Today, we’re releasing version 1.3.8 of the App Engine SDK. Whether you’re a Java or a Python developer, this release includes several exciting new features for improving monitoring, performance, and maintenance tasks.
This release includes a new page in the Admin Console, called the Instances page. This page allows you to view information about all server instances currently in use by your application. This information can be useful in debugging your application and also understanding its performance characteristics. There’s no configuration needed for this feature. Just click the “Instances” link on the left hand navigation of the Admin Console to see Average QPS, latency, and memory for an instance.
This release also has a couple new Task Queue features: First, the maximum bucket size that you can specify during queue configuration is now 100, up from 50. Second, we’ve added a new "Run Now" button to the Task Queues section of the Admin Console that enables developers to run a task immediately. This can be very helpful for debugging your tasks in production.
This release contains a new feature for Python apps: builtin handlers that allow you to quickly and easily enable standard functionality in your application without adding additional code to your codebase. The libraries available today are remote_api, appstats, and the datastore_admin feature (see below). For example, to use the remote_api with your application, simply add the following to your app.yaml file:
remote_api
appstats
datastore_admin
app.yaml
builtins:- remote_api: on
If you are already using the remote api endpoint your app, you can choose to remove the entry in the handlers section of your app.yaml and use the above directive instead to simplify your app.yaml file.
Support for builtin handlers is not yet available for Java applications, but will be available in an upcoming release.
Note: this feature is currently only available by default for Python; see the note below for ways to use it with Java application.
Today, we are releasing an experimental addition to the admin console which provides a simple UI for delete all entities, or all entities of a given kind, in your datastore. To enable this functionality, simply enable the following builtin in your app.yaml file:
builtins:- datastore_admin: on
Adding these lines to app.yaml enables the “Datastore Admin” page in your app’s Admin Console, where you can see all of the entity types you are able to delete:
Be aware that these deletes are issued by your application (you can read about how the handler works by looking at this code file in the SDK). For this reason, your application will use resources, most significantly CPU, for the deletions you issue which will count towards your application’s daily resource budget.
Datastore delete is currently available only with the Python runtime. Java applications, however, can still take advantage of this feature by creating a non-default Python application version that enables Datastore Admin in the app.yaml. Native support for Java will be included in an upcoming release.
Finally, the python pre-compilation feature we announced in 1.3.5 is now turned on for all new python application uploads using the 1.3.8 SDK by default. If you wish to disable this feature, just specify the flag --no-precompilation on the appcfg.py command line when uploading your app.
--no-precompilation
appcfg.py
This release also contains a few more small features and bug fixes. You can read about the full release in our release notes in Python and Java. As always, your feedback in the forums is appreciated (and had a significant influence on this release!).
Why are java developers treated like step children? :(I don't even know how to create a non-default python project for deleting all data.
Does clearing the data also clear the memcache? If not can we please have a way to do that as well.
Great features.
Why are java developers treated like step children? :(
ReplyDeleteI don't even know how to create a non-default python project for deleting all data.
Does clearing the data also clear the memcache? If not can we please have a way to do that as well.
ReplyDeleteGreat features.
ReplyDelete