This paper examines the similarities and differences between grid computing and cloud computing by following the analytical framework proposed by Foster et al. in their 2008 survey, "Cloud Computing and Grid Computing 360-Degree Compared." Drawing on six comparative dimensions — business model, architecture, security, resource management, data models, and applications — the paper argues that the most enduring distinction between the two paradigms is the contrast between standardization and customization. While both approaches aim to provide scalable, shared computing resources, grid computing favors specialized, project-oriented collaboration among expert organizations, whereas cloud computing targets broad consumer and business audiences through a utility-style, pay-per-use model. The paper concludes by noting the commodification of computing as the overarching long-term trend.
The paper models effective exegesis — it takes a single scholarly source (Foster et al., 2008) as its primary lens and uses additional sources to support, extend, or contextualize its claims. Each section synthesizes quoted evidence from the primary source with the author's own analytical commentary, demonstrating how to build an argument from close reading rather than summary alone.
The paper opens with a broad framing of scalability challenges in IT, narrows to the cloud-versus-grid question, and states its scope and method clearly in the introduction. Each body section addresses one comparative dimension, moving logically from commercial framing (business model) through technical architecture, applications, and management. The conclusion synthesizes the central tension — standardization versus customization — and gestures toward future convergence trends without overreaching into speculation.
Sequencing a genome, storing vast video libraries, or utilizing a non-essential application for occasional use are all functions performed within the realm of information technology. Meeting a particular task need was once the challenge of the end user or organization to ascertain their current and future use in order to guide technology purchases. In the not so distant past, limitations of hardware or budget constrained the application of technology. Networking information technology proved one solution to sharing resources and boosting capabilities, while at the same time allowing for centralized governance models to facilitate access and protect privileged information.
As the capabilities of technology advance in computational power, storage, and connectivity, new uses emerge to enhance the capabilities of science, business, and individuals. Scalability — the matching of correct resources to a particular need at a given time, both up and down — has long proved an elusive target for users and organizations. As specialized organizations with robust computing networks and common interests sought to enhance their capabilities, grid computing emerged to enable pooled resources.
The newest label for large-scale, shared resources is "cloud computing." References to "the cloud" raise questions of whether this is a unique approach to delivering scalable resources, or merely a marketing label for grid computing. Ian Foster et al. survey this question in a 2008 conference paper entitled "Cloud Computing and Grid Computing 360-Degree Compared" (Foster, Zhao, Raicu, & Shiyong, 2008). The lack of a definitive line of demarcation between grid and cloud computing is best characterized by noting the overarching goal of both: "the vision is the same — to reduce the cost of computing, increase reliability, and increase flexibility by transforming computers from something that we buy and operate ourselves to something that is operated by a third party" (Foster, Zhao, Raicu, & Shiyong, 2008).
This paper provides an exegesis of the Foster et al. survey of grid and cloud platforms, with a focus on the particular aspects that most concretely differentiate the two. It briefly follows Foster et al. through six areas: business model, architecture, resource management, data models, applications, and security. Through this framework, a clearer view of the similarities and differences between the Grid and the Cloud emerges. This paper refrains from long-term predictions of convergence upon a single grid or cloud-computing paradigm, but does note trends that fit with a more general theme of computing as a utility.
The most visible differentiating characteristic between cloud and grid computing lies in the business model. Foster et al. largely accept that the evolutionary course of information technology comprises three main functions: computation, data storage, and connective infrastructure. In his well-known article "IT Doesn't Matter," Nicolas Carr noted that "the core functions of IT — data storage, data processing, and data transport — have become available and affordable to all," while arguing that a technology-based business strategy relied upon maintaining proprietary capabilities (Carr, 2003). Foster et al. articulate an egalitarian business model that integrates Carr's view: "in a cloud-based business model, a customer will pay the provider on a consumption basis, very much like the utility companies charge for basic utilities such as electricity, gas, and water, and the model relies on economies of scale in order to drive prices down for users and profits up for providers" (Foster, Zhao, Raicu, & Shiyong, 2008).
In contrast, Foster et al. note that the grid computing business model "is project-oriented" and rationed through a currency of "service units" (Foster, Zhao, Raicu, & Shiyong, 2008). Grid computing resembles a cooperative, in that joining integrates a node into a larger external network that enables shared use and creates the experience of a virtual organization — defined by Foster et al. as "a logical entity within which distributed resources can be discovered and shared as if they were from the same organization" (Foster, Zhao, Raicu, & Shiyong, 2008).
While both represent large-scale sharing of resources aimed at enabling dynamic scaling to match needs, a divergence in architecture and accessibility provides another key point of differentiation between the Grid and the Cloud.
If operational continuity is viewed as a security issue, then the Grid retains an edge over the Cloud in the event of service or connection disruptions. Because the Grid is comprised of smaller nodes that connect for resource sharing, each node retains core capabilities should an outage to the larger network occur. The Cloud also retains end-user or node capabilities; however, depending upon the type of services employed, an outage may result in partial or complete disruption of cloud-dependent functions.
A key characteristic of cloud computing is the configuration of services aimed at a very broad user group. The homogeneous nature of a cloud operation is driven by economies of scale: "the construction and operation of extremely large-scale, commodity-computer data centers at low-cost locations was the key necessary enabler of cloud computing" (Armbrust et al., 2010). Mass appeal and scale entail a lower threshold of security and control, since little more than a credit card is necessary to gain access to most cloud computing platforms. Foster et al. note the ease of access: "new users could use Clouds relatively easily and almost instantly, with a credit card and/or email address" (Foster, Zhao, Raicu, & Shiyong, 2008).
Grid computing, by contrast, is notably targeted at more specialized groups. Organizations heavily reliant upon information technology are most likely to have robust computing capabilities, budgets for specialized applications, and a paramount concern for data security. Grid computing may best be characterized as the model adopted by industry leaders and experts who benefit from shared resources, but only among their peers. The scientific community, for example, is more likely to be found decoding and sequencing genes within a grid-configured system.
The cloud-computing model may be best suited for small businesses whose computing needs are best served by specialized third parties whose core competency is information technology. A real estate office or mortgage-brokering firm is likely to find cloud services attractive, as it outsources expensive and onerous tasks that are not integral to the business. A further benefit of this centralized and standardized approach is that security updates and monitoring are more conducive to such an environment. Organizations that rely upon proprietary information and continuity of service are unlikely to fully embrace cloud services in the near term; however, this merely denotes one area where customization is warranted for particular cases.
The line between Grid and Cloud computing is likely to become increasingly blurry. However, the key point of differentiation likely to endure is the contrast between standardization and customization.
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