Tag Archives: google cloud

Cloud Covered: What was new in May on Google Cloud

May flowered with new products, technologies and learning resources from Google Cloud. Here’s a recap of May’s most popular posts on the Google Cloud blog. 

A new platform makes machine learning easier

At Google I/O, our annual conference for developers, we announced the general availability of Vertex AI, Google’s unified machine learning platform that allows companies to speed up the building, deployment and management of their artificial intelligence (AI) models. Because it requires far less coding to build custom models, Vertex AI can be used by data analysts and data scientists with varying levels of expertise. For example, a division of L'Oreal uses Vertex AI to create tools that let people “try on” beauty products online.

New data products come in threes

At our Data Cloud Summit, we introduced a number of new solutions to help organizations gain value from their data in support of their data cloud strategies. These include Dataplex, which allows organizations to centrally manage,  monitor and govern data across a variety of systems; Datastream, which allows companies to replicate data in real-time across heterogeneous databases, storage systems and applications reliably and with minimal latency; and Analytics Hub, which provides a way to access and share data and analytics models across organizational boundaries. 

A first-of-its-kind technology powers carbon-free energy

We announced a new technology that will help us reach our goal of operating on 24/7 carbon-free energy by 2030. Fervo is a next-generation geothermal project that will soon add carbon-free energy to the electric grid that powers our data centers and infrastructure throughout Nevada. Using fiber-optic cables inside wells, Fervo will gather information on flow, temperature and performance of the geothermal resource. Fervo will bring our data centers in Nevada closer to round-the-clock clean energy, and demonstrate how clean energy sources such as next-generation geothermal could eventually help replace carbon-emitting power sources around the world.

A video series teaches Anthos basics

Anthos is a managed application platform that extends Google Cloud services and engineering practices to development environments so you can modernize apps faster and establish operational consistency across them. To help you get started, we introduced the Anthos 101 video learning series, a great starting point for understanding the basics of Anthos and how to use it. Even better, you can watch the whole series of 11 episodes in less than an hour.

FAQs that clear up the clouds

Speaking of 101s, we also created a popular one with frequently asked questions about cloud computing. Do you want to learn the basics of containers, virtual machines, Kubernetes, data warehouses and more? The blog gives a quick rundown of common cloud computing terms and products. It’s just one guide available in our learning resources to help you understand cloud computing and start working with cloud-based tools and products. 

That’s a wrap for May. Stay tuned to the Google Cloud blog for all things cloud.

Introducing the Open Source Insights Project

Open Source Insights

Google has been working on software supply-chain security for many years, and transitive dependencies remain one of the most complex and least understood aspects. While we will be integrating this data into our Cloud and internal products in a variety of ways, we believe there is an immediate value in helping developers understand and visualize dependencies. Today, we are excited to share an exploratory visualization site: Open Source Insights, which provides an interactive view of the dependencies of open source projects.

Software development practices have evolved significantly over the last few years. Collaborative development with distributed feature development, consumption of open source and third-party packages, and publicly maintained software libraries have become commonplace, partly as a result of the widespread use of open source software. The advantages of open source are so clear that people and companies that would once have rejected OSS are now adopting it as a critical element of their environment.

But there are challenges brought by OSS too. The pace of change is electric, and it can be hard to keep up. The software packages that a large project depends on might update too frequently to keep a clear picture of what is happening. And those packages, in turn, can change their dependencies to provide new features or fix bugs. Security problems and other issues can arise unexpectedly in your project as a result, and the scale of the problem can make it all difficult to manage. Even a modest OSS project might depend on hundreds of packages.

There are tools to help, of course: vulnerability scanners and dependency audits that can help identify when a package is exposed to a vulnerability. But it can still be difficult to visualize the big picture, to understand what you depend on, and what that implies.

Open Source Insights provides a visualization of a project’s dependencies and their properties. Our exploratory website can be used to get an overview of how a particular software package is put together. Among other features, it provides interactive tools to visualize and analyze full, transitive dependency graphs. It also has a comparison tool to highlight how different versions of a package might affect your dependencies, perhaps by changing their own dependencies, adding licensing requirements, or fixing security problems.

Dependency graph for express 4.17.1

Open Source Insights shows you all this information about a package without asking you to install the package first. You can see instantly what installing a package—or an updated version—might mean for your project, how popular it is, find links to source code and other information, and then decide whether it should be installed. Insights also helps you see the importance of your project by showing the projects that depend on it: its dependents. Even a small project is important if a large number of other projects depend on it, either directly or through transitive dependencies.

Open Source Insights continuously scans millions of projects in the open source software ecosystem, gathering information about packages, including licensing, ownership, security issues, and other metadata such as download counts, popularity signals, and OpenSSF Scorecards. It then constructs a full dependency graph—transitively tracking dependencies, dependencies' dependencies, and so on—and incorporates the metadata, then publishes it so you can see how it all might affect your software. And the information it provides is continually updated.
Filtered dependency graph showing how eslint 7.27.0 depends on chalk 2.4.2 and 4.1.1

Filtered dependency graph showing how eslint 7.27.0 depends on chalk 2.4.2 and 4.1.1

This information can help visualize how software is put together, whether an update is worth doing, or how to fix a problem.

Today, Open Source Insights supports npm, Maven, Go modules, and Cargo. While we work on adding additional packaging systems, we want to hear from you: How could this data fit into your development workflow? What would make it more useful? You can reach the team at deps.dev to share your thoughts; we’ll be collecting feedback for the upcoming months and look forward to hearing your ideas on how best to improve supply-chain security.

Visit our website at deps.dev to try it out.

From the Google Cloud team: What this means for GCP’s open cloud

For users of open source software, this may be the first time you’re seeing dependency and vulnerability information in an organized and accessible way. If you’re using a managed service based on open source, it’s important to remember that you may not be affected by all vulnerabilities listed. Your provider may have taken steps to harden the products you use, and when a new vulnerability is disclosed, your provider may take responsibility for patching this on your behalf.

Google Cloud follows both these steps to help users get the benefits of open cloud while prioritizing security. Multiple layers of hardening create defense-in-depth, which helps protect services like Google Kubernetes Engine (GKE), Cloud Run and Cloud Functions from a container escape vulnerability. For components that are the user’s responsibility, we’re constantly rolling out new services—like GKE Autopilot—that automate these responsibilities.

We’re committed to protecting our customers, both through our patch rewards program and the recently launched cyber insurance partnership, the Risk Protection Program, which moves from shared responsibility to shared fate. We look forward to bringing our customers new information on their open source dependencies.

By Andrew Gerrand, Michael Goddard, Rob Pike and Nicky Ringland of the Open Source Insights Team

Helping Mulberry bag more customers during COVID-19

Something struck solutions architect Neill Randall in the first week he joined the iconic British fashion brand Mulberry. The company had access to an impressive amount of data, but it wasn’t being fully exploited.

Renowned for its leather craftsmanship, Mulberry’s made-to-last accessories are sold across 25 countries via 120 stores and its digital network. The brand’s diverse physical and online touch points meant it was producing data through many different channels. And yet it didn’t have a central solution to bring all this information together. It was against this backdrop that the company turned to Google for a solution.

“All the data at Mulberry was coming in at different times, from different silos, in different formats, into different systems, making it impossible to gain end-to-end visibility,” Neill explains. “To create a global view of our stock, products and customers, we needed to bring all that information together. Google Cloud made that possible.”

With a centralised data solution on Google Cloud, Mulberry was able to connect the dots between data that was previously scattered across different systems. This extra capability would be useful at the best of times, but it proved to be even more lucrative when the brand had to shut its doors during the UK’s lockdown in March 2020. 

Transforming its closed bricks-and-mortar stores into warehouses for online sales, Mulberry was able to add all products still out on the shop floors to the company’s digital channels.

The benefits quickly made their way to customers, who now had an even larger selection of products to choose from when shopping online. Better still, with an improved view of each order status, issues were easier to resolve and customers received their favourite Mulberry items faster than expected.

Full stock visibility coupled with fewer order issues and faster shipping led to a 25% boost in sales. Some of Mulberry’s stores even got back to their normal sales levels, despite COVID-19.

That wasn’t the only benefit the brand enjoyed thanks to our partnership. With more than 2.7 million customers and 5,000 products, Mulberry gains valuable insights from each purchase. Now, having established a centralised data view, Mulberry could take the customer relationship to the next level by using this data to tailor marketing campaigns and offer hyper-personalised product recommendations. 

As a result, the company saw an increased click-through rate by 37%, which led to an 110% increase in return on ad spend in general.

For Niell and the team, simplicity was high on the shopping list. “We managed to get up and running within days, and began to see the benefits quickly,” he recalls. “We are basically self-taught, which is a testament to how easy to use Google Cloud is.”

With the tools to make its products even more fashionable to customers, we’re excited to see what Mulberry does next. 


Create your own journaling app without writing code

Studies show that regularly writing down your thoughts and feelings can improve your mental, emotional and physical health. Despite all of journaling’s benefits, it can feel like an insurmountable challenge. 

While writing by hand is therapeutic for some, many may find it uncomfortable and tiring. Others may find an inventive way to leverage Google Doc, Keep, or Sheets to log their thoughts, but these tools are not optimized for the struggling journaler. In reality, the challenge may not be journaling itself but creating and customizing a routine that helps you get into a rhythm and document your day in the ways most useful to you.

A few months ago, I decided to put this theory to the test by building my own journaling app in AppSheet, Google Cloud’s no-code application development platform. It lets me customize my journaling experience the way I want, I was able to build the app without writing any code, and it’s been extremely useful.

Phone screenshots showing a custom journaling app created in AppSheet.

The journaling app, built with AppSheet, has a form that makes it easy for me to log my moods and activities, write a few notes, and add photos. I’ve also added a list and a calendar view so I can read through previous entries.

With AppSheet, anyone can create their own custom apps, connected directly to their data in Sheets — no technical background needed. To help you create your own journaling app, without writing a single line of code,  I’ve made a tutorial video.

And that’s just a starting point. From there, try adding your own customizations, like your own activities, notification and text message reminders and charts to show trends over time. 

AppSheet lets you build and use your own personal apps for free. For example, you can build a custom workout app to help track your progress at the gym or you can build an inventory management app to keep track of inventory at your local community events. These are just a few ideas, but feel free to explore our app templates library or start with your own ideas.

Hopefully creating a custom journaling app inspires you to start writing — and dive into no-code app building at the same time.

Ready to use AppSheet? Get started now.

Finding any Cartier watch in under 3 seconds

Cartier is legendary in the world of luxury — a name that is synonymous with iconic jewelry and watches, timeless design,  savoir-faire and exceptional customer service. 

Maison Cartier’s collection dates back to the opening of Louis-François Cartier’s very first Paris workshop in 1847. And with over 174 years of history, the Maison’s catalog is extensive, with over a thousand wristwatches, some with only slight variations between them. Finding specific models, or comparing several models at once, could take some time for a sales associate working at one of Cartier’s 265 boutiques — hardly ideal for a brand with a reputation for high-end client service. 

In 2020, Cartier turned to Google Cloud to address this challenge. 

An impressive collection needs an app to match 

Cartier’s goal was to develop an app to help sales associates find any watch in its immense catalog quickly. The app would use an image to find detailed information about any watch the Maison had ever designed (starting with the past decade) and suggest similar-looking watches with possibly different characteristics, such as price. 

But creating this app presented some unique challenges for the Cartier team. Visual product search uses artificial intelligence (AI) technology like machine learning algorithms to identify an item (like a Cartier wristwatch) in a picture and return related products. But visual search technology needs to be “trained” with a huge amount of data to recognize a product correctly — in this case, images of the thousands of watches in Cartier’s collections. 

As a Maison that has always been driven by its exclusive design, Cartier had very few in-store product images available. The photos that did exist weren’t consistent, varying in backgrounds, lighting, quality and styling. This made it very challenging to create an app that could categorize images correctly. 

On top of that, Cartier has very high standards for its client service. For the stores to successfully adopt the app, the visual product search app would need to identify products accurately 90% of the time and ideally return results within five seconds. 

Redefining Cartier’s luxury customer experience with AI technology

Working together with Cartier’s team, we helped them build a visual product search system using Google Cloud AI Platform services, including AutoML Vision and Vision API.

The system can recognize a watch’s colors and materials and then use this information to figure out which collection the watch is from. It analyzes an image and comes back with a list of the three watches that look most similar, which sales associates can click on to get more information. The visual product search system identifies watches with 96.5% accuracy and can return results within three seconds.

Now, when customers are interested in a specific Cartier watch, the boutique team can take a picture of the desired model (or use any existing photo of it) and use the app to find its equivalent product page online. The app can also locate products that look similar in the catalog, displaying each item with its own image and a detailed description that customers can explore if the boutique team clicks on it. Sales associates can also send feedback about how relevant the recommendations were so that the Cartier team can continually improve the app. For a deeper understanding of the Cloud and AI technology powering this app, check out this blog post

High-quality design and service never go out of style

Today, the visual product search app is used across all of the Maison’s global boutiques, helping sales associates find information about any of Cartier’s creations across its catalog. Instead of several minutes, associates can now answer customer questions in seconds. And over time, the Maison hopes to add other helpful features to the app. 

The success of this project shows it’s possible to embrace new technology and bring innovation while preserving the quality and services that have established Cartier as a force among luxury brands. With AI technology, the future is looking very bright. 

How The FA used tech to get the ball rolling

For millions of football fans across the U.K. and around the world, the return of live matches in the English Premier League was a long-awaited milestone in the recovery from the COVID-19 pandemic.


Enter Project Restart: the nickname given to the Premier League’s attempts to resume the season while ensuring the safety of players and fans. But with self-distancing as one of the key preventive measures against COVID-19, how could the safety of players be ensured when they’re interacting on the pitch? We at The Football Association (FA) were proud to have partnered with the Premier League to help in this aspect of the project.


A critical area addresses the challenge of ensuring players can interact at peak levels while observing the self-distancing norms still recommended by health authorities. To do this, we created a new analysis of thousands of hours of match play, and used machine learning technology to tell us about contact risk during a 90-minute football match.


We looked at all 380 games from the 2018/19 Premier League season, and the 288 pre-lockdown games from the 2019/20 Premier League season. Incredibly, this showed us over 40 billion interactions between players, captured in 100 million video frames which collectively made up 10 terabytes of data. Even the longtime players, coaches, and fans among us were staggered by how much goes on, even in one game.


Our system tracked players on the field at a rate of four-one hundreths of every second, ensuring we could analyse every interaction for concern about possible exposure. We employed the Exponential Model, developed by Danish public health academics, which at the time was considered the most accurate modelling of virus transmission during a football match. 


The model focuses on the 1.5 metre radius around each player, paying strict attention to the two second rate of decay, or half life, that COVID particles typically have in infecting a person in certain environmental conditions. Staying on the safe side, we employed a simplified model, which considered a player that is within two metres of an infected player during the half-life of the virus to be 100% exposed. 


As you may have guessed, all of this work involved gathering and analysing a tremendous amount of data from multiple sources, on some of the most advanced computing available. Working with Google Cloud, we used Google BigQuery to store the data and run a built-in machine learning model based on the simplified Model. BigQuery looked at an average of 145,000 rows of data per game analysed, examining every frame of tracking data for distance between all pairs of players on the pitch throughout an entire match. This fast and powerful toolset was critical to our success. 

What we concluded was good news: During a 90-minute football match, players spent on average a total of 90 seconds within a two-metre proximity of each other. Include goalkeepers into the calculation, and the average time decreases to 70 seconds. 


In other words: the risk factor of exposure to players was considered low, and we therefore determined that it was safe to keep the ball rolling. To be sure, players continue to be tested for symptoms of COVID infection before games, but this interaction data provides us with a critical level of reassurance.


It's great news, but it also reminds us that vigilant awareness and rigorous analytic insight help ensure not just a successful return to play, but a broader sense of confidence about the future of Premier League Football. We're building on a proud heritage of innovation, camaraderie and looking out for each other — the true heart of sport. 


The end result - we were able to keep the ball rolling

The end result - we were able to keep the ball rolling

Cloud Covered: What was new in April on Google Cloud

As many countries got a glimpse of post-COVID changes for life and work on the horizon, Google Cloud introduced new trainings, features, and products to help you make the most of what the future holds. Here’s our recap from last month’s most popular Google Cloud blog posts.

Google Cloud trainings help you increase your cloud skills at no cost.

Since January, we’ve introduced a number of no-cost training opportunities for you to grow your cloud computing knowledge and showcase your cloud skills. You can now see all the trainings from the first quarter of 2021 in one place. These included skills challenges in areas like data analytics and artificial intelligence, and events like Google Cloud OnBoards that offer introductions to the core components of Google Cloud. Other trainings explore specific Google Cloud products such as Looker and Google Kubernetes Engine (GKE). Check back regularly for the latest updates.

Visual cheat sheets illustrate Google Cloud products.

Last month we introduced a number of cheat sheets designed by Cloud Developer Advocate Priyanka Vergadia to help developers visually navigate important decisions. The cheat sheets cover topics like determining the best way to move your business to the cloud, options totransfer your data to the cloud or deciding on the best storage options for your business data. You can find colorful cheat sheets to guide you through scenarios for using Google Cloud products like Dataproc and VMware Engine. Finally, for those just getting started with the cloud or those looking to brush up on their cloud knowledge, check out this list that quickly summarizes every Google Cloud product in four words or less.

Three new products arrived to help you manage your documents.

We announced the general availability of three different Google Cloud products to help customers make the most of their documents. Document (Doc) AI platform

https://cloud.google.com/document-ai

 is a unified console for document processing that lets you quickly access all processors, tools and solutions. Lending DocAI helps mortgage brokers, banks and other financial institutions speed up the loan application process from weeks to days, dramatically reducing the cost of issuing a loan. Procurement DocAI helps businesses accelerate document processing for receipts, invoices and other important documents in the procurement cycle. All three products are built on decades of AI innovation at Google to bring powerful solutions to these challenges.

Boost your Workspace productivity with video tips.

We also introduced recent updates to the Google Workspace Productivity Tips video series to help Workspace users get the most out of Gmail, Meet, Docs, Sheets and Slides. The series of video topics walk you through mastering your inbox with Gmail’s right-click menu, asking Google Assistant to take notes, and filtering out distractions with noise cancellation in Meet. These videos come from Google’s productivity expert, Laura Mae Martin, and you can check out her entire series of videos online for more productivity tips. 

That’s a wrap for April. Stay tuned to the Google Cloud blog for all things cloud.

Woolaroo: a new tool for exploring indigenous languages

“Our dictionary doesn’t have a word for shoe” my Uncle Allan Lena said, so when kids ask him what to call it in Yugambeh, he’ll say “jinung gulli” - a foot thing.


Uncle Allan Lena is a frontline worker in the battle to reteach the Yugambeh Aboriginal language to the children of southeast Queensland, Australia, where it hasn’t been spoken fluently for decades and thus is – like many other languages around the world – in danger of disappearing.  


For the younger generation, even general language can be a challenge to understand, but it can be especially difficult to try to describe modern items using Indigenous languages like Yugambeh. For example in the Australian outdoors, it’s easy to teach children the words for trees and animals, but around the house it becomes harder. Traditional language didn't have a word for a fridge - so we say waring bin - a cold place. The same with a telephone - we call it a gulgun biral - voice thrower.


However, today’s technology can help provide an educational and interactive way to promote language learning and preservation.  I’m particularly proud for Yugambeh to be the first Australian Aboriginal language to be featured on Woolaroo, a new Google Arts & Culture experiment using the Cloud Vision API. 


The team behind the Yugambeh Museum has been working for three decades to help gather local language and cultural stories. Given the importance of Aboriginal language to Australian culture we have the incentive to record the known but in particular new words our community members are using as the world evolves bringing us new technology we didn’t have before.
An info graphic with numbers on the Yugambeh language

Woolaroo is open source and allows language communities like ours to preserve and expand their language word lists and add audio recordings to help with pronunciation. Today it supports 10 global languages including Louisiana Creole, Calabrian Greek, Māori, Nawat, Tamazight, Sicilian, Yang Zhuang, Rapa Nui, Yiddish and Yugambeh. Any of these languages are an important aspect of a community’s cultural heritage. 


Crucial to Indigenous communities is that Woolaroo puts the power to add, edit and delete entries completely in their hands. So people can respond immediately to newly remembered words and phrases and add them directly.


So if you, your grandparents or people in your community speak any of these languages – even if just a few words –  you can help to expand the growing coverage of Woolaroo.


We hope people will enjoy learning and interacting with a new language and  learn about the diversity of communities and heritage we all share together. 


Explore more on the Google Arts & Culture app for iOS and Android and at g.co/woolaroo.

Woolaroo: a new tool for exploring indigenous languages

“Our dictionary doesn’t have a word for shoe” my Uncle Allan Lena said, so when kids ask him what to call it in Yugambeh, he’ll say “jinung gulli” - a foot thing.


Uncle Allan Lena is a frontline worker in the battle to reteach the Yugambeh Aboriginal language to the children of southeast Queensland, Australia, where it hasn’t been spoken fluently for decades and thus is – like many other languages around the world – in danger of disappearing.  


For the younger generation, even general language can be a challenge to understand, but it can be especially difficult to try to describe modern items using Indigenous languages like Yugambeh. For example in the Australian outdoors, it’s easy to teach children the words for trees and animals, but around the house it becomes harder. Traditional language didn't have a word for a fridge - so we say waring bin - a cold place. The same with a telephone - we call it a gulgun biral - voice thrower.


However, today’s technology can help provide an educational and interactive way to promote language learning and preservation.  I’m particularly proud for Yugambeh to be the first Australian Aboriginal language to be featured on Woolaroo, a new Google Arts & Culture experiment using the Cloud Vision API. 


The team behind the Yugambeh Museum has been working for three decades to help gather local language and cultural stories. Given the importance of Aboriginal language to Australian culture we have the incentive to record the known but in particular new words our community members are using as the world evolves bringing us new technology we didn’t have before.
An info graphic with numbers on the Yugambeh language

Woolaroo is open source and allows language communities like ours to preserve and expand their language word lists and add audio recordings to help with pronunciation. Today it supports 10 global languages including Louisiana Creole, Calabrian Greek, Māori, Nawat, Tamazight, Sicilian, Yang Zhuang, Rapa Nui, Yiddish and Yugambeh. Any of these languages are an important aspect of a community’s cultural heritage. 


Crucial to Indigenous communities is that Woolaroo puts the power to add, edit and delete entries completely in their hands. So people can respond immediately to newly remembered words and phrases and add them directly.


So if you, your grandparents or people in your community speak any of these languages – even if just a few words –  you can help to expand the growing coverage of Woolaroo.


We hope people will enjoy learning and interacting with a new language and  learn about the diversity of communities and heritage we all share together. 


Explore more on the Google Arts & Culture app for iOS and Android and at g.co/woolaroo.

Google Developer Group Spotlight: A conversation with Cloud Architect, Ilias Papachristos

Posted by Jennifer Kohl, Global Program Manager, Google Developer Communities

The Google Developer Groups Spotlight series interviews inspiring leaders of community meetup groups around the world. Our goal is to learn more about what developers are working on, how they’ve grown their skills with the Google Developer Group community, and what tips they might have for us all.

We recently spoke with Ilias Papachristos, Google Developer Group Cloud Thessaloniki Lead in Greece. Check out our conversation with Ilias on Cloud architecture, reading official documentation, and suggested resources to help developers grow professionally.

Tell us a little about yourself?

I’m a family man, ex-army helicopter pilot, Kendo sensei, beta tester at Coursera, Lead of the Google Developer Group Cloud Thessaloniki community, Google Cloud Professional Architect, and a Cloud Board Moderator on the Google Developers Community Leads Platform (CLP).

I love outdoor activities, reading books, listening to music, and cooking for my family and friends!

Can you explain your work in Cloud technologies?

Over my career, I have used Compute Engine for an e-shop, AutoML Tables for an HR company, and have architected the migration of a company in Mumbai. Now I’m consulting for a company on two of their projects: one that uses Cloud Run and another that uses Kubernetes.

Both of them have Cloud SQL and the Kubernetes project will use the AI Platform. We might even end up using Dataflow with BigQuery for the streaming and Scheduler or Manager, but I’m still working out the details.

I love the chance to share knowledge with the developer community. Many days, I open my PC, read the official Google Cloud blog, and share interesting articles on the CLP Cloud Board and GDG Cloud Thessaloniki’s social media accounts. Then, I check Google Cloud’s Medium publication for extra articles. Read, comment, share, repeat!

How did the Google Developer Group community help your Cloud career?

My overall knowledge of Google Cloud has to do with my involvement with Google Developer Groups. It is not just one thing. It’s about everything! At the first European GDG Leads Summit, I met so many people who were sharing their knowledge and offering their help. For a newbie like me it was and still is something that I keep in my heart as a treasure

I’ve also received so many informative lessons on public speaking from Google Developer Group and Google Developer Student Club Leads. They always motivate me to continue talking about the things I love!

What has been the most inspiring part of being a part of your local Google Developer Group?

Collaboration with the rest of the DevFest Hellas Team! For this event, I was a part of a small group of 12 organizers, all of whom never had hosted a large meetup before. With the help of Google Developer Groups, we had so much fun while creating a successful DevFest learning program for 360 people.

What are some technical resources you have found the most helpful for your professional development?

Besides all of the amazing tricks and tips you can learn from the Google Cloud training team and courses on the official YouTube channel, I had the chance to hear a talk by Wietse Venema on Cloud Run. I also have learned so much about AI from Dale Markovitz’s videos on Applied AI. And of course, I can’t leave out Priyanka Vergadia’s posts, articles, and comic-videos!

Official documentation has also been a super important part of my career. Here are five links that I am using right now as an Architect:

  1. Google Cloud Samples
  2. Cloud Architecture Center
  3. Solve with Google Cloud
  4. Google Cloud Solutions
  5. 13 sample architectures to kickstart your Google Cloud journey

How did you become a Google Developer Group Lead?

I am a member of the Digital Analytics community in Thessaloniki, Greece. Their organizer asked me to write articles to start motivating young people. I translated one of the blogs into English and published it on Medium. The Lead of GDG Thessaloniki read them and asked me to become a facilitator for a Cloud Study Jams (CSJ) workshop. I accepted and then traveled to Athens to train three people so that they could also become CSJ facilitators. At the end of the CSJ, I was asked if I wanted to lead a Google Developer Group chapter. I agreed. Maria Encinar and Katharina Lindenthal interviewed me, and I got it!

What would be one piece of advice you have for someone looking to learn more about a specific technology?

Learning has to be an amusing and fun process. And that’s how it’s done with Google Developer Groups all over the world. Join mine, here. It’s the best one. (Wink, wink.)

Want to start growing your career and coding knowledge with developers like Ilias? Then join a Google Developer Group near you, here.