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Seo Master present to you:
By Navneet Joneja, Product Manager

Cross-posted from the Google Cloud Platform Blog

Last year we announced Google Compute Engine to enable any business or developer to use Google’s infrastructure for their applications. Now we’re taking the next step: Google Compute Engine is open to everyone in preview, and you can sign up online now.

Over the past year, we’ve launched several features and made significant improvements behind the scenes. We’re now announcing several new capabilities that make it easier and more economical to use Compute Engine for a broader set of applications.

• Sub-Hour Billing: We heard feedback from our early users who wanted more granular billing increments so they could run short-lived workloads. Now all instances are charged for in one-minute increments with a ten-minute minimum, so you don’t pay for compute minutes that you don’t use.
• New shared-core instance types: Compute Engine’s new micro and small instance types are designed as a cost-effective option for running small workloads that don’t need a lot of CPU power, like development and test workloads.
• Larger Persistent Disks: We’re increasing the size of Persistent Disks that can be attached to instances by up to 8,000%. You can now attach up to 10 terabytes of persistent disk to a Compute Engine virtual machine, giving you plenty of persistent storage for a wide variety of applications.
• Advanced Routing Capabilities: Compute Engine now supports software-defined routing capabilities based on our broad SDN innovation. These capabilities are designed to handle your advanced network routing needs like configuring instances to function as gateways, configuring VPN servers and building applications that span your local network and Google’s cloud.
• ISO 27001 Certification: We’ve also completed ISO 27001:2005 certification for Compute Engine, App Engine, and Cloud Storage to demonstrate that these products meet the international standard for managing information security.

To get started, go to the Google Cloud Console, select Compute Engine and click the “New Instance” button.

Fill out the required information and click “Create” on the right hand side. Your new virtual machine will be ready to use in about a minute.

To all of our customers who helped us evolve the product over the past months, thank you; your feedback has helped shape Compute Engine. To those of you who have been eager to try Compute Engine, the wait is over and you can sign up for Compute Engine online today.


Navneet Joneja loves being at the forefront of the next generation of simple and reliable software infrastructure, the foundation on which next-generation technology is being built. When not working, he can usually be found dreaming up new ways to entertain his intensely curious three-year-old.

Posted by Scott Knaster, Editor

2013, By: Seo Master

Seo Master present to you:
By Urs Hölzle, Senior Vice President, Technical Infrastructure, and Google Fellow

Cross-posted from the Google Cloud Platform Blog

Watch the video of the Cloud track kickoff.

Over the last fourteen years we have been developing some of the best infrastructure in the world to power Google’s global-scale services. With Google Cloud Platform, our goal is to open that infrastructure and make it available to any business or developer anywhere. Today, we are introducing improvements to the platform and making Google Compute Engine available for anyone to use.

Google Compute Engine - now available for everyone

Google Compute Engine provides a fast, consistently high-performance environment for running virtual machines. Later today, you’ll be able to go online to cloud.google.com and start using Compute Engine.

In addition, we’re introducing new Compute Engine features:

• Sub-hour billing charges for instances in one-minute increments with a ten-minute minimum, so you don’t pay for compute minutes that you don’t use
• Shared-core instances provide smaller instance shapes for low-intensity workloads
• Advanced Routing features help you create gateways and VPN servers, and enable you to build applications that span your local network and Google’s cloud
• Large persistent disks support up to 10 terabytes per volume, which translates to 10X the industry standard

We’ve also completed ISO 27001:2005 international security certification for Compute Engine, Google App Engine, and Google Cloud Storage.

Google App Engine adds the PHP runtime

App Engine 1.8.0 is now available and includes a Limited Preview of the PHP runtime - your top requested feature. We’re bringing one of the most popular web programming languages to App Engine so that you can run open source apps like WordPress. It also offers deep integration with other parts of Cloud Platform including Google Cloud SQL and Cloud Storage.

We’ve also heard that we need to make building modularized applications on App Engine easier. We are introducing the ability to partition apps into components with separate scaling, deployments, versioning and performance settings.

Introducing Google Cloud Datastore

Google Cloud Datastore is a fully managed and schemaless solution for storing non-relational data. Based on the popular App Engine High Replication Datastore, Cloud Datastore is a standalone service that features automatic scalability and high availability while still providing powerful capabilities such as ACID transactions, SQL-like queries, indexes and more.

Over the last year we have continued our focus on feature enhancement and developer experience across App Engine, Compute Engine, Google BigQuery, Cloud Storage and Cloud SQL. We also introduced Google Cloud Endpoints and Google Cloud Console.

With these improvements, we have seen increased usage with over 3 million applications and over 300,000 unique developers using Cloud Platform in a given month. Our developers inspire us everyday, and we can’t wait to see what you build next.


Urs Hölzle is Senior Vice President of Technical Infrastructure and Google Fellow. As one of Google's first ten employees and its first VP of Engineering, he has shaped much of Google's development processes and infrastructure.

Posted by Scott Knaster, Editor

2013, By: Seo Master

Seo Master present to you: By Michael Manoochehri, Developer Programs Engineer, Google Cloud Platform

Cross-posted with the Google Cloud Platform Blog

After last year's Google I/O conference, the Google Cloud Platform Developer Relations team started to think about how attendees experienced the event. We wanted to help attendees gain more insight about the conference space and the environment itself. Which developer Sandboxes were the busiest? Which were the loudest locations, and which were the best places to take a quick nap? We think about data problems all the time, and this looked like an interesting big data challenge that we could try to solve. So this year, we decided to try to answer our questions with a project that's a bit different, kind of futuristic, and maybe a little crazy.

Since we love open source hardware hacking as much as we love to share open source code, we decided to team up with the O'Reilly Data Sensing Lab to deploy hundreds of Arduino-based environmental sensors at Google I/O 2013. Using software built with the Google Cloud Platform, we'll be collecting and visualizing ambient data about the conference, such as temperature, humidity, air quality, in real time! Altogether, the sensors network will provide over 4,000 continuous data streams over a ZigBee mesh network managed by Device Cloud by Etherios.

In addition, our motes will be able to detect fluctuations in noise level, and some will be attached to footstep counters, to understand collective movement around the conference floor. Of course, since a key goal of Google I/O is to promote innovation in the open, the project's Cloud Platform code, the Arduino hardware designs, and even the data collected, will be open source and available online after the conference.

Google Cloud Platform, which provides the software backend for this project, has a variety of features for building applications that collect and process data from a large number of client devices - without having to spend time managing hardware or infrastructure. Google App Engine Datastore, along with Cloud Endpoints, provides a scalable front end API for collecting data from devices. Google Compute Engine is used to process and analyse data with software tools you may already be familiar with, such as R and Hadoop. Google BigQuery provides fast aggregate analysis of terabyte datasets. Finally, App Engine's web application framework is able to surface interactive visualizations to users.

Networked sensor technology is in the early stages of revolutionizing business logistics, city planning, and consumer products. We are looking forward to sharing the Data Sensing Lab with Google I/O attendees, because we want to show how using open hardware together with the Google Cloud Platform can make this technology accessible to anyone.

With the help of the Google Maps DevRel team, we'll be displaying visualizations of interesting trends on several screens around the conference. Members of the Data Sensing Lab will be on hand in the Google I/O Cloud Sandbox to show off prototypes and talk to attendees about open hardware development. Lead software developer Amy Unruh and Kim Cameron from the Cloud Platform Developer Relations team will talk about how we built the software involved in this project in a talk called "Behind the Data Sensing Lab". In case you aren't able to attend Google I/O 2013, this session will be available online after the conference. Learn more about the Google Cloud Platform on our site, and to dive in to building applications, check out our developer documentation.


Michael Manoochehri is a Developer Programs Engineer supporting the Google Cloud Platform. He is passionate about making cloud computing and data analysis universally accessible and useful.

Posted by Scott Knaster, Editor

2013, By: Seo Master

Seo Master present to you: By Marc Cohen, Google Cloud Platform team

Cross-posted with the Google App Engine blog

Starting today, Google Compute Engine is available to all customers who sign up for our Gold Support package. We’re also happy to announce a 4% reduction on all Compute Engine pricing.

In the nine months since announcing Compute Engine, customers have been using Google’s Infrastructure as a Service product and giving us valuable feedback. Sebastian Stadil of Scalr wrote, in a recent review:

“Google Compute Engine is not just fast. It’s Google fast. In fact, it’s a class of fast that enables new service architectures entirely.”

We’re happy to hear that, because one of our main goals in building Compute Engine is to enable a new generation of applications with direct access to the capabilities of Google’s vast computing infrastructure.

Based on user feedback, we’ve added a number of major features including:

• The option to boot from persistent disks mounted as the root file system, persistent disk snapshots, the ability to checkpoint and restore the contents of network resident persistent disks on demand, and the ability to attach and detach persistent disks from running instances.
• An improved administration console, the Google Cloud Console (preview), which allows you to administer all your Google Cloud Platform services via a unified interface. Here’s a screenshot of the new Cloud Console in action:
  
  
• Five new instance type families (diskless versions of our standard instance types, plus diskful and diskless versions of high-memory and high-cpu configurations), with 16 new instance types.
• Two new supported zones in Europe, which provide lower latency and higher performance for our European customers. We’ve also made it easy to migrate virtual machine instances from one zone to another via an enhancement to our gcutil command line tool.
• An enhanced metadata server, with the ability to support recursive queries, blocking gets and selectable response formats, along with support for updating virtual machine tags and metadata on running instances (which enables dynamic reconfiguration scenarios).

While we've been hard at work developing new features, we've also had the opportunity to play. Check out the amazing World Wide Maze Chrome Experiment, developed by the Chrome team in Japan. This game converts any web site of your choice into an interactive, three dimensional maze, navigated remotely via your smartphone. Compute Engine virtual machines run Node.js to manage the game state and synchronization with the mobile device, while Google App Engine hosts the game’s web UI. This application provides an excellent example of the new kinds of rich, high performance back end services enabled by Google Cloud Platform.

With today’s announcement, we look forward to welcoming many new customers, and bringing exciting new applications to Google Cloud Platform!

Marc Cohen is a Developer Programs Engineer focusing on helping developers get the most out of Google’s advanced cloud computing technologies. He has over 25 years of experience designing and building reliable, distributed systems in the telecommunications industry. A Seattle resident, Marc enjoys programming, indie pop/rock music, blogging and teaching.

Posted by Ashleigh Rentz, Editor Emerita

2013, By: Seo Master

Seo Master present to you: By Robert Do, Google Cloud Platform team

Cross-posted from the Google App Engine blog

Have you ever wanted to integrate SMS or voice communications into your app? We’ve been working with our friends over at Twilio to make it easier to do so. Today we’re announcing native Python and Java libraries for working with Twilio APIs onto Google Cloud Platform.

Lots of apps on App Engine have already been built with phone functionality. Check out the sample code for a group messaging app and the sample code for an app that dispatches voicemails and SMS messages to PagerDuty. Learn how to send business cards via sms through this step by step guide.

You can start building voice and SMS features into your App Engine apps today. Together with Twilio, we’ll help you get started with 2,000 free text message or voice minutes.

Ready to get started?

1. Sign up for App Engine.
2. Get your Twilio account and 2,000 free text message or voice minutes.
3. Check out our guide on how to integrate Twilio services into your app.

Here’s a quick peek at how easy it can be to send a text message from App Engine using Python. After installing the Twilio library, it just takes a few lines of code to send an SMS.

import webapp2
from twilio import twiml
from twilio.rest import TwilioRestClient
class SendSMS(webapp2.RequestHandler):
   def get(self):
       # replace with your credentials from: https://www.twilio.com/user/account
       account_sid = "ACxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
       auth_token = "xxxxxxxxxxxxxxxxxxxxxxxxxx"
       client = TwilioRestClient(account_sid, auth_token)
       # replace "to" and "from_" with real numbers
       rv = client.sms.messages.create(to="+14155551212",
                                       from_="+14085551212",
                                       body="Hello Monkey!")
       self.response.write(str(rv))
app = webapp2.WSGIApplication([('/send_sms', SendSMS)],
                             debug=True)

Posted by Ashleigh Rentz, Editor Emerita2013, By: Seo Master

Seo Master present to you:
By Michael Manoochehri, Developer Programs Engineer, Cloud Platform

Google BigQuery is designed to make it easy to analyze large amounts of data quickly. Overwhelmingly, developers have asked us for features to help simplify their work even further. Today we are launching a collection of updates that gives BigQuery a greater range of query and data types, more flexibility with table structure, and better tools for collaborative analysis.

Big JOIN and Big Group Aggregations

Extracting insights from multiple datasets can be challenging and time-consuming. This is especially true when datasets become too large to query with a traditional database system. With traditional databases, SQL functions like joining and grouping are typically used to bring together data for analysis. What happens when your data is too large to fit into a conventional database? Working with multi-terabyte datasets often requires developing complicated MapReduce workflows, investing in expensive infrastructure, and great deal of time. Very often, it's a combination of all three.

In response to developer feedback, we're launching new features that enable analysts and developers to run fast SQL-like join and aggregate queries on datasets without the need for batch-based processing. Our new Big JOIN feature gives users the ability to produce a result set by merging data from two large tables by a common key. Big JOIN simplifies data analysis that would otherwise require a data transformation step, by allowing users to specify JOIN operations using SQL.

Popular web applications produce user activity logs that can grow by billions of rows each week. Dividing users into smaller groups is a key step for analysis. However, each group of users can number in the millions. To handle this for such large volumes, we've enabled Big Group Aggregations, which significantly increases the number of distinct values that can be grouped in a result set.

To use these new features, simply add the EACH modifier to JOIN or GROUP BY clauses.



For more information, including best practices, when using JOIN EACH and GROUP EACH BY, visit the BigQuery query reference.

Native support for TIMESTAMP data type

We are also adding a new TIMESTAMP data type, in response to one of our most frequent requests from developers. This new data type lets you import date and time values in formats familiar to users of databases such as MySQL, while preserving timezone offset information.

Along with the new data type come new functions for converting TIMESTAMP fields into other formats, calculating intervals, and extracting components such as the hour, day of week, and quarter.



Read more about the available TIMESTAMP functions in our query reference guide.

Add columns to existing BigQuery tables

When working with large amounts of fast moving data, it's not uncommon to find out that you need to add additional fields to your tables. In response to developer feedback, we have added the ability to add new columns to existing BigQuery tables.

To take advantage of this feature, simply provide a new schema with additional columns using either the "Tables: update" or "Tables: patch" BigQuery API methods.

For more information on this feature, visit the BigQuery API reference.

BigQuery Web UI: Dataset links and dataset sharing notifications

BigQuery has always provided project owners with very fine-grained control of how their datasets are shared. To make it easier for teams to work on collaborative data analysis, we've added direct links to individual datasets in the BigQuery Web UI. This provides a convenient way for authorized users to quickly access a dataset, and allows for bookmarking and sharing.

In addition, we've also added email notifications to inform users when they've been given dataset access privileges. When a dataset has been shared with another user via the sharing control panel, BigQuery sends a notification email containing a direct link to the dataset.


The BigQuery UI features a collection of public datasets for you to use when trying out these new features. To get started, visit our sign up page and Quick Start guide. You should take a look at our API docs, and ask questions about BigQuery development on Stack Overflow. Finally, don't forget to give us feedback and join the discussion on our Cloud Platform Developers Google+ page.


Michael Manoochehri is a Developer Programs Engineer supporting the Google Cloud Platform. His goal is to help make cloud computing and data analysis universally accessible and useful.

Posted by Scott Knaster, Editor

2013, By: Seo Master

Seo Master present to you: By Brett McCully, Google Cloud Platform Team

(Cross-posted with the App Engine and Enterprise Blogs)

Support is as important as product features when choosing a platform for your applications. And let’s face it, sometimes we all need a bit of help. No matter which Google Cloud Platform services you are using — App Engine, Compute Engine, Cloud Storage, Cloud SQL, BigQuery, etc. — or what time of day, you should be able to get the answers you need. While you can go to Stack Overflow or Google Groups, we realize some of you may need 24x7 coverage, phone support or direct access to a Technical Account Manager team.

To meet your support requirements, we’re introducing a comprehensive collection of support packages for services on Google Cloud Platform, so you can decide what level best fits your needs:

• Bronze: All customers get access to online documentation, community forums, and billing support. (Free)
• Silver: In addition to Bronze, you can email our support team for questions related to product functionality, best practices, and service errors. ($150/month)
• Gold: In addition to Silver, you'll receive 24x7 phone support and consultation on application development, best practices or architecture for your specific use case. (Starts at $400/month)
• Platinum: The most comprehensive and personalized support. In addition to Gold, you’ll get direct access to a Technical Account Manager team. (Contact Sales for more information)

Sign up or click here to find out more information about the new Google Cloud Platform support options.

Brett McCully is the Manager of the Google Cloud Platform Support team and is currently based in Seattle.

Posted by Ashleigh Rentz, Editor Emerita

2013, By: Seo Master

Seo Master present to you: By Brad Abrams, Google Cloud Platform Team
(Cross-posted with the Google App Engine Blog)
Today we are announcing two new preview features: App Engine Java 7 runtime support and Google Cloud Endpoints.   Preview features are ‘experimental’ features on a path towards general availability.

Java 7 Runtime Support for App Engine

The App Engine Java 7 runtime allows App Engine developers to keep pace with innovations in the Java language and runtime. It is important that you begin testing your applications with the new Java 7 runtime before the complete rollout in a few months.
Some of the language features you now have access to include:
invokedynamic support, which allows developers, tools providers, and language implementations to take advantage of a new bytecode, invokedynamic, to handle method invocations efficiently even when there is no static type information. For example:

  public static void invokeExample() {
    String s;
    MethodType mt; 
    MethodHandle mh;

    MethodHandles.Lookup lookup = MethodHandles.lookup();
    MethodType mt = MethodType.methodType(String.class, char.class,
                                          char.class);
    MethodHandle mh = lookup.findVirtual(String.class, "replace", mt);
    s = (String) mh.invokeExact("App Engine Java 6 runtime",'6','7');
    System.out.println(s);
  }

Try-with-resources, which helps avoid memory leaks and related bugs by automatically closing resources that are used in a try-catch statement.

  public static void viewTable(Connection con, String query) throws SQLException {

   try (
Statement stmt = con.createStatement();
ResultSet rs = stmt.executeQuery(query)
) {
      while (rs.next()) {
      // process results
      //
      }
   } catch (SQLException e) {
      // con resource is auto-closed, no need to do anything here!
      //
   }
}

Flexible Type Creation when using generics, enabling you to create parameterized types more succinctly. For example, you can write:

  Map<String, List<String>> myMap = new HashMap<>();

instead of:

Map<String, List<String>> myMap = new HashMap<String, List<String>>();

In addition to the language features listed above, the App Engine Java 7 runtime also includes:

• Use of String class in Switch statements.
• Expression of binary literals using simple prefixes 0b or 0B.
• Single catch blocks that can handle multiple exceptions.
• Simplified varargs method invocation.

Want to get started now? Download the latest App Engine Java SDK and then check out the docs here.

Cloud Endpoints Preview

Have you ever wanted a simple way to get a cloud backend for that Android or iPhone app you are working on?  Wish it was easier to expose RESTful APIs from your web application?  Google Cloud Endpoints simplifies building highly scalable and flexible backends for your web and mobile applications. Use Cloud Endpoints to store application data in the cloud that spans both devices and users. You can now easily expose your own authenticated, reliable, REST-based APIs hosted from an App Engine application and consume them in your Android, iOS, or web clients. Deeply integrated authentication support allows your users to have a transparent yet secure experience accessing your services. You have access to strongly typed client libraries for your custom service optimized for Android and iOS.
To use Cloud Endpoints, you simply write a Java or Python class with methods you want to expose to web or mobile clients. You then annotate the methods with attributes that control exactly how they are represented in REST interfaces on the wire. Finally, use Cloud Endpoints to generate your strongly-typed client libraries for Android, iOS and a lightweight JavaScript library.
For example, you can create a simple class to list some important data:

  public class SuperHeroes {

    public List listSuperHeroes() {
  
  List list = new ArrayList();
  list.add(new SuperHero ("Champion of the Obvious", "Brad Abrams"));
  list.add(new SuperHero ("Mr. Justice", "Chris Ramsdale"));

  return list;

 }
}

Then, expose it over a standard REST interface with a simple attribute and a versioning pattern.

@Api(name = "superheroes", version = "v1")
public class SuperHeroesV1 {
 ...
}

Now you have a simple REST interface.

$ curl http://localhost:8888/_ah/api/superheroes/v1/superheroes
{
 "items": [
  {
   "knownAs" : "Champion of the Obvious",
   "realName" : "Brad Abrams"
  },
  {
   "knownAs" : "Mr. Justice",
   "realName" : "Chris Ramsdale"
  }

And you can make strongly typed calls from your Android clients:

Real result = superheroes.list().execute();

Or Objective-C iOS client:

GTLQuerySuperHeroesV1 *query = [GTLQuerySuperHeroesV1 queryForSuperHeroesList];
[service executeQuery:query completionHandler:^(GTLServiceTicket *ticket, 
GTLSuperHeroes *object, NSError *error) {
  NSArray *items = [object items];
}];

Or the web client in JavaScript:

// ...
var ROOT = 'https://' + window.location.host + '/_ah/api';
gapi.client.load('superheroes', 'v1',
                 loadSuperheroesCallback, ROOT);

// Get the list of superheroes
gapi.client.superheroes.superheroes.list().execute(function(resp) {
  displaySuperheroesList(resp);
});

Read the documentation for Java or Python to discover how you can build a simple tic-tac-toe game using Cloud Endpoints.
To get started with Cloud Endpoints, download the App Engine 1.7.5 SDK and the latest Google Plugin for Eclipse. Be sure to look at the docs and follow along in the discussion forums on Stack Overflow.
For more on using Cloud Endpoints with Python, check out +Danny Hermes and +Dan Holevoet on Google Developers Live.


Brad Abrams is a Product Manager on the Google Cloud Platform where he looks after the developer experience. Brad is currently learning to ride the unicycle, so far with no broken bones!
Posted by Ashleigh Rentz, Editor Emerita2013, By: Seo Master