Executive Guides

Grid computing guide for CIOs

Grid computing is slowly becoming a reality as more corporations begin to adopt this type of technology. According to one IBM analyst, grid computing will allow companies to leverage their distributed resources to get more value out of their infrastructure, even the idle resources. This Executive Guide offers advice, resources and research to better help you decide if grid computing is appropriate for your organization.

This Executive Guide is part of the SearchCIO Executive Guide series, which is designed to give IT leaders strategic guidance and advice that addresses the management and decision-making aspects of timely topics. For a complete list of topics covered to date visit the Executive Guide section.

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Over the last few years, grid computing has dramatically evolved from its roots in science/academia, and is currently at the onset of mainstream commercial adoption. But with the recent explosion of commercial interest in grid, we're seeing some industry confusion about what the term means. This is partially because the true definition has been somewhat convoluted by the onslaught of marketing hype around the category.

So what is Grid? I created a three-part checklist with my colleagues back in 2002. According to this checklist, a grid:

  1. coordinates resources that are not subject to centralized control. A grid integrates and coordinates resources and users that live within different control domains -- for example, different administrative units of the same company, or even different companies. A grid addresses the issues of security, policy, payment membership and so forth that arise in these settings.
  2. uses standard, open, general-purpose protocols and interfaces. A grid is built from multipurpose protocols and interfaces that address such fundamental issues as authentication, authorization, resource discovery and resource access. It is important that these protocols and interfaces be standard and open. Otherwise, we are dealing with application-, hardware- or operating system-specific systems.
  3. delivers nontrivial qualities of service. A grid should be transparent to the end user, addressing issues of response time, throughput, availability, security and/or co-allocation of multiple resource types to meet complex user demands. The goal is that the utility of the combined system is significantly greater than that of the sum of its parts.

In even simpler terms, grid is at the foundation level of the trends that are driving better synchronization between IT and the underlying hardware and software resources. In this new wave of innovation, we are starting to see IT more effectively manage its own resources -- and in the process, lead business to this world of "adaptive enterprise."

So why should the enterprise professional care about grid?

The primary reason is that grid will ultimately usher the enterprise into a new era of efficiency in managing its resources. Historically, IT organizations have had to overbuy resources -- planning for peak requirements and worst-case scenarios. In the past there was no ability to turn the dial up and down on resources as users required them. Nor had there been a means for transitioning of resources as they dynamically changed state.

Grid is at the foundation of important trends like utility computing, virtualization and IT automation -- and there are a number of things that your organization should be doing to prepare for the arrival of grid in the enterprise. These steps range from how you plan your SOA and utility computing strategy, to evaluating commodity hardware purchasing options, to affecting cultural change in your organization (i.e. a departure from siloed resources) -- there are a whole host of new challenges and skill sets related to this innovation wave.

I look forward to hearing about your experiences and questions with grid.

Ian Foster is an internationally recognized researcher and leader in the area of grid computing. He is also associate director of the Mathematics and Computer Science Division of Argonne National Laboratory and the Arthur Holly Compton Professor of Computer Science at the University of Chicago.

  Analyst findings and predictions
  Table of Contents
  Expert advice
  Table of Contents
  Utility computing
  Table of Contents


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This was first published in October 2004

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