Today at Google I/O, we are introducing new services that help developers build and optimize data pipelines, create mobile applications, and debug, trace, and monitor their cloud applications in production.

Introducing Google Cloud Dataflow
A decade ago, Google invented MapReduce to process massive datasets using distributed computing. Since then, more devices and information require more capable analytics pipelines — though they are difficult to create and maintain.

Today at Google I/O, we are demonstrating Google Cloud Dataflow for the first time. Cloud Dataflow is a fully managed service for creating data pipelines that ingest, transform and analyze data in both batch and streaming modes. Cloud Dataflow is a successor to MapReduce, and is based on our internal technologies like Flume and MillWheel.

Cloud Dataflow makes it easy for you to get actionable insights from your data while lowering operational costs without the hassles of deploying, maintaining or scaling infrastructure. You can use Cloud Dataflow for use cases like ETL, batch data processing and streaming analytics, and it will automatically optimize, deploy and manage the code and resources required.

Debug, trace and monitor your application in production
We are also introducing several new Cloud Platform tools that let developers understand, diagnose and improve systems in production.

Google Cloud Monitoring is designed to help you find and fix unusual behavior across your application stack. Based on technology from our recent acquisition of Stackdriver, Cloud Monitoring provides rich metrics, dashboards and alerting for Cloud Platform, as well as more than a dozen popular open source apps, including Apache, Nginx, MongoDB, MySQL, Tomcat, IIS, Redis, Elasticsearch and more. For example, you can use Cloud Monitoring to identify and troubleshoot cases where users are experiencing increased error rates connecting from an App Engine module or slow query times from a Cassandra database with minimal configuration.

We know that it can be difficult to isolate the root cause of performance bottlenecks. Cloud Trace helps you visualize and understand time spent by your application for request processing. In addition, you can compare performance between various releases of your application using latency distributions.

Finally, we’re introducing Cloud Debugger, a new tool to help you debug your applications in production with effectively no performance overhead. Cloud Debugger gives you a full stack trace and snapshots of all local variables for any watchpoint that you set in your code while your application continues to run undisturbed in production. This brings modern debugging to cloud-based applications.

New features for mobile development
With rapid autoscaling, caching and other mobile friendly capabilities, many apps like Snapchat or Rising Star have built and run on Cloud Platform. We’re adding new features that make building a mobile app using Cloud Platform even better.

Today, we’re demonstrating a new version of Google Cloud Save, which gives you a simple API for saving, retrieving, and synchronizing user data to the cloud and across devices without needing to code up the backend. Data is stored in Google Cloud Datastore, making the data accessible from Google App Engine or Google Compute Engine using the existing Datastore API. Google Cloud Save is currently in private beta and will be available for general use soon.

We’ve also added tooling to Android Studio, which simplifies the process of adding an App Engine backend to your mobile app. In particular, Android Studio now has three built-in App Engine backend module templates, including Java Servlet, Java Endpoints and an App Engine backend with Google Cloud Messaging. Since this functionality is powered by the open-source App Engine plug-in for Gradle, you can use the same build configuration for both your app and your backend across IDE, CLI and Continuous Integration environments.

We’ll be doing more detailed follow-up posts about these announcements in the coming days, so stay tuned.

-Posted by Greg DeMichillie, Director of Product Management

*Apache, Nginx, MongoDB, MySQL, Tomcat, IIS, Redis, Elasticsearch and Cassandra are trademarks of their respective owners.