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. Applications are sandboxed and run across multiple servers. 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.
Google App Engine is free up to a certain level of consumed resources. Fees are charged for additional storage, bandwidth, or instance hours required by the application. It was first released as a preview version in April 2008, and came out of preview in September 2011.
Runtimes and frameworks
Currently, the supported programming languages are Python, Java (and, by extension, other JVM languages such as Groovy, JRuby, Scala, Clojure, Jython and PHP via a special version ofQuercus), and Go. 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.
Reliability and Support
All billed High-Replication Datastore App Engine applications have a 99.95% uptime SLA
Portability Concerns
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/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. AppScale and TyphoonAE are two of the open source efforts.
AppScale can run Python, Java, and Go GAE applications on EC2 and other cloud vendors.
TyphoonAE can run python App Engine applications on any cloud that support linux machines.
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.
Differences with 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. 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. Existing web applications that require a relational database will not run on App Engine without modification.
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 60 seconds or return more than 32MB 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. 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 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.
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Cloud Computing 