Google PaaS Updates App Engine Modules

Google Cloud Platform continues to roll out consistent updates to its App Engine Platform-as-a-service (PaaS). Its  latest release, version 1.9.0, makes available App Engine Modules, which aims to help developers break their applications into logical components to bring significant efficiency to both cost and performance. The update also includes a MapReduce library for Java and several PHP Runtime improvements.

App Engine Modules allows a developer to factor large applications into logical components or modules and to address different functionalities such as Front-end APIs or long-running Back-end tasks. The Modules feature now has General Availability status, and it allows uses to not only refactor modules based on the Function they have to perform, but also to run different versions, instance types and their own performance settings. The Modules feature greatly improves the ability to manage these modules and, at the same time, helps reduce costs and boost performance in areas where you really want it.

All Modules within a given application can communicate with each other securely and share various App Engine services like Datastore, Memcache and Task Queues. Refer to the App Engine Modules docs (JavaPython) and samples (Java | Python).

Several customers of App Engine Modules have been using the MapReduce libraries to perform intensive data-processing tasks. To make setting up such implementations easier within the Google Cloud Platform, a preview release of MapReduce library for Java is available, which integrates seamlessly with  Google Cloud Storage. Check out this blog post that shows how, if you use Apache Hive with Hadoop, you can connect the Hive relational database to an existing Google Cloud SQL instance itself, thereby removing the need to manage your own SQL instances elsewhere.

The PHP SDK now supports autoloading, resulting in a fewer number of libraries and a faster start-up time. PHP Integration with Google Cloud Storage has also been enhanced with additional methods and improved security around inclusion of code fragments from a specific directory of a cloud storage bucket.

In related news about Google Cloud Platform, the team has made available Google Cloud Platform Calculator, a simple form for calculating the total cost of deploying your application on Google Cloud Platform. Currently, it provides estimates for Compute Engine, Cloud Storage and Cloud SQL. When you are a developer on the platform, it definitely helps you to understand the costs before jumping into your cloud implementation.

For more information on App Engine Release 1.9.0, refer to the release notes for the respective run times.

Be sure to read the next Mapping article: Mapbox Adds Smart Directions to its Mapping Platform