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Designing and architecting for cloud scale
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through distributed, on-net processing. Second, different scenarios require different network interconnects between the enterprise and the cloud. The internet alone may be fine if clusters are independent; but for many scenarios, you may require much higher-speed mechanisms. We ll focus on the various options for large and expanding quantities of cloud storage in the next section.
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Designing for exponentially expanding storage
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In these days of Web 2.0, with picture and video sharing all the rage and some social networks growing bigger than 400 million registered users, it s not hard to understand why we need to talk about exponentially expanding storage. It s the rare application that needs the kind of storage that YouTube, Flickr, and Facebook require (see table 5.2). But even more modest applications are finding it desirable to include video- or photo-upload capability. Many more applications need to be designed for expanding storage than used to be the case. Not surprisingly, the cloud is excellent for providing expanding storage capacity. Let s address how applications take advantage of this capability.
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Table 5.2 YouTube Facebook Some very large data hoarders 1 billion video views per day (11,574 views per second) 15 billion photos (and 60 billion image files with replication for different sizes) 220 million new photos added every week 1.5 PB of storage for photos; growing at 25 TB per week Flickr 2 PB of storage to serve 2 billion photos from 4 billion queries per day 400,000 photos added per day PlentyOfFish 30+ million hits per day leading to 1.1 billion page views 1 TB/day serving 171 million images 6 TB storage array for millions of images uploaded per day
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Cloud storage defined
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Cloud storage is storage accessed over a network (internal or external) via web services APIs. Cloud storage access APIs are typically RESTful in nature. Representational state transfer (REST) is a style of software architecture for distributed hypermedia systems, such as the World Wide Web itself. RESTful means conforming to the REST model of an architecture consisting of clients and servers, where clients initiate requests to servers and servers process requests and return appropriate responses. Similar to thinking of compute as elastic thanks to server virtualization, you can look at cloud storage as an abstracted layer of storage as opposed to the storage device directly. As you can imagine, this simplifies integration and development, and facilitates the introduction of many desirable features and options we ll discuss here.
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Designing for exponentially expanding storage
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Amazon S3
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Amazon s S3 was the first and is the most successful cloud storage service. With the release of S3 in March 2006, for the first time, a large pool of storage was available for use where it was accessed via web services APIs on a nonpersistent network connection. You had immediate availability of very large quantities of storage, which operated on a pay-for-what-you use model. The most important attributes of cloud storage are that it must be scalable, reliable, fast, inexpensive, and simple. Amazon was able to benefit from a decade of work on its own storage system that had all these requirements before exposing it to the outside world through a simple API. This is why S3 worked so well from the start and took off as a highly successful service.
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Example cloud storage API (using S3)
It s useful to examine the API of the largest and most successful cloud storage service, because just as the API to Amazon s EC2 is being copied and may become a de facto standard, so too may the S3 API become an industry standard. The basic units of storage S3 deals with are objects and buckets. Objects are the entities used to write, read, and delete collections of data. Objects can be from 1 to 5 GB in size. You can have an unlimited number of objects in S3. Objects are stored in buckets. You can specify whether the bucket is located in the United States or Europe. (Other locales will be available in the future. This becomes important when you re dealing with a specific country or region s regulations, such as a locale s privacy rules.) Access to a bucket is secure and can only proceed through a unique developer-assigned key. Within a bucket, each object can be made private, public, or with access rights granted to specific users. See table 5.3.
Table 5.3 Overview of the Amazon S3 API API call API description The GET operation returns a list of all the buckets owned by the authenticated sender of the request. The PUT request operation with a bucket URI creates a new bucket. This is where you can specify a location constraint that affects where your data physically resides (such as U.S. or Europe). The PUT request operation with a requestPayment URI configures an existing bucket to be Requester Pays or not. With Requester Pays buckets, the requester, instead of the bucket owner, pays the cost of the request and the data download from the bucket. This is important when you want to share data but not incur charges associated with others accessing the data. You may, for example, use Requester Pays buckets when making available large data sets, such as various kinds of directories, reference data, and so forth. A GET request operation using a bucket URI lists information about the objects in the bucket if the requestor has READ access to the bucket.
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