|Initial release||April 7, 2008|
|Operating system||Any (Web-based application)|
Google App Engine is cloud computing technology. It virtualizes applications across multiple servers and data centers. Other cloud-based platforms include offerings such as Amazon Web Services and Microsoft's Azure Services Platform.
Google App Engine is free up to a certain level of used resources. Fees are charged for additional storage, bandwidth, or CPU cycles required by the application.
Currently, the supported programming languages are Python and Java (and, by extension, other JVM languages such as Groovy, JRuby, Scala, and Clojure). Python web frameworks that run on Google App Engine include Django, CherryPy, Pylons, and web2py, as well as a custom Google-written webapp framework and several others designed specifically for the platform that emerged since the release. 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. 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.
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. 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 Python or any JVM language (e.g. Java, Groovy, JRuby, Scala) as the programming language and a limited set of APIs. 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.
Google App Engine's datastore has a SQL-like syntax called "GQL". Select statements in GQL can be performed on one table only. GQL intentionally does not support the Join statement, because it seems to be inefficient when queries span more than one machine. Instead, one-to-many and many-to-many relationships can be accomplished using ReferenceProperty(). This shared-nothing approach allows disks to fail without the system failing. Switching from a relational database to the Datastore requires a paradigm shift for developers when modeling 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.
Developers worry that the applications will not be portable from App Engine and fear being locked into the technology. In response, there are a number of projects to create open-source back-ends for the various proprietary 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. 
Web2py has, since the beginning of its support for GAE, been incredibly easy to migrate back and forth from SQL Databases to Google App Engine. In fact, it rivals many other frameworks in ease of migration. To take a project from GAE to an SQL database such as MySQL or MSSQL, all that is required is to change the database connection string in the db.py file from db = DAL('gae') to something like (in the case of PostgreSQL) db = DAL("postgres://myuser:mypassword@localhost:5432/mydb"). The Django web framework and applications running on it can be used on App Engine with modification.
App Engine defines usage quotas for free applications. Extensions to these quotas can be requested, and application authors can pay for additional resources.
|Apps per developer||10|
|Time per request||30 sec|
|Files per app||3,000|
|HTTP response size||10 MB|
|Datastore item size||1 MB|
|Application code size||150 MB|
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 and were reduced again on June 22, 2009.
|Emails per day||2,000|
|Bandwidth in per day||1,000 MB|
|Bandwidth out per day||1,000 MB|
|CPU time per day||6.5 hours per day|
|HTTP Requests per Day||1,300,000*|
|Datastore API calls per day||10,000,000*|
|Data stored||1 GB|
|URLFetch API calls per day..||657,084*|
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. Many tech analysts have been predicting Google's entry into this field for years. "Google finally realizes it needs to be the web platform," Techdirt publisher Mike Masnick wrote. "The easier it is to develop and deploy highly scalable web applications, the more innovative and creative solutions we're going to start to see."
AppScale is an open-source framework for running Google AppEngine applications.