The terms “cloud computing” and “grid computing” both describe ways to buy or share computing power in order to process information and complete tasks. One is more widely used and understood, but they provide similar functionality and both require investments in infrastructure and management.
However, there are major differences that should be of interest to professionals in the Software-as-a-Service (SaaS) and Infrastructure-as-a-Service (IaaS) fields as well as companies and organizations that depend on digital connectivity to stay nimble, effective and competitive.
What’s Cloud Computing, Again?
In “traditional” cloud computing, clients make use of remotely owned and operated servers in order to store information or process data. Cloud providers are responsible for providing access on-demand, from a variety of locations, and for maintaining as close to 100 percent uptime as possible.
There are several types of cloud computing architecture, including:
- Public clouds
- Private clouds
- Community-owned clouds
- Hybrid public-private clouds
The chief benefits of cloud computing are that it allows organizations to offload and outsource the time and labor required to build and maintain IT infrastructure, and that it provides remote access to databases or cloud services at any time from a variety of endpoints. Cloud computing is a cost-saving measure: it means companies don’t have to build their own server farms or look after the endless minutia and breaking news in cybersecurity.
Grid Computing in More Detail
Grid computing may take place in the cloud, depending on the operational needs of the participants. However, it represents a different computing philosophy compared to cloud computing.
Despite offering data mobility and ubiquitous computing, cloud-based solutions are centralized in design. A single provider maintains server and processing capacity for a few or many clients, with unused server capacity sitting idle and potentially going to “waste.”
Grid computing differs by putting existing idle computing potential to work. It doesn’t rely on one or a handful of servers to function. Instead, grid computing uses distributed computers attached to the same network to pool resources and analytical power. It provides a way to distribute a potentially huge single system image – an analytical “problem” to be “solved” – to as many as thousands of separate computers for processing. Redundancies and failovers ensure that if one node fails, the entire process doesn’t stop in its tracks.
There are several advantages of grid computing over cloud computing:
- Grid computing is more efficient in the use of processing power and energy usage. Rather than build and maintain capacity in advance, as with cloud computing, grid computing makes sensible use of unallocated capacity as it becomes available and as it’s needed.
- Unlike a cloud provider, which can provide a single point of failure, grid computing is relatively more robust, provided failsafes are incorporated.
- With grid computing, companies don’t pay a flat rate – they only pay for access to resources when they need it.
As with cloud computing, there isn’t just one type of grid setup. Some of the more common grid computing paradigms include:
- Data grid: Provides basic infrastructure to share access to common data resources as multiple parties process or act on the data in different ways.
- Utility grid: Utility grids are service-based and provide resources to a potentially large base of clients who call on the grid’s capacity for separate purposes.
- Collaboration grid: This is grid computing where a single data processing project is separated into tightly controlled, mutually exclusive network environments.
- Enterprise grid: Large enterprises may establish their own high-speed networks across remote branches or subsidiaries to share data and resources quickly and efficiently.
Grid computing may also be used interchangeably and have overlap with similar concepts like “utility computing,” “cluster computing” and “distributed computing.”
Final Thoughts on Grid Computing vs. Cloud Computing
In a sense, cloud computing is a more mature version of grid computing – although, as we’ve seen, there are ample opportunities to use both or either across the public and private sectors.
Grid computing is less centralized, but it still requires some kind of central control mechanism to allocate or schedule access to resources. It also requires that each participant accesses the data and computing resources from a full workstation. Cloud-based computing services offer web apps and other functionality that doesn’t require participants to have direct access to one of the “nodes” doing the “work.”
Nevertheless, both types of computing help organizations reduce their costs and outsource portions of their IT infrastructure to stay focused on their core competencies. Since no two organizations are precisely alike, there’s a future for both types of computing as organizations stake their claim in the digital age.
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About the Author
Kayla Matthews is a tech-loving blogger who writes and edits ProductivityBytes.com. Follow her on Twitter @productibytes to read all of her latest posts!
