Category Archives: Google for Work Blog

Work is going Google

#GraciasALosProfes: Celebrating Teacher Appreciation Day in Mexico

Today is Teacher Appreciation Day, or Día del Maestro, in Mexico, where 30 GEG (Google Educator Groups) leaders are at the helm of the movement to transform education through technology in Latin America. Our Mexican GEG leaders empower their fellow teachers to harness tech to meet students’ needs. We are amazed at the innovative and inspiring ways these teachers and leaders are building their movement across Mexico—from Guadalajara to Mexico City to Monterrey.

In Quéretaro, Nay Belaunzaran thought up an idea to scale the impact of tech across generations by mobilizing children to teach their parents about the internet. Under Nay’s leadership, primary school students prepare classes for their parents about G Suite for Education where the parents learn to jot their thoughts down in Docs, build presentations in Slides, and communicate with teachers through Google Classroom. Galvanizing students to bridge the generational tech literacy gap has made it easier for parents to stay engaged with kids’ schools.

4

Nay connected with fellow teachers from all over Latin America at last year’s Google for Education Certified Innovators Summit in Mexico City.

In Tijuana, Gabriela Torres Beltrán has paved the way for dozens of her students to become Google Certified Educators themselves. By building a community of future teachers who keep innovation and technology top of mind, Gabriela is making her mark on the future of education in her community.  “Seeing the smile of satisfaction on their faces as they explore ways to implement technology in class is extremely inspiring,” she shared with an inspired smile of her own.

RVP_8345baja_halfimage.jpg

Verónica stays after class on most days, providing extra support for students whose curiosity extends beyond school hours.

In Verónica Nuñez Loyo’s classroom in Mexico City, students find themselves at the intersection of traditions of the past and technology of the future. She challenges her middle schoolers not only to research the history of Mexico, but to leverage the internet to share their learnings. Recently, Verónica’s  seventh grade class collaborated to create a multimedia presentation about the Axolotl, an endangered amphibian species endemic to Baja California. Technology was at the heart of the project, whether students were exploring the Náhuatl origin of the word “Axolotl” or investigating how portrayals of this “walking fish” have changed over time.

These are three of many educators who work tirelessly to ignite curiosity and give life to the ideas of Mexico’s rising generation. Which teachers inspire you? Today—and everyday—join us in celebrating the educators who dedicate their lives to working with students to create a more connected Latin America. #GraciasALosProfes.

Source: Google Cloud


Protecting you against phishing

As many email users know, phishing attacks—or emails that impersonate a trusted source to trick users into sharing information—are a pervasive problem. If you use Gmail, you can rest assured that every day, millions of phishing emails are blocked from ever reaching your inbox.

This week, we defended against an email phishing campaign that tricked some of our users into inadvertently granting access to their contact information, with the intent to spread more phishing emails. We took quick action to revoke all access granted to the attacker as well as steps to reduce and prevent harm from future variants of this type of attack.

Here’s some background to help you understand how the campaign worked, how we addressed it and how you can better protect yourself against attacks.

How the campaign worked and how we addressed it

Victims of this attack received an email that appeared to be an invite to a Google Doc from one of their contacts. When users clicked the link in the attacker’s email, it directed them to the attacker’s application, which requested access to the user’s account under the false pretense of gaining access to the Google Doc. If the user authorized access to the application (through a mechanism called OAuth), it used the user's contact list to send the same message to more people.

Upon detecting this issue, we immediately responded with a combination of automatic and manual actions that ended this campaign within an hour. We removed fake pages and applications, and pushed user-protection updates through Safe Browsing, Gmail, Google Cloud Platform, and other counter-abuse systems. Fewer than 0.1% of our users were affected by this attack, and we have taken steps to re-secure affected accounts.

We protect our users from phishing attacks in a number of ways, including:

  • Using machine learning-based detection of spam and phishing messages, which has contributed to 99.9% accuracy in spam detection
  • Providing Safe Browsing warnings about dangerous links, within Gmail and across more than 2 billion browsers
  • Preventing suspicious account sign-ins through dynamic, risk-based challenges
  • Scanning email attachments for malware and other dangerous payloads 

In addition, we’re taking multiple steps to combat this type of attack in the future, including updating our policies and enforcement on OAuth applications, updating our anti-spam systems to help prevent campaigns like this one, and augmenting monitoring of suspicious third-party apps that request information from our users.

How users can protect themselves

We’re committed to keeping your Google Account safe, and have layers of defense in place to guard against sophisticated attacks of all types, from anti-hijacking systems detecting unusual behavior, to machine learning models that block malicious content, to protection measures in Chrome and through Safe Browsing that guard against visiting suspicious sites. In addition, here are a few ways users can further protect themselves:

How G Suite admins can protect their users 

We’ve separately notified G Suite customers whose users were tricked into granting OAuth access. While no further admin or user action is required for this incident, if you are a G Suite admin, consider the following best practices to generally improve security:

Here is a list of more tips and tools to help you stay secure on the web.

Source: Google Cloud


Protecting you against phishing

As many email users know, phishing attacks—or emails that impersonate a trusted source to trick users into sharing information—are a pervasive problem. If you use Gmail, you can rest assured that every day, millions of phishing emails are blocked from ever reaching your inbox.

This week, we defended against an email phishing campaign that tricked some of our users into inadvertently granting access to their contact information, with the intent to spread more phishing emails. We took quick action to revoke all access granted to the attacker as well as steps to reduce and prevent harm from future variants of this type of attack.

Here’s some background to help you understand how the campaign worked, how we addressed it and how you can better protect yourself against attacks.

How the campaign worked and how we addressed it

Victims of this attack received an email that appeared to be an invite to a Google Doc from one of their contacts. When users clicked the link in the attacker’s email, it directed them to the attacker’s application, which requested access to the user’s account under the false pretense of gaining access to the Google Doc. If the user authorized access to the application (through a mechanism called OAuth), it used the user's contact list to send the same message to more people.

Upon detecting this issue, we immediately responded with a combination of automatic and manual actions that ended this campaign within an hour. We removed fake pages and applications, and pushed user-protection updates through Safe Browsing, Gmail, Google Cloud Platform, and other counter-abuse systems. Fewer than 0.1% of our users were affected by this attack, and we have taken steps to re-secure affected accounts.

We protect our users from phishing attacks in a number of ways, including:

  • Using machine learning-based detection of spam and phishing messages, which has contributed to 99.9% accuracy in spam detection
  • Providing Safe Browsing warnings about dangerous links, within Gmail and across more than 2 billion browsers
  • Preventing suspicious account sign-ins through dynamic, risk-based challenges
  • Scanning email attachments for malware and other dangerous payloads 

In addition, we’re taking multiple steps to combat this type of attack in the future, including updating our policies and enforcement on OAuth applications, updating our anti-spam systems to help prevent campaigns like this one, and augmenting monitoring of suspicious third-party apps that request information from our users.

How users can protect themselves

We’re committed to keeping your Google Account safe, and have layers of defense in place to guard against sophisticated attacks of all types, from anti-hijacking systems detecting unusual behavior, to machine learning models that block malicious content, to protection measures in Chrome and through Safe Browsing that guard against visiting suspicious sites. In addition, here are a few ways users can further protect themselves:

How G Suite admins can protect their users 

We’ve separately notified G Suite customers whose users were tricked into granting OAuth access. While no further admin or user action is required for this incident, if you are a G Suite admin, consider the following best practices to generally improve security:

Here is a list of more tips and tools to help you stay secure on the web.

Source: Google Cloud


How machine learning in G Suite makes people more productive

Email management, formatting documents, creating expense reports. These are just some of the time-sinks that can affect your productivity at work. At Google, this is referred to as “overhead”—time spent working on tasks that do not directly relate to creative output—and it happens a lot.

According to a Google study in 2015, the average worker spends only about 5 percent of his or her time actually coming up with the next big idea. The rest of our time is caught in the quicksand of formatting, tracking, analysis or other mundane tasks. That’s where machine learning can help.

Machine learning algorithms observe examples and make predictions based on data. In G Suite, machine learning models make your workday more efficient by taking over menial tasks, like scheduling meetings, or by predicting information you might need and surfacing it for you, like suggesting Docs.

Time spent chart

Source: Google Data, April 2015

Eliminating spam within Gmail using machine learning

One of the earliest machine learning use cases for G Suite was within Gmail. Historically, Gmail used a rule-based system, which meant our anti-spam team would create new rules to match individual spam patterns. Over a decade of using this process, we improved spam detection accuracy to 99 percent.

Starting in 2014, our team augmented this rule-based system to generate rules using machine learning algorithms instead, taking spam detection one step further. Now, we use TensorFlow and other machine learning to continually regenerate the “spam filter,” so the system has learned to predict which emails are most likely junk. Machine learning finds new patterns and adapts far quicker than previous manual systems—it’s a big part of the reason that more than one billion Gmail users avoid spam within their account.

See machine learning in your favorite G Suite apps

G Suite’s goal is to help teams accomplish more with its intelligent apps, no matter where they are in the world. And chances are, you’ve already seen machine learning integrated into your day-to-day work to do just that.

Smart Reply, for example, uses machine learning to generate three natural language responses to an email. So if you find yourself on the road or pressed for time and in need of a quick way to clear your inbox, let Smart Reply do it for you.
Smart Reply GIF

Explore in Docs, Slides and Sheets uses machine learning to eliminate time spent on mundane tasks, like tracking down documents or information on the web, reformatting presentations or performing calculations within spreadsheets.

Explore

Quick Access in Drive predicts and suggests files you might need within Drive. Using machine intelligence, Quick Access can predict files based on who you share files with frequently, when relevant meetings occur within your Calendar or if you tend to use files at certain times of the day.

Quick Access

To learn more about how machine intelligence can make your life easier, sign up for this free webinar on June 15, 2017, featuring experts from MIT Research, Google and other companies. You can also check out the Big Data and Machine Learning blog or watch this video from Google Cloud Next with Ryan Tabone, director of product management at Google, where he explains more about “overhead.”

Source: Google Cloud


Google Classroom outside the classroom

Technology makes learning possible anytime, anywhere. Learners aren’t always sitting in a classroom, and educators aren’t always lecturing at a chalkboard. That’s why last month we made Google Classroom available to users without G Suite for Education accounts. Now, using a personal Google account, teachers and learners in many different settings can teach or attend classes, manage assignments, and instantly collaborate.

Starting today, users can do more than join classes—they can create them, too. Over the past few weeks, teachers and students have been piloting this new feature, and they’ve already created some great new classes for adult education, hobbies, and after school programs. Below we’ll share some of these classes with you.

Classroom-for-Consumer-Launch_4.18.gif

Teaching virtual adult education classes

On March 27th, educator Tony Vincent tweeted an invitation for a free online class teaching graphic design with Google Drawings. He quickly enrolled 75 enthusiastic educators across the U.S., Australia, Greece, and South Africa. Every week during the six-week class, Vincent would post instructional videos to Classroom. Then students would have a week to post their assignments, so they could get feedback from Vincent and other students. “I didn’t want to just publish a video tutorial and never see the end results. So when I heard that Google Classroom was open for personal accounts, I thought it would be a great place to gather a group of educators to learn, create, and share.”
ClassroomConsumer-Tony-350px.jpg

For Vincent, topics has been a key feature. “For a self-paced class like mine,” he says, “I really like the ability to use topics to label announcements, assignments, and questions. This feature will also be incredibly useful after the class concludes as I’ll be able to navigate the archive of posted work, questions, ideas, and inspiration.”

In addition, Vincent likes how he can use Classroom to email students weekly summaries and reminders, and how he can refer students to previous posts, because every announcement, assignment, and question in Google Classroom has its own link. “I’m having a blast teaching in Google Classroom,” he says. “I’m seeing enlightening interactions and generous sharing from the educators who make up the class. I truly look forward to checking in on my class several times a day.”

Running after school programs

Linda Scarth, an elementary school STEM teacher, used Classroom in a Girl Scouts robotics club for 4th, 5th and 6th graders. Dubbed the “Turtle Scouts,” the group meets in person once a week. Scarth was inspired to use Classroom when her group found it hard to share ideas and YouTube videos over email. “We needed a better way to share and access resources and to comment and share ideas based on them. And with Classroom, the girls are able to share videos, build ideas, and work collaboratively.” she said. “It really helps facilitate the work we are doing at our meetings and between them too!”

Managing school groups

Brazilian student Khin Baptista and his classmates at the Universidade Federal do Rio Grande do Sul (UFRGS) created a school club called GameDev Society UFRGS that hosts weekly discussions on topics such as design, art, and programming.

Baptista found Classroom when he was looking for an online tool to manage his growing group. “We have limited space available for our group meetings, but we have many more people interested in our activities. Google Classroom allows us to enroll participants who can easily access all the same resources we use in our meetings and get in touch with us and other group members,” he says.

The group is now using Classroom to inform members about upcoming lectures, share resources, and manage weekly tasks and assignments. They use the comments section of posts to help members with any questions they may have. After using Classroom for just a few weeks, Baptista says, “Its usability is amazing and we like how well integrated the web and mobile versions are. It's already very promising and seems like a perfect fit for us.”

Whether you’re an adult educator like Tony Vincent, a group leader like Khin Baptista, a teacher like Linda Scarth who’s using Classroom for extracurricular activities -- or you’re using Classroom in other creative ways, we’d love to hear your stories. You can submit them through this Google Form. And, as always, if you have further questions, check out our FAQ to learn more about these changes.

Source: Google Cloud


How British charity Comic Relief processed millions of UK pounds in seven hours on Red Nose Day

When you concentrate two years worth of fundraising into seven hours, every second counts. That’s the reality for Comic Relief, one of the U.K.’s most notable charities. Held every two years, Comic Relief’s Red Nose Day encourages the public to make the world a better place in the easiest way imaginable: by having a great time.

For this year’s fundraising event, Comic Relief turned to Google Cloud’s technology partner Pivotal to host its donation-processing systems. The platform also automated management of the underlying cloud infrastructure. Cloud services from Google Cloud Platform (GCP) were used to run Pivotal Cloud Foundry during Red Nose Day. In advance of the 2017 event, the charity was forecasting peaks of several hundred transactions a second for its online donation system. The stakes couldn’t have been higher.

We’re happy to report that Comic Relief raised over £73 million (and counting) for its marquee event! We caught up with David Laing, director of software engineering at Pivotal, to discuss running Pivotal Cloud Foundry on GCP for the 2017 event.

What kind of scale were you expecting for Red Nose Day?

Comic Relief does most of its two-year fundraising cycle in a seven-hour window. The donation system needed to scale with 100% uptime and reliability. It’s your classic elastic, spin-up/spin-down use case for the public cloud.

There are more than 14,000 call center reps that take donations via phone. The reps log donation details in the system. We also expected up to 100,000 concurrent web sessions, where individuals donate online. We expected nearly a million donations in all, with up to 300 donations a second.

What kind of apps did you run on Pivotal Cloud Foundry?

These were cloud-native applications, authored by consultancy Armakuni, in conjunction with Comic Relief. The apps used horizontally scalable, stateless microservices. Capturing donor information and processing their donation immediately is critical. This core availability requirement drove the architecture to have layers upon layers of redundancy. We hosted three independent shards of the full system in different datacenters spread over four countries and two continents, balancing traffic between them using DNS. Each shard then load balanced donations to multiple payment providers. Choosing availability over consistency and an “eventually consistent” architecture like this prepared us to continue to take donations in the event of multiple system failures. An async background process collected all the donation information to a central reporting shard.

What was it like working with GCP’s services?

At Pivotal, we love the performance and rapid provisioning of Compute Engine. The automated usage discounts on Google Cloud are so refreshing. You don’t need engineers to parse through consumption data to minimize your bill.

The load for Comic Relief is highly variable, with major consequences if performance suffers during traffic spikes. Unlike other clouds, GCP load balancers don't require a call to technical support to pre-warm. This saves our cloud admin's time and allows us to survive unexpected load increases. It gives us peace of mind knowing that GCP load balancers are built for scale, and backed up by the largest network of any cloud provider. In our experience, Google Cloud is able to handle traffic spikes that might stress other cloud providers.

We used Stackdriver Logging in our weekly capacity tests. We really liked its tight integration with BigQuery and Google Cloud Storage. Having the telemetry data stored in a massively scalable data analysis system helped us to analyze and pinpoint problematic areas ahead of time.

Identity management is another area where GCP shines. Since we already use G Suite for our corporate identity management, user management to all the GCP services was effortless.

How was the deployment of Pivotal Cloud Foundry on GCP? 

Both Pivotal and Google have invested a lot in making Cloud Foundry and GCP work well together. 

Pivotal Cloud Foundry

Deployment of Pivotal Cloud Foundry on Google Cloud “just worked.”  From the application’s perspective, Pivotal Cloud Foundry makes GCP look identical to other clouds; making multi-cloud deployment very simple. We followed the recommended deployment architecture and our reference architecture patterns for GCP.

red-dot-4

The only real work was in figuring out how many Compute Engine VMs were required to handle the expected traffic.

For mission-critical workloads—like this scenario with Comic Relief—multi-site availability is a common pattern. This often takes the shape of multi-cloud, as it did with Red Nose Day. What’s your guidance for organizations looking to move to this model?

Organizations need to evolve their application architectures following two key architectural patterns.  

The first is to adopt a microservices architecture that breaks an application into components that are stateless and stateful. Stateless components are easy to scale and distribute; so doing as much of the “work” in these components provides flexibility. Stateful components are harder to manage; so it’s good practise to minimise these and ensure your application degrades gracefully should one of these fail or stall.

The second is to follow 12 factor app principles and build each microservice so that it can be run on an infrastructure agnostic platform like Pivotal Cloud Foundry. Pivotal Cloud Foundry abstracts away all the differences between different clouds. This makes it trivial to deploy and run the exact same application artifacts in multiple clouds.

An application architected according to the above two principles allows an organisation to wire the full stack together based on performance needs as well as organisational and governance requirements. Most importantly, you get the flexibility to change quickly as requirements change.

Comic Relief—whose donations app is architected like this—can massively scale up the application to run on multiple clouds with multiple layers of redundancy for the seven hours of the year when donations peak. For the rest of the year, they can run a single copy of the donations application in a scaled-down form to minimize costs.

Since Pivotal Cloud Foundry makes all clouds look the same, Comic Relief gets to choose the best cloud provider(s) every year. Over the past five years the app has been run in a private data center and across three public clouds—all with no changes to the application code.

What was the multi-cloud experience like for the engineering teams supporting the event?

This is where Pivotal Cloud Foundry can really help. The platform makes all infrastructure targets look the same. For Comic Relief—and everyone for that matter—Pivotal Cloud Foundry abstracts away the  differences between running  on-premises  and running on GCP. Once the Pivotal Ops team figured out how to run Pivotal Cloud Foundry on GCP, there was basically no work involved for the app developers. They just had to target a new Pivotal Cloud Foundry endpoint and rerun cf-push to get their application running on GCP.

If something unexpected happened on Red Nose Day, the application operations team can simply remove the affected site from the DNS round-robin list. Traffic would be re-directed to the other installations while we calmly triaged the issue. Regardless, despite a potential disruption, we knew that donations would still be accepted and processed.

Want to learn more about how Pivotal and Google are collaborating? Check out the Cloud Native Roadshow in a city near you. To hear more from Comic Relief, please register for Google Cloud Next London May 3-4.

Source: Google Cloud


How British charity Comic Relief processed millions of UK pounds in seven hours on Red Nose Day

When you concentrate two years worth of fundraising into seven hours, every second counts. That’s the reality for Comic Relief, one of the U.K.’s most notable charities. Held every two years, Comic Relief’s Red Nose Day encourages the public to make the world a better place in the easiest way imaginable: by having a great time.

For this year’s fundraising event, Comic Relief turned to Google Cloud’s technology partner Pivotal to host its donation-processing systems. The platform also automated management of the underlying cloud infrastructure. Cloud services from Google Cloud Platform (GCP) were used to run Pivotal Cloud Foundry during Red Nose Day. In advance of the 2017 event, the charity was forecasting peaks of several hundred transactions a second for its online donation system. The stakes couldn’t have been higher.

We’re happy to report that Comic Relief raised over £73 million (and counting) for its marquee event! We caught up with David Laing, director of software engineering at Pivotal, to discuss running Pivotal Cloud Foundry on GCP for the 2017 event.

What kind of scale were you expecting for Red Nose Day?

Comic Relief does most of its two-year fundraising cycle in a seven-hour window. The donation system needed to scale with 100% uptime and reliability. It’s your classic elastic, spin-up/spin-down use case for the public cloud.

There are more than 14,000 call center reps that take donations via phone. The reps log donation details in the system. We also expected up to 100,000 concurrent web sessions, where individuals donate online. We expected nearly a million donations in all, with up to 300 donations a second.

What kind of apps did you run on Pivotal Cloud Foundry?

These were cloud-native applications, authored by consultancy Armakuni, in conjunction with Comic Relief. The apps used horizontally scalable, stateless microservices. Capturing donor information and processing their donation immediately is critical. This core availability requirement drove the architecture to have layers upon layers of redundancy. We hosted three independent shards of the full system in different datacenters spread over four countries and two continents, balancing traffic between them using DNS. Each shard then load balanced donations to multiple payment providers. Choosing availability over consistency and an “eventually consistent” architecture like this prepared us to continue to take donations in the event of multiple system failures. An async background process collected all the donation information to a central reporting shard.

What was it like working with GCP’s services?

At Pivotal, we love the performance and rapid provisioning of Compute Engine. The automated usage discounts on Google Cloud are so refreshing. You don’t need engineers to parse through consumption data to minimize your bill.

The load for Comic Relief is highly variable, with major consequences if performance suffers during traffic spikes. Unlike other clouds, GCP load balancers don't require a call to technical support to pre-warm. This saves our cloud admin's time and allows us to survive unexpected load increases. It gives us peace of mind knowing that GCP load balancers are built for scale, and backed up by the largest network of any cloud provider. In our experience, Google Cloud is able to handle traffic spikes that might stress other cloud providers.

We used Stackdriver Logging in our weekly capacity tests. We really liked its tight integration with BigQuery and Google Cloud Storage. Having the telemetry data stored in a massively scalable data analysis system helped us to analyze and pinpoint problematic areas ahead of time.

Identity management is another area where GCP shines. Since we already use G Suite for our corporate identity management, user management to all the GCP services was effortless.

How was the deployment of Pivotal Cloud Foundry on GCP? 

Both Pivotal and Google have invested a lot in making Cloud Foundry and GCP work well together. 

Pivotal Cloud Foundry

Deployment of Pivotal Cloud Foundry on Google Cloud “just worked.”  From the application’s perspective, Pivotal Cloud Foundry makes GCP look identical to other clouds; making multi-cloud deployment very simple. We followed the recommended deployment architecture and our reference architecture patterns for GCP.

red-dot-4

The only real work was in figuring out how many Compute Engine VMs were required to handle the expected traffic.

For mission-critical workloads—like this scenario with Comic Relief—multi-site availability is a common pattern. This often takes the shape of multi-cloud, as it did with Red Nose Day. What’s your guidance for organizations looking to move to this model?

Organizations need to evolve their application architectures following two key architectural patterns.  

The first is to adopt a microservices architecture that breaks an application into components that are stateless and stateful. Stateless components are easy to scale and distribute; so doing as much of the “work” in these components provides flexibility. Stateful components are harder to manage; so it’s good practise to minimise these and ensure your application degrades gracefully should one of these fail or stall.

The second is to follow 12 factor app principles and build each microservice so that it can be run on an infrastructure agnostic platform like Pivotal Cloud Foundry. Pivotal Cloud Foundry abstracts away all the differences between different clouds. This makes it trivial to deploy and run the exact same application artifacts in multiple clouds.

An application architected according to the above two principles allows an organisation to wire the full stack together based on performance needs as well as organisational and governance requirements. Most importantly, you get the flexibility to change quickly as requirements change.

Comic Relief—whose donations app is architected like this—can massively scale up the application to run on multiple clouds with multiple layers of redundancy for the seven hours of the year when donations peak. For the rest of the year, they can run a single copy of the donations application in a scaled-down form to minimize costs.

Since Pivotal Cloud Foundry makes all clouds look the same, Comic Relief gets to choose the best cloud provider(s) every year. Over the past five years the app has been run in a private data center and across three public clouds—all with no changes to the application code.

What was the multi-cloud experience like for the engineering teams supporting the event?

This is where Pivotal Cloud Foundry can really help. The platform makes all infrastructure targets look the same. For Comic Relief—and everyone for that matter—Pivotal Cloud Foundry abstracts away the  differences between running  on-premises  and running on GCP. Once the Pivotal Ops team figured out how to run Pivotal Cloud Foundry on GCP, there was basically no work involved for the app developers. They just had to target a new Pivotal Cloud Foundry endpoint and rerun cf-push to get their application running on GCP.

If something unexpected happened on Red Nose Day, the application operations team can simply remove the affected site from the DNS round-robin list. Traffic would be re-directed to the other installations while we calmly triaged the issue. Regardless, despite a potential disruption, we knew that donations would still be accepted and processed.

Want to learn more about how Pivotal and Google are collaborating? Check out the Cloud Native Roadshow in a city near you. To hear more from Comic Relief, please register for Google Cloud Next London May 3-4.

Source: Google Cloud


How LumApps and G Suite keep employees organized and informed

This year at Google Cloud Next, we recognized some of our partners for outstanding innovation. One of those partners, LumApps, received the “Solution Innovation of the Year” award for its corporate intranet and social platform for businesses. Deeply integrated with G Suite, LumApps houses resources like corporate news, social communities, employee directories and go-to G Suite apps—like Drive, Calendar or Gmail—all in one place. Check it out:

With LumApps, employees use single sign-on to securely access their corporate information and G Suite apps. Plus, it’s easy to search within the Google tools they use everyday because LumApps uses the power of Google Search to surface the right information when it’s needed.

“Our solution runs on Google Cloud Platform and we really appreciate the performance and scale that Google solutions offer,” says Elie Mélois, chief technology officer of LumApps. “Google's expertise in cloud service made it a clear choice for LumApps, which is why we decided to build on their reliable and powerful platform.”

Companies are using LumApps and G Suite to centralize resources and connect teams throughout their organizations. To learn more about how your business can use LumApps and G Suite, sign up for this free webinar on April 27, 2017 at 1pm ET/10am PT.

Source: Google Cloud


Google Cloud expands Education Grants Program to 30 additional countries

This month the Google Cloud team attended the Special Interest Group on Computer Science Education (SIGCSE), a conference that brings together 1,200 computer science (CS) professors from around the world. We had the chance to learn from professors who are leading CS innovation at more than 500 universities worldwide. At Google, we understand the critical role professors play in enabling students to build what’s next. Last summer we launched the Google Cloud Platform Education Grants for computer science for professors in the United States. We're excited to extend this program to 30 new countries across continental Europe, the UK, Israel, Switzerland and Canada.

University professors, who teach CS or related subjects and are from qualifying countries, can apply for grants to support their courses. Through the Google Cloud Platform (GCP) Education Grants program,  professors and their students can access GCP to use the same infrastructure, analytics and machine learning that we use across Google to power our innovation. Whether it’s launching an app seamlessly with Google App Engine or using our Cloud Machine Learning tools, including the popular Cloud Natural Language API or Cloud Vision API, you can incorporate Google’s state-of-the-art image recognition capabilities into web apps.

Computer science professors in certain European Union countries, the UK, Israel, Switzerland and Canada can apply here for Education Grants. Others interested in GCP for Higher Education should complete this form to stay up to date with the latest from Google Cloud.

We look forward to seeing the new ways professors and students will use their GCP Education Grants. We'll share stories about cool projects on this blog and our social channels.

Source: Google Cloud


Say bees! The buzz about Cloud Vision API

What do declining bee populations and machine learning have in common? Natural personal care brand Burt’s Bees hopes to plant 2 billion bee-nourishing wildflowers through its latest Bring Back the Bees campaign, and has enlisted the Cloud Vision API to help.

For every “selfless selfie” that bee lovers create, Burt’s Bees will plant 5,000 wildflower seeds in its home state of North Carolina, in hopes of restoring the furry pollinators’ habitat and food supply. The Burt’s Bees mobile-optimized site takes the selfie, overlays pictures of wildflowers onto it and encourages people to spread the word by sharing the image back to social media.  

burtsbees-1

But before Burt’s Bees can apply the wildflower filter, Cloud Vision API first analyzes the image to make sure it's a good fit. Its image recognition capabilities detect whether the image is in fact of a single face, and whether the face is appropriately centered in the frame. It also determines where on the frame the filter can add wildflowers, so that no one’s face is covered.

When done correctly, planting wildflowers can be a simple way to help declining worldwide bee populations. Likewise, using the Cloud Vision API is a simple approach to the difficult task of machine-assisted image recognition. Cloud Vision API provides developers with a drop-dead easy way to access the state-of-the-art machine learning models that Google artificial intelligence researchers have developed over decades. Cloud Vision API can easily detect objects, people, landmarks, logos and text, and describes those attributes in a web-friendly JSON format. Burt’s Bees #SelflessSelfie is just one—albeit very sweet—example of what Cloud Vision API can do.

To upload your own selfless selfie, visit selflessselfie.burtsbees.com, and to learn more about Cloud Vision API and other services, visit our Cloud Machine Learning page.

Source: Google Cloud