Tag Archives: Announcements

The latest round of Google Open Source Peer Bonus winners

Google relies on open source software throughout our systems, much of it written by non-Googlers. We’re always looking for ways to say “thank you!” so 5 years ago we started asking Googlers to nominate open source contributors outside of the company who have made significant contributions to codebases we use or think are important. We’ve recognized more than 500 developers from 30+ countries who have contributed their time and talent to over 400 open source projects since the program’s inception in 2011.

Today we are pleased to announce the latest round of awardees, 52 individuals we’d like to recognize for their dedication to open source communities. The following is a list of everyone who gave us permission to thank them publicly:

Name Project Name Project
Philipp Hancke Adapter.js Fernando Perez Jupyter & IPython
Geoff Greer Ag Michelle Noorali Kubernetes & Helm
Dzmitry Shylovich Angular Prosper Otemuyiwa Laravel Hackathon Starter
David Kalnischkies Apt Keith Busch Linux kernel
Peter Mounce Bazel Thomas Caswell matplotlib
Yuki Yugui Sonoda Bazel Tatsuhiro Tsujikawa nghttp2
Eric Fiselier benchmark Anna Henningsen Node.js
Rob Stradling Certificate Transparency Charles Harris NumPy
Ke He Chromium Jeff Reback pandas
Daniel Micay CopperheadOS Ludovic Rousseau PCSC-Lite, CCID
Nico Huber coreboot Matti Picus PyPy
Kyösti Mälkki coreboot Salvatore Sanfilippo Redis
Jana Moudrá Dart Ralf Gommers SciPy
John Wiegley Emacs Kevin O'Connor SeaBIOS
Alex Saveau FirebaseUI-Android Sam Aaron Sonic Pi
Toke Hoiland-Jorgensen Flent Michael Tyson The Amazing Audio Engine
Hanno Böck Fuzzing Project Rob Landley Toybox
Luca Milanesio Gerrit Bin Meng U-Boot
Daniel Theophanes Go programming language Ben Noordhuis V8
Josh Snyder Go programming language Fatih Arslan vim-go
Brendan Tracey Go programming language Adam Treat WebKit
Elias Naur Go on Mobile Chris Dumez WebKit
Anthonios Partheniou Google Cloud Datalab Sean Larkin Webpack
Marcus Meissner gPhoto2 Tobias Koppers Webpack
Matt Butcher Helm Alexis La Goutte Wireshark dissector for QUIC

Congratulations to all of the awardees, past and present! Thank you for your contributions.

By Helen Hu, Open Source Programs Office

Google Summer of Code 2017 student applications are open!

Are you a university student looking to learn more about open source software development? Consider applying to Google Summer of Code (GSoC) for a chance to spend your break coding on an open source project.

vertical GSoC logo.jpg


For the 13th straight year GSoC will give students from around the world the opportunity to learn the ins and outs of open source software development while working from their home. Students will receive a stipend for their successful contributions to allow them to focus on their coding during the program.

Mentors are paired with the students to help address technical questions and to monitor their progress throughout the program. Former GSoC participants have told us that the real-world experience they’ve gained during the program has not only sharpened their technical skills, but has also boosted their confidence, broadened their professional network and enhanced their resumes.

Interested students can submit proposals on the program site now through Monday, April 3 at 16:00 UTC. The first step is to search through the 201 open source organizations and review the “Project ideas” for the organizations that appeal to you. Next, reach out to the organizations to introduce yourself and determine if your skills and interests are a good match with their organization.




Since spots are limited, we recommend writing a strong project proposal and submitting a draft early to receive feedback from the organization which will help increase your chances of selection. Our Student Manual, written by former students and mentors, provides excellent helpful advice to get you started with choosing an organization and crafting a great proposal.

For information throughout the application period and beyond, visit the Google Open Source Blog, join our Google Summer of Code discussion lists or join us on Internet Relay Chat (IRC) at #gsoc on Freenode. Be sure to read the Program Rules, Timeline and FAQ, all available on the program site, for more information about Google Summer of Code.

Good luck to all the open source coders who apply, and remember to submit your proposals early — you only have until Monday, April 3 at 16:00 UTC!

By Stephanie Taylor, Google Summer of Code Program Manager

Join us live on May 23, 2017 as we announce the latest Analytics, DoubleClick and Ads innovations

What: Google Marketing Next keynote live stream
When: Tuesday, May 23, 9:00 a.m. PT/12:00 p.m. ET.
Duration: 1 hour
Where: Here on the Google Analytics Blog

Be the first to hear about Google’s latest marketing innovations, the moment they’re announced. Watch live as my team and I share new Ads, Analytics and DoubleClick innovations designed to improve your ability to reach consumers, simplify campaign measurement and increase your productivity. We’ll also give you a sneak peek at how brands are starting to use the Google Assistant to delight customers.

Register for the live stream here.

Until then, follow us on Twitter, Google+, Facebook and LinkedIn for previews of what’s to come.

Getting ready for Google Summer of Code 2017

Spring is just around the corner here in the Northern Hemisphere and Google Summer of Code is fast approaching. If you are a student interested in participating this year, now is the time to prepare -- read on for tips on how to get ready.

This year we’ve accepted 201 open source organizations into the program, nearly 40 of which are new to the program. The organizations cover a wide range of topics including (but certainly not limited to!):

  • Operating systems
  • Web application frameworks
  • Healthcare and bioinformatics
  • Music and graphic design
  • Machine learning
  • Robotics
  • Security




How should you prepare for Google Summer of Code?

While student applications don’t open until March 20th at 16:00 UTC, you need to decide which projects you’re interested in and what you’ll propose. You should also communicate with those projects to learn more before you apply.

Start by looking at the list of participating projects and organizations. You can explore by searching for specific names or technologies, or filtering by topics you are interested in. Follow the “Learn More” link through to each organization’s page for additional information.

Once you’ve identified the organizations that you’re interested in, take a look at their ideas list to get a sense of the specific projects you could work on. Typically, you will choose a project from that list and write a proposal based on that idea, but you could also propose something that’s not on that list.

You should reach out to the organizations after you’ve decided what you want to work on. Doing this can make the difference between a good application and a great application.

Whatever you do, don’t wait until March 20th to begin preparing for Google Summer of Code! History has shown that students who reach out to organizations before the start of the application period have a higher chance of being accepted into the program, as they have had more time to talk to the organizations and understand what they are looking for with the project.

If you have any questions along the way, take a look at the Student Manual, FAQ and Timeline. If you can’t find the answer to your question, try taking your question to the mailing list.

By Josh Simmons, Open Source Programs Office

Google Cloud Platform: your Next home in the cloud



San Francisco Today at Google Cloud Next ‘17, we’re thrilled to announce new Google Cloud Platform (GCP) products, technologies and services that will help you imagine, build and run the next generation of cloud applications on our platform.

Bring your code to App Engine, we’ll handle the rest

In 2008, we launched Google App Engine, a pioneering serverless runtime environment that lets developers build web apps, APIs and mobile backends at Google-scale and speed. For nearly 10 years, some of the most innovative companies built applications that serve their users all over the world on top of App Engine. Today, we’re excited to announce into general availability a major expansion of App Engine centered around openness and developer choice that keeps App Engine’s original promise to developers: bring your code, we’ll handle the rest.

App Engine now supports Node.js, Ruby, Java 8, Python 2.7 or 3.5, Go 1.8, plus PHP 7.1 and .NET Core, both in beta, all backed by App Engine’s 99.95% SLA. Our managed runtimes make it easy to start with your favorite languages and use the open source libraries and packages of your choice. Need something different than what’s out of the box? Break the glass and go beyond our managed runtimes by supplying your own Docker container, which makes it simple to run any language, library or framework on App Engine.

The future of cloud is open: take your app to-go by having App Engine generate a Docker container containing your app and deploy it to any container-based environment, on or off GCP. App Engine gives developers an open platform while still providing a fully managed environment where developers focus only on code and on their users.


Cloud Functions public beta at your service

Up one level from fully managed applications, we’re launching Google Cloud Functions into public beta. Cloud Functions is a completely serverless environment to build and connect cloud services without having to manage infrastructure. It’s the smallest unit of compute offered by GCP and is able to spin up a single function and spin it back down instantly. Because of this, billing occurs only while the function is executing, metered to the nearest one hundred milliseconds.

Cloud Functions is a great way to build lightweight backends, and to extend the functionality of existing services. For example, Cloud Functions can respond to file changes in Google Cloud Storage or incoming Google Cloud Pub/Sub messages, perform lightweight data processing/ETL jobs or provide a layer of logic to respond to webhooks emitted by any event on the internet. Developers can securely invoke Cloud Functions directly over HTTP right out of the box without the need for any add-on services.

Cloud Functions is also a great option for mobile developers using Firebase, allowing them to build backends integrated with the Firebase platform. Cloud Functions for Firebase handles events emitted from the Firebase Realtime Database, Firebase Authentication and Firebase Analytics.

Growing the Google BigQuery universe: introducing BigQuery Data Transfer Service

Since our earliest days, our customers turned to Google to promote their advertising messages around the world, at a scale that was previously unimaginable. Today, those same customers want to use BigQuery, our powerful data analytics service, to better understand how users interact with those campaigns. With that, we’ve developed deeper integration between broader Google and GCP with the public beta of the BigQuery Data Transfer Service, which automates data movement from select Google applications directly into BigQuery. With BigQuery Data Transfer Service, marketing and business analysts can easily export data from Adwords, DoubleClick and YouTube directly into BigQuery, making it available for immediate analysis and visualization using the extensive set of tools in the BigQuery ecosystem.

Slashing data preparation time with Google Cloud Dataprep

In fact, our goal is to make it easy to import data into BigQuery, while keeping it secure. Google Cloud Dataprep is a new serverless browser-based service that can dramatically cut the time it takes to prepare data for analysis, which represents about 80% of the work that data scientists do. It intelligently connects to your data source, identifies data types, identifies anomalies and suggests data transformations. Data scientists can then visualize their data schemas until they're happy with the proposed data transformation. Dataprep then creates a data pipeline in Google Cloud Dataflow, cleans the data and exports it to BigQuery or other destinations. In other words, you can now prepare structured and unstructured data for analysis with clicks, not code. For more information on Dataprep, apply to be part of the private beta. Also, you’ll find more news about our latest database and data and analytics capabilities here and here.

Hello, (more) world

Not only are we working hard on bringing you new products and capabilities, but we want your users to access them quickly and securely  wherever they may be. That’s why we’re announcing three new Google Cloud Platform regions: California, Montreal and the Netherlands. These will bring the total number of Google Cloud regions up from six today, to more than 17 locations in the future. These new regions will deliver lower latency for customers in adjacent geographic areas, increased scalability and more disaster recovery options. Like other Google Cloud regions, the new regions will feature a minimum of three zones, benefit from Google’s global, private fibre network and offer a complement of GCP services.

Supercharging our infrastructure . . .

Customers run demanding workloads on GCP, and we're constantly striving to improve the performance of our VMs. For instance, we were honored to be the first public cloud provider to run Intel Skylake, a custom Xeon chip that delivers significant enhancements for compute-heavy workloads and a larger range of VM memory and CPU options.

We’re also doubling the number of vCPUs you can run in an instance from 32 to 64 and now offering up to 416GB of memory, which customers have asked us for as they move large enterprise applications to Google Cloud. Meanwhile, we recently began offering GPUs, which provide substantial performance improvements to parallel workloads like training machine learning models.

To continually unlock new energy sources, Schlumberger collects large quantities of data to build detailed subsurface earth models based on acoustic measurements, and GCP compute infrastructure has the unique characteristics that match Schlumberger's needs to turn this data into insights. High performance scientific computing is integral to its business, so GCP's flexibility is critical.

Schlumberger can mix and match GPUs and CPUs and dynamically create different shapes and types of virtual machines, choosing memory and storage options on demand.

"We are now leveraging the strengths offered by cloud computation stacks to bring our data processing to the next level. Ashok Belani, Executive Vice President Technology, Schlumberger

. . . without supercharging our prices

We aim to keep costs low. Today we announced Committed Use Discounts that provide up to 57% off the list price on Google Compute Engine, in exchange for a one or three year purchase commitment. Committed Use Discounts are based on the total amount of CPU and RAM you purchase, and give you the flexibility to use different instance and machine types; they apply automatically, even if you change instance types (or size). There are no upfront costs with Committed Use Discounts, and they are billed monthly. What’s more, we automatically apply Sustained Use Discounts to any additional usage above a commitment.

We're also dropping prices for Compute Engine. The specific cuts vary by region. Customers in the United States will see a 5% price drop; customers in Europe will see a 4.9% drop and customers using our Tokyo region an 8% drop.

Then there’s our improved Free Tier. First, we’ve extended the free trial from 60 days to 12 months, allowing you to use your $300 credit across all GCP services and APIs, at your own pace and on your own schedule. Second, we’re introducing new Always Free products  non-expiring usage limits that you can use to test and develop applications at no cost. New additions include Compute Engine, Cloud Pub/Sub, Google Cloud Storage and Cloud Functions, bringing the number of Always Free products up to 15, and broadening the horizons for developers getting started on GCP. Visit the Google Cloud Platform Free Tier page today for further details, terms, eligibility and to sign up.

We'll be diving into all of these product announcements in much more detail in the coming days, so stay tuned!

Real-time just got real: Google Analytics 360 offers fresher insight

You’ve just launched a website or feature. Your toe is already tapping. Wait, wait, wait — you can hardly wait one hour to see exactly how it’s performing. Sound familiar? If you’ve been there, we have exciting news for you.

Google Analytics 360 can now provide updated insights as quickly as every 10 minutes. We’re proud to give our customers the fastest access to the freshest first party data Google Analytics has ever offered.

What did you just say?!
If you need to know how your sites, microsites, or digital engagements are doing right now, we’ve got you covered. Most first-party data in Analytics 360 can now be collected, processed, and available — via our UI, API, and BigQuery integration (coming soon) — in as fast as 10 minutes. This means you can move faster to:
  • Fix things when they’re broken
  • Detect trends and react when things are popular
  • Understand and take action on the impact of cultural events or social memes
To see how fresh the data is in your report at any time, just look for this icon in the upper right:
When you see this icon, it means you’re looking at today’s data and the report is supported and super fresh. Hover over the icon to see how fresh the data is!

This new level of freshness is only available to Analytics 360 users. To learn more about which reports, views, and properties support fresher data, and the factors affecting data freshness, check out our help center.

Some site owners just can’t wait
Brands and sites in the business of capitalizing on momentary consumer attention are excited about fresher insights. Take the case of publishers and retailers as an example.

Publishers strive to put the richest, most interesting content in front of users at any given point in time. The trick is understanding what’s rich and interesting right now — and that’s a constantly moving target.

Publishers have long referenced our real-time Google Analytics reports to make decisions, but sometimes they’re looking for deeper insight than what is provided in those reports. Fresher insights across additional Google Analytics reports help our publishers make even more informed content decisions, paving the way to better user acquisition, user engagement, and a stronger relationship between content consumer and publisher brand.

Online retailers are in the same boat. When celebrities wear a product or mention a brand on social media, product interest may spike. Retailers may have just minutes to capitalize on purchase intent before it wanes.

When a product’s popularity is on the rise, retailers can react by upping its prominence to capture interest, running focused promotions or recommending related products to expand consideration. With fresh insights available as soon as every 10 minutes, retailers move faster and turn trending interest into sales.

Speed is good, but safety comes first
As you know, Google Analytics has the ability to pull in data from other sources like AdWords and DoubleClick. We refer to these as “integration sources” and these sources operate with additional requirements, like fraud detection, that mean that the data in these reports are exempt from our enhanced freshness capabilities.

For example, any report with Ads data, including a dimension widened by an Ads integration, will continue to be made available within hours. For further details on which reports are supported or not supported, please read the help center article here.

Introducing the Google Summer of Code 2017 Mentor Organizations

Today’s the day! We are excited to announce the mentor organizations accepted for this year’s Google Summer of Code (GSoC). Every year we receive more applications than we can accept and 2017 was no exception. After carefully reviewing almost 400 applications, we have chosen 201 open source projects and organizations, 18% of which are new to the program. Please see the program website for a complete list of the accepted organizations.

Interested in participating as a student? We will begin accepting student applications on Monday, March 20, 2017 at 16:00 UTC and the deadline is Monday, April 3, 2017 at 16:00 UTC.

Over the next three weeks, students who’d like to participate in Google Summer of Code should research the organizations and their Ideas Lists to explore which organizations are a good fit for their interests and skills and learn how they might contribute. Some of the most successful proposals have been completely new ideas submitted by students, so if you don’t see a project that appeals to you, don’t hesitate to suggest a new idea to the organization! There are contacts listed for each organization on their Ideas List — students should contact the organization directly to discuss their ideas. We also strongly encourage all interested students to reach out to and become familiar with the organization before applying.

You can find more information on our website, including a full timeline of important dates and program milestones. We also highly recommend all interested students read the Student Manual, FAQ and the Program Rules.

Congratulations to all of our mentor organizations! We look forward to working with all of you during Google Summer of Code 2017.

By Josh Simmons, Open Source Programs Office

Google Cloud Platform is the first cloud provider to offer Intel Skylake



I’m excited to announce that Google Cloud Platform (GCP) is the first cloud provider to offer the next generation Intel Xeon processor, codenamed Skylake.

Customers across a range of industries, including healthcare, media and entertainment and financial services ask for the best performance and efficiency for their high-performance compute workloads. With Skylake processors, GCP customers are the first to benefit from the next level of performance.

Skylake includes Intel Advanced Vector Extensions (AVX-512), which make it ideal for scientific modeling, genomic research, 3D rendering, data analytics and engineering simulations. When compared to previous generations, Skylake’s AVX-512 doubles the floating-point performance for the heaviest calculations.

We optimized Skylake for Google Compute Engine’s complete family of VMs  standard, highmem, highcpu and Custom Machine Types to help bring the next generation of high performance compute instances to everyone.
"Google and Intel have had a long standing engineering partnership working on Data Center innovation. We're happy to see the latest Intel Xeon technology now available on Google Cloud Infrastructure. This technology delivers significant enhancements for compute-intensive workloads, efficiently accelerating data analytics that businesses depend on for operations and growth.”  Diane Bryant, Intel Executive Vice President and GM of the Data Center Group
Skylake processors are available in five GCP regions: Western US, Eastern US, Central US, Western Europe and Eastern Asia Pacific. Sign up here to take advantage of the new Skylake processors.

You can learn more about Skylake for Google Compute Engine and see it in action at Google Cloud NEXT ’17 in San Francisco on March 8-10. Register today!

GPUs are now available for Google Compute Engine and Cloud Machine Learning



Google Cloud Platform gets a performance boost today with the much anticipated public beta of NVIDIA Tesla K80 GPUs. You can now spin up NVIDIA GPU-based VMs in three GCP regions: us-east1, asia-east1 and europe-west1, using the gcloud command-line tool. Support for creating GPU VMs using the Cloud Console appears later this week.

If you need extra computational power for deep learning, you can attach up to eight GPUs (4 K80 boards) to any custom Google Compute Engine virtual machine. GPUs can accelerate many types of computing and analysis, including video and image transcoding, seismic analysis, molecular modeling, genomics, computational finance, simulations, high performance data analysis, computational chemistry, finance, fluid dynamics and visualization.

NVIDIA K80 GPU Accelerator Board

Rather than constructing a GPU cluster in your own datacenter, just add GPUs to virtual machines running in our cloud. GPUs on Google Compute Engine are attached directly to the VM, providing bare-metal performance. Each NVIDIA GPU in a K80 has 2,496 stream processors with 12 GB of GDDR5 memory. You can shape your instances for optimal performance by flexibly attaching 1, 2, 4 or 8 NVIDIA GPUs to custom machine shapes.

Google Cloud supports as many as 8 GPUs attached to custom VMs, allowing you to optimize the performance of your applications.

These instances support popular machine learning and deep learning frameworks such as TensorFlow, Theano, Torch, MXNet and Caffe, as well as NVIDIA’s popular CUDA software for building GPU-accelerated applications.

Pricing

Like the rest of our infrastructure, the GPUs are priced competitively and are billed per minute (10 minute minimum). In the US, each K80 GPU attached to a VM is priced at $0.700 per hour per GPU and in Asia and Europe, $0.770 per hour per GPU. As always, you only pay for what you use. This frees you up to spin up a large cluster of GPU machines for rapid deep learning and machine learning training with zero capital investment.

Supercharge machine learning

The new Google Cloud GPUs are tightly integrated with Google Cloud Machine Learning (Cloud ML), helping you slash the time it takes to train machine learning models at scale using the TensorFlow framework. Now, instead of taking several days to train an image classifier on a large image dataset on a single machine, you can run distributed training with multiple GPU workers on Cloud ML, dramatically shorten your development cycle and iterate quickly on the model.

Cloud ML is a fully-managed service that provides end-to-end training and prediction workflow with cloud computing tools such as Google Cloud Dataflow, Google BigQuery, Google Cloud Storage and Google Cloud Datalab.

Start small and train a TensorFlow model locally on a small dataset. Then, kick off a larger Cloud ML training job against a full dataset in the cloud to take advantage of the scale and performance of Google Cloud GPUs. For more on Cloud ML, please see the Quickstart guide to get started, or this document to dive into using GPUs.

Next steps

Register for Cloud NEXT, sign up for the CloudML Bootcamp and learn how to Supercharge performance using GPUs in the cloud. You can use the gcloud command-line to create a VM today and start experimenting with TensorFlow-accelerated machine learning. Detailed documentation is available on our website.


Delivering a better platform for your SQL Server Enterprise workloads



Our goal at Google Cloud Platform (GCP) is to be the best enterprise cloud environment. Throughout 2016, we worked hard to ensure that Windows developers and IT administrators would feel right at home when they came to GCP: whether it’s building an ASP.NET application with their favorite tools like Visual Studio and PowerShell, or deploying the latest version of Windows Server onto Google Compute Engine.

Continuing our work in providing great infrastructure for enterprises running Windows, we’re pleased to announce pre-configured images for Microsoft SQL Server Enterprise and Windows Server Core on Compute Engine. High-availability and disaster recovery are top of mind for our larger customers, so we’re also announcing support for SQL Server AlwaysOn Availability Groups and persistent disk snapshots integrated with Volume Shadow Copy Service (VSS) on Windows Server. Finally, all of our Windows Server images are now enabled with Windows Remote Management support, including our Windows Server Core 2016 and 2012 R2 images.

SQL Server Enterprise Edition images on GCE


You can now launch Compute Engine VMs with Microsoft SQL Server Enterprise Edition pre-installed, and pay by the minute for SQL Server Enterprise and Windows Server licenses. Customers can also choose to bring their own licenses for SQL Server Enterprise.

We now support pre-configured images for the following versions in Beta:

  • SQL Server Enterprise 2016
  • SQL Server Enterprise 2014
  • SQL Server Enterprise 2012 
Supported SQL Server images available on Compute Engine (click to enlarge)

SQL Server Enterprise
targets mission-critical workloads by supporting more cores, higher memory and important enterprise features, including:

  • In-memory tables and indexes
  • Row-level security and encryption for data at rest or in motion
  • Multiple read-only replicas for integrated HA/DR and read scale-out
  • Business intelligence and rich visualizations on all platforms, including mobile
  • In-database advanced analytics with R


Combined with Google’s world-class infrastructure, SQL Server instances running on Compute Engine benefit from price-to-performance advantages, highly customizable VM sizes and state-of-the-art networking and security capabilities. With automatic sustained use discounts and the prospect of retiring hardware and associated maintenance on the horizon, customers can achieve total costs lower than those of other cloud providers.

To get started, learn how to create SQL Server instances easily on Google Compute Engine.



High-availability and disaster recovery for SQL Server VMs


Mission-critical SQL Server workloads require support for high-availability and disaster recovery. To achieve this, GCP supports Windows Server Failover Clustering (WSFC) and SQL Server AlwaysOn Availability Groups. AlwaysOn Availability Groups is SQL Server’s flagship HA/DR solution, allowing you to configure replicas for automatic failover in case of failure. These replicas can be readable, allowing you to offload read workloads and backups.

Compute Engine users can now configure AlwaysOn Availability Groups. This includes configuring replicas on VMs in different isolated zones as described in these instructions.
A highly available SQL Server reference architecture using Windows Server Failover Clustering and SQL Server AlwaysOn Availability Groups (click to enlarge)


Better backups with VSS-integrated persistent disk snapshots for Windows VMs


Being able to take snapshots in coordination with Volume Shadow Copy Service ensures that you get application-consistent snapshots for persistent disks attached to an instance running Windows -- without having to shut it down. This feature is useful when you want to take a consistent backup for VSS-enabled applications like SQL Server and Exchange Server without affecting the workload running on the VMs.

To get started with VSS-enabled persistent disk snapshots, select Snapshots under the Cloud Console Compute Engine page. There you'll see a new check-box on the disk snapshot creation page that allows you to specify whether a snapshot should be VSS-enabled.
(click to enlarge)

This feature can also be invoked via the gcloud SDK and API, following these instructions.

Looking ahead


GCP’s expanded support for SQL Server images and high availability are our latest efforts to improve Windows support on Compute Engine, and to build a cloud environment for enterprise Windows that leads the industry. Last year we expanded our list of pre-configured images to include SQL Server Standard, SQL Server Web and Windows Server 2016, and announced comprehensive .NET developer solutions, including a .NET client library for all GCP APIs through NuGet. We have lots more in store for the rest of 2017!

For more resources on Windows Server and Microsoft SQL Server on GCP, check out cloud.google.com/windows and cloud.google.com/sql-server. And for hands-on training on how to deploy and manage Windows and SQL Server workloads on GCP, come to the GCP NEXT ‘17 Windows Bootcamp. Finally, if you need help migrating your Windows workloads, don’t hesitate to contact us. We’re eager to hear your feedback!