Cloud computing: The very definition of cloud computing remains controversial. Consulting firm Accenture has crafted a useful, concise definition: the dynamic provisioning of IT capabilities (hardware, software, or services) from third parties over a network.
Cloud computing is computing model, not a technology. In this model of computing, all the servers, networks, applications and other elements related to data centers are made available to IT and end users via the Internet, in a way that allows IT to buy only the type and amount of computing services that they need. The cloud model differs from traditional outsourcers in that customers don't hand over their own IT resources to be managed. Instead they plug into the "cloud" for infrastructure services, platform (operating system) services, or software services (such as SaaS apps), treating the "cloud" much as they would an internal data center or computer providing the same functions.
Despite snarky comments among industry insiders and imprecise metaphors meant to explain virtualization and cloud computing to the masses, it is patently untrue that the corporate computing world is returning to the mainframe model of computing.
Today's hardware, software and networks are cheaper, more flexible and more accepting of anything a user or data-center manager wants to do, for one thing. Rather than making users wait days or weeks for any changes or reports, typical data centers can easily add extra storage or computing power to accommodate an online-sales promotion, for example.
On the other hand, constrictive budgets, a bad economy, and computing hardware that has largely outstripped the demands business applications put on it have increased the pressure on CIOs to not only show they're using IT dollars efficiently, but also actually do it.
Virtualization — as well as the cloud computing model within which it often runs — answer much of that need, by giving CIOs the ability to cover a week-long spike in demand by turning up the spigot on the computing power a business unit gets. A layer of virtualization software allows a bank of servers to share the available workload, and lets the CIO give a business unit 10% more storage capacity or compute power, rather than having to go buy completely new servers that add 10 times the required capacity.
The mainframe-like miracle is abstraction — the ability to hide the complexities of a system from the end user while providing all the power and capabilities the user requires.
The World Wide Web is the largest abstraction layer in IT — hiding the complexity of a global network with hundreds of thousands of specialized servers and arcane data behind search engines and hotlinks.
In IT, "virtualization" most often means server virtualization — in which one physical server acts as host to several virtual servers, each of which runs on a layer of software called a hypervisor whose job it is to parcel out storage, memory and other computing resources while making each virtual server believe it is running by itself on a standalone computer.
Cloud computing takes that abstraction one further step. Rather than making one server appear to be several, it makes an entire data-center's worth of servers, networking devices, systems management, security, storage and other infrastructure, look like a single computer, or even a single screen.
The idea is to let companies buy exactly the amount of storage, computing power, security and other IT functions that they need from specialists in data-center computing — in the same way they used to pay AT&T to come install the number of phones they required.
What are the different types of cloud computing?
Web-based email services from Google and Yahoo, backup services from Carbonite or MozyHome, customer-resource management applications like Salesforce.com, instant messaging and voice-over-IP services from AOL, Google, Skype, Vonage and others are all cloud-computing services, hidden behind yet another layer of abstraction to make them seem even simpler to end users who want the kind of power sophisticated computing can give them, but don't want to know how it's done.
There are three basic types of cloud computing:
• Infrastructure as a Service — provides grids or clusters or virtualized servers, networks, storage and systems software designed to augment or replace the functions of an entire data center. The highest-profile example is Amazon's Elastic Compute Cloud [EC2] and Simple Storage Service, but IBM and other traditional IT vendors are also offering services, as is telecom-and-more provider Verizon Business.
• Platform as a Service — Provides virtualized servers on which users can run existing applications or develop new ones without having to worry about maintaining the operating systems, server hardware, load balancing or computing capacity. Highest-profile examples include Microsoft's Azure and Salesforce's Force.com.
• Software as a Service — The most widely known and widely used form of cloud computing, SaaS provides all the functions of a sophisticated traditional application, but through a Web browser, not a locally-installed application. SaaS eliminates worries about app servers, storage, application development and related, common concerns of IT. Highest-profile examples are Salesforce.com, Google's Gmail and Apps, instant messaging from AOL, Yahoo and Google, and VoIP from Vonage and Skype.
Pros of Cloud Computing Model
• Quick deployment – add capacity or applications almost at a moment's notice.
• Metered cost – pay-as-you-go approach for storage, processing and applications means more efficient use of IT spending.
• Little or no capital investment – costs don't stay on the books for years.
• Little or no maintenance cost – maintenance is all from a workstation or configuration screen. You never have to go touch a physical server.
• Lower costs – Many customers use the same infrastructure, so the vendor is able to buy in bulk and amortize costs over more customers, potentially lowering per-unit cost to each customer.
Cons of Cloud Computing Model
• Little or no capital investment – services don't depreciate over years as capital expenses do, so there could be a tax disadvantage over time.
• Monitoring and maintenance tools are not mature yet – visibility into the cloud is limited, despite recent announcements by BMC, CA, Novell and others that they're modifying their data-center management applications to provide better control over data in Amazon's EC2 and other cloud services.
• Immature standards – groups such as the Distributed Management Task Force, the Cloud Security Alliance and the Open Cloud Consortium are developing standards for interoperable management, data migration, security and other functions, but real standards at the quality levels corporate IT requires are still a couple of years away, most analysts agree.
Risks of Cloud Computing Model
• Data mobility – Most SaaS or cloud vendors have some ability for customers to download and store data, but the cost of using someone else's application is often that you can't get all your data out of it in a way that's usable in a different vendor's software.
• Privacy – Most cloud contracts include privacy language that promises a customer's data is secure and private. But with cloud-monitoring and management software still in its infancy, a customer's ability to know for sure who's looking at what data — especially who within their own organizations is using it — is limited.
• Service levels – Cloud computing isn't entirely one-size-fits-all; there is some ability to customize the applications and services each customer gets. But the ability to tailor service-level requirements to the specific needs of a business is far less than with internal data centers where IT's whole purpose is to further the company's business goals.
• Interoperability – The highly-customized internal applications that many companies rely on most heavily are often incompatible with generic IT infrastructures available within the cloud. That may be fine with many companies, which would prefer to use only relatively generic applications outside their own firewalls.
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