Internet scale in .NET framework

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Internet scale
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The internet scale design pattern involves creating an application for the cloud that has the ability to handle huge numbers of users, such as YouTube, Flickr, or Facebook,
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Designing and architecting for cloud scale
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without requiring the corresponding substantial capital investment from day one. This is a common pattern for prototyping new applications because it allows a significantly lower entrance cost (no servers are being purchased). It also lets you start very small yet expand when needed. When Facebook started, it was run off a single server and serviced only Harvard University students. Facebook built its own data center on its way to supporting 400 million users. If the cloud had existed, the company would have avoided a few growing pains caused by data center and application limitations along the way. Twitter also started as one guy on one server; and because it resonated with people, it grew at an unprecedented pace. It faced many outages because of scaling problems. If you re a small company with big visions of building a service that people want, you need to think hard about starting in the cloud with a strong, scalable design. Finally, designing for and starting in a cloud is applicable as a risk-mitigation measure for applications with unpredictable growth. One of the most challenging design issues for this application pattern, when the application does have to scale, revolves around the database structure: without care, it quickly becomes the database that prevents scale. You ll see how to address this issue in detail later in this chapter.
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Burst compute
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Applications that fit the burst compute pattern have the ability to handle additional compute capability on an as-needed basis without idle, over-provisioned resources. Applications ideal for this pattern have large swings in capacity requirements, particularly if the spikes are somewhat rare. A good example is the site Eventseer.net. It routinely bursts out to Amazon s cloud to statically generate changed pages on its 600,000-page site because it doesn t have the capacity internally to do this fast enough. The burst compute pattern is driven by the economic factors of the cloud. The cost of additional hardware capacity required to support this pattern internally is prohibitive. Real bursts of load can be handled cost effectively in the pay-only-for-whatyou-use cloud model. You ll read about cloudbursting as a nice solution for the burst compute application pattern later in the chapter.
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Elastic storage
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In the elastic storage application pattern, applications have the ability to grow exponentially from a storage perspective. Although local storage is relatively cheap, its management is fairly expensive. As a result, using a cloud platform can be a cheaper alternative to local storage management. But using this pattern requires careful thought and planning for accessing the data. For instance, if you re using the cloud purely to store data, but processing it locally, performance may be unacceptable; that would make this pattern not applicable.
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Designing and architecting for internet scale: sharding
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Summarizing the application patterns
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Table 5.1 summarizes the five major cloud application patterns. Note that the sense of the word design we re using in this chapter is the act of working out the form of something. And the word architecture is the structure and organization of a computer s hardware or system software.
Table 5.1 Summary of the five major cloud-scaling application patterns, their major issues, and the section in which they re discussed Pattern Transference Description Existing on-premises application moved to the cloud as is for economic benefits New web-facing applications with unpredictable growth Applications with large swings of capacity requirements, particularly if spikes are rare Application storage that has the ability to grow exponentially Major issues Application customizations may not transfer or work. Database design can throttle growth; consider sharding. Load-balancing requires a strategy; database access from data center to cloud is the issue. Local processing of cloud accessed data may preclude this pattern. Section N/A
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