Deploying applications in google app engine is free

Deploying applications in Google App Engine is free, within limited usage. Thus
applications can be developed and tried out free and begin to obtain cost only
when accessed by a sufficient volume of requests. The PaaS model enables
Google to provide such a free service because applications do not run on
dedicated virtual machines. A deployed application that is not accessed just
consumes storage for its code and data and expends no CPU cycles.
 GAE applications are served by a large number of web servers in Google’s data
centers that execute requests from end-users across the globe. The web servers
load code from the GFS into memory and serve these requests. Each request to a
particular application is served by any one of GAE’s web servers. There is no
guarantee that the same server will serve requests to any two requests, even
from the same HTTP session. Applications can also specify some functions to be
executed as batch jobs which are run by a scheduler.
 While this architecture is able to ensure that applications scale naturally as load
increases, it also means that application code cannot easily rely on in-memory
data. A distributed in-memory cache called Memcache is made available to
partially solve this issue. In particular HTTP sessions are implemented using
Memcache so that even if requests from the same session go to different servers
they can retrieve their session data.

B. Sc. (SE)/BCA TY V Sem CBCS Cloud Computing (S5.CC.5)
9 |
College of Computer Science & Information Technology, Latur Prepared By: Arun S Shinde
3.2.1 Google Datastore
 Applications store data in the Google Datastore, which is also a non-relational
database. The Datastore allows applications to define structured types (called
‘kinds’) and store their instances (called ‘entities’) in a distributed manner on the
GFS file system. While one can view Datastore ‘kinds’ as table structures and
entities as records. There are important differences between a relational model
and the Datastore, some of which are also shown in Figure 4.3.
Figure 3.3 Google Datastore
 In a relational schema, all rows in a table have the same set of columns but all
entities of a ‘kind’ need not have the same properties. Additional properties can
be added to any entity. This feature is particularly useful in situations where one
cannot predict all the potential properties in a model.

B. Sc. (SE)/BCA TY V Sem CBCS Cloud Computing (S5.CC.5)
10 |
College of Computer Science & Information Technology, Latur Prepared By: Arun S Shinde
 For example, a model storing ‘products’ of different types (shows, books, etc.)
would need to allow each product to have a different set of features. In a
relational model, this would probably be implemented using a separate
FEATURES table, as shown on the bottom left of Figure 3.3. Using the Datastore,
this table (‘kind’) is not required; instead, each product entity can be assigned a
different set of properties at runtime.