c# code 128 Getting to know Windows Azure in Visual C#.NET

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Getting to know Windows Azure
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100,000 hits per day. The traffic dropped off after about a week, and then the website had a new baseline of around 10,000 hits per day. With Windows Azure, you can dynamically scale up to handle the increased traffic load for that week (and get all the extra shirt sales); then, as the traffic decreases, you can Figure 1.14 Traffic before, during, and after Ashton Kutcher scale back down again, paying plugged your site only for the resources you use. Scaling up and down in Azure is quite simple, and we ll discuss how to do it in detail in chapter 6. You have several options at your disposal. It s important to remember that Azure doesn t scale your service for you. Because it costs money, you have to tell Azure how many servers you want. Azure gives you tools to do this. You can simply log into the portal and make a small change to a configuration file, which is the easy, manual way. You can also use the Service Management API (covered in chapter 18). This API lets you change the resources you have allocated to your application in an automated way. It s not only possible to scale up and down for predictable (or unpredictable) bursts of growth; you can also dynamically scale your service based on normal, varied usage patterns.
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VARIED USAGE PATTERNS
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Returning to the Hawaiian Shirt Shop example: after the Ashton Kutcher hype died down a little, your website leveled off at around 10,000 hits per day. Figure 1.15 shows how this traffic varies over the course of a day. Most of the time there s little traffic on the site, apart from during lunch and in the evening. Evidently, most people don t buy Hawaiian shirts when they re at work. Because it takes only a few minutes to provision a new web server in Windows Azure, you can dynamically scale your website as your usage patterns dictate. For the Hawaiian Shirt Shop, you might decide to run one instance of the website during the day, but in the evening to run three instances to deal with the increased traffic. Figure 1.15 Distribution of website traffic over a single day
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Why run in the cloud
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This sort of scenario is a perfect example of when cloud computing, specifically using Windows Azure, is a perfect fit for your business. If you need to scale beyond a single web server for certain periods of the day when traffic is high, Windows Azure is a cost-effective choice because it allows you to scale back when traffic dies down. Cloud computing solutions are the only offerings that give you this elastic scalability. Other solutions typically require you to over-provision your hardware to cope with the peak periods, but that hardware is underused at off-peak times.
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Enough capacity
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This example of utility computing can be extended further in regard to available capacity. It s fair to say that most people don t have any idea of the available spare electricity capacity of the network supplying their home, but most of us are confident that if we plug in an extra television, the required electricity will be supplied. The same holds true in Windows Azure. We have no idea how much spare capacity the Microsoft data centers have, but we do know that there s enough. If you require an extra instance of your website, web service, or backend service to be hosted, this will be provisioned for you, within minutes. If the data that your service stores is much larger than you originally anticipated due to the level of growth, more disk space will be allocated to you. You never have to worry about running out of disk space or running out of computing power. You only have to worry about running out of money to pay for the services. Growth is difficult to model effectively, so knowing there s always enough capacity to grow allows you to concentrate on providing your service rather than worrying about capacity planning, provisioning of new servers, and all their associated tasks.
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So far, we ve discussed the cost savings you can achieve by scaling your application up and down. Let s now look at how you can save money in maintenance costs.
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