activity, and far higher up the stack, than grid computing.”
IBM and Oracle could drop “grid” from their products “in favor of a broader term,” the 451 Group analysts wrote, while Microsoft “has made it very clear that it will not use the term ‘grid.'”
Terminology aside, virtualization could “deliver the dream of grid computing, if we assume that the dream is the provision of computational resources, on demand, from distributed sources,” the analysts wrote.
“To run a job on a grid today, a user has to identify a set of platforms capable of running that job, with the right operating system, libraries and so on,” Wallage and Fellows said. “Virtualization introduces a layer of abstraction, which means that instead of having to snoop out what resources are available and try to adapt a problem to use them, a user can describe a resource environment — or workspace — and expect it to be deployed on the grid. Virtual machines and virtual appliances — together with distributed storage facilities and network overlays — look as though they will be able to map this kind of virtual workspace onto physical resources. Moreover, the promise is that they will be easy to define, test, install, transport and adjust on demand. Putting them together into ‘virtual grids’ should enable users to test them before the actual allocation of virtual resources is made.”
The notion that grid computing could be subsumed by virtualization technologies that provide the foundations for a service-oriented infrastructure is already causing grid vendors such as Platform Computing, DataSynapse and United Devices to add virtualization offerings to their product lineups.
For 2007, the analysts predicted that:
- Virtualization will go mainstream, changing the data center.
- Grid infrastructure will get baked in to support utility computing, on-demand and SaaS activities.
- SOA will move from experimentation to implementation.
- Virtualization will allow grids to be absorbed into enterprise fabrics.
This article was first published on InternetNews.com. To read the full article, click here.
-
Ethics and Artificial Intelligence: Driving Greater Equality
FEATURE | By James Maguire,
December 16, 2020
-
AI vs. Machine Learning vs. Deep Learning
FEATURE | By Cynthia Harvey,
December 11, 2020
-
Huawei’s AI Update: Things Are Moving Faster Than We Think
FEATURE | By Rob Enderle,
December 04, 2020
-
Keeping Machine Learning Algorithms Honest in the ‘Ethics-First’ Era
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 18, 2020
-
Key Trends in Chatbots and RPA
FEATURE | By Guest Author,
November 10, 2020
-
Top 10 AIOps Companies
FEATURE | By Samuel Greengard,
November 05, 2020
-
What is Text Analysis?
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 02, 2020
-
How Intel’s Work With Autonomous Cars Could Redefine General Purpose AI
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 29, 2020
-
Dell Technologies World: Weaving Together Human And Machine Interaction For AI And Robotics
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 23, 2020
-
The Super Moderator, or How IBM Project Debater Could Save Social Media
FEATURE | By Rob Enderle,
October 16, 2020
-
Top 10 Chatbot Platforms
FEATURE | By Cynthia Harvey,
October 07, 2020
-
Finding a Career Path in AI
ARTIFICIAL INTELLIGENCE | By Guest Author,
October 05, 2020
-
CIOs Discuss the Promise of AI and Data Science
FEATURE | By Guest Author,
September 25, 2020
-
Microsoft Is Building An AI Product That Could Predict The Future
FEATURE | By Rob Enderle,
September 25, 2020
-
Top 10 Machine Learning Companies 2021
FEATURE | By Cynthia Harvey,
September 22, 2020
-
NVIDIA and ARM: Massively Changing The AI Landscape
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
September 18, 2020
-
Continuous Intelligence: Expert Discussion [Video and Podcast]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 14, 2020
-
Artificial Intelligence: Governance and Ethics [Video]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 13, 2020
-
IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI
FEATURE | By Rob Enderle,
September 11, 2020
-
Artificial Intelligence: Perception vs. Reality
FEATURE | By James Maguire,
September 09, 2020
SEE ALL
ARTICLES
Paul Shread has covered nearly every aspect of enterprise technology in his 20+ years in IT journalism, including an award-winning series on software-defined data centers. He wrote a column on small business technology for Time.com, and covered financial markets for 10 years, from the dot-com boom and bust to the 2007-2009 financial crisis. He holds a market analyst certification.