App Engine 1.6.4 Released
March 27th, 2012 | Published in Uncategorized, Google App Engine
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
Runtime Changes
Datastore Framework Changes
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.
- Posted by the App Engine Team
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.
- Serve objects from Google Cloud Storage - You can now serve blobs directly from Google Cloud Storage as well as Blobstore.
Runtime Changes
- 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.
- Posted by the App Engine Team