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Google App Engine

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Developer(s)Google
Initial releaseApril 7, 2008
Written inPython, Java, Go
TypeWeb development
Websitehttp://appengine.google.com

Google App Engine (often referred to as GAE or simply App Engine, and also used by the acronym GAE/J) is a platform as a service (Paas) cloud computing platform for developing and hosting web applications in Google-managed data centers. It virtualizes applications across multiple servers,[1]. App Engine offers automatic scaling for web applications - as the number of requests increases for an application, App Engine automatically allocates more resources for the web application to handle the additional demand.[2]

Google App Engine is free up to a certain level of consummed resources. Fees are charged for additional storage, bandwidth, or CPU cycles required by the application.[3] It was first released as a beta version in April 2008, and out of beta in Sept 2011.

Supported features/restrictions

Currently, the supported programming languages are Python, Java, and Go (and, by extension, other JVM languages such as Groovy, JRuby, Scala, Clojure, Jython and PHP via a special version of Quercus) [2]. Python web frameworks that run on Google App Engine include GAE framework, Django, CherryPy, Pylons, Flask, web2py and webapp2, as well as a custom Google-written webapp framework and several others designed specifically for the platform that emerged since the release.[4] Google has said that it plans to support more languages in the future, and that the Google App Engine has been written to be language independent.[citation needed] Any Python framework that supports the WSGI using the CGI adapter can be used to create an application; the framework can be uploaded with the developed application. Third-party libraries written in pure Python may also be uploaded.[5][6]

Bulk downloading

SDK version 1.2.2 adds support for bulk downloads of data using Python.[7] The open source Python projects gaebar,[8] approcket,[9] and gawsh[10] also allow users to download and backup App Engine data. No method for bulk downloading data from GAE using Java currently exists.

Restrictions

  • Developers have read-only access to the filesystem on App Engine. Applications can use only virtual filesystems, like gae-filestore.
  • App Engine can only execute code called from an HTTP request (scheduled background tasks allow for self calling HTTP requests).
  • Users may upload arbitrary Python modules, but only if they are pure-Python; C and Pyrex modules are not supported.
  • Java applications may only use a subset (The JRE Class White List) of the classes from the JRE standard edition.[11]
  • Java applications cannot create new threads.
  • Does not support 'naked' domains (without www) like http://example.com. The required alias to ghs.google.com is implemented with a DNS CNAME record in order for changes in Google server IP addresses not to impact the service. This record cannot be used with other DNS records (RFC 1034 section 3.6.2, RFC 1912 section 2.4), including the required Start of Authority for the example.com DNS zone. Suggested workaround is to use the domain registrar HTTP redirection to a subdomain, e.g. "www.example.com".[12]
  • SSL/HTTPS is only available via *.appspot.com domains and not via Google Apps Domains.[13]
  • Datastore cannot use inequality filters on more than one entity property per query.[14]
  • A process started on the server to answer a request can't last more than 30 seconds. (with the 1.4.0 release, this restriction does not apply to background jobs anymore)
  • Does not support sticky sessions (a.k.a. session affinity), only replicated sessions are supported including limitation of the amount of data being serialized and time for session serialization.

Major differences

Differences from other application hosting

Compared to other scalable hosting services such as Amazon EC2, App Engine provides more infrastructure to make it easy to write scalable applications, but can only run a limited range of applications designed for that infrastructure.

App Engine's infrastructure removes many of the system administration and development challenges of building applications to scale to hundreds of requests per second and beyond.[15] Google handles deploying code to a cluster, monitoring, failover, and launching application instances as necessary.

While other services let users install and configure nearly any *NIX compatible software, App Engine requires developers to use only its supported languages, APIs, and frameworks. Current APIs allow storing and retrieving data from a BigTable non-relational database; making HTTP requests; sending e-mail; manipulating images; and caching. Most existing Web applications can't run on App Engine without modification, because they require a relational database.

Per-day and per-minute quotas restrict bandwidth and CPU use, number of requests served, number of concurrent requests, and calls to the various APIs, and individual requests are terminated if they take more than 30 seconds or return more than 10MB of data.

Differences between SQL and GQL

Google App Engine's datastore has a SQL-like syntax called "GQL". GQL intentionally does not support the Join statement, because it seems to be inefficient when queries span more than one machine.[16] Instead, one-to-many and many-to-many relationships can be accomplished using ReferenceProperty().[17] This shared-nothing approach allows disks to fail without the system failing.[18] Switching from a relational database to the Datastore requires a paradigm shift for developers when modelling their data.

Unlike a relational database the Datastore API is not relational in the SQL sense.

The Java version supports asynchronous non-blocking queries using the Twig Object Datastore interface. This offers an alternative to using threads for parallel data processing.

Portability concerns

Developers worry that the applications will not be portable from App Engine and fear being locked into the technology.[19] In response, there are a number of projects to create open-source back-ends for the various proprietary/closed APIs of app engine, especially the datastore. Although these projects are at various levels of maturity, none of them is at the point where installing and running an App Engine app is as simple as it is on Google's service.[20]

Web2py web framework offers migration between SQL Databases and Google App Engine, however it doesn't support several App Engine-specific features such as transactions and namespaces.[21]

The Django web framework and applications running on it can be used on App Engine with modification. Django-nonrel aims to allow Django to work with non-relation databases and the project includes support for App Engine.[22]

Applications developed for the Grails web application framework may be modified and deployed to Google App Engine with very little effort using the App Engine Plugin.

The GAE Java servlet container uses the Jetty Web Server,[23] an open source project that implements the 2.5 servlet specification.

AppScale can run Python, Java, and Go GAE applications on EC2 and other cloud vendors.

Backends

In Google I/O 2011, Google announced App Engine Backends, which are allowed to run continuously, and consume more memory. [24] [25] Unlike normal App Engine instances, backends are billed for uptime rather than CPU usage.

Usage quotas

Google App Engine requires a google account to get started, and an account may allow the developer to register up to 10 applications. This limit can be increased by Google staff.

Google App Engine defines usage quotas for free applications. Extensions to these quotas can be requested, and application authors can pay for additional resources.[26] Below are limit and quotas defined per application:

Hard limits

Quota Limit
Time per request 30 sec, indefinite for backends
Blobstore size (total file size per app) 2 GB
HTTP response size 32 MB
Datastore item size 1 MB
Application code size 150 MB
Memory cap 128MB, up to 1GB per instance for backends

Free quotas

Application creators who enable billing pay only for CPU, bandwidth, storage, and e-mails used in excess of the free quotas. Limits marked with * are increased for application authors who enable billing, even if their application never uses enough resources to incur charges. Free quotas were reduced on May 25, 2009[27], reduced again on June 22, 2009.[28] but then revised in May 2011 to allow for more infrastructure and pricing changes.[29][30]

Quota Limit
Emails per day 2000
Bandwidth in per day 1 GB
Bandwidth out per day 1 GB
CPU time per day (to be removed) 6.5 hours per day
Instance-hours (IH) 24 hours per day*
Data stored 1 GB
URLFetch API calls per day 657,084*

Competition

The service competes with Amazon Web Services, a set of application services that enable web sites to host files and execute code on Amazon's servers.

Other competitors include Microsoft's Azure Services Platform, Salesforce.com's Force.com Platform, Sina.com's Sina App Engine (Chinese) and Heroku.

AppScale is an open-source framework for running Google App Engine applications.[31]

References

  1. ^ http://code.google.com/appengine/docs/python/runtime.html
  2. ^ Sanderson, Dan (2009). Programming Google App Engine: Build and Run Scalable Web Apps on Google's Infrastructure. O'Reilly Media. ISBN 978-0596522728.
  3. ^ http://code.google.com/appengine/docs/quotas.html
  4. ^ http://code.google.com/p/tipfy/wiki/AppEngineFrameworks
  5. ^ http://code.google.com/appengine/docs/whatisgoogleappengine.html
  6. ^ http://code.google.com/appengine/docs/python/tools/webapp/overview.html
  7. ^ http://code.google.com/appengine/docs/python/tools/uploadingdata.html#Downloading_Data_from_App_Engine
  8. ^ http://github.com/aral/gaebar/tree/master
  9. ^ http://code.google.com/p/approcket/
  10. ^ http://code.google.com/p/gawsh/
  11. ^ The JRE Class White List
  12. ^ Officially Support Naked Domains for GAE Apps
  13. ^ Issue 792
  14. ^ Google App Engine Datastore Gotchas
  15. ^ "Python Runtime Environment - Google App Engine". 2009-11-10. Retrieved 2009-11-10.
  16. ^ Introducing Google App Engine part 3
  17. ^ http://code.google.com/appengine/articles/modeling.html
  18. ^ http://highscalability.com/google-architecture
  19. ^ http://arstechnica.com/old/content/2008/04/analysis-google-app-engine-alluring-will-be-hard-to-escape.ars
  20. ^ A blog post that lists such efforts as it announces another one.
  21. ^ http://web2py.com/book/default/section/11/13
  22. ^ http://www.allbuttonspressed.com/projects/djangoappengine
  23. ^ http://www.infoq.com/news/2009/08/google-chose-jetty
  24. ^ Google I/O 2011: App Engine Backends on YouTube
  25. ^ Backends Python API Overview
  26. ^ "Understanding Application Quotas with Google App Engine". Retrieved 2010-04-16.
  27. ^ Google, Inc., Upcoming Changes to the Free Quotas, accessed February 26, 2009
  28. ^ Google, Inc., [1], accessed June 17, 2009
  29. ^ "Google App Engine Blog: The Year Ahead for Google App Engine!". Google App Engine blog. Retrieved 11 May 2011.
  30. ^ "Google App Engine - Pricing and Features". Google. Retrieved 11 May 2011.
  31. ^ http://appscale.cs.ucsb.edu

Bibliography

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