John David N. Dionisio, Loyola Marymount University


Project description: The objective of this undergraduate database systems course is for students to implement one database application in two technology stacks, a traditional relational database and on Google App Engine. Students are asked to study both models and provide concrete comparison points.



Xiaohui (Helen) Gu, North Carolina State University



The goal of the project is to allow the students to learn distributed system concepts by developing real distributed system management systems and testing them on real world cloud computing infrastructures such as Google App Engine.



Shriram Krishnamurthi, Brown University


Project description:  WeScheme is a programming environment that runs in the Web browser and supports interactive development. WeScheme uses App Engine to handle user accounts, serverside compilation, and file management.



Feifei Li, University of Utah


Project description: A graduate-level course that will be offered in Fall 2013 on the design and implementation of large data management system kernels.  The objective is to integrate features from a relational database engine with some of the new features from NoSQL systems to enable efficient and scalable data management over a cluster of commodity machines.



Mark Liffiton, Illinois Wesleyan University


Project description: TeacherTap is a free, simple classroom-response system built on Google App Engine. It lets students give instant, anonymous feedback to teachers about a lecture or discussion from any computer or mobile device with a web browser, facilitating more adaptive class sessions.



Eni Mustafaraj, Wellesley College


Project description: Topics in Computer Science: Web Mashups. A CS2 course that combines Google App Engine and MIT App Inventor. Students will learn to build apps with App Inventor to collect data about their life on campus. They will use Google App Engine to build web services and apps to host the data and remix it to create web mashups. Offered in the 2013 Spring semester.



Manish Parashar, Rutgers University


Project description: Cloud Computing for Scientific Applications -- Autonomic Cloud Computing teaches students how a hybrid HPC/Grid + Cloud cyber infrastructure can be effectively used to support real-world science and engineering applications. The goal of our efforts is to explore application formulations, Cloud and hybrid HPC/Grid + Cloud infrastructure usage modes that are meaningful for various classes of science and engineering application workflows.



Orit Shaer, Wellesley College


Project description: GreenTouch


GreenTouch is a collaborative environment that enables novice users to engage in authentic scientific inquiry. It consists of a mobile user interface for capturing data in the field, a web application for data curation in the cloud, and a tabletop user interface for exploratory analysis of heterogeneous data.



Elliot Soloway, University of Michigan


Project description: WeLearn Mobile Platform: Making Mobile Devices Effective Tools for K-12. The platform makes mobile devices (Android, iOS, WP8) effective, essential tools for all-the-time, everywhere learning.  WeLearn’s suite of productivity and communication apps enable learners to work collaboratively; WeLearn’s portal, hosted on Google App Engine, enables teachers to send assignments, review, and grade student artifacts. WeLearn is available to educators at no charge.



Jonathan White, Harding University


Project description: Teaching Cloud Computing in an Introduction to Engineering class for freshmen.  We explore how well-designed systems are built to withstand unpredictable stresses, whether that system is a building, a piece of software or even the human body.  The grant from Google is allowing us to add an overview of cloud computing as a platform that is robust under diverse loads.



Dr. Jiaofei Zhong, University of Central Missouri

Project description: By building an online Course Management System, students will be able to work on their team projects in the cloud.  The system allows instructors and students to manage the course materials, including course syllabus, slides, assignments and tests in the cloud; the tool can be shared with educational institutions worldwide.



Last year we invited proposals for innovative projects built on Google’s infrastructure. Today we are pleased to announce the 11 recipients of a Google App Engine Education Award. Professors and their students are using the award in cloud computing courses to study databases, distributed systems, web mashups and to build educational applications. Each selected project received $1000 in Google App Engine credits.





Awarding computational resources to classroom projects is always gratifying. It is impressive to see the creative ideas students and educators bring to these programs.





Below is a brief introduction to each project. Congratulations to the recipients!



John David N. Dionisio, Loyola Marymount University


Project description: The objective of this undergraduate database systems course is for students to implement one database application in two technology stacks, a traditional relational database and on Google App Engine. Students are asked to study both models and provide concrete comparison points.



Xiaohui (Helen) Gu, North Carolina State University



The goal of the project is to allow the students to learn distributed system concepts by developing real distributed system management systems and testing them on real world cloud computing infrastructures such as Google App Engine.



Shriram Krishnamurthi, Brown University


Project description:  WeScheme is a programming environment that runs in the Web browser and supports interactive development. WeScheme uses App Engine to handle user accounts, serverside compilation, and file management.



Feifei Li, University of Utah


Project description: A graduate-level course that will be offered in Fall 2013 on the design and implementation of large data management system kernels.  The objective is to integrate features from a relational database engine with some of the new features from NoSQL systems to enable efficient and scalable data management over a cluster of commodity machines.



Mark Liffiton, Illinois Wesleyan University


Project description: TeacherTap is a free, simple classroom-response system built on Google App Engine. It lets students give instant, anonymous feedback to teachers about a lecture or discussion from any computer or mobile device with a web browser, facilitating more adaptive class sessions.



Eni Mustafaraj, Wellesley College


Project description: Topics in Computer Science: Web Mashups. A CS2 course that combines Google App Engine and MIT App Inventor. Students will learn to build apps with App Inventor to collect data about their life on campus. They will use Google App Engine to build web services and apps to host the data and remix it to create web mashups. Offered in the 2013 Spring semester.



Manish Parashar, Rutgers University


Project description: Cloud Computing for Scientific Applications -- Autonomic Cloud Computing teaches students how a hybrid HPC/Grid + Cloud cyber infrastructure can be effectively used to support real-world science and engineering applications. The goal of our efforts is to explore application formulations, Cloud and hybrid HPC/Grid + Cloud infrastructure usage modes that are meaningful for various classes of science and engineering application workflows.



Orit Shaer, Wellesley College


Project description: GreenTouch


GreenTouch is a collaborative environment that enables novice users to engage in authentic scientific inquiry. It consists of a mobile user interface for capturing data in the field, a web application for data curation in the cloud, and a tabletop user interface for exploratory analysis of heterogeneous data.



Elliot Soloway, University of Michigan


Project description: WeLearn Mobile Platform: Making Mobile Devices Effective Tools for K-12. The platform makes mobile devices (Android, iOS, WP8) effective, essential tools for all-the-time, everywhere learning.  WeLearn’s suite of productivity and communication apps enable learners to work collaboratively; WeLearn’s portal, hosted on Google App Engine, enables teachers to send assignments, review, and grade student artifacts. WeLearn is available to educators at no charge.



Jonathan White, Harding University


Project description: Teaching Cloud Computing in an Introduction to Engineering class for freshmen.  We explore how well-designed systems are built to withstand unpredictable stresses, whether that system is a building, a piece of software or even the human body.  The grant from Google is allowing us to add an overview of cloud computing as a platform that is robust under diverse loads.



Dr. Jiaofei Zhong, University of Central Missouri

Project description: By building an online Course Management System, students will be able to work on their team projects in the cloud.  The system allows instructors and students to manage the course materials, including course syllabus, slides, assignments and tests in the cloud; the tool can be shared with educational institutions worldwide.



-Posted by Andrea Held, Google University Relations







The App Engine team is continuing to make monthly improvements to our platform.  We have a number of new features and fixes for this month’s release.  



New App Engine billing system for paid applications





We’re making it easier to pay for App Engine each billing cycle by transitioning to a new billing system.  This change will happen automatically for billing-enabled applications, with no action required on your part.  With the new system you can now:



  • take advantage of monthly billing cycles



  • make a payment at any time during the month



  • specify direct debit as a form of payment



  • assign a primary and backup credit card







We’ll start moving applications to this new billing system over the next few weeks.  You don’t need to make any changes and the migration itself will be transparent.



Other notable features






  • Full Text Search API stats are now available in the admin console.  You can start viewing these stats in advance of being able to pay for additional search resources in an upcoming release.



  • We’ve added asynchronous methods, which is now in Preview, to the Task Queue API.  This feature improves utilization by allowing your app to add, lease and delete multiple tasks in parallel.



  • A major overhaul to the Python dev_appserver, the software used to simulate App Engine while in development. The new dev_appserver is multi-threaded, meaning development is faster, and provides a more accurate simulation of the production environment.



  • Admin console dashboard charts and current load/errors reports are moving to a new, more reliable backend over the next few weeks.



  • Improved support for Python libraries, with Django 1.4.2 and webob 1.2.3 now Generally Available.





The complete list of features and bug fixes for 1.7.6 can be found in our release notes. For App Engine coding questions and answers check us out on Stack Overflow, and for general discussion and feedback, find us on our Google Group.


-Posted by Chris Ramsdale, Product Manager









Today’s post comes from Doug Fritz from the Data Arts Team of the Google Creative Lab.  In this post, Doug shares a small open source project for reading and writing to the Google App Engine Datastore with JavaScript.





Today, the Google Creative Lab is sharing a small open source project called Tailbone that lets developers read and write to the Google App Engine Datastore using JavaScript. We’re hoping that it makes App Engine a bit more accessible to developers who aren’t familiar with Python, Java or Go, or prefer not to use them.



I share an office with three creative programmers who work almost entirely in HTML5 and JavaScript. An important part of our work is writing server-side code for new projects that read or write data to to the App Engine Datastore or use Google accounts to store authenticated user-specific information. To make that process easier for my JavaScript-fluent colleagues, I created Tailbone to act as a RESTful API for an app’s Datastore.











To get started, you still have to install App Engine’s SDK and Python, but after that you’re all set. We’ve written a detailed tutorial that guides you through the installation and an example app for creating an authenticated profile page with an editable name and photo.



It’s my hope that Tailbone makes App Engine a little bit less intimidating for people who don’t have much experience with server-side coding. I know there are a few in my office. If there are any others out there, this is for you.





-Posted by Doug Fritz, Creative Lab, Data Arts Team
Labels:





  • We will continue to run Python 2.5 applications throughout the deprecation period. For most customers, upgrading to Python 2.7 is trivial as most elements of Python 2.5 are forwards-compatible with Python 2.7. We’ve prepared a handy migration guide that covers the steps to migrate in detail.

  • If your application is still using the already deprecated Master/Slave Datastore, then you should first plan the migration to our more reliable High Replication Datastore, as the Master/Slave Datastore is not accessible from Python 2.7.

  • Future versions of the App Engine Python Development SDK will display warnings to developers deploying updates to a deprecated runtime.

  • Starting from January 2014, we will no longer allow new applications to be created using the Python 2.5 runtime.



Python 2.5 has a special place in the heart of any Google App Engine developer, as it was the first runtime we launched way back in 2008. Since then, both Python and App Engine have advanced a great deal.

A year ago we announced our support for Python 2.7, which brings syntactic and semantic improvements to the language and includes powerful features like threading and a large selection of third-party libraries.

Not only does Python 2.7 make developers’ lives easier, the runtime is extremely cost-effective. Our customers have taken advantage of features like concurrent requests to reduce their front-end instance costs by more than 70% while handling the same amount of traffic.

Not surprisingly, the Python 2.7 runtime has proven to be extremely popular. Just over a year after launch, more than 78% of active Python applications on App Engine are using the new runtime, and more are being added every minute.

As both Python and App Engine evolve, we must occasionally make hard choices about which legacy runtimes we should continue to support. Today we are announcing the deprecation of the Python 2.5 runtime. The deprecation period will follow the guidelines set in our terms of service.

What does this mean?


  • We will continue to run Python 2.5 applications throughout the deprecation period. For most customers, upgrading to Python 2.7 is trivial as most elements of Python 2.5 are forwards-compatible with Python 2.7. We’ve prepared a handy migration guide that covers the steps to migrate in detail.

  • If your application is still using the already deprecated Master/Slave Datastore, then you should first plan the migration to our more reliable High Replication Datastore, as the Master/Slave Datastore is not accessible from Python 2.7.

  • Future versions of the App Engine Python Development SDK will display warnings to developers deploying updates to a deprecated runtime.

  • Starting from January 2014, we will no longer allow new applications to be created using the Python 2.5 runtime.



We encourage all developers using Python 2.5 to consider migrating as soon as possible. We’re confident that the vast majority of our customers will find the upgrade straightforward and the benefits substantial.

If you’re considering migrating, here are some useful resources:


If you have any questions about this deprecation, we encourage you to contact us at google-appengine-python25-deprecation@googlegroups.com.

-Posted by Andrew Jessup, Product Manager