One of the most rewarding things about working on App Engine is watching our customers use the platform in new and unexpected ways. We're lucky to have a front row seat to the growth and success of so many innovative new projects, and in that spirit, we are pleased to announce the Google App Engine Research Awards.
This new awards program will support 15 projects by providing App Engine credits in the amount of $60,000 to each project for one year, additional Google services such as Google Cloud Storage will be coming soon as part of the program.
We are committed to supporting scientific and academic research and welcome university faculty from all fields to participate. Award projects may focus on activities such as social or economic experiments, developing academic aids, analysis of gene sequence data, or using App Engine MapReduce in ways we hadn’t even considered! If your research has the potential to advance discovery, generates heavy data loads or is in need of an easy-to-use, easy-to-scale platform, we encourage you to submit your proposal.
You can find details on how to apply on our Google Research website. Applications will be accepted until 11:59 p.m. PST, May 11, 2012.
Go is a statically typed, compiled language with a dynamic and lightweight feel. With Go you get the efficiency benefits of being close to the machine–your programs compile to native code–with the productivity and quick turnaround of a scripting language. Go apps are easy to write, start fast, and run fast. There has never been a better way to build scalable high-performance cloud applications.
The Go runtime provides clean, idiomatic Go APIs for the popular App Engine services (Blobstore, Datastore, Memcache, and so on) and a straightforward development process. As with the Python and Java SDKs, Go apps can be tested locally with the development server and, most convenient, the development server automatically compiles your Go code, so to test a change all you need to do is to refresh your browser.
The Go 1 SDK also brings improvements and bug fixes. It uses the new Go 1 time API throughout the SDK, provides a MultiError type for error handling in batch operations, and supports Datastore Cursors and the XMPP and Log services. See the release notes for the details.
Although the Go App Engine runtime is still in experimental status for now, the language stability offered by Go 1 is a major milestone. To learn more about Go 1, see the announcement post at the Go blog and the wealth of documentation at golang.org.Read More
Today, with the release of Go 1, a stable version of the Go language, libraries and tools, we're releasing a new Google App Engine SDK for the Go runtime.
Go is a statically typed, compiled language with a dynamic and lightweight feel. With Go you get the efficiency benefits of being close to the machine–your programs compile to native code–with the productivity and quick turnaround of a scripting language. Go apps are easy to write, start fast, and run fast. There has never been a better way to build scalable high-performance cloud applications.
The Go runtime provides clean, idiomatic Go APIs for the popular App Engine services (Blobstore, Datastore, Memcache, and so on) and a straightforward development process. As with the Python and Java SDKs, Go apps can be tested locally with the development server and, most convenient, the development server automatically compiles your Go code, so to test a change all you need to do is to refresh your browser.
The Go 1 SDK also brings improvements and bug fixes. It uses the new Go 1 time API throughout the SDK, provides a MultiError type for error handling in batch operations, and supports Datastore Cursors and the XMPP and Log services. See the release notes for the details.
Although the Go App Engine runtime is still in experimental status for now, the language stability offered by Go 1 is a major milestone. To learn more about Go 1, see the announcement post at the Go blog and the wealth of documentation at golang.org.
App Engine’s march of progress continues with another release that’s full of new features, system improvements, and bug fixes. As we spring forward into pre-Google I/O season, we’re keeping our focus on product polish and this release is a shining example.
App Engine’s march of progress continues with another release that’s full of new features, system improvements, and bug fixes. As we spring forward into pre-Google I/O season, we’re keeping our focus on product polish and this release is a shining example.
System Wide Changes
Logs - Now that the new settings for log storage have been available for one month, logs over the limit you specify will be deleted.
Datastore Index Stats - The Datastore Statistics page in the Admin Console now displays the storage used by your Datastore Indexes in addition to your Datastore Entities.
Blobstore Migration - The Datastore Migration tool now includes an experimental option which allows you to migrate your Blobstore objects during the migration process from M/S to HRD. We strongly encourage all applications to migrate to HRD.
Datastore Backup to Google Cloud Storage - In 1.6.3, we launched backup and restore to Blobstore, and in this release we’ve added the ability to backup your data to Google Cloud Storage.
Memcache viewer - We’ve introduced the ability to view Memcache statistics and examine memcache entries by key.
Threads - Both Java and Python now offer background threads when running on backends as an experimental feature. Additionally, we’ve added the ability to use threads for frontend requests in Java to match Python 2.7.
Datastore Framework Changes
NDB for Python - The NDB API has graduated from experimental and is now a fully supported feature. This next-generation datastore API improves data modeling and querying and has been built from the ground up to support an asynchronous computing model.
JPA 2 and JDO 3 for Java - We have made significant improvements to App Engine’s DataNucleus plugin. This experimental release of version 2.0 of the plugin adds support for JPA 2, JDO 3, and contains over 40 bug fixes. Check out the full release notes here.
And that’s not all, you can read about all the new features and bug fixes in our release notes (Python, Java). Send all your feedback to our Google Group, and if you have coding questions, find help from us and other talented developers on Stack Overflow.
One of the best things about App Engine is our lively developer community. This week, we’re officially moving technical and development questions to Stack Overflow and retiring the language-specific App Engine Google groups. With this week’s move, we wanted to take a moment to highlight some of the best ways to engage with the community.
Technical & Development Questions For technical and development questions big and small, add the google-app-engine tag to your App Engine questions on Stack Overflow. You can also join our hangouts or office hours to talk directly with App Engine team members. Google+ Many community and team members are active on Google+, using the #appengine hashtag. Our weekly community updates and chats with App Engine community and team members are a great source of tips and tricks and to learn more about what ourcommunity membersare up to.
One of the best things about App Engine is our lively developer community. This week, we’re officially moving technical and development questions to Stack Overflow and retiring the language-specific App Engine Google groups. With this week’s move, we wanted to take a moment to highlight some of the best ways to engage with the community.
Technical & Development Questions For technical and development questions big and small, add the google-app-engine tag to your App Engine questions on Stack Overflow. You can also join our hangouts or office hours to talk directly with App Engine team members. Google+ Many community and team members are active on Google+, using the #appengine hashtag. Our weekly community updates and chats with App Engine community and team members are a great source of tips and tricks and to learn more about what ourcommunity membersare up to.
Although we can’t reliably compare its future-predicting abilities to a crystal ball, the Google Prediction API unlocks a powerful mechanism to use machine learning in your applications.
The Prediction API allows developers to train their own predictive models, taking advantage of Google’s world-class machine learning algorithms. It can be used for all sorts of classification and recommendation problems from spam detection to message routing decisions. In the latest release, the Prediction API has added more detailed debugging information on trained models and a new App Engine sample, which illustrates how to use the Google Prediction API for the Java and Python runtimes.
To help App Engine developers get started with the prediction API, we’ve published an article and walkthrough detailing how to create and manage predictive models in App Engine apps with simple authentication using OAuth2 and service accounts. Check out the walkthrough and let us know what you think on the group. Happy coding!
Although we can’t reliably compare its future-predicting abilities to a crystal ball, the Google Prediction API unlocks a powerful mechanism to use machine learning in your applications.
The Prediction API allows developers to train their own predictive models, taking advantage of Google’s world-class machine learning algorithms. It can be used for all sorts of classification and recommendation problems from spam detection to message routing decisions. In the latest release, the Prediction API has added more detailed debugging information on trained models and a new App Engine sample, which illustrates how to use the Google Prediction API for the Java and Python runtimes.
To help App Engine developers get started with the prediction API, we’ve published an article and walkthrough detailing how to create and manage predictive models in App Engine apps with simple authentication using OAuth2 and service accounts. Check out the walkthrough and let us know what you think on the group. Happy coding!
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