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The final example of a situation in which it may be economically advantageous to deploy in a cloud model is when you re dealing with applications that are commodities and aren t strategic to the business. Many tactical applications serve internal constituents within an organization that could be moved to a cloud deployment, resulting in savings of scarce IT resources in an organization. A classic example is backup data storage. Instead of wasting internal IT resources on maintaining a backup system, you can use a cloud-based backup service. Because this is a core competency of the company providing the cloud backup service, it can be done more efficiently and economically by them than it can be by using internal IT resources. This can free up these resources to work on projects that are generally more strategic to the business.
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Where does the cloud not make sense
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Although many application types make a good case for deployment to the cloud, in several cases you should pause before running down a cloud path. This isn t to say that these scenarios should never consider a cloud computing paradigm, but serious consideration and planning are certainly wise if you want to proceed down this path.
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Cloud service providers have put together large data-center infrastructures built on commodity hardware running commodity software. The sweet spot for deployment on the cloud is applications designed to run on these sorts of hardware and software platforms. Standard virtual instances are available loaded with operating systems such as Linux and Windows, not HP-UX or VMS. Legacy applications built some time ago on legacy or proprietary hardware and software platforms would take an inordinate amount of effort to convert onto a cloud platform. Instead of conversion, if the systems are near end-of-life and are good candidates for the cloud, you should redesign and rewrite the applications from scratch.
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Applications involving real-time/mission-critical scenarios
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One of the strengths of the cloud is access to a tremendous amount of computing capacity without the carrying cost of all that hardware on your books. Real-time image processing, as is necessary for processing MRI brain scans, is an example of this type of application. This sort of real-time view of the brain is incredibly useful as a guide for surgeons during an operation. But a cloud deployment for this type of application is probably not the way to go. Cloud services are at this time delivered on a best-effort basis, and the only recourse for poor service availability is a refund of the service fee. Even assuming the cloud service could perform flawlessly and deliver 100 percent uptime, the fact that the application must rely on connectivity over the public internet makes it a questionable proposition to try to run an application with extreme mission criticality (such as life and death) and with stringent real-time constraints. If you look at the sectors where SaaS businesses thrive, you ll see that they re successful in providing services such as customer relationship management (CRM) that are important to a business and need to be highly available, but where a glitch that requires a browser refresh isn t catastrophic. These classes of application too aren t amenable for an organization to attempt to deploy in a cloud model yet.
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Applications dealing with confidential data
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Another genre of application that requires caution when thinking about cloud deployment models deals with highly sensitive or confidential data. For example, the healthcare industry is careful about complying with privacy, as mandated by the Health
The business case for cloud computing
Insurance Portability and Accountability Act (HIPAA). IT organizations have over the years developed best practices, such as classifying the level of security required for different classes of data. If you re contemplating migrating potentially sensitive information, you must make sure you take as much care protecting that data as you do with data in the internal IT infrastructure. Let s consider the problem of deleting confidential data. Typically, when data is deleted from a disk it isn t truly deleted, but only marked for deletion. When another process needs to write data to the disk, it has the opportunity to write over the location marked for deletion, thereby destroying the data. In the case of a disk that you own or have direct control over, if simple deletion isn t good enough, you can choose to reformat the disk; or if that is insufficient, you can take an axe to the disk drive and then throw it into an incinerator. But data stored in a cloud infrastructure is sitting on a shared disk drive. You lose a degree of control over the disposition of the data. You can attempt to delete a file, but you have no way to be certain the data is truly destroyed.
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