Designing and architecting for cloud scale in .NET

Creator QR Code in .NET Designing and architecting for cloud scale

Designing and architecting for cloud scale
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This chapter covers
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Dealing with internet scale through the use of database sharding Connecting a data center to the cloud Expanding to the cloud through cloudbursting Handling exponentially expanding storage through the use of cloud storage
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In this chapter, you ll learn how to design and architect applications that can handle the potentially massive scale possible when you re using the cloud and are exposed to the entire internet. You re now prepared for an in-depth discussion of designing and architecting applications specifically for the cloud. This is important because you may have applications that scale to large numbers of users a number so large that we call it cloud scale. Although this chapter doesn t require a programmer s background, we do go into some detail about issues that are unique to building applications that are designed for the cloud and prepared for broad-scale use. After all, one of the primary reasons for utilizing the cloud is to be prepared for, and to
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High-scale application patterns that fit the cloud best
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have an affordable economic model for, that wonderful problem of suddenly having too many users. We ll describe the kinds of applications that fit well into the cloud model. And you ll learn about several design topics: building for internet scale (including the concept of sharding); building in on-demand capacity in your data center (cloudbursting); and storage that keeps expanding. First, let s examine a set of design patterns that fit well with the unique characteristics of the cloud.
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High-scale application patterns that fit the cloud best
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Let s begin with a discussion about broad types, or patterns, of high-scale applications and how they do or don t fit well into the model of cloud computing. The categories we ll consider are called transference, internet scale, burst compute, and elastic storage. These are the most common application patterns that motivate a move to the cloud to deal with high scale (lots of users, lots of compute, lots of data, or rapid swings of any of these). We ll look at these in order, first defining the category followed by a short discussion of the issues to watch out for.
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Transference
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Transference is when you take an existing on-premises application and move it to the cloud as is. This pattern is typically driven by economic factors (as you ve read earlier in this book). It can be cheaper to use cloud resources than to run these applications in-house if you re not fully employing virtualization for higher utilization in your local data center. Commodity services, such as email, CRM, and other packaged applications, are candidates for this pattern. Zillow.com a website dedicated to providing consumers accurate expected home values on any U.S. residential address is a small business that moved its application as is to the cloud because it couldn t afford the servers needed to process the large number of changes in home values across the entire country when the housing market bubble burst. It had a huge spike in compute work it needed to accomplish but didn t want to buy the necessary servers because they would be excess capacity in a few weeks. When the transference pattern is the appropriate one to use, you need to watch out for customizations that work in your local data center but that the host/cloud doesn t support. For example, if the application depends on a custom device driver you built for Linux, you won t be able to transfer this application to a cloud: cloud providers won t allow you to re-create that device driver modification in their Linux implementation. This aside, you ll find no other design issues with this pattern, and it won t get further coverage in this chapter.
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