2013 Year in review: topping 100,000 requests-per-second

2013 was a busy year for Google Cloud Platform. Watch this space: each day, a different Googler who works on Cloud Platform will be sharing his or her highlight from the past year.



Seeing one of our customers top 100,000 requests per second was the highlight of the year. That is enough capacity to answer a request by every single person on the planet in a single day. It feels that people can take our platform and change the world with new business models, cool applications, and knowledge sharing at a truly global level. The real exciting part for me is that Google App Engine allowed the customer to do it easily, as they kept all their focus on a great mobile app and customer experience instead of worrying about the underlying infrastructure.



-Posted by Ophir Kra-Oz, Group Product Manager

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2013 Year in review: making Google Compute Engine Generally Available

2013 was a busy year for Google Cloud Platform. Watch this space: each day, a different Googler who works on Cloud Platform will be sharing his or her highlight from the past year.



At the beginning of this month, we made Compute Engine Generally Available. It’s wonderful to see the great products our customers (like Brightcove, Cooladata, Evite, Fishlabs and Mendelics) are building on the Cloud Platform. And that they’re already seeing the benefits of Google’s scalability, reliability and consistently high performance. I’m also excited to see all the great products that partners like DataStax, DataTorrent, Rightscale, SaltStack and Scalr, as well as many open-source projects, are bringing to our customers. And yet, what gets me out of bed in the morning is knowing that that we’re only just getting started.



-Posted by Navneet Joneja, Senior Product Manager

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2013 Year in review: bringing App Engine to the PHP community

2013 was a busy year for Google Cloud Platform. Watch this space: each day, a different Googler who works on Cloud Platform will be sharing his or her highlight from the past year.



The addition of the PHP runtime to Google App Engine was undoubtedly the highpoint of my year. When we launched PHP support at Google I/O 2013, PHP was the top customer requested feature. By combining App Engine with Google Cloud SQL and Google Cloud Storage, we already see a number of pre-existing high-traffic PHP applications, like Motherboard, move to App Engine to take advantage of the worry free scaling and zero-administration overhead. And, within the last month, we hosted a live online quiz for the largest livestreamed music event in history - built using PHP on App Engine. With so many great users already, it’s exciting to think that the next Snapchat or Khan Academy could be written in PHP, hosted inside Google’s datacenters.



-Posted by Stuart Langley, Software Engineer

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Now Get Programmatic Access to your Billing Data With the New Billing API

Tools for monitoring, analyzing and optimizing cost have become an important part of managing cloud services. But these tools are difficult to build if the usage data is only in the Google Cloud Console. We are happy to announce a solution to this problem. The Billing Export feature addresses this need, and it is available in Preview.



Once enabled, your daily Google Cloud Platform usage and cost estimates will be exported automatically to a CSV or JSON file stored in a Google Cloud Storage bucket you specify. You can then access the data via the Cloud Storage API, CLI tool or Cloud Console file browser. Usage data is labelled with project Number and resource type. You have full control of who can access this data via ACLs on your Cloud Storage bucket.

"Billing Export is a great new feature of Google Cloud Platform. It allows us to analyze the detailed usage of all our cloud projects in one place and optimize our costs. It also gives us a great tool to monitor our applications over time and understand trends in our usage" said Dave Tucker, Director of Platform Development, WebFilings.



You can manage Billing Export from Cloud Console.

View of the cloud Storage bucket after enabling billing export

As you can see in the example output below, your billing data appears in simple JSON displaying all the important attributes such as service name, date, project number, measurement and cost.

[ {
  "lineItemId" : "com.google.cloud/services/compute-engine/StoragePdCapacity",
  "startTime" : "2013-11-02T00:00:00-07:00",
  "endTime" : "2013-11-03T00:00:00-07:00",
  "projectNumber" : "176782591794",
  "measurements" : [ {
    "measurementId" : "com.google.cloud/services/compute-engine/StoragePdCapacity",
    "sum" : "66325032468480000",
    "unit" : "byte-seconds"
  } ],
  "cost" : {
    "amount" : "2.383101",
    "currency" : "USD"
  }
}, {
  "lineItemId" : "com.google.cloud/services/compute-engine/VmimageN1Highcpu_8",
  "startTime" : "2013-11-02T00:00:00-07:00",
  "endTime" : "2013-11-03T00:00:00-07:00",
  "projectNumber" : "176782591794",
  "measurements" : [ {
    "measurementId" : "com.google.cloud/services/compute-engine/VmimageN1Highcpu_8",
    "sum" : "44220",
    "unit" : "seconds"
  } ],
  "cost" : {
    "amount" : "6.4119",
    "currency" : "USD"
  }
} ]
 

We would love to hear your feedback and cool ideas on how to improve Google Cloud Platform billing experience.



-Posted by Rae Wang, Product Manager

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2013 year in review: making scalability easy with dedicated memcache

2013 was a busy year for Google Cloud Platform. Watch this space: each day, a different Googler who works on Cloud Platform will be sharing his or her highlight from the past year.



Seeing customers like Snapchat grow on Google Cloud Platform is what gets me up in the morning. Its exciting to watch customers achieve new heights of scalability with less effort than was possible before. One of the features I worked on this year that was part of that scalability story is dedicated memcache. Dedicated memcache lets customers scale their caching capacity indefinitely without having to manage a server farm of memcached servers. After going into Preview in July, hundreds of customers have deployed many terabytes in production, including a single application using six terabytes. As we go into the New Year, I can’t wait to see which startups use App Engine to bring innovative and fun applications to the world.



-Posted by Logan Henriquez, Product Manager

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2013 Year in review: taking Google Cloud Platform on the road

2013 was a busy year for Google Cloud Platform. Watch this space: each day, a different Googler who works on Cloud Platform will be sharing his or her highlight from the past year.



My highlight of this year was leading Google Cloud Platform talks and code labs in five cities around the world. Myself and colleagues gave talks about Google Compute Engine, App Engine, and the services that glue the fabric of the platform together. We had a great time speaking with all of the attendees, but my favorite part of this tour happened during one of the Google Compute Engine code labs. Attendees were each processing astronomical data on a virtual machine and generating an image of a section of the universe, which was then pulled into a overall collage of the images. However, one of our attendees was feeling a bit mischievous, and replaced his image with -- what else? -- an image of a cat! Well played, very well played.



-Posted by Julia Ferraioli, Developer Advocate

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2013 Year in review: pushing the limits of Big Data

2013 was a busy year for Google Cloud Platform. Watch this space: each day, a different Googler who works on Cloud Platform will be sharing his or her highlight from the past year.



My highlight from 2013 was speaking to developers from across the world at the Big Data Spain conference. I used the opportunity to share with people everything that we have accomplished with Big Query. Although every tool has its limits, it was a joy to review how many big data limits we broke during 2013. Some of the highlights included how to grow a database that already can be as tall you need it to be - in 2012 each row could contain up to 64kB of data. Today, that number is up to 20MB. Other updates include the ability to combine and join 2 insanely huge tables, aggregate values in cases that were considered to have too many groups to group by, or return results of arbitrary sizes (JOIN EACH, GROUP EACH BY, and the allowLargeResults flag). BigQuery not only got bigger this year, it also got smarter: The new window and analytic functions allow users to run richer queries while the new correlation function allows surfacing and discovering relationships previously invisible. What a good way to close this year!



-Posted by Felipe Hoffa, Developer Programs Engineer

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