1. Google App Engine
N. Koprowski, W. Sanchez, K. Thissen, M. Tryniecki,
A. Klos
The slides are licensed under a
1 Web Technologies – Prof. Dr. Ulrik Schroeder – WS 2010/11 Creative Commons Attribution 3.0 License

2. Cloud Computing
 Resources and software on demand
 Providers offer APIs
 Platform as a service
 Software as a Service
 Infrastructure as a service
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3. Google App Engine – Idea/Concept
 Developing & hosting web applications
 Run web applications on Google's Cloud infrastructure
 Free up to a certain quota of used resources
 Metered bandwidth/CPU time/storage use
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4. General Features
 Automatic scaling and load balancing
 Malfunction detection & Backup
 Managing of cache and databases
 SDK for local development and testing
 Persistent data storage
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5. Programming Features
 Supports Java and Python
 APIs for additional features
 Sandbox environment
 Each environment provides standard protocols and common
technologies, but there are restrictions
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6. General Restrictions
 Datastore: Limitation of inequality filters
 Answer a request in 30 seconds
 No saving of environment between requests
 Filesystem: read-only access
 Code execution only via HTTP request
 SSL/HTTPS: only via *.appspot.com domains
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7. Programming Restrictions
 Typical restrictions of a sandbox
 Java: only subset of classes from standard JRE
 Java applications cannot create new threads
 Python modules: only pure Python
(no C)
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8. Java/Python differences in GAE
 Java:
 Big set of advanced libraries available
 Datastore: Standard method is to use JDO or JPA
 Flexibility: The possibility of running JVM bytecode made by
different languages
 Python:
 Lacks third-party libraries
 Specific API for Google Datastore
 More support and extensive knowledge base available
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9. Google Datastore
 Distributed data storage service
 SQL-like syntax (no JOINS)
 Communication over a provided API
 No traditional relational database
 Datastore entities are schemaless
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10. IDEs - Eclipse
 Plugin available for Eclipse:
 Create empty app engine projects
 Test applications with local sandbox
 Deployment
 Compatible with Google Web Toolkit
 As-you-type validation
 Ant is not needed
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11. Programming Example
 Creating a new Google Project
 Testing the Project
 Test run on local server
 Modifying the Project
 Working with the Datastore
 Deploying the Project
 Creating the Application ID
 Deploying on Appengine
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12. Comparison – Amazon Web Services
Google: Amazon:
• Platform as a Service • Infrastructure as a Service
• Only supports a limited • Wide support for languages
range of languages, APIs, and databases
frameworks
• Simple deployment • Deployment is more akin to
using single servers
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13. Comparison – Amazon Web Services
Google: Amazon:
• No relational database • Supports relational
databases
• Lower hosting costs and a
free quota • Higher hosting costs
• Easier to write scalable
applications
-> Low costs and easy to use, -> Flexible, but higher costs
but limited
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14. Literature
 http://code.google.com/appengine/ is the Google App Engine
official website
 Google provides extensive articles, tutorials, videos and
documentation both for Python and Java with and without the use
of the Eclipse IDE which can be found on
 http://code.google.com/appengine/articles/
 http://code.google.com/appengine/docs/
 http://code.google.com/appengine/community.html
 http://www.youtube.com/user/GoogleDevelopers
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