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The Cloud's Essential Characteristics

The main motivation behind the pervasive adoption of cloud use today is economic. Cloud technology allows taking a very expensive asset, such as a $200 million data center, and delivering its capabilities to individual users for a few dollars per month, or even for free, in some business models. This feat is achieved through resource pooling, which is essentially treating an asset like a server as a fungible resource; a resource-intensive application might take a whole server, or even a cluster of servers, whereas the needs of users with lighter demands can be packed as hundreds or even thousands to a server.

This dynamic range in the mapping of applications to servers has been achieved through virtualization technology. Every intervening technology and the organizations needed to run them represent overhead. However, the gains in efficiency are so large that this inherent overhead is rarely in question. With applications running on baremetal operating systems, it is not unusual to see load factors in the single digits. Cloud applications running on virtualized environments, however, typically run utilizations up to 60 to 80 percent, increasing the application yield of a server by several-fold.

Cloud applications are inherently distributed, and hence they are necessarily delivered over a network. The largest applications may involve millions of users, and the conveyance method is usually the Internet. An example is media delivery through Netflix, using infrastructure from Amazon Web Services. Similarly, cloud applications are expected to have automated interfaces for setup and administration. This usually means they are accessible on demand through a self-service interface. This is usually the case, for instance, with email accounts through Google Gmail or Microsoft

With the self-service model, it is imperative to establish methods for measuring service. This measuring includes guarantees of service provider performance, measurement of services delivered for billing purposes, and very important from the perspective of our discussion, measurement of security along multiple vectors. The management information exchanged between a service provider and consumers is defined as service metadata. This information may be facilitated by auxiliary services or metaservices.

The service provider needs to maintain a service pool large enough to address the needs of the largest customer during peak demand. The expectation is that, with a large customer base, most local peaks and valleys will cancel out. In order to get the same quality of service (QoS), an IT organization would need to size the equipment for expected peak demand, leading to inefficient use of capital. Under some circumstances, large providers can smooth out even regional peaks and valleys by coordinating their geographically disperse data centers, a luxury that mid-size businesses might not be able to afford.

The expectation for cloud users, then, is that compute, network, and data resources in the cloud should be provided on short order. This property is known as elasticity. For instance, virtual machines should be available on demand in seconds, or no more than minutes, compared to the normal physical server procurement process that could take anywhere from weeks to years.

At this point, we have covered the what question—namely, the essential characteristics of the cloud. The next section covers service models, which is essentially the how question.

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