云中编码：掌握Google AppEngine的云端开发

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"Code in the Cloud" 《Code in the Cloud》是一本专注于云应用开发的书籍，特别是聚焦于Google的AppEngine平台。该书旨在帮助读者掌握如何在云计算环境中进行软件开发，从而适应Web 2.0时代的多用户服务模式。这种新型的应用开发方式不再局限于个人计算机上的单用户应用，而是转向全球数据中心运行的多用户云服务。云计算是当前信息技术领域的一个重要趋势，它允许开发者构建可扩展、灵活的多用户服务，而不必关心传统的基础设施问题，如服务器硬件购置、操作系统安装以及对应用程序未来需求的担忧。Google AppEngine作为一个强大的、易于使用的框架，为开发者提供了构建这些云服务的机会。书中通过Python和Java的实例，向读者展示了如何利用AppEngine平台进行云开发，帮助读者理解和掌握云环境下的技术。作者Mark Jason Dominus以平易近人的方式解释了相关技术，避免了过多的市场宣传，而是提供了更多实际操作的指导，使得阅读体验更为愉快。 Fred Daoud，作者的评价者之一，强调了《Code in the Cloud》对于区分网络应用开发中的基本复杂性和偶然复杂性的重要性。书中阐述了如何使用AppEngine的服务来编写高灵活性和可扩展性的基于Web的应用程序，让开发者可以避开过去困扰他们的许多底层部署细节。 Lyle Johnson，Senitar Inc.的高级分析师，赞扬了书中紧凑、注释清晰的代码示例，以及对如何编写无需过多关注基础架构问题的云应用的明确说明。他认为这本书为开发者提供了解决过去问题的新方法，使他们能够更专注于应用的核心功能和用户体验。综上，《Code in the Cloud》是一本针对云开发，尤其是Google AppEngine的实践指南，对于想要进入云开发领域的开发者或寻求提高云服务构建能力的现有开发者来说，都是一本宝贵的参考资料。通过学习本书，读者可以深入了解如何利用云技术构建高效、可扩展的Web应用，从而跟上Web 2.0时代的发展步伐。

CLOUDCOMPUTINGPROGRAMMINGSYSTEMS 16

ability to listen to snippets, read reviews, comment on things that

they’ve listened to, get suggestions for new things based on what

they like, and ultimately select things to purchase. That’s clearly

a service, and it makes sense to keep it in the cloud.

Large computations.

Is your application intended to perform a massive computation,

which you could never afford to do if you needed to buy your own

computers to run it? If so, the cloud allows you to purchase time

on a server farm of computers in an affordable way and run your

application. This is gr eat for people like genetics researchers, who

need to run massive computations but don’t have the money or

other resources to set up a dedicated data center for their com-

putations. Instead, they can purchase time on commercial data

centers, which they share with many other users.

1.2 Cloud Computing Programming Systems

There are multiple ways of programming the cloud. Before we start

actually writing programs, we’ll take a quick look at a few examples to

give you a sense of what sorts of options are available.

Amazon EC2

Amazon provides a variety of cloud-based services. Their main pro-

gramming tool is called EC2, Elastic Computing Cloud.

EC2 is really a family of related services. Compared to App Engine,

which provides a single, narrowly focused suite of APIs, EC2 is com-

pletely agnostic about programming APIs. It provides hundreds of dif-

ferent environments: you can run your application in EC2 using Linux,

Solaris, or W i n d o w s Server; you can store data using DB2, Informix,

MySQL, SQL Server, or Oracle; you can implement your code in Perl,

Python, Ruby, Java, C++, or C#; you can run it using IBM’s W e b S p h e r e

or sMash, Apache JBoss, Oracle W e b L o g i c , or Microsoft IIS. Depend-

ing on which combination you prefer and how much of each kind of

resource (storage, CPU, network bandwidth) you plan to use, the costs

vary from $0.10 per CPU hour and $0.10 per gigabyte of bandwidth to

around $0.74 per CPU hour for high-end instances.

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CLOUDCOMPUTINGPROGRAMMINGSYSTEMS 17

Amazon S3

Amazon provides another extremely interesting cloud service, which is

very different from most other cloud offerings. S3, Simple Storage Ser-

vice, is a pure storage system. It doesn’t provide the ability to run pro-

grams; it doesn’t provide any ﬁlesystem; it doesn’t provide any index-

ing. It’s pure block storage: you can allocate a chunk of storage that

has a unique identiﬁer, and then you can read and write bytes from

that chunk using its identiﬁer.

A variety of systems have been created that use S3 for storage: web-

based ﬁlesystems, native OS ﬁlesystems, database systems, and table

storage systems. It’s a wonderful example of the cloud’s resource-based

paradigm: the computation involved in storage is completely separated

from the actual data storage itself. When you need storage, you buy a

bunch of bytes of storage space from S3. When you need computation,

you buy EC2 resources.

S3 is a really fascinating system. It’s very focused: it does exactly one

thing and does it in an incredibly narrow way. But in an important

sense, that’s exactly what the cloud is about. S3 is a perfectly focused

service; it stores bytes for you.

S3 charges are based on two criteria: how much data you store and how

much network bandwidth you use storing and retrieving your data.

Amazon currently charges $0.15 per gigabyte per month and about

$0.10 per gigabyte uploaded and $0.17 per gigabyte downloaded.

On a related note, Google provides a very similar cloud service, called

Google Developer Storage, which replicates the basic features of S3 in

the Google cloud.

IBM Computing on Demand

IBM provides a cloud service platform based on IBM’s suite of web ser-

vice development that uses W e b S p h e r e , DB2, and Lotus collaboration

tools. The environment is the same as the IBM-based environment on

EC2, but it runs in IBM’s data centers instead of Amazon’s.

Microsoft Azure

Microsoft has developed and deployed a cloud platform called Azure.

Azure is a W i n d o w s - b a s e d platform that uses a combination of stan-

dard web services technologies (such as SOAP, REST, Servlets, and

ASPs) and Microsoft’s proprietary APIs, like Silverlight. As a result,

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CLOUDCOMPUTINGPROGRAMMINGSYSTEMS 18

you get the ability to create extremely powerful applications that look

very much like standard desktop applications. But the downside is it’s

closely tied to the W i n d o w s platform, so the application clients run

primarily on W i n d o w s . While there are Silverlight implementations for

other platforms, the applications tend to only be reliable on W i n d o w s

platforms and only fully functional in Internet Explorer.

So that’s the cloud. Now that we know what it is, we’re going to start

learning about how to build applications in the cloud. Google has put

together a really terriﬁc platform, called App Engine, for you to build

and run your own cloud applications.

In the rest of the book, we’re going to look in detail at the key pieces

of building cloud-based web applications. W e ’ l l start of f working in

Python. Python’s gr eat for learning the basics: it lets you see what’s

going on, and it makes it easy to quickly try different approaches and

see what happens.

W e ’ l l go through the full stack of techniques that you need for build-

ing a Google App Engine application in Python, starting with the basic

building blocks: HTTP, services, and handlers. Then we’ll look at how

you work with persistent data in the cloud using the App Engine data-

store service. And then, we’ll look at how to build user interfaces for

your applications using HTTP, CSS, and AJAX.

From there, we’ll leave Python for a while and move into Java. In my

opinion, Java can be a lot more convenient for building complex appli-

cations. Not that Python can’t or shouldn’t be used for advanced App

Engine development, but my preference is to use Java. And App Engine

provides access to an absolutely brilliant framework called GWT, which

abstracts away most of the boilerplate plumbing of a web-based cloud

application, allowing you to focus on the interesting parts. W e ’ l l spend

some time learning about how to build beautiful user interfaces using

GWT and how to do AJAX-style communication using GWT’s remote

procedure call service.

Finally, we’ll spend some time looking at the most complicated aspects

of real web development. W e ’ l l look at the details of how you can do

sophisticated things using the App Engine datastore service, how to

implement server-side processing and computation using things like

cron, and how to integrate security and authentication into your App

Engine application.

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