How to mix and match web services, batch processing pipelines, mobile deployments and data analysis

Do you need an environment that seamlessly scales to meet demand? Do multiple teams develop your app using a variety of programming languages? Do you need to mix managed applications and self-serve virtual machines running a variety of separate services? Google Cloud Platform has you covered on all fronts.



Take a look at our latest paper to learn how to overcome the challenges of deploying large applications in Cloud Platform. Our paper discusses a solution that shows how to use the right tools for:

• Different developer expertise


• Different data storage requirements


• Interactive and batch processing requirements


• Custom analysis engines


• Logically separate business components

Our paper walks through a real-world scenario of building a video sharing community. In this scenario, users upload videos from a mobile phone, the content is transcoded for playback in multiple formats and is presented on a web community site for watching and commenting.

Our sample solution showcases Google App Engine applications written in PHP, Java and Python. We use Google Cloud SQL for storing video metadata, to capitalize on the popularity and reduced learning curve of MySQL, and we store the videos in Google Cloud Storage for speed and scalability. The mobile client is written in Java and runs on Android. Hadoop clusters running on Google Compute Engine analyze and add sentiments to users' comments. And the whole shebang is orchestrated by another App Engine application. To learn how to build a solution like this yourself, get started now by reading all about it.



-Posted by Brian Lynch, Solutions Architect