The Google Cloud Platform announcements made at the Google I/O 2014 developers conference include a raft of new tools and services aimed at helping with data handling, application development and more.
One of the key tools unveiled so far is Google Cloud Dataflow, which is seen by Google as a successor to the popular MapReduce service, Greg DeMichillie, director of product management for the Google Cloud Platform, wrote in a June 25 posting on the Google Cloud Platform Blog. Cloud Dataflow, which was demonstrated publicly here for the first time, is a managed service that developers can use to create data pipelines that analyze data in both batch and streaming modes, wrote DeMichillie.
"A decade ago, Google invented MapReduce to process massive data sets using distributed computing," he wrote. "Since then, more devices and information require more capable analytics pipelines—though they are difficult to create and maintain."
That's where Cloud Dataflow will help, he wrote."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."
Another key new tool introduced at the event is Google Cloud Monitoring, which can help users find and fix unusual behaviors across their application stacks, wrote DeMichillie. "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."
One of the included tools, Cloud Trace, can help users isolate the root cause of performance bottlenecks by giving users a visual picture of how much time an application is performing request processing, he wrote, while also allowing users to compare performance between various releases of their application using latency distributions.
A Cloud Debugger tool is also being introduced to help debug applications in production with minimal performance overhead, wrote DeMichillie. "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."
Features aimed at helping developers ready their applications for mobile users are also included in the new tools. At the conference, Google demonstrated a beta version of Google Cloud Save, an API used for saving, retrieving and synchronizing user data to the cloud and across devices without needing to code up the backend, he wrote. "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."
New tools have also been added to Android Studio, "which simplifies the process of adding an App Engine backend to your mobile app," wrote DeMichillie. The improvements now give Android Studio three built-in App Engine backend module templates, including Java Servlet, Java Endpoints and an App Engine backend with Google Cloud Messaging, he wrote. "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."