Google Cloud Platform Podcast

On the podcast this week, our guests Laurie White and Aaron Yeats talk with Stephanie Wong and Kelci Mensah about higher education and how Google Cloud is helping students realize their potential. As a former educator, Laurie has seen the holes in tech education and, with the help of Google, is determined to aid faculty and students in expanding learning to include cloud education as well as the standard on prem curriculum. Aaron and Laurie work together toward this goal with programs like their Speaker Series.

Laurie’s approach involves supporting faculty as they design courses that incorporate cloud technologies. With the busy lives of students today, she recognizes that the best way to get the information into the hands of students is through regular coursework, not just through elective activities outside the regular classroom.

Aaron’s work with students and student organizations rounds out their support of higher education learning. He facilitates the creation of student clubs that use Cloud Skills Boost, a program in which students navigate full pathways as they learn the skills they need to create and manage cloud builds. Soon, Aaron will offer hack-a-thons that encourage students to attend weekend events to work together on passion projects outside of regular classwork.

Our guests talk more about the specifics of Google Cloud Higher Education Programs and the importance of incorporating certifications into the higher education learning process. Aaron talks about expanding the program and his hopes for reaching out to more schools and students and Laurie talks about the funding for students and how Google Cloud’s system of credits for students enables them to use real cloud tools without a credit card. Laurie and Aaron tell us fun stories about past student successes, conference interactions, and hack-a-thon projects that went well.

Laurie taught CS in higher ed for over 30 years where her biggest frustration was trying to keep the curriculum up with the field. She thought she was retiring seven years ago but got the call from Google to a job where she could help faculty around the world keep their curriculum up with cloud computing, so here she is.

Aaron Yeats has been working in education outreach for two decades. His work in education has included Texas government education programs including public health, non-profit advocacy, and education.

• How Wayfair is reaching MLOps excellence with Vertex AI blog
• Hidden gems of Google BigQuery blog
• Google Cloud Innovators site
• Google Cloud and Apollo24|7: Building Clinical Decision Support System (CDSS) together blog

• Google Cloud Higher Education Programs site
• Google Cloud Speaker Series site
• Google Cloud Skills Boost site
• CSSI site
• Tech Equity Collective site
• GDSC site

Steph has been working on an AlphaFold video. You can learn more here.

Kelci is working on developing a Neos tutorial for introductory Google Cloud developers to learn how to write HTTP functions in Python all within the Google Cloud environment and wrapping up her summer internship with Google!

Stephanie Wong and Kelci Mensah

Stephanie Wong and Brian Dorsey are joined today by fellow Googlers Jaisen Mathai and Sara Ford to hear all about Cloud Functions (2nd gen) and how it differs from the original.

Jaisen gives us some background on Cloud Functions and why it was built. Supporting seven languages, this tool allows clients to write a function without worrying about scaling, devops, and a number of other things that are handled by Cloud Functions automatically. Customer feedback led to new features, and that’s how the second evolution of Cloud Functions came about. Don’t worry, first gen users! This will continue to be available and supported.

Features in the 2nd gen fit into three categories: performance, cost, and control. Among other benefits, costs stay low or may even be reduced with some of the new features, larger instances and longer processing times mean better performance, and traffic splitting means better control over projects. Sara details an example illustrating the power of the new concurrency features, and Jaisen helps us understand when Cloud Functions is the right choice for your project and when it’s not. Our guests walk us through getting started with Cloud Functions and using the 2nd gen additions.

Companies like Lucille Games are using Cloud Functions, and our guests talk more about how specific users are leveraging the new features of the 2nd gen.

Jaisen is a product manager for Cloud Functions. He’s been at Google for about six years and before joining Google was both a developer and product manager.

Sara is a Cloud Developer Advocate focusing on Cloud Functions and enjoys working on serverless.

• No pipelines needed. Stream data with Pub/Sub direct to BigQuery blog
• Cloud IAM Google Cloud blog
• The Diversity Annual Report is now a BigQuery public dataset blog

• Cloud Functions site
• Cloud Functions 2nd gen walkthrough video
• Cloud Functions version comparison docs
• Lucille Games: Playing to win with Google Cloud Platform site
• BigQuery site
• Cloud Run site
• Eventarc docs
• Cloud Shell site
• GCP Podcast Episode 261: Full Stack Dart with Tony Pujals and Kevin Moore podcast
• Working with Remote Functions docs
• Cloud Console site
• Where should I run my stuff? Choosing compute options video

Stephanie has been working on GCP Support Shorts.

Stephanie Wong and Brian Dorsey

Max Saltonstall and new host Anu Srivastava are in the studio today talking about Vertex Explainable AI with guests Irina Sigler and Ivan Nardini. Vertex Explainable AI was born from a need for developers to better understand how their models determine classifications. Trusting the operation of models for business decision making and easier debugging are two reasons this classification understanding is so important.

Explainable models help developers understand and describe how their trained models are making decisions. Google’s managed service, Vertex Explainable AI, offers Feature Attribution and Example Based Explanations to provide better understanding of model decision making. Irina describes these two services and how each works to foster better decision-making based on AI models. One or both services can be used in every stage of model building and to create a more precise model with better results. Example Based Explanations, Irina tells us, also makes it easier to explain the model to those who may not have strong technical backgrounds.

Ivan runs us through a sample build of a model taking advantage of the Vertex Explainable AI tools. Presets provide easier setup and use as well. We talk more about the benefits of being able to easily explain your models. When decision-makers understand the importance of your AI tool, it’s more likely to be cleared for production, for example. When you understand why your model is making certain choices, you can trust the model’s outcomes as part of your decision-making process.

Irina Sigler is a Product Manager on the Vertex Explainable AI team. Before joining Google, Irina worked at McKinsey and did her Ph.D. in Explainable AI. She graduated from the Freie Universität Berlin and HEC Paris.

Ivan Nardini is a customer engineer specialized in ML and passionate about Developer Advocacy and MLE. He is currently collaborating and enabling Data Science developers and practitioners to define and implement MLOps on Vertex AI. He also leads a worldwide hackathon community initiative and he is an active contributor in Google Cloud.

• Unify data lakes and warehouses with BigLake, now generally available blog
• What it’s like to have a hybrid internship at Google blog

• Vertex AI site
• Explainable AI site
• Vertex Explainable AI docs
• Vertex Explainable AI Notebooks docs
• Feature Attribution docs
• AI Explanations Whitepaper site
• Explainable AI with Google Cloud Vertex AI article
• Why you need to explain machine learning models blog

Anu just got back from a nice vacation and is picking back up on how to use our AI APIs with Serverless workflows. She’s working on some exciting tutorials for our AI backed Translation API.

Max just got back from family dance camp and is working to make excellent intern experiences.

Max Saltonstall and Anu Srivastava

We’re learning all about Arm servers on Google Cloud Platform this week. Hosts Brian Dorsey and Stephanie Wong welcome fellow Googlers Jon Masters and Emma Haruka Iwao to talk about the newest VMs on GCP.

To start, our guests dive in to Arm, explaining what it is and how it’s grown over the years. Nowadays, Arm-based chips dominate the mobile market and this volume has allowed them to build both advanced chips for supercomputers and beneficial partnerships. Emma explains how having the Arm architecture available in the cloud helps keep projects efficient and walks us through example setups of an Arm projects, illustrating the ease of setup in Google Cloud. Jon and Emma talk about the T2A VMs running Arm workloads at Google, including their balance of performance and cost.

Emma and Jon bust some myths about Arm, emphasizing how performant it is despite its humble beginnings.

Jon Masters is a compute architect focused on Arm server architecture, platform standards, and ecosystem with almost a dozen years of experience working on Arm.

Emma Haruka Iwao is a DevRel engineer focused on Compute products and a computer architecture enthusiast.

• Introducing Batch, a new managed service for scheduling batch jobs at any scale blog
• • Examples of Batch for Transcoding site
  • Using Google Kubernetes Engine’s GPU sharing to search for neutrinos blog

• Arm site
• Arm Documentation docs
• Arm VMs on Computer docs
• Expanding the Tau VM family with Arm-based processors blog
• Run your Arm workloads on Google Kubernetes Engine with Tau T2A VMs blog
• Compute Engine site
• GKE site

Brian is switching his focus from VMs to developer tooling.

Stephanie Wong and Brian Dorsey

Hosts Carter Morgan and Anthony Bushong are in the studio this week! We’re talking about Prometheus with guests Lee Yanco and Ashish Kumar and learning about the build process for Google Cloud’s Managed Service for Prometheus and how Home Depot uses this tool to power their business.

To begin with, Lee helps us understand what Managed Service for Prometheus is. Prometheus, a popular monitoring solution for Kubernetes, lets you know that your project is up and running and in the event of a failure, Prometheus lets you know what happened. But as Kubernetes projects scale and spread across the globe, Prometheus becomes a challenge to manage, and that’s where Google Cloud’s Managed Service for Prometheus comes in. Lee describes why Prometheus is so great for Kubernetes, and Ashish talks about CNCF’s involvement helps open source tools integrate easily. With the help of Monarch, Google’s Managed Service stands above the competition, and Lee explains what Monarch is and how it works with Prometheus to benefit users.

Ashish talks about Home Depot’s use of Google Cloud and the Managed Service for Prometheus, and how Home Depot’s multiple data centers make data monitoring both trickier and more important. With Google Cloud, Home Depot is able to easily ensure everything is healthy and running across data centers, around the world, at an immense scale. He describes how Home Depot uses Managed Service for Prometheus in each of these data center environments from the point of view of a developer and talks about how easy Prometheus and the Managed Service are to integrate and use.

Lee and Ashish wrap up the show with a look at how Home Depot and Google have worked together to create and adjust tools for increased efficiency. In the future, tighter integration into the rest of Google Cloud’s suite of products is the focus.

Lee Yanco is the Product Management lead for Google Cloud Managed Service for Prometheus. He also works on Monarch, Google’s planet-scale in-memory time series database, and on Cloud Monitoring’s Kubernetes observability experience.

Ashish Kumar is Senior Manager for Site Reliability and Production Engineering for The Home Depot.

• Cloud Next registration is open site
• Introducing Parallel Steps for Workflows: Speed up workflow executions by running steps concurrently blog
• How to think about threat detection in the cloud blog
• • GCP Podcast Episode 218: Chronicle Security with Dr. Anton Chuvakin and Ansh Patniak podcast

• Prometheus site
• PromQL site
• Google Cloud Managed Service for Prometheus docs
• Kubernetes site
• CNCF site
• Monarch: Google’s Planet-Scale In-Memory Time Series Database research
• Cloud Monitoring site
• Cloud Logging site
• Google Cloud’s operations suite site

Carter is focusing on getting organized, managing overwhelm, and comedy festivals.

Anthony is testing a few new exciting features, working with build provenance in Cloud Build, jobs and network file systems in Cloud Run.

Carter Morgan and Anthony Bushong

Stephanie Wong and Carter Morgan are back this week learning about Google’s Distributed Cloud Edge for telcos with guests Krishna Garimella and DP Ayyadevara. Launched last year, Google Distributed Cloud Edge has benefited companies across many industries. Today, our guests are here to elaborate on how telecommunications companies specifically are leveraging this powerful tool.

Because telcos deliver essential services, they tend to create detailed plans for their infrastructure in advance and stick with this setup for many years, DP tells us. Identifying the right tools for their project is vital, and Google has created and improved on many services to aid the telecommunications sector. Contact Center AI, for example, helps with customer service needs. Specifically, our guests elaborate on the modernization of telco networks through managed infrastructure offerings.

We learn more about Google Distributed Cloud Edge and the managed hardware and software stack that’s included. Container as a service for optimal network function is the first focus of Google in supporting telcos companies with Distributed Cloud and has been used for 5G rollouts. Google has been working behind the scenes to make Kubernetes more telco friendly as well, so that projects are more portable, scalable, and able to leverage Kubernetes benefits easily. Krishna gives us some great real-life examples of telecommunications companies using GDC Edge in areas like virtual broadband networks. In order to dedicate maximum resources to customer workloads, the team chose to keep the Kubernetes control plane in the cloud while worker nodes are at the edge. With superior security protection, minimal service disruption, and more, GDC Edge boasts fleet management as a core capability.

In order to continue satisfying telco’s needs, Google collaborates with many businesses to grow with changing customer needs.

Krishna is a technology evangelist who has worked with service providers across the globe in the network and media areas.

DP is the Product Group Product Manager leading Telco Network Modernization products and solutions at Google Cloud.

• Cloud TPU v4 records fastest training times on five MLPerf 2.0 benchmarks blog
• Show off your cloud skills by completing the #GoogleClout weekly challenge blog

• Distributed Cloud site
• Distributed Cloud Edge Documentation docs
• Contact Center AI site
• Kubernetes site
• Anthos site
• Nephio site
• BigQuery site
• Vertex AI site

Carter made a test for a video recap version of the recent pi episode.

Stephanie recently made a pi video as well and is working on an Alphafold video and the Cloud client library new reference docs homepage rollout.

Carter Morgan and Stephanie Wong

Your hosts Max Saltonstall and Carter Morgan talk with guests Cody Ault and Jo-Anne Bourne of Veeam. Veeam is revolutionizing the data space by minimizing data loss impacts and project downtime with easy backups and user-friendly disaster recovery solutions.

As a software company, Veeam is able to stay flexible with its solutions, helping customers keep any project safe. Cody explains what is meant by disaster recovery and how different systems might require different levels of fail-safe protection. Jo-Anne talks about the financial cost of downtime and how Veeam can help save money by planning for and preventing downtime. Veeam backup and replication is the main offering that can be customized depending on workloads, Cody tells us. He gives examples of how this works for different types of projects. Businesses can easily make plans for recovery and data backups then implement them with the help of Veeam. Cody talks about cloud migration and how Veeam can streamline this process with its replication services, and Jo-Anne emphasizes the importance of these recovery processes for data in the cloud.

The journey from fledgling Veeam to their current suite of offerings was an interesting one, and Cody talks about this evolution, starting with the simple VM backups of version 5. As companies have brought new recovery challenges, Veeam has grown to provide these services. Their partnership with Google has grown as well, as they continue to leverage Google offerings and support Google Cloud customers. We hear examples of Veeam customers and how they use the software, and Cody tells us a little about the future of Veeam.

Cody has been at Veeam for over 11 years in various roles and departments including Technical Lead for US Support team, Advisory Architect for Presales Solutions Architect and Staff Solutions Architect for Product Management Alliances. He has acted as the performance, databases, security, and monitoring specialist for North America for the Presales team and has helped develop the Veeam Design Methodology and Architecture Documentation template. Cody is currently working with the Alliances team focusing on Google Cloud, Kubernetes and Red Hat.

Jo-Anne is a Partner Marketing Strategist who works with global companies to support them in positioning company products with their customer base. She is effective in developing strategic partnerships with International Resellers, CCaaS partners, Systems Integrators, OEM partners and ISV partnerships like Amazon, Microsoft, Avaya, Cisco, Five9, BT to develop strategies to enable sales teams to generate significant revenue and in turn, build profitability for the company. Jo-Anne is a brand steward successful in using analytics to create results-driven campaigns that increase brand awareness, generate sales leads, improve customer engagement and strengthen partner relationships.

• Announcing general availability of reCAPTCHA Enterprise password leak detection blog
• Cloud Podcasts site
• Bio-pharma organizations can now leverage the groundbreaking protein folding system, AlphaFold, with Vertex AI blog

• Veeam site
• Veeam for Google Cloud site
• VeeamHub site
• Google Cloud VMware Engine site
• Cloud SQL site
• Kasten site
• Kubernetes site
• GKE site

Carter is working on the new Cloud Podcasts website.

Max is working on research papers about how we built and deployed Google’s Zero Trust system for employees, BeyondCorp.

Kelci is working on creating a series of blog posts highlighting the benefits of having access to public data sets embedded within BigQuery.

Carter Morgan and Max Saltonstall

This week on the GCP Podcast, Carter Morgan and Max Saltonstall are joined by Amit Kumar and Vasili Triant. Our guests are here to talk about new features in Contact Center AI.

Amit starts the show helping us understand what Contact Center as a Service is and what makes this unified platform so useful for enterprise companies. The scalability helps keep costs down and overall satisfaction up while leveraging advances in cloud. UJET and Google Cloud have worked together to bring this AI advancement, and our guests describe the partnership and evolution CCAI. CCAI has streamlined the Contact Center as a Service space, helping businesses work efficiently and while putting an emphasis on positive experiences for the end customer.

CCAI users can use the platform straight out of the box or customize it to build specific experiences with tools like Dialogflow. Amit further describes the tools available like Interactive Voice Response and for which circumstances each tool would be most useful. The journey to CCAI can be easily managed by a team who knows the business well. We learn more about the onboarding experience and the skills required to transition.

Vasili talks about the past and future of Contact Center and how customer information is used not just for sales purposes but for bettering the customer service experience. Our guests share success stories from companies like FitBit and how CCAI is used to handle customer interactions through the app. Things like the call back feature save customers the time and frustration of waiting on hold and save businesses money.

Amit is responsible for bringing GCP’s native CCaaS offering to market and helps enterprise customers modernize their contact centers. Previously, Amit worked as a Cloud AI Incubator lead where he helped customers in adopting Google’s conversational AI technology. He also has an extensive background in large scale cloud transformational efforts and have worked with enterprise software companies mainly Salesforce and TIBCO Software.

As UJET’s Chief Operating Officer, Vasili Triant oversees all Go To Market activities including Sales, Channel, Alliances, and Customer Success. Triant brings more than 20 years of experience in Telecoms, Unified Communications (UC), and Contact Center industries, having previously served as VP/GM of Contact Center at Cisco, where he achieved the fastest growth in over a decade through a focus on global alliances and enterprise cloud-readiness.

• DALL-E mini site
• EbSynth site
• Announcing general availability of Confidential GKE Nodes blog

• Contact Center AI Platform site
• Contact Center AI reimagines the customer experience through full end-to-end platform expansion blog
• UJET site
• Dialogflow site
• Google Assistant site
• One United Bank site
• FitBit site

Max is working on expanding the podcast platform by collecting and adding more content.Carter is working on his Google Project Management: Professional Certificate.Kelci has been working on Google Cloud Skills Boost.

Carter Morgan and Max Saltonstall

Carter Morgan and Brian Dorsey are working on their math skills today with guests Emma Haruka Iwao and Sara Ford. What kind of computing power does it take to break the world record for pi computations? Emma and Sara are here to tell us.

Emma tells us how she started with pi and how she and Sara came to work together to break the record. In 2019, Emma was on the show with her previous world record, and with the advancements in technology and Google products since, she knew she could do even more this year. Her 100 trillion digit goal wasn’t enough to scare people away, and Sara, along with other partners, joined Emma on the pi computation journey. Together, Sara and Emma talk about the hardware required, building the algorithm, how it’s run, and where the data is stored. Running on a personal computer was cheaper and easier than a super computer, and Emma explains why. Performing these immense calculations can also help illustrate just how far computers have come.

The storage required for this project was immense, and Emma tells us how they worked around some of the storage limitations. We hear more about Ycruncher and how it was used to help with calculations. Our guests talk about how things might change for computing and specifically for pi computations in the next few years, and Sara tells us about the storage journey from the perspective of a mathematician, and gives us some interesting facts about the algorithms involved, and we learn how world records are verified.

Emma is a developer advocate for Google Cloud Platform, focusing on application developers’ experience and high performance computing. She has been a C++ developer for 15 years and worked on embedded systems and the Chromium Project. Emma is passionate about learning and explaining the most fundamental technologies such as operating systems, distributed systems, and internet protocols. Besides software engineering, she likes games, traveling, and eating delicious food.

Sara Ford is a Developer Advocate on Google Cloud focusing on Serverless. She received a Masters degree in Human Factors (UX) because she wants to make dev tools more usable. Her lifelong dream is to be a 97-year old weightlifter so she can be featured on the local news.

• New Cloud Podcasts Website site
• Even more pi in the sky: Calculating 100 trillion digits of pi on Google Cloud blog

• GCP Podcast Episode 167: World Pi Day with Emma Haruka Iwao podcast
• pi.delivery 100 Trillion Digits site
• pi.delivery Github site
• A History of Pi book
• Distributing historically linear calculations of Pi with serverless video
• Ycruncher site
• Compute Engine site
• Cloud Functions site
• SRE site
• Terraform site

Carter and Brian are working on a new season of VM End to End

Carter Morgan and Brian Dorsey

On the podcast this week, guest Joe Daly tells Stephanie Wong, Mark “Money” Mirchandani, and our listeners all about FinOps principles and how they’re helping companies take advantage of the cloud while saving their bottom lines. He describes FinOps as financial DevOps, making financial decisions in an effective and optimized way. With his experience in finance and tax accounting, Joe has developed a special knack for navigating the sometimes confusing world of cloud finance policies, and his contributions to the FinOps Foundation have been many.

For starters, collaboration with various business departments is important for developing a plan that leverages the benefits of the cloud but keeps the company using resources wisely, Joe explains. He talks about the FinOps Foundation and their focus on creating community for knowledge sharing. By fostering collaboration among different company roles and promoting financial education, companies are better able to determine financial goals while making sure each facet of the company reaps all the benefits of cloud participation.

Following the FinOps cycle is the easiest way for community members to get started. The three steps, Joe tells us, are inform, optimize, and operate. The inform phase involves clarity in spending so teams understand how much money is being spent. In the optimize phase, benefits of spending are matched with expenditures to ensure resources are being used to their full potential. Finally, in the operate phase, engineers and finance managers come together to understand why solutions were chosen and understand if these tools are offering the right answers for the company.

Every company is different but the sooner it’s possible to start the FinOps journey the easier it will be to maintain in the future. Joe gives us examples of how companies are using the principles for successful strategies and the challenges that some of them have faced. The Foundation has monthly summits that offer perspectives from these companies as well as partner presentations. The FinOpsX conference is coming up soon as well. To wrap up, Joe offers other resources from the FinOps Foundation, including his podcast.

Joe set up two FinOps teams at Fortune 100 companies. He joined the FinOps Foundation and has been setting up the ambassador program, supporting meetup groups, and producing FinOpsPod.

• AlloyDB for PostgreSQL under the hood: Columnar engine blog
• • GCP Podcast Episode 304: AlloyDB with Sandy Ghai and Gurmeet “GG” Goindi podcast
• How Google Cloud is helping more startups build, grow, and scale their businesses blog
• Automate identity document processing with Document AI blog

• FinOps Foundation site
• FinOpsX site
• FinOpsPod podcast
• Cloud FinOps: The Secret To Unlocking The Economic Potential Of Public Cloud whitepaper
• Maximize Business Value with Cloud FinOps whitepaper
• Unlocking the value of cloud FinOps with a new operating model whitepaper

Stephanie Wong and Mark Mirchandani

Stephanie Wong and Lorin Price welcome guests Zach Seils and Manasa Chalasani to talk about networking and the newly released Network Analyzer. Google Cloud’s Network Intelligence Center is described as a one-stop shop that simplifies network monitoring, troubleshooting, workload expansion, security, and more. Manasa tells us about the four modules of Network Intelligence Center and how they work together.

As part of Network Intelligence Center, the new Network Analyzer monitors and proactively runs tests and detects issues on the network automatically, taking the guesswork out of network troubleshooting. Network Analyzer checks the entire network ecosystem, finding any connectivity issues and extrapolating them to other similar situations as well. Zach tells us more about the specific features of Analyzer, like its ability to check for overlapping or shadowed routes and validating network configurations in relation to any managed services being used.

Zach walks us through the set up of Network Analyzer and how to navigate results. Manasa expands on the development of Network Analyzer, including how customer feedback really shaped the project, and we hear about challenges along the way. Through examples, Zach describes different types of Analyzer customers and how they’re using the product. More analyzers will be available soon, and the team is open to suggestions for future projects.

Zach Seils is a Networking Specialist with Google Cloud, where he works with customers to accelerate their adoption of cloud networking.

Manasa is a Product Manager on the Google Cloud Networking team with a focus on network observability.

• The new Google Cloud region in Columbus, Ohio is open blog
• Assembling and managing distributed applications using Google Cloud Networking solutions blog

• Network Intelligence Center site
• Network Analyzer Documentation docs
• Introducing Network Analyzer: One stop shop to detect service and network issues blog
• CloudSQL site
• GKE site
• Cloud Monitoring site
• Contact the Network Analyzer team email
• GCP Podcast Episode 270: Traditional vs. Service Networking with Ryan Przybyl podcast

Lorin is working on a new video series called Concepts of Networking on the Networking End to End Playlist

Stephanie Wong and Lorin Price

Kaslin Fields and Mark Mirchandani learn how GKE manages their releases and how customers can take advantage of the GKE release channels for smooth transitions. Guests Abdelfettah Sghiouar and Kobi Magnezi of the Google Cloud GKE team are here to explain.

With releases every four months or so, Kobi tells us that Kubernetes requires two pieces to be managed with each release: the control plane and the nodes. Both are managed for the customer in GKE. The new addition of release channels allows flexibility with release updating so customers can adjust to their specific project needs. Each channel offers a different updating mix and speed, and clients choose the channel that’s right for their project. The idea for release channels isn’t a new one, Kobi explains. In fact, Google’s frequent project releases, while keeping things secure and running well, also can be customized by choosing from an assortment of channels in other Google offerings like Chrome.

Our guests talk us through the process of releasing through channels and how each release marinates in the Rapid channel to be sure the version is supported and secure before being pushed to customers through other channels. We hear how release channels differ from no-channel releases, the benefits of specialized channels, and recommendations for customers as far as which channels to use with different development environments. Abdel describes real-world use cases for the Rapid, Regular, and Stable channels, the Surge Upgrade feature, and how GKE notifications with Pub/Sub helps in the updating process. Kobi talks about maintenance and exclusion windows to help customers further customize when and how their projects will update.

Kobi and Abdel wrap up with a discussion of the future of GKE release channels.

Kobi is the Product Manager for GKE at Google Cloud.

Abdel is a Cloud Dev Advocate with a focus on Cloud native, GKE, and Service Mesh technologies.

• GKE Essentials videos
• KubeCon EU 2023 site
• KubeCon Call for Proposals site
• Kubernetes 1.24: Stargazer site
• • GCP Podcast Episode 292: Pulumi and Kubernetes Releases with Kat Cosgrove podcast
• Optimize and scale your startup on Google Cloud: Introducing the Build Series blog

• Kubernetes site
• GKE site
• Autoscaling with GKE: Overview and pods video
• GKE release schedule dcos
• Release channels docs
• Upgrade-scope maintenance windows docs
• Configure cluster notifications for third-party services docs
• Cluster notifications docs
• Pub/Sub site
• Agones site

Kaslin is working on KubeCon and new episodes of GKE Essentials.

Mark Mirchandani and Kaslin Fields

AlloyDB for PostgreSQL has launched and hosts Mark Mirchandani and Gabe Weiss are here this week to talk about it with guests Sandy Ghai and Gurmeet Goindi. This fully managed, Postgres compatible database for enterprise use combines the power of Google Cloud and the best features of Postgres for superior data management.

AlloyDB began years ago as a solution to help manage huge data migrations to the cloud. Customers needed a way to take advantage of the benefits of cloud, modernizing their databases as they migrated in an easy, flexible, and scalable way. Databases had to maintain performance and availability while offering enterprise customers optimal security features and more. We learn why PostgreSQL is important in the equation and how AlloyDB is built with Google scaling abilities and ML while supporting open source compatibility.

We talk about data analytics workloads and how AlloyDB handles in-the-moment analytics needs. Our guests describe and compare different database offerings at Google, emphasizing the solutions that set AlloyDB apart. We chat about the types of projects each database is best suited for and how AlloyDB fits into the Google database portfolio. We hear examples of customers moving to AlloyDB and how they’re using this new service. Clients have been leveraging the embedded ML features for better data management.

Sandy is a product manager on GCP Databases and has been working on the AlloyDB team since the beginning.

GG is a product manager at Google, where he focuses on databases and attends meetings. Prior to joining Google, GG led product management for Exadata at Oracle, where he also worked on databases and attended meetings. GG has had various product management, management, and engineering roles for the last 20 years in Silicon Valley, but his favorite meetings have been at Google. He holds an MBA from the University of Chicago Booth School of Business.

• Google I/O site
• Introducing “Visualizing Google Cloud: 101 Illustrated References for Cloud Engineers and Architects” blog
• Meet the people of Google Cloud: Priyanka Vergadia, bringing Google Cloud to life in illustrations blog
• Working with Remote Functions docs

• AlloyDB for PostgreSQL site
• AlloyDB Documentation docs
• AlloyDB for PostgreSQL under the hood: Intelligent, database-aware storage blog
• PostgreSQL site
• Introducing AlloyDB for PostgreSQL video
• Introducing AlloyDB, a PostgreSQL-compatible cloud database service video
• BigQuery site
• Spanner site
• CloudSQL site

Gabe is working on some exciting content to support landing the AlloyDB launch.

Mark Mirchandani and Gabe Weiss

This week, Googler Denise Pearl and NGIS Executive Director Nathan Eaton join hosts Alexandrina Garcia-Verdin and Donna Schut to talk about how modern technology and data collection can significantly enhance environmental protection practices.

Denise starts the show with a thorough explanation of geospatial awakening and how Google is making its backend geo services like Google Earth Engine more usable for Google Cloud customers. With better data, easier access, and substantially more cloud compute power, companies are awakening to the possibilities of geospatial driven projects that analyze not just text but photographic data as well. Thousands of satellites collect information about Earth every day, and companies are realizing just how much of this data is available for their own sustainability, geo-centric, and location-based projects. Geospatial, Nathan explains, can help combine layers of text and photo data based on one location for a richer, more robust view of a particular location in real time.

As a geospatial partner with Google for a decade, NGIS has had experience using Earth Engine, Google Maps, and more to help Google Cloud customers use this data in meaningful ways. Because most projects involve analyzing locations as they change over time, companies need massive storage and processing power for their data. This is only made possible with the recent advances in infrastructure afforded by the cloud. With these amazing advances in technology, Denise and Nathan are seeing more and more exciting use cases. Companies are taking this data and making meaningful decisions for their future and the future of the planet. Sustainability goals like limiting deforestation in the supply chain can be made and measured. Climate change models can be created and applied. And all of this can be done quickly.

Nathan and Denise talk about TraceMark, the sustainable sourcing solution built by NGIS and made to integrate flexibly with customer projects. Consumers are increasingly aware of their affect on the environment and are pushing for change. With TraceMark, companies are able to see the environmental impact of their supply chain partners and make changes in line with customer values. These decisions can influence the growth of the company as well, as suppliers are vetted and chosen based on sustainability and availability. We hear about the building of TraceMark and the challenges the team overcame. Denise runs through some features of the software and how users can take advantage of them. Our guests give some great tips for organizations to get started with their data-driven sustainability goals, and Nathan talks about what’s next with NGIS and TraceMark.

As Executive Director at NGIS, Nathan has worked with hundreds of clients to deliver fit for purpose, innovative solutions. Nathan leads our GIS capabilities and stakeholder management including consulting with a range of large multinational companies and federal government departments. Most recently, Nathan has led the development, build and launch of TraceMark, a SaaS sustainable sourcing solution from NGIS, Google Cloud and partners Planet and CARTO.

Denise Pearl leads strategic ISV efforts for Google Cloud’s Geospatial, Earth Observation and Sustainability vertical. Her primary focus is to align engineering, marketing and sales teams within Google around the issues that matter to enterprise customers and government agencies enabling the use of technology to better solve sustainability challenges communities face across the globe.

• Planet and People AI Series videos
• Planet and People AI: Mapping carbon pollution globally with satellites video
• Geobeam site

• GCP Podcast Episode 282: Geospatial Cloud and Earth Engine with Chad Jennings and Joel Conkling podcast
• Google Earth Engine site
• NGIS site
• NGIS and TraceMark site
• TraceMark site
• EO Data Science site
• EO Data Science GEE Impact site
• The technology and climate science helping CPG brands with sustainable sourcing blog
• Adopting real-world sustainability solutions with Google Cloud’s ecosystem blog
• Achieve Your Sustainability Goals with the Google Cloud Ecosystem site
• The data-driven path to real-world sustainability solutions whitepaper
• It takes an ecosystem: How the Google Cloud Partner Initiative speeds the transition to enterprise sustainability article
• Google Cloud Sustainability Summit site
• BigQuery site

Dana is focusing on geospatial analytics, helping customers achieve their sustainability goals. She’s building solutions that solve repeatable problems.

AGV is getting ready for the Cloud Sustainability Summit on June 28th.

Alexandrina Garcia-Verdin and Donna Schut

Stephanie Wong and Debi Cabrera are learning all about BigLake from guests Gaurav Saxena and Justin Levandoski of the BigQuery team.

BigLake offers unified data management from both data warehouses and data lakes. What exactly is the difference between a data warehouse and a data lake? Justin explains what a data lake is, how they came to be, and the benefits. Each data option has its cons too, like the limitations of data lakes for enterprise use. Enter BigLake built on BigQuery, which helps enterprise clients manage and analyze their data from both data warehouses and data lakes. The best features of BigQuery are now available for Google Cloud Storage and across multi-cloud solutions.

Guarav describes BigLake behind the scenes and how the principles of BigQuery’s data management can now be used for open file formats in BigLake. It’s BigQuery for more data formats, Justin explains. BigLake solves many data problems quickly with a special emphasis on improving security. Our guests talk specifically about clients who gain the most from using BigLake, especially those looking to analyze distributed data and those who need easy and fast security and compliance solutions. With tightened security, BigLake offers access delegation and secure APIs that work over object storage. We hear about the user experience and how easy it is to get started, especially for customers already familiar with and using other GCP products.

Google’s advocacy of open source projects means many clients are coming in with workloads built with open source software. BigLake supports multi-cloud projects so that tables can be built on top of any data system. No matter the format of your data, you can run analytics with BigLake. We talk more about the security features of BigLake and how easy it is to unify data warehouses and data lakes with optimal data security.

The customers have helped shape BigLake, and Gaurav describes how these clients are using this data software. We hear about integration with BigQuery Omni and Dataplex and how BigLake is different. In the future, Google will continue to make simple, effective solutions for data management and analytics, building further off of BigQuery.

Gaurav Saxena is a product management lead at Google BigQuery. He has 12+ years of experience building products at the intersection of cloud, data and AI. Before Google, Gaurav led product management at Microsoft Azure and Amazon Web Services for some of the most widely used cloud offerings in storage and data.

Justin is a tech lead/manager in BigQuery leading BigLake and other projects pushing the frontier of BigQuery. Prior to Google, just worked on Amazon Aurora and was part of the Database research group at Microsoft Research.

• Your ultimate guide to Speech on Google Cloud blog
• Announcing the Climate Innovation Challenge—grants to support cutting-edge earth research blog

• BigLake site
• BigQuery site
• Cloud Storage site
• Spark site
• Apache Ranger site
• BigQuery Omni docs
• Apache Iceberg site
• Delta Lake site
• Presto site
• TensorFlow site
• Dataplex site

Debi is working on a series about automatic DLP. Cloud Data Loss Prevention is now automatic and allows you to scan data across your whole org with the click of one button!

Stephanie Wong and Debi Cabrera

This week, we’re busting myths around Cloud Spanner with our guests Pritam Shah and Vaibhav Govil. Mark Mirchandani and Max Saltonstall host this episode and learn about the fantastic capabilities of Cloud Spanner. Our guests give us a quick run-down of Spanner database software and its fully-managed offerings.

Spanner’s unique take on the relational database has sparked some myths. We start by addressing cost and the idea that Spanner is expensive. With its high availability achieved through synchronously replicating data, failures are virtually a non-issue, making the cost well worth it. Our guests describe other features that add to the value of Spanner as well. Workloads of any size are a good fit for Spanner because of its scalability and pricing based on use.

Despite rumors, Spanner is now very easy to start using. New additions like the PostgreSQL interface and ORM support have made the usability of Spanner much more familiar. Regional and multi-regional instances are supported, busting the myth that Spanner is only good for global workloads. Our guests offer examples of projects using local and global configurations with Spanner.

In the database world, Vaibhav sees trends like the convergence of non-relational and relational databases as well as convergence in the OLTP and OLAP database semantics, and he tells us how Spanner is adapting and growing with these trends. Pritam points out that customers are paying more attention to total cost of ownership, the importance of scalable and reliable database solutions, and the peace of mind that comes with a managed database system. Spanner helps customers with these, freeing up business resources for other things.

This year, Spanner has made many announcements about new capabilities coming soon, like PostgreSQL interface on spanner GA, Query Insights visualization tools, cross-regional backups GA, and more. We hear all about these awesome updates.

Pritam is the Director of Engineering for Cloud Spanner. He has been with Google for about four and a half years. Before Spanner, he was the Engineering Lead for observability libraries at Google. That included Distributed Tracing and Metrics at Google scale. His mission was to democratize the instrumentation libraries. That is when he launched Open Census and then took on Cloud Spanner.

Vaibhav is the Product lead for Spanner. He has been in this role for the past three years, and before this he was a Product Manager in Google Cloud Storage in Google. Overall, he has spent close to four years at Google, and it has been a great experience.

• Our plans to invest $9.5 billion in the U.S. in 2022 blog
• A policy roadmap for 24⁄7 carbon-free energy blog
• SRE Prodcast site
• Meet the people of Google Cloud: Grace Mollison, solutions architect and professional problem solver blog
  • GCP Podcast Episode 224: Solutions Engineering with Grace Mollison and Ann Wallace podcast

• Spanner site
• Cloud Spanner myths busted blog
• PostgreSQL interface docs
• Cloud Spanner Ecosystem site
• Spanner: Google’s Globally-Distributed Database white paper
• Spanner Docs docs
• Spanner Qwiklabs site
• Using the Cloud Spanner Emulator docs
• GCP Podcast Episode 62: Cloud Spanner with Deepti Srivastava podcast
• GCP Podcast Episode 248: Cloud Spanner Revisited with Dilraj Kaur and Christoph Bussler podcast
• Cloud Spanner federated queries docs

Max is working on a new podcast platform and some spring break projects.

Mark Mirchandani and Max Saltonstall

Hosts Anthony Bushong and Kaslin Fields welcome Bowei Du and Abdelfettah Sghiouar to talk about the Gateway Controller, a tool that helps developers use the Gateway API in GKE.

Bowei starts the show with a thorough explanation of how and why the Gateway Controller was developed. Compared to tools like Ingress, Gateway Controller allows engineers to implement more expressive solutions. While providing developers with portability has been an important part of Gateway Controller, it also gives developers freedom to use non-portable features in a structured, consistent environment and helps manage tenancy across different teams. Bowei and Abdel describe the difference between Ingress and Service and how these tools fit in with Gateway Controller. Abdel walks us through how a company would use the Gateway Controller for optimal tenancy management across name spaces and how this is an improvement over Ingress and Service. He gives examples of how companies are using this new tool.

We hear more about the GKE Gateway Controller and how its fully-managed deployments and integration with other Google APIs make it so easy to use. Bowei tells us how Gateway helps with the unification of mesh and non mesh environments through the standardization of noun describers in both instances. A handy edge to mesh tutorial is available to help developers.

Abdel is a Cloud Dev Advocate with a focus on Cloud native, GKE, and Service Mesh technologies.

Bowei is tech lead on Gateway Controller and a specialist in distributed systems and networking.

• Strengthening your DevOps muscle site

• Kubernetes site
• GKE site
• GKE Gateway API docs
• Kubernetes Gateway API site
• Ingress docs
• Service docs
• From edge to mesh: Exposing service mesh applications through GKE Ingress docs
• Google Cloud Armor site
• Kubernetes Slack site
• • Slack channel: #sig-network-gateway-api
• GKE Networking Recipes GitHub repo site
• The evolution of Kubernetes networking with the GKE Gateway controller blog

Kaslin is working on KubeCon EU.

Anthony is working on software supply chain security with Cloud Build.

Kaslin and Anthony are working together on the GKE Essentials Series

Anthony Bushong and Kaslin Fields

On the podcast this week, your hosts Stephanie Wong and Mark Mirchandani talk about the data processing tool Apache Beam with guests Pablo Estrada and Kenneth Knowles.

Kenn starts us off with an overview of how Apache Beam began and how Cloud Dataflow was involved. The unique batch and stream method and emphasis on correctness garnered support from developers early on and continues to attract users. Pablo helps us understand why Beam is a better option for certain projects looking to process large amounts of data. Our guests describe how Beam may be a better fit than microservices that could become obsolete as company needs change.

Next, we step back and take a look at why batch and stream is the gold standard of data processing because of its balance between low latency and ease of “being done” with data collection. Beam’s focus on the correctness of data and correctness in processing that data is a core component. With good data, processing becomes easier, more reliable, and cheaper. Kenn gives examples of how things can go wrong with bad data processing. Beam strives for the perfect combination of low latency, correct data, and affordability. Users can choose where to run Beam pipelines, from other Apache software offerings to Dataflow, which means excellent flexibility. Our guests talk about the pros and cons of some of these options and we hear examples of how companies are using Beam along with supporting software to solve data processing challenges.

To get started with Beam, check out Beam College or attend Beam Summit 2022.

Kenn Knowles is chair of the Apache Beam Project Management Committee. Kenn has been working on Google Cloud Dataflow—Google’s Beam backend—since 2014. Kenn holds a PhD in programming languages from the University of California, Santa Cruz.

Pablo is a Software Engineer at Google, and a management committee member for Apache Beam. Pablo is big into working on an open source project, and has worked all across the Apache Beam stack.

• Under the sea: Building the world’s fiber optic internet video
• • Discovering Data Centers videos
• Google Data Cloud Summit site
• It’s official—Google Distributed Cloud Edge is generally available blog
• • GCP Podcast Episode 228: Fastly with Tyler McMullen podcast
• Save big by temporarily suspending unneeded Compute Engine VMs—now GA blog

• Apache Beam site
• Apache Beam Documentation site
• Dataflow site
• Apache Flink site
• Apache Spark site
• Apache Samza site
• Apache Nemo site
• Spanner site
• BigQuery site
• Beam College site
• Beam College on Github site
• Beam Developer Mailing List email
• Beam User Mailing List email
• Beam Summit site

Mark is working on a new Apache Beam video series Getting Started Wtih Apache Beam

Stephanie Wong and Mark Mirchandani

On the podcast this week, your hosts Stephanie Wong and Mark Mirchandani talk about the data processing tool Apache Beam with guests Pablo Estrada and Kenneth Knowles.

Kenn starts us off with an overview of how Apache Beam began and how Cloud Dataflow was involved. The unique batch and stream method and emphasis on correctness garnered support from developers early on and continues to attract users. Pablo helps us understand why Beam is a better option for certain projects looking to process large amounts of data. Our guests describe how Beam may be a better fit than microservices that could become obsolete as company needs change.

Next, we step back and take a look at why batch and stream is the gold standard of data processing because of its balance between low latency and ease of “being done” with data collection. Beam’s focus on the correctness of data and correctness in processing that data is a core component. With good data, processing becomes easier, more reliable, and cheaper. Kenn gives examples of how things can go wrong with bad data processing. Beam strives for the perfect combination of low latency, correct data, and affordability. Users can choose where to run Beam pipelines, from other Apache software offerings to Dataflow, which means excellent flexibility. Our guests talk about the pros and cons of some of these options and we hear examples of how companies are using Beam along with supporting software to solve data processing challenges.

To get started with Beam, check out Beam College or attend Beam Summit 2022.

Kenn Knowles is chair of the Apache Beam Project Management Committee. Kenn has been working on Google Cloud Dataflow—Google’s Beam backend—since 2014. Kenn holds a PhD in programming languages from the University of California, Santa Cruz.

Pablo is a Software Engineer at Google, and a management committee member for Apache Beam. Pablo is big into working on an open source project, and has worked all across the Apache Beam stack.

• Under the sea: Building the world’s fiber optic internet video
• • Discovering Data Centers videos
• Google Data Cloud Summit site
• It’s official—Google Distributed Cloud Edge is generally available blog
• • GCP Podcast Episode 228: Fastly with Tyler McMullen podcast
• Save big by temporarily suspending unneeded Compute Engine VMs—now GA blog

• Apache Beam site
• Apache Beam Documentation site
• Dataflow site
• Apache Flink site
• Apache Spark site
• Apache Samza site
• Apache Nemo site
• Spanner site
• BigQuery site
• Beam College site
• Beam College on Github site
• Beam Developer Mailing List email
• Beam User Mailing List email
• Beam Summit site

Mark is working on a new Apache Beam video series Getting Started Wtih Apache Beam

Stephanie Wong and Mark Mirchandani

Stephanie Wong and Debi Cabrera host a special episode highlighting the amazing accomplishments of our guest Vidya Nagarajan Raman as we celebrate Women’s History Month! With her more than 20 years of experience fostering growth and monetization in enterprise and education platforms, investing and working in the holistic lifestyle space, and earning her MBA while raising her two children, Vidya has certainly done a lot!

Vidya tells us about her latest blog post stressing the importance of being an event-driven organization. In this business structure, reactions to events are planned in advance and developers consider how services are integrated for maximum efficiency. With synchronous extensions, projects retain flexibility in existing applications as they work with Cloud Functions to extend to new areas. Vidya gives our listeners examples of how this works.

The journey from engineer to Head of Product Management was an interesting one for Vidya, and she describes how she got started in computer engineering. Her passion for connecting with users later pushed her to product management. She tells us about her contributions to Chromebooks for Education as well as other milestones during her time with Google. Vidya talks about the support system she credits with helping her along the way and gives our listeners advice for finding mentors in their fields. She touches on the challenges she faced, describes what it was like for a woman in the industry when she first started, and offers encouragement to women getting started now. Balancing work, continuing her education, and raising children was tough, but Vidya says that, along with her incredible professional and personal support systems, defining priorities is vital.

Vidya offers our listeners the insights she’s gained as she’s watched Google and workplace teams change and adapt over the years. Building an inclusive team, encouraging diverse perspectives, and defining a framework for settling disagreements are some of the pieces of advice she shares. Don’t be afraid to fail and be a risk-taker, Vidya says, because that promotes growth and learning. If you learn something new every day and have fun doing it, then you will be successful.

In her spare time, Vidya leads a charitable foundation that partners with organizations in countries like India and Peru to further education, build orphanages and libraries, and provide medical care for women. She is an angel investor and runs workshops on creating a holistic lifestyle to help others lead well-rounded, fulfilling lives.

Vidya Nagarajan Raman is the Head of Product Management for Serverless at Google Cloud. She is also an angel investor, advisor, and co-founder of a holistic lifestyle platform that empowers people to grow and transform their lives.

• Ready to solve for the future? Data Cloud Summit ‘22 is coming April 6 blog
• Visualizing Google Cloud: 101 Illustrated References for Cloud Engineers and Architects site

• Evolving to a programmable cloud blog
• Cloud Functions site
• Cloud Run site
• Eventarc docs
• Work Flows site
• Chromebook site

Debi is working on Apache Beam series with Mark Mirchandani.

Stephanie is working on scripts for a series about getting into a career in cloud.

Stephanie Wong and Debi Cabrera

This week, Stephanie Wong and Anthony Bushong introduce a special podcast of the Gtalk at Airbus speaker series where prestigious Googlers have been invited to talk with Airbus. In this episode, Vint Cerf, who is widely regarded as one of the fathers of the Internet, talks with Rhys Phillips of Airbus and fellow Googler Rafael Lami Dozo.

Vint tells us about his journey to Google, including his interest in science which stemmed from a chemistry set he received as a child. After high school, he got a job writing data analyzation software on the Apollo project. His graduate work at UCLA led him to the ARPANet project where he developed host protocols, and eventually to his work on the original Internet with Bob Kahn. Vint tells us about the security surrounding this project and the importance of internet security still today.

The open architecture of the internet then and now excites Vint because it allows new, interesting projects to contribute without barriers. Vint is also passionate about accessibility. At Google, he and his team continue to make systems more accessible by listening to clients and adapting software to make it usable. He sees an opportunity to train developers to optimize software to work with common accessibility tools like screen readers to ensure better usability.

Later, Vint tells us about the Interplanetary Internet, describing how this system is being built to provide fast, effective Internet to every part of the planet. Along with groups like the Internet Engineering Task Force, this new Internet is being deployed and tested now to ensure it works as expected. He talks about his work with NASA and other space agencies to grow the Interplanetary Internet.

Digital obsolescence is another type of accessibility that concerns Vint. Over time, the loads of data we store and their various storage devices could become unreadable. Software needed to use or see this media could no longer be supported as well, making the data inaccessible. Vint hopes we will begin practicing ways to perpetuate the existence of this data through copying and making software more backward compatible. He addresses the issues with this, including funding.

While at UCLA, Vint Cerf worked on ARPANet - the very beginnings of what we know as the internet today and is now, fittingly, Chief Internet Evangelist & VP at Google. He is an American Internet pioneer and is recognized as one of “the fathers of the Internet”, sharing this title with TCP/IP co-developer Bob Kahn.

Rhys Phillips is Change and Adoption Leader, Digital Workplace at Airbus.

Rafael Lami Dozo is Customer Success Manager, Google Cloud Workspace for Airbus.

• Celebrating Pi Day with Cloud Functions blog
• Apollo Scales GraphQL Platform using GKE blog

• Vinton G. Cerf Profile site
• ARPANet on Wikipedia site
• To Boldly Go Where No Internet Protocol Has Gone Before article
• Building the backbone of an interplanetary internet video
• IETF site
• CCSDS site
• IPNSIG site
• The Internet Society site
• NASA site

Stephanie is working on new Discovering Data Centers videos.

Anthony is working on content for building scalable GKE clusters.

Stephanie Wong and Anthony Bushong

First time co-host Jan Kleinert joins Mark Mirchandani this week to talk about database observability and the cool tools that make it possible. Morgan McLean and Nimesh Bhagat describe database observability, which uses metrics, logs, and other tools to help users understand the health of your database.

We talk about Object Relational Mappers and the challenges with using these for debugging database performance. SQL Commenter helps database observability in two ways: it is both a library and a standard, Nimesh tells us. He describes the process for us, detailing exactly how SQL Commenter effects projects. Recently, SQL Commenter was donated to OpenTelemetry to augment the observability offerings, create an application standard, and make it easier for developers to use a variety of different tools and languages. Engineers can get end-to-end traces no matter which database technologies they use.

Morgan tells us about Splunk and how information from SQL Commenter is taken into Splunk and used. Backend data like metrics from Cloud Monitoring and client libraries can be correlated together with SQL Commenter and brought into Splunk for full stack observability. Nimesh offers client examples to help us understand how these useful tools integrate for optimal observability. He tells us about the databases and ORMs supported by SQL Commenter. Our guests and co-host Jan give tips to help our listeners get started with SQL Commenter and talk about what they’re looking forward to in the future of observability.

Nimesh is a product manager at Google Cloud, he leads Database Observability. He has worked across engineering and product roles, building highly available and high performance enterprise infrastructure used by Fortune 500 companies. His passion lies in combining powerful infrastructure with simple user experience so that every business and developer can build software at scale and velocity.

Morgan is ​​Director of Product Management at Splunk and co-creator of OpenCensus / OpenTelemetry.

• Google Cloud Innovators site
• Redesigning the Cloud SDK + CLI for easier development blog
• • GCP Podcast Episode 291: Redesigning the Cloud SDK and CLI with Wael Manasra and Cody Oss podcast
• What is Active Assist? video
• • GCP Podcast Episode 235: Active Assist with Chris Law + MariaDB SkySQL with Robert Hedgepeth podcast

• SQL Commenter site
• Sequelize site
• SQL Alchemy site
• ADO.net site
• GCP Podcast Episode 247: Cloud SQL Insights with Nimesh Bhagat podcast
• OpenTelemetry site
• Splunk site
• Cloud Monitoring site
• Cloud Spanner site
• Cloud SQL site
• Cloud Trace site
• Sqlcommenter now extending the vision of OpenTelemetry to databases blog

Mark Mirchandani and Jan Kleinert

On the show this week, we’re talking about Google Cloud Reader, a nifty podcast we created to narrate Google Tech blog posts. Host Jenny Brown tells us her inspiration for creating Google Cloud Reader and she and cohost Stephanie Wong walk us through a series of published episodes.

First up, we learn what Cloud SQL Maintenance is and how customers can customize maintenance schedules to limit the impacts of downtime. Region picker is the topic of our next segment, and we hear how it helps projects stay cost efficient while conserving resources. Using three inputs, companies can decide quickly which region offers the best balance between cost, latency, and carbon footprint for them. Next, we learn about search abandonment’s effect on brand loyalty and how important it is for the right products to show in search results.

We tackle the working environment with the next piece, redefining productivity to make it more personal and less robotic and offering advice on being productive while maintaining a good work-life balance. Making learning more personalized is the subject of our next segment. We hear how Google is using AI to aid the instruction of students no matter their learning style. Building diversity, equity, and inclusion into companies is important for success, and our last segment offers advice on how to incorporate DEI initiatives to ensure employees feel valued.

• Build a data mesh on Google Cloud with Dataplex, now generally available blog
• From watersheds to Koala habitats - tackling ecosystem restoration with data blog

• Understanding Cloud SQL Maintenance: why is it needed? blog
• Cloud SQL site
• Faster, cheaper, greener? Pick the Google Cloud region that’s right for you blog
• Google Cloud Region Picker on GitHub site
• Reduce your cloud carbon footprint with new Active Assist recommendations blog
• Research: Search abandonment has a lasting impact on brand loyalty blog
• Why Search Abandonment Is the Metric That Matters video
• The Google Workspace guide to productivity and wellbeing blog
• New Google Cloud Student Success Services help educators scale individualized learning blog
• Why representation matters: 6 tips on how to build DEI into your business blog
• Why representation matters blog

Stephanie Wong and Jenny Brown

Guests Leigha Jarett and Debi Cabrera from the Looker team join Mark Mirchandani this week to talk about this powerful tool. Looker, Google’s data analytics platform, was built to provide enterprise companies with customizable analytics tools that allow anyone to get the data they need when they need it. This facilitates better business decisions.

Leigha talks about how Looker and LookML keep data consistent among data analysts no matter where they pull data from or what they do with it. Data is more trustworthy, fostering a positive data-driven business. She details how LookML works, from database connection to metric creation, and tells us how easy it is for non-data engineers to work with as well.

Robust data analysis based on trusted data points used to drive decision making is how Looker builds an environment of business intelligence rather than simple reporting. By offering easy integration into other Google tools like Data Studio and BigQuery, Looker is easy to set up, learn, and use. Our guests help listeners navigate Looker’s Explore From Here functionality and explain how it could help them answer important business questions. With advanced admin permissioning, Looker also helps limit the chaos that comes with multiple people accessing the same data.

Later, we hear real-world examples of companies taking the Looker journey. Our guests offer advice based on these experiences with clients and talk about how client feedback has influenced new Looker tools, like the Looker Tableau Connector that’s coming soon. We hear about the relationship between BigQuery and Looker and suggestions for companies newly embarking on their data journey.

Leigha is a Product Manager for Looker’s application platform. She focuses on making Looker both simple and powerful for developers.

Debi recently became a Developer Advocate after being at Looker for three years as an Engagement Manager and StratOps PgM. You can find her on Linkedin

• Introducing a Google Cloud architecture diagramming tool blog
• Black History Month: Celebrating the success of Black founders with Google Cloud: DOSS blog

• Looker site
• LookML site
• Data Studio site
• Looker Connect site
• Looker Documentation docs
• Looker Products Page site
• Tableau site
• Google Cloud Training site
• Google Cloud Skills Boost site
• Looker and BigQuery Important Considerations whitepaper
• BigQuery Playlist videos
• Data Analytics Playlist videos
• Looker Channel videos
• Contact Google Cloud Support site
• Request a Free Trial site

Debi is planning her wedding!

Mark Mirchandani and Debi Cabrera

On the show this week, Mark Mirchandani and Stephanie Wong share two popular episodes of Bruno Aziza’s YouTube series Data Journeys.

First up, Bruno talks with Aaron Biller of Postmates about their triangle of complex data that includes customer, courier, and merchant. He details their data storage and analytics structure, describing it as a reverse pyramid of tons of data with few engineers to manage and analyze it. To handle this, Postmates takes a stay-out-of-the-way approach by providing good data and letting the analysts do what they do best without micromanaging. Aaron talks about this data architecture, including the use of BigQuery as data lakes to keep data storage simple, and how Google collaboration tools streamline access and authorization tasks. Communication and flexibility are important, Aaron tells us, and he offers other advice for companies designing data systems. Feedback loops, dedicated training, and an open environment with no silos also help foster a productive, healthy data workplace.

Matteo of Delivery Hero speaks to Bruno next. With the goal of increasing their global reach and offerings, it’s important that Delivery Hero has a smooth data system. Matteo outlines the new data structure they’ve built to ease onboarding of new companies and territories and describes different use cases for their data. From determining the number of delivery people necessary in each area to offering personalized customer recommendations, Delivery Hero uses Google offerings like Google Analytics and BigQuery to interpret collected data. Matteo details how they tailor data infrastructures for each use case and offers tips to help companies think through their data infrastructure design. Don’t work in a bubble, Matteo stresses, and focus on thorough onboarding of team members and clear communication with colleagues and customers.

Bruno is the Head of Data & Analytics at Google Cloud. He specializes in everything data, from data analytics, to business intelligence, data science, and artificial intelligence. Before working at Google, he worked at companies like Business Objects when it went IPO and Oracle, where his team led a big turnarounds in the business analytics industry. Bruno also had the opportunity to help launch startups like Alpine Data (now part of Tibco). Sisense and AtScale and helped Microsoft grow its Data unit into a $1B business. He has been educated in the US, France, the UK, and Germany and has written two books on Data Analytics and Performance Management. In his spare time, Bruno writes a monthly column on Forbes.com on everything Data, AI and Analytics.

Aaron is the Manager of Data Engineering at Postmates.

Matteo is Senior Director of Global Data Products and Analytics at Delivery Hero.

• Celebrating National Muffin Day with machine learning blog
• Managed Istio-based service mesh on our managed GKE clusters: Anthos Service Mesh comes to GKE Autopilot blog

• Data Journeys videos
• Episode 12: How Postmates delivers on data needs with just six data engineers video
• Episode 5: How Delivery Hero uses data to deliver meals video
• BigQuery site
• Google Workspace site
• Dataproc site
• Pub/Sub site
• Google Analytics site
• Looker site
• Tableau site
• Data Studio site
• GCP Podcast Episode 266: Data Analytics Launches with Bruno Aziza and Eric Schmidt podcast
• GCP Podcast Episode 281: Google Cloud Next Data, Analytics, and AI Launches with Eric Schmidt and Bruno Aziza podcast

Steph is working on the next Ask Google Cloud event and she wants your Kubernetes questions!

Mark Mirchandani and Stephanie Wong

Brian Dorsey and Kaslin Fields welcome Kat Cosgrove of Pulumi this week to talk about what’s new with Kubernetes 1.24. Pulumi is infrastructure as code, allowing developers to use whatever language they are comfortable with to create and test infrastructure. Kat walks us through typical Pulumi infrastructure test scenarios to demonstrate the benefits of this software, especially with GCP.

In the new Kubernetes release, one of the biggest updates is the removal of Dockershim. If you’re using a managed Kubernetes service through GCP, this update should not affect you, Kat tells us. She clears up some common Docker misconceptions and tells us how Kubernetes and Docker still work together. Kat describes the situations where this update might affect certain projects and how to tell if you’re one of the unlucky few.

Later, we talk about the future of tech conferences. Kat is excited to get back to some in-person learning and networking, but at the same time, is hopeful that conferences will continue a hybrid model and allow some online interaction. Pulumi will be at KubeCon, Devlopsdays, and Jfokus in the next few months with some cool new free merchandise.

Kat is Staff Developer Advocate at Pulumi.

• Find products faster with the new All products page blog
• Introducing Ephemeral Containers blog
• Open sourcing the App Engine Standard Java runtime blog

• Pulumi site
• Kubernetes site
• Docker site
• Kubernetes 1.24 Release Notes site
• GKE site
• We Didn’t Start the Fire: Communication Breakdowns and How to Prevent Them - Ian Coldwater, Twilio & Kat Cosgrove, JFrog video
• Jfokus site
• Devopsdays Chicago site
• KubeCon EU Valencia site

Brian just started releasing the next six episodes of VMs End-to-end. It’s a video series all about Compute Engine, starting with a discussion of building reliable systems from unreliable components.

Kaslin is working on the GKE/OSS K8s Events.

• Cloud OnAir Webinar - February 24th
• Innovators Hive - March 29-30
• • Google Cloud Innovators Program
• OSPO Panel on Dockershim Deprecation - March 31st

Brian Dorsey and Kaslin Fields

This week on the podcast, Wael Manasra and Cody Oss join hosts Carter Morgan and Mark Mirchandani to chat about new branding in Cloud SDK and gcloud CLI. Google Cloud SDK was built and designed to take over mundane development tasks, allowing engineers to focus on specialized features and solutions. The SDK documentation and tutorials are an important part of this as well. With clear instructions, developers can easily make use of Cloud SDK.

Software Development Kits have evolved so much over the years that recently, Cody, Wael, and their teams have found it necessary to redefine and rethink SDKs. The popularity of cloud projects and distributed systems, for example, means changes to kit requirements. The update is meant to reevaluate the software included in SDKs and CLIs and to more accurately represent what the products offer. Giving developers the tools they need in the place they work means giving developers code language options, providing thorough instruction, and listening to feedback. These are the goals of this redesign.

The Google Cloud SDK contains downloadable parts and web publications. Our guests explain the types of software and documentation in each group and highlight the importance of documentation and supporting materials like tutorials. The Cloud Console is a great place for developers to start building solutions using the convenient point-and-click tools that are available. When these actions need to be repeated, the downloadable Command Line Interface tool can do the work. Cody talks about authentication and gcloud, including its relationship to client libraries. He walks us through the steps a typical developer might take when using Google products and how they relate to the SDK and CLI. Through examples, Wael helps us further understand client libraries and how they can interact with the CLI.

The Cloud SDK is a work in progress. Our guests welcome your feedback for future updates!

Wael manages the gcloud CLI, the client libraries for all GCP services, and the general Cloud SDK developer experience.

Cody works on the Go Cloud Client libraries where he strives to provide an delightful and idiomatic experience to all the Gophers on Google Cloud.

• Google Tau VMs deliver over 40% price-performance advantage to customers blog
• Find products faster with the new All products page blog

• Cloud SDK site
• Cloud SDK Documentation docs
• Go site
• Google Cloud site
• Cloud Storage site
• Cloud Storage Documentation docs
• Cloud Code site
• Cloud Run site
• GKE site
• Cloud Functions site
• Cloud Client Libraries docs
• Cloud Shell site
• Cloud Shell Editor docs

Carter is working on his comedy.

Carter Morgan and Mark Mirchandani

Carter Morgan and Stephanie Wong host Shopify guests Camilo Lopez and Tai Dickerson this week. Shopify streamlines the online purchasing process so merchants and customers can transact with confidence.

Camilo and Tai talk in-depth about Shopify’s tech stack and why the choices made are so important to performance. Shopify engineers use a combination of Ruby on Rails, MySQL and Google products like Kubernetes. Resiliency systems like active-active configurations, chat ops for quick solutions, and bot and overload protection are worked in. By leveraging these tools and staying flexible in their resiliency efforts, Shopify is able to adjust to new merchant requirements and teams are able to work efficiently.

While tech continues to progress and change, the Shopify culture remains a driving force for advancement, Camilo tells us. The company ideals and axioms help steer the brand and dictate which technologies they’ll use to solve new and changing client demands. The 2014 outage shaped the future of these cultural ideals, emphasizing the need for quick action and resiliency components like constraints to ensure system safety. Shopify engineers also built enhanced testing tools like Toxiproxy to simulate poor network conditions and account for potential issues.

The 2021 Black Friday Cyber Monday shopping season was Shopify’s biggest yet. Camilo and Tai describe how Shopify’s resiliency culture and intense prep work made the biggest shopping weekend of the year so successful. By offering educational tools and a support network that values good communication, their company culture continues to grow, and Tai tells us how it’s not just the software that should be resilient. Building a resilient, flexible company culture is just as important.

Camilo talks about Shopify’s recent shift to a completely remote work place and the new challenges and opportunities it presents.

Camilo has worked at Shopify for more than 10 years, he has been an IC and a manager leading teams that take care of Shopify’s scalability and resiliency.

Tai is a production engineer at Shopify, where she shares her passion for resilience engineering with others via paper discussions and as a leader in Shopify’s Resiliency SIG.

• Machine images is GA docs
• New Cloud Logging and Monitoring capabilities
• • Monitoring third-party applications: MariaDB docs
  • Monitoring third-party applications: MySQL docs
  • Monitoring third-party applications: Memcached docs
  • Starting with version 2.8.0, the Ops Agent supports Ubuntu 21.10. For more information, see Linux operating systems docs

• Shopify site
• Kubernetes site
• GKE site
• Kafka site
• Redis site
• Elastic Search site
• Memcached docs
• Toxiproxy site
• Shopify Engineering site
• Shopify Careers site
• BFCM Twitter Thread site
• Shopify engineers deliver on peak performance during Black Friday Cyber Monday 2021 blog
• Cloud, Load, and Modular Code: What 2022 Looks Like for Shopify blog
• Terri Haber on Resiliency at Scale site
• Terri Haber on Enforced Pacing site
• Bart Jedrocha on Load Testing site
• Bart Jedrocha on Tooling for Load Testing site
• Bart Jedrocha on The Future of Load Testing site
• Ryan McIlmoyl on Code Red site
• Ryan McIlmoyl on Working with IMOC site
• Camilo Lopez on The 2014 Outage site
• Camilo Lopez on Holiday Season Learnings site
• Tai Dickerson on Doing Things Differently site
• Tai Dickerson on Learning & Community site

Stephanie is working on season 2 of the Where the Internet Lives podcast.

Carter is working on season 2 of VM End to End.

Carter Morgan and Stephanie Wong

We’re back for a new, exciting year of the Google Cloud Platform Podcast! Mark Mirchandani and Carter Morgan start 2022 with a jointly hosted interview with Anton Chuvakin and Timothy Peacock of the Cloud Security Podcast team. Our guest, Phil Venables, is here to tell us about the driving trends in cloud security today.

Phil starts the show with a discussion on the advances in cloud security in general and how it compares with on-prem security. Megatrends like economies of scale and competition between cloud providers benefit cloud users by allowing better security for less money. Cloud environments tend to be simpler and therefore easier to manage, and with scaling and geographic location options, cloud projects allow more flexibility to reach security and sustainability goals.

Phil talks about the iteration process of advances in security based on customer requirements and how this builds client trust. The Shared Responsibility Model, where the cloud provider runs a secure infrastructure and the customer configures their project securely in the cloud, is a great start, Phil tells us. But with Shared Fate, he sees the provider crossing the responsibility barrier to work together with the client towards a secure project through actions like analyzation of security defaults. Customer feedback helps Google Cloud make a better product, which in turn helps customers, creating an environment of reliability and shared trust.

We talk about how the Shared Fate model and shared incentives work together to create a closer partnership between cloud providers and customers, and Phil elaborates on the idea of project security as an immune system. We tackle the idea of security diversity and whether it benefits clients to expand their security outside of cloud provider offerings. Phil helps security novices understand valuable feature-add security services and what to look for in the future.

Phil leads the risk, security, compliance, and privacy teams for Google Cloud. Prior to joining Google Cloud, Phil was a Partner at Goldman Sachs where he held multiple roles over a long career, initially as their first Chief Information Security Officer, a role he held for 17 years. Before Goldman Sachs, Phil held multiple CISO roles as well as senior engineering roles across a range of finance, energy and technology companies.

• 2022 Resolution: Learn Google Cloud, free of charge blog
• How to build a virtual employment center on Google Cloud & Workspace video

• Cloud Security Podcast podcast
• IT Leaders: Pay Attention To These 8 Security Megatrends In 2022 article
• GCP Podcast Episode 218: Chronicle Security with Dr. Anton Chuvakin and Ansh Patniak podcast

Mark and Carter are working on some cool new changes to the podcast.

Carter Morgan, Mark Mirchandani, Anton Chuvakin and Timothy Peacock

We’re finishing out 2021 with a celebration of our favorite episodes and topics from the year! From new tools for Cost Optimization in GKE and advances in AI to tips for improving feelings of imposter syndrome, Carter Morgan, Stephanie Wong, and Mark Mirchandani share memorable moments from 2021 and look forward to future episodes.

Carter Morgan is Developer Advocate for Google Cloud, where he creates and hosts content on Google’s Youtube channel, co-hosts several Google Cloud podcasts, and designs courses like the Udacity course “Scalable Microservices with Kubernetes” he co-created with Kelsey Hightower. Carter Morgan is an international standup comedian, who’s approach of creating unique moments with the audience in front of him has seen him perform all over the world, including in Paris, London, the Melbourne International Comedy Festival with Joe White. And in 2019, and the 2019 Edinburgh Fringe Festival. Previously, he was a programmer for the USAF and Microsoft.

Stephanie Wong is a Developer Advocate focusing on online content across all Google Cloud products. She’s a host of the GCP Podcast and the Where the Internet Lives podcast, along with many GCP Youtube video series. She is the winner of a 2021 Webby Award for her content about data centers. Previously she was a Customer Engineer at Google and at Oracle. Outside of her tech life she is a former pageant queen and hip hop dancer and has an unhealthy obsession with dogs.

Mark Mirchandani is a developer advocate for Google Cloud, occasional host of the Google Cloud Platform podcast, and helps create content for users.

• Anthos Multi-Cloud v2 is generally available docs
• Machine learning, Google Kubernetes Engine, and more: 10 free training offers to take advantage of before 2022 blog
• The past, present, and future of Kubernetes with Eric Brewer blog
• • GCP Podcast Episode 124: VP of Infrastructure Eric Brewer podcast

• Mark’s Favorites
• • GCP Podcast Episode 252: GKE Cost Optimization with Kaslin Fields and Anthony Bushong podcast
  • GCP Podcast Episode 267: Cloud Firestore for Users who are new to Firestore podcast
• GKE Essentials videos
• Beyond Your Bill vidoes
• Stephanie’s Favorites
• • GCP Podcast Episode 270: Traditional vs. Service Networking with Ryan Przybyl podcast
  • GCP Podcast Episode 271: The Future of Service Networking with Ryan Przybyl podcast
  • GCP Podcast Episode 279: MLB with Perry Pierce and JoAnn Brereton podcast
• Carter’s Favorites
• • GCP Podcast Episode 284: State of DevOps Report 2021 with Nathen Harvey and Dustin Smith podcast
  • GCP Podcast Episode 287: Imposter Syndrome with Carter Morgan podcast
• Most Popular Episodes of 2021
• • GCP Podcast Episode Episode 264: SRE III with Steve McGhee and Yuri Grinshtey podcast
  • GCP Podcast Episode 258: The Power of Serverless with Aparna Sinha and Philip Beevers podcast
  • GCP Podcast Episode 253: Data Governance with Jessi Ashdown and Uri Gilad podcast
  • GCP Podcast Episode 263: SAP + Apigee: The Power of APIs with Benjamin Schuler and Dave Feuer podcast
  • GCP Podcast Episode 271: The Future of Service Networking with Ryan Przybyl podcast

• “Dun Dun Duuun” by Divenorth of Freesound.org
• “Cash Register” by Kiddpark of Freesound.org
• “Jingles and Pings” by BristolStories of HDInteractive.com
• “Time – Inception Theme” Composed by Hanz Zimmer (super-low-budget midi version)

Stephanie Wong, Carter Morgan and Mark Mirchandani

Carter Morgan takes the guest seat today to chat with host Stephanie Wong about imposter syndrome in tech. The technology ecosystem is constantly changing, with new advances every day. To keep up, tech workers are learning and developing new skills so frequently that at times it can feel as though they don’t actually know everything they need to know. Here is where self-doubt can really take hold.

Imposter syndrome is most prevalent around transition points, Carter tells us. A new job or new responsibility, for example, opens tech workers to feelings of inadequacy. But there’s hope, and he explains how we can learn and develop skills to overcome this difficulty. Through tales of his own experiences, Carter offers supportive tips he’s learned, including how important it is to communicate with your manager and seek help rather than isolating.

Unhealthy comparisons can foster self-doubt as well. Depth and breadth of knowledge are important factors to consider as well, and Carter points out that each has its benefits. Knowing when to go deep into a subject and when to obtain surface level knowledge can foster a sense of ease and adequacy in knowledge workers. Stephanie shares her experiences with imposter syndrome, highlighting the difference between self-perception and audience perception and why it’s important to give yourself credit for what you’ve accomplished. Breaking into a new space can be intimidating. Carter walks us through important steps to take to start tackling imposter syndrome from the beginning, including the effects of positive mentorships.

This month, Carter is giving a presentation at Cloud Learn (Dec 8-9, 2021), and he wraps up this episode with a sneak peak.

Carter Morgan is Developer Advocate for Google Cloud, where he creates and hosts content on Google’s Youtube channel, co-hosts several Google Cloud podcasts, and designs courses like the Udacity course “Scalable Microservices with Kubernetes” he co-created with Kelsey Hightower.

Carter Morgan is an international standup comedian, who’s approach of creating unique moments with the audience in front of him has seen him perform all over the world, including in Paris, London, the Melbourne International Comedy Festival with Joe White. And in 2019, and the 2019 Edinburgh Fringe Festival.

Previously, he was a programmer for the USAF and Microsoft.

• Cloud Learn site
• 5 things not to do with Cloud Functions, and 5 things you absolutely should do instead blog

• Cloud Learn site
• What do I really need to know to succeed at work? blog

Stephanie Wong

Guest Jason Polites joins Stephanie Wong and Bukola Ayodele this week to talk about advances in serverless computing with Cloud Run and how developers and wallets are benefiting.

Cloud Run, a managed service which allows developers to run containers, is now available in all GCP regions, offers increased resource access, global load balancing, and more. Jason tells us how this evolution of Cloud Run has led to the support of bigger, more complicated, and even legacy software fully and efficiently functioning in a serverless environment. The team at Google continues to expand offerings in order to afford the benefits of auto-scaling and other managed services to all workloads. Always On CPU, for example, supports projects with running background functions.

Later, Jason gives us examples of projects that best fit a serverless infrastructure and the cost benefits of using Cloud Run. He offers cost-saving tips for projects, like committed use discounts and auto-scaling limits. Balancing cost efficiency with global reliability is important, and Jason tells us how this is easily achieved with Cloud Run features like scaling to zero.

To limit the barrier to entry for new Cloud Run and container users, Jason and his team have been working on open source build packs. Developers can turn code into a container without creating Docker files. The containers running in Cloud Run are highly portable as well, giving companies the freedom to move their containers freely.

Jason leads the Serverless Compute product team in Google Cloud, including products like Cloud Run and App Engine.

• Illicit coin mining, ransomware, APTs target cloud users in first Google Cybersecurity Action Team Threat Horizons report blog
• Microservices architecture on Google Cloud blog

• Cloud Run site
• Cloud Run CPU Allocation docs
• Run more workloads on Cloud Run with new CPU allocation controls blog
• Docker site
• Google Cloud Buildpacks site
• App Engine site
• Cloud Functions site
• GCP Podcast Episode 173: Cloud Run with Steren Giannini and Ryan Gregg podcast
• GCP Podcast Episode 203: Cloud Run GKE with Donna Malayeri podcast
• GCP Podcast Episode 261: Full Stack Dart with Tony Pujals and Kevin Moore podcast

Bukola just finished Season 2 of the Click to Deploy series.

We’re learning all about Vertex AI this week as Carter Morgan and Jay Jenkins host guest Erwin Huizenga. He helps us understand what is meant by Asia Pacific and how Machine Learning is growing there. APAC’s Machine Learning scene is exciting for its enterprise companies leveraging ML for innovative projects at scale. The ML journey of many of these customers revealed challenges with things like efficiency that Vertex AI was built to solve.

The Vertex AI platform boasts tools that help with everything from the beginning stages of data collection to analysis, validation, transformation, model training, evaluation, serving the model, and metadata tracking. Erwin offers detailed examples of this pipeline process and describes how Feature Store helps clients manage their projects.

Using Vertex AI not only simplifies the initial development process but streamlines the iteration process as the model is adjusted over time. Pipelines offers automation options that help with this, Erwin explains. ML Operations are also built into Vertex AI to ensure everything is done in compliance with industry standards, even at scale. Using customer recommendations as an example, Erwin walks us through how Vertex AI can employ embedding to enhance customer experiences through ML.

By using Vertex AI in combination with other Google offerings like AutoML, companies can effectively build working ML projects without data science experience. We talk about the Vertex AI user interface and the other tools and APIS that are available there. Erwin tells us how Digits Financial uses Vertex AI and Pipeline to bring models to production in days rather than months, and how others can get started with Vertex AI, too.

Erwin Huizenga is a Data Scientist at Google specializing in TensorFLow, Python, and ML.

• Announcing Spot Pods for GKE Autopilot—save on fault tolerant workloads blog
• Indosat Ooredoo and Google Launch Strategic Partnership to Accelerate Digitalization Across SMBs and Enterprises in Indonesia site
• Indosat Ooredoo dan Google Luncurkan Kemitraan Strategis untuk Percepatan Digitalisasi UMKM dan Perusahaan di Indonesia site

• Vertex AI site
• Google Cloud in Asia Pacific blog
• Introduction to Vertex AI docs
• What Is a Machine Learning Pipeline? site
• TensorFlow site
• PyTorch site
• Vertex AI Feature Store docs
• AutoML site
• BigQuery ML site
• Vertex AI Matching Engine docs
• ScaNN site
• Announcing ScaNN: Efficient Vector Similarity Search blog
• Vertex AI Workbench site
• Vertex Pipeline Case Study: Digits Financial site
• Intro to Vertex Pipelines Codelab site
• Vertex AI: Training and serving a custom model Codelab site
• Vertex AI Workbench: Build an image classification model with transfer learning and the notebook executor Codelab site
• APAC Best of Next 2021 site
• TFX: A TensorFlow-Based Production-Scale Machine Learning Platform site
• Rules of Machine Learning site
• Google Cloud Skills Boost: Build and Deploy Machine Learning Solutions on Vertex AI site
• Monitoring feature attributions: How Google saved one of the largest ML services in trouble blog

Jay is working on APAC Best of Next and will be doing a session on sustainability!

Carter is working on transitioning the GCP Podcast to a video format!

This week, Stephanie Wong and Carter Morgan are talking about the recently released State of DevOps Report. Guests Dustin Smith and Nathen Harvey tell us all about DORA, the research group working to study DevOps, and the findings of their years-long study aimed at improving workplace environments, fostering sustainable increased productivity, and ensuring quality output across industries.

During their years of research, the DORA team has developed ways to measure team results and workplace culture. Our guests tell us about the five measures they use, including deployment frequency and reliability. The shared responsibility and collaboration of teams at a company to optimize these five metrics is what makes good DevOps performance. Through a real-life example, we hear how the coordination of goals and incentives across departments can improve results of the DevOps metrics, thus improving the speed and stability of finished products.

Once businesses identify problems, they need realistic expectations of the time and energy required to solve these issues. Learning from each change made and growing during the process is an important part of optimization, and our guests talk about the best practices their research has identified for facilitating smoother transitions. High quality documentation is a vital part of optimizing DevOps, and this year’s report examined internal documentation for the first time. Nathan describes what makes good documentation, like clear ownership of the documents and docs that are regularly updated for easy sharing and scaling of up-to-date material across the company. Dustin elaborates, explaining other factors that make quality, reliable documents.

Later, we talk SRE and how companies can measure and optimize Site Reliability Engineering. A supportive team culture and ensuring a secure product and supply chain are some important factors in optimal SRE, the DORA study found. Our guests offer advice for companies looking to get started with DevOps practices.

Nathen Harvey is a developer relations engineer at Google who has built a career on helping teams realize their potential while aligning technology to business outcomes. Nathen has had the privilege of working with some of the best teams and open source communities, helping them apply the principles and practices of DevOps and SRE.

Dustin Smith is a UX Research Manager and the DORA research lead. He studies the factors that influence a team’s ability to deliver software quickly and reliably.

• Email is 50 years old, and still where it’s @ blog
• Make the most of hybrid work with Google Workspace blog
• We analyzed 80 million ransomware samples – here’s what we learned blog

• DevOps site
• DORA site
• SRE site
• 2021 Accelerate State of DevOps report addresses burnout, team performance report

Mark Mirchandani and Max Saltonstall are back this week to learn everything there is to know about Assured Workloads with Bryce Buffaloe and Mikaela Misaka. Google’s Assured Workloads helps companies and governments ensure secure projects and privacy protection in sectors with extensive compliance requirements while taking advantage of Cloud capabilities.

Bryce and Mikaela start the show talking about the challenges faced when using a public cloud for projects with very specific regulations and how Assured Workloads was developed to help solve these issues. The easy setup steps and uncomplicated UI help customers move from their on-prem infrastructure to Google Cloud where scaling, local customer support, and other advantages can be easily leveraged while maintaining a secure, compliant environment.

With so many compliance standards in sectors like finance and healthcare, our guests walk us through the process Assured Workloads clients go through from identifying the regulations of markets they participate in to planning their data security, keeping customer support local to maintain privacy, and using Google Cloud to put these plans into practice with their projects across the world. On the Google Cloud side, the team works to create regulation maps that organize the rules of potential markets so customers can click a button and rest easy knowing their projects are compliant. Bryce details what goes into making Google Services like GKE compliant for customers as well. Assured Workloads continues to grow as new client challenges are presented. In the future, monitoring support, audit management, and other features will be introduced. Global expansion and sovereign cloud capabilities are coming soon, and our guests tell us more.

Bryce is the Assured Workloads Product Manager at Google.

Mikaela is a Customer Care Offer Lead at Google Cloud, focused on creating new customer care offerings and value-added services tailored to the needs of regulated customer segments.

• Run your fault-tolerant workloads cost-effectively with Google Cloud Spot VMs blog
• 8 more things to love about the new Pixel phones blog
• Government and Education Summit site

• Assured Workloads site
• Assured Workloads Documentation site
• New capabilities for Assured Workloads for Government blog
• GKE site
• New data sovereignty controls for EU customers blog
• T-Systems and Google Cloud partner to deliver sovereign cloud for Germany article

Max has been sharing AI use cases from inside Google IT and tech support and was working on red panda and sith warrior Halloween costumes for his kids.

Mark is planning some cool podcast updates for next year.

On the podcast this week, Mark Mirchandani and Carter Morgan host guests Chad Jennings and Joel Conkling in a fascinating discussion about Earth Engine and performing geospatial processing to help companies become more environmentally conscious.

Google’s geospatial functionality is some of the most advanced in the world, and with the Next announcements, commercial companies can now take advantage of this with tools like Earth Engine and in Cloud analytics offerings like BigQuery. Together, these tools make the three pillars of geospatial cloud: analysis of vector data with tools like CloudSQL or BigQuery, analysis of image data with Earth Engine, and taking advantage of the data assets. This geospatial analysis helps us understand the world and how it’s changing, then apply this information to make important, environmentally friendly decisions.

As a key part of this system, Earth Engine is a geospatial data-processing platform specializing in the analysis of satellite images and other image data. It provides access to over 800 datasets and processing software that scales to planetary-scale analysis. At Next, Google announced Earth Engine availability for commercial use. Our guests talk about the applications of this in the real world, from the effect of climate risk on a financial portfolio to locations most susceptible to forest fire.

Chad and Joel tell us about the sources of Earth Engine’s data, the pre-processing work done to the images collected, and the ease of data sharing between platforms. By working with BigQuery, users have access to additional datasets and analytics tools as well. Google clients are taking this data and creatively using the information to make meaningful decisions. Insurance companies, for example, analyze data to assess flood risk, while the U.S. Forest Service uses the platform to advance their mission of sustainable forest management. Unilever uses Earth Engine in their commitment to zero additional deforestation in their supply chain, and our guests talk more about the Next presentation with Unilever. Additional BigQuery announcements at Next can be leveraged in Earth Engine as well, and new features such as Analytics Hub make accessing datasets even easier.

Google works to meet users where they are and make tools easy to use from day one. Earth Engine’s data processing, scalability, and more make it easy for users to focus on the analysis rather than the prep work. Our guests offer advice for getting started with Earth Engine and BigQuery and share a little about Climate Engine.

Chad came to Google from the startup world doing big data navigation processing and research. Working at the intersection of geospatial and big data at Google Cloud is a marvelous place to work.

Joel is the Product Manager for both Earth Engine and Environmental Insights Explorer and has worked at Google since 2010.

• BigQuery Omni now available for AWS and Azure, for cross cloud data analytics blog
• How geospatial insights can help meet business goals blog
• 9 things I freakin’ love about Google Cloud identity and environments blog

• Earth Engine site
• Earth Engine Development Guides site
• Big Query site
• CloudSQL site
• Climate Engine site
• Geospatial analytics and AI site
• Analytics Hub site
• Monitoring air quality with S5P TROPOMI data blog
• Visualizing geospatial data with pydeck and Earth Engine blog
• More accurate and flexible cloud masking for Sentinel-2 images blog
• NICFI’s satellite imagery of the global tropics now available in Earth Engine for analysis blog
• Earth Engine for Commercial Use: Now in Preview with Google Cloud site
• Next Session: Geospatial Innovation at Unilever video
• Next Developer Keynote: technology trends video
• What is Google Earth Engine? video
• Helping companies tackle climate change with Earth Engine blog
• Google has the cleanest cloud. Now it’s helping other companies go green article

Mark Mirchandani is back this week with cohost Bukola Ayodele. We’re talking with Eric Schmidt and Bruno Aziza about all the awesome new analytics, data, and AI launches from last week’s Google Cloud Next conference.

Our guests start the show outlining the challenges clients face when storing, organizing, and analyzing data in the cloud. These needs have inspired Google solutions that focus on simplifying data management for customers. Next announcements like BigQuery Omni, which helps customers achieve full data visibility with cross-cloud analytics, and DataPlex, which facilitates data management at scale, will change the way companies think about their data. BigQuery integration with AppSheets and the new Cloud Looker LookML let customers build once and access from anywhere. The new Looker and Tableau integration revolutionizes the use of the semantic model in Tableau, allowing things like company-established data governance and the Looker Blocks ecosystem to pull into Tableau analysis. New Looker Blocks specifically targeted to the healthcare industry were also introduced at Next.

We talk about the ML announcements including Vertex AI Workbench, a fully-managed service used for data exploration aimed at simplifying the workloads of data engineers. Serverless Spark on Google Cloud shares these goals by making performance tuning, scaling, infrastructure provisioning, and other tasks fully-managed. The new PostgreSQL interface for Spanner lets clients use tools already developed in PostgreSQL while leveraging the global scaling and other benefits of Spanner.

Bruno and Eric share some favorite customer stories as we wrap up this week’s episode. Albertson’s, Renault, and others have interesting data journeys on Google Cloud and our listeners can learn more in the YouTube series hosted by Bruno.

Eric is the the Head of Advocacy for Data Analytics at Google and has been at Google for almost eight years. Previously, he was with Microsoft, where he led Advocacy and Evangelism there, too. He focuses on products like BigQuery, Dataflow, Dataproc and leads a team of advocates who help customers turn data into value. In his downtime, Eric is a DJ at 90.3 KEXP here in Seattle or online at kexp.org where he focuses on global music culture.

You can find Eric on Twitter. His handle is “not that eric” - not to be confused with the ‘other Eric Schmidt’ here at Google. In fact, internally, people affectionately call him “cloud E”.

Bruno is the Head of Data & Analytics at Google Cloud. He specializes in everything data, from data analytics, to business intelligence, data science, and artificial intelligence. Before working at Google, he worked at companies like Business Objects when it went IPO and Oracle, where his team led a big turnarounds in the business analytics industry. Bruno also had the opportunity to help launch startups like Alpine Data (now part of Tibco). Sisense and AtScale and helped Microsoft grow its Data unit into a $1B business. He has been educated in the US, France, the UK, and Germany and has written two books on Data Analytics and Performance Management.

In his spare time, Bruno writes a monthly column on Forbes.com on everything Data, AI and Analytics.

• Next Reaction: Security and zero-trust announcements blog
• Next Reaction: New Data Cloud launches blog
• Next Reaction: Making multicloud easier for all blog
• Next Reaction: Features to reduce IT carbon emissions and build climate-related solutions blog
• Next Reaction: Monitor your conversations, get started with CCAI Insights blog

• GCP Podcast Episode 266: Data Analytics Launches with Bruno Aziza and Eric Schmidt podcast
• BigQuery site
• Bringing multi-cloud analytics to your data with BigQuery Omni blog
• Google Cloud Next—Day 1 livestream - WalMart video
• Dataplex site
• AppSheet site
• Cloud Looker LookML site
• Tableau site
• Vertex AI site
• Vertex AI Workbench site
• TensorFlow site
• Apache Spark on Google Cloud site
• New PostgreSQL Interface makes Cloud Spanner’s scalability and availability more open and accessible blog
• PostgreSQL site
• Cloud Spanner site
• Google Earth Engine site
• Google Maps Platform site
• Inside Industry Data Management 4.0 at Renault site
• Chess.com site
• Google Next Opening Keynote site
• Data Journeys with Bruno Aziza videos
• Cloud Next Catalog site
• Bruno’s Cloud Next Playlist videos
• Cloud Next Data Analytics Playlist videos
• Bruno on Linkedin site
• Lak on Twitter site

Bukola is working on the Click to Deploy video series.

On the podcast this week, Mark Mirchandani and Stephanie Wong hear all about the cool stuff happening at Cloud Next 2021. Brian Hall and Forrest Brazeal join the show to outline exciting announcements, fun partnerships, and what the future holds for Google Cloud.

The immense prep and planning that went into Next shows through in the intentional and unified strategy of announcements and offerings at the conference. Our guests talk about this process and the challenges and decisions that went into the content choices and scheduling. The addition of Community Day, for example, was implemented to create a sense of in-person participation in an online-only event.

Next kicked off this week with a Keynote presentation talking about the momentum of production and infrastructure innovation at Google Cloud, new product announcements across data cloud and open cloud infrastructure, security advancements, sustainability, and more. Our guests talk about important partnerships Google Cloud has fostered this year with clients like Ford, Univision, and GE using AI and other technologies to advance innovative ideas in their businesses. Announcements around AI and analytics at Google Cloud were plentiful, including Spark on Google Cloud that offers managed serverless data processing. Brian details the work Tableau and Google Cloud are doing to advance data visualization.

Our guests talk about the work Google has done to embrace the multi-cloud culture with advancements in Anthos and BigQuery Omni. The newly announced Google Distributed Cloud lets clients use their multi-cloud infrastructures across edge locations. Forrest talks about the pragmatic evolution to the Google Distributed Cloud offering and how other announcements like security advancements through strategic European partnerships have positively affected multi-cloud customers. We talk more about the importance of the new security announcements, like the Google Cyber Security Action Team. The changing landscape of work brought on by the pandemic has lead to more and more remote work. Workspace is adapting to this new environment, and our guests tell us about the new features available to workers at home.

As Google works to revolutionize technologies for clients, they also keep sustainability in mind. Next saw announcements in the clean cloud space and Google’s continued commitment to a carbon-free existence. New carbon reporting for clients and new features in Google Earth Engine and Active Assist help Google clients with their sustainability goals, too.

Brian is the VP of Product and Industry Marketing at Google Cloud. He was formerly a VP at AWS, CEO of Doppler Labs, and VP for Microsoft Surface with 20+ years at Microsoft.

Forrest is a cloud educator, author, speaker, and Pwnie Award-winning songwriter based in Charlotte, NC.

• Cloud Next site
• Solving for What’s Next blog
• Training more than 40 million new people on Google Cloud skills blog

• Cloud Next site
• Next Catalog site
• Opening Keynote site
• Solving for What’s Next blog
• GKE Autopilot site
• Workspace site
• Vertex AI site
• Apache Spark on Google Cloud site
• Tableau site
• Fivetran site
• HVR site
• Informatica site
• Trifacta site
• Anthos site
• Bringing multi-cloud analytics to your data with BigQuery Omni blog
• Google Distributed Cloud site
• NetApp site
• T-Systems and Google Cloud Partner to Deliver Sovereign Cloud for Germany press release
• Thales and Google Cloud Announce Strategic Partnership to Jointly Develop a Trusted Cloud Offering in France press release
• Google Cybersecurity Action Team site
• AppSheet site
• BeyondCorp site
• Google Earth Engine site
• Active Assist site
• Data Cloud Keynote site

Stephanie is working on a video series with Eric Brewer.

This week, Mark Mirchandani and Brian Dorsey welcome Perry Pierce and JoAnn Brereton of Major League Baseball to the show to talk sports and cloud. Baseball teams are independently owned franchises, Perry explains, with MLB acting as the oversight corporation. This keeps game play fair and consistent. Like most large corporations these days, technology has become a vital business tool for MLB. Their partnership with Google facilitated a shift from on-prem to the cloud, allowing MLB to take advantage of advanced capabilities like scaling and managed services in a safe environment. JoAnn talks about the process of this shift and the teams at Google that helped make it happen. She details the systems that MLB has moved to GCP, like game scheduling, umpire management, backend systems, and especially the draft.

The amateur draft, a multi-day event, has a special set of challenges that MLB and Google had to overcome. Analyzing player statistics and updating which players have been picked and who is still available are important information for teams. These stats must update quickly and accurately. On the backend, the Electronic Baseball Information System (EBIS) is the MLB software making this all happen, and JoAnn helps us understand the technical side of this Kubernetes-built platform. Google monitoring and EBIS-specific tools keep the draft running smoothly. Our guests take us through this list of tools employed and why they were chosen.

We hear more about the process of moving such a complicated system to the cloud and what MLB did to make the shift easier. Perry and JoAnn talk about the testing done before draft days to ensure a smooth experience for all and important lessons they learned. To wrap up the show, our guests offer advice, stressing the importance of observability and starting small. Major League Baseball trademarks used with permission.

Baseball is what Perry Pierce loves and tech is what he does. Living at the intersection of sports and tech is a cool place to be!

JoAnn loves baseball and tech, so she’s happy to be working at a job where she gets to do both.

• Cloud NAT explained! blog
• Build your data analytics skills with the latest no cost BigQuery trainings blog
• Introducing Workflows callbacks blog

• MLB site
• MLB Draft site
• Kubernetes site
• Grafana site
• Inside Baseball: How MLB Transactions Actually Get Done blog
• LBi Software site

Brian has been working on a YouTube series on VMs with Carter Morgan.

Next week is Google Cloud Next!

Alexandrina Garcia-Verdin and Stephanie Wong host this week’s episode all about managing non-REST APIs. Guests Nandan Sridhar and Dave Feuer start the show introducing our listeners to Apigee, a full life cycle API management tool, and the three tenets of Apigee that streamline the relationship between producers of APIs and their users.

APIs have come a long way as technologies have changed, and David explains the evolution of API development and how it relates to the newer non-REST APIs. The consumption of applications has significantly changed, but Nandan points out that developer strategies and experiences have also changed. These advances have led to the popularity of non-REST APIs. APIs are being used in new ways David tells us, and through examples, we hear how Apigee is helping these companies realize their cutting-edge API goals.

Nandan helps our listeners understand the difference between REST and non-REST APIs and the advantages of the latter in today’s technological environments. Each of the four main types of non-REST APIs have their specialities, he explains, like GraphQL which is great for experiences, and gRPC, which has special communication features that increase efficiency. Our guests elaborate on the exciting features of these two protocols and how their uses will continue to innovate business and consumer interactions into the future.

Our guests offer advice for companies and developers looking to take advantage of these non-REST APIs and help us understand the role Apigee plays in protecting the quality of all types of APIs.

Dave Feuer is Senior Product Manager at Apigee, a part of Google Cloud Platform. Previously, Dave ran the Platforms & Strategies practice at a boutique consulting firm, designing and implementing developer programs for Fortune 100 companies. Prior to that, Dave ran enterprise product development and software engineering at IDT and Net2Phone, a telecommunications and payments company. Dave started his career as an embedded software development engineer, and frequently questions how he ended up spending so much time in Google Slides.

Nandan Sridhar works in the Product Management team at Google Cloud, Apigee. Nandan’s expertise includes API design standards, API security and microservices.

• What’s your org’s reliability mindset? Insights from Google SREs blog
• Climate TRACE site

• Apigee API Management site
• GraphQL site
• GraphQL Documentation docs
• Announcing Apigee’s native support for managing lifecycle of GraphQL APIs blog
• Getting started with Apigee API management using Apigee videos
• gRPC site

Alexandrina has been working on the Getting Started with Apigee API Management YouTube series.

Next is coming up soon, too!

On the podcast this week, our guests Brian Schwarz and Sean Derrington discuss the ins and outs of the new storage launches with your hosts Stephanie Wong and Jenny Brown. Brian gives light introductions to the five facets of Google’s data storage portfolio, like the primary storage solutions for files, storage of backups of data, and data transfer software and hardware.

Lately, the Google team has been enhancing existing data solutions and building new ones. Cloud Storage’s multi-region and custom dual-region options easily let customers keep data safe and accessible. Our guests explain what happens behind the scenes to make these features so effective. Brian and Sean describe the user experience, including how clients can see when data is being replicated and where. New capabilities like Turbo Replication allow more modernization for clients moving to the cloud as well.

Sean talks about the new Filestore Enterprise, which allows companies to move critical apps to the cloud quickly and securely, and we learn why accurate, fast file and data replication is so important for these large customers. If there is corruption or accidental deletion of a file, Brian and Sean tell us about the fail-safes that are in place and the process for recovery. Filestore Enterprise, Filestore Basic, and GKE working together offer a more customized approach for large clients, allowing them to allocate their critical projects to Enterprise and other less important applications to Basic. Stateful applications in containers are becoming more popular as well, and our guests tell us how Backup for GKE is the easiest way to protect GKE workloads.

Brian has had 20 years in product management in data center infrastructure. Before Google, he spent time at Veritas, Cisco, and most recently Pure Storage.

Sean has spent 20 years in storage product management. Before Google, he spent time at Veritas, Exablox, and StorageCraft.

• Run code samples directly in the Google Cloud documentation blog
• Why representation matters: 6 tips on how to build DEI into your business blog
• Google Cloud announces new Cloud Digital Leader training and certification blog
• Google Cloud Next site

• GKE site
• Google Cloud Storage site
• Filestore site
• Filestore Enterprise docs
• New storage features help ensure data is never lost blog
• Announcing Filestore Enterprise, for your most demanding apps blog
• Announcing Backup for GKE: the easiest way to protect GKE workloads blog
• Webinar: What’s New with Storage at Google Cloud site

Jenny is working on Google Cloud Reader and further audio formats for all your favorite cloud content.

Mark Mirchandani and Brian Dorsey are together again this week for an episode all about cloud migration using Txture and Accenture. Our guests Matthias Farwick of Txture, Patrick Niesel of Accenture, and Jason Purvor of Google help us understand their roles in cloud migration with some formal introductions to start the show.

Txture helps companies assess their migration capabilities, providing insights to what will be necessary in the process and how viable cloud migration is as an option. Accenture works with Txture to augment the planning of migration strategies for clients. Jason helps us understand how Google uses the information gleaned from these assessments to help customers understand what the journey to Google Cloud will look like for their business. Txture provides good data which helps Google and clients make better decisions, not just in migration, but for the future health of the project while operating in the cloud.

Our guests share the challenges of cloud migration and detail how these three powerhouse companies work together to overcome hurdles. From information gathering and budgeting to security and implementation, Txture, Accenture, and Google help companies understand their specific obstacles and develop a plan. Matthias uses a large banking client as an example to walk our listeners through a typical cloud migration process that takes advantage of Txture, Accenture, and Google.

Jason details the process customers go through with Google as they establish their cloud environments and make decisions about the future of their projects. Through the analysis of four layers, Google helps customers think through this highly technical and involved migration process. Matthias describes the three assessment steps Txture applies to the process as well, and how these multiple-company analyses work together to create a solid cloud project now and continue to improve the project in the future.

Matthias, Patrick, and Jason offer advice for companies considering a shift to the cloud, stressing the importance of preparing good data and keeping time predictions realistic. Company-wide cooperation is an important tool in the success of a cloud migration as well.

Matthias Farwick co-founded Txture, a software for large scale cloud application assessments and modernization programs that is currently expanding to the US. Matthias is an avid mountaineer and skier.

Patrick Niesel has been working within Accenture focusing on cloud transformations and in particular on application assessments.

Jason Purvor is a data centre exit strategist engaged in large scale migrations and “all in” transformations. He formerly ran CloudPhysics EMEA supporting Googlers with high resolution data center assessments.

• What is Cloud SQL? blog
• Save money and time with automated VM management and suspend/resume blog
  • Cost optimization using automated VM management docs

• Txture site
• Accenture site
• Cloud Insider site
• Txture Cloud Transformation site
• Data Centre Transformation with Google site
• Cloud Maturity Assessment site
• Google Cloud Adoption Framework whitepaper
• Accenture-Google Business Group site
• The Txture Cloud Transformation Platform site
• Cloud Center of Excellence blog
• The 6Rs of Cloud Transformation blog
• Cloud-to-Cloud Assessment blog

Brian is working on a video series called VM End to End with Carter Morgan.

Carter Morgan and Guillaume Laforge co-host this week’s episode about what it took to develop the Google I/O Adventure Game. Our guest Valentin Deleplace and Guillaume introduce us to the game designed to encourage interaction with I/O attendees at the virtual conference held this year.

Adventure takes the look of a 90s role-playing game. The online world facilitates the meeting of hundreds of conference attendees and presenters to mimic the in-person conference setting and facilitate meaningful conversations. With avatars, text chatting capabilities, and mini games, attendees’ experiences go beyond simply watching online technical presentations.

The development of Adventure Game required scalability to handle varying attendee numbers. It takes advantage of many GCP products, including Compute Engine and Cloud Run. Valentin describes why he and the team chose Cloud Run and how they used it to to stress test the game. He talks about challenges the team faced and how they overcame them to produce a smooth, enjoyable experience for conference-goers. Being a game that’s live for specific periods of time rather than indefinitely presented different challenges as well. Valentin explains that scaling down, for example, is treated differently for this type of game.

Adventure will be available at future conferences.

Valentin Deleplace is a developer advocate at Google. He’s also a senior cloud backend engineer, interested in performance and UX, and an enthusiast Gopher.

• New Cloud Functions min instances reduces serverless cold starts blog
• What’s the key to a more secure Cloud Function? It’s a secret! blog
• Shift security left with on-demand vulnerability scanning blog
• All you need to know about Cloud Storage blog

• Google I/O site
• Chrome Dev Summit site
• Join the Adventure at Google I/O video
• Google’s I/O Adventure was almost as good as being there article
• Set Snail site
• Compute Engine site
• Cloud Run site
• Using WebSockets docs
• App Engine site
• Agones site

Carter is working VM End to End.

Guillaume is working on new features for Cloud Workflows and helping with the Serverless Expeditions videos.

Your hosts Stephanie Wong and Alicia Williams talk about BigQuery Admin Reference Guides with guest Leigha Jarett. Leigha tells us a bit about the origins of the Admin Reference Guide, which was developed to address frequent customer questions. The series of guides and videos covers onboarding topics from resource hierarchy and APIs to BigQuery tables and storage in an effort to help new admins get started.

The team’s Reference Guide on tables helps admins understand the difference between federated and native tables, and Leigha tells our listeners some tips for using each type. Slots and reservations for workload management in BigQuery can be challenging to understand, but these Reference Guides and accompanying videos offer clear explanations. Optimizing projects for speed and monetary efficiency are important topics for any client, and Leigha and the optimization team have addressed these concerns as well. Tips for monitoring, data governance, and the secure sharing of data are also included in their video series, BigQuery Spotlight.

We wrap up with a discussion on BigQuery APIs and how easy it is to integrate BigQuery and other Google products.

Leigha is a developer advocate on the Google Cloud Data & Analytics team. She focuses on making sure developers using tools like BigQuery and Looker are getting the most possible value from their data.

• Analyze Cloud Spanner data in BigQuery with federated queries docs
• Release notes dataset in BigQuery docs and XML feed
  • Google Cloud release notes docs and XML feed
  • Release notes in Cloud Console site
  • Top 25 Google Search terms, now in BigQuery blog

• BigQuery Admin Reference Guide Blog Recap site
• BigQuery Admin Reference Guide blog posts site
• BigQuery Spotlight Video Series videos
• BigQuery site
• BigQuery Documentation docs
• Cloud Spanner site
• Data Catalog site
• Apps Script site
• Looker site

Alicia is building new BigQuery architectures in order to understand the journey and identify potential pain areas that may need more support.

This week on the podcast, we welcome guest Megan O’Keefe to talk about KRM and Kubernetes with your hosts Mark Mirchandani and Anthony Bushong. To start the show, Megan gives us a quick rundown of Kubernetes, an open-source tool to orchestrate containers and manage other GCP resources. She explains the difference between declarative and imperative to help us better understand the basics of Kubernetes.

We tackle the challenges people face when beginning their Kubernetes journey and how it works with other open-source projects, like Anthos. This year, Megan and her team have been working to help developers understand the Kubernetes Resource Model, a concept that helps define how companies can organize and run clusters, enforce policies, and more for improved standardization across multiple teams.

Megan explains GitOps, a deployment model for Kubernetes focusing on Git, and takes us through examples of implementation. We learn about Config Sync and how it helps with optimizing and automating GitOps. Megan goes over some other valuable tools, including Open Policy Agent and Gatekeeper, which help developers specify not just which resources are allowed, but also what kinds of things are allowed within each resource.

We wrap up the show with a discussion on streamlining the development process with strategic use of Kubernetes and the help of open-source tools like Skaffold. Megan also talks about controllers like Config Connector that help with deploying to a GCP project and the things she finds most exciting about this space.

Megan O’Keefe is a Developer Relations Engineer at Google Cloud, helping developers build platforms with Kubernetes and Anthos.

• Listen up! Google Cloud Reader reaches 50 episodes blog
• Private Pools Overview docs

• Kubernetes site
• GKE site
• KRM site
• KRM Tutorial Demos site
• Build a platform with KRM: Part 1 - What’s in a platform? blog
• Build a platform with KRM: Part 2 - How the Kubernetes resource model works blog
• Build a platform with KRM: Part 3 - Simplifying Kubernetes app development blog
• Build a platform with KRM: Part 4 - Administering a multi-cluster environment blog
• Build a platform with KRM: Part 5 - Manage hosted resources from Kubernetes blog
• I do declare! Infrastructure automation with Configuration as Data blog
• Multi-cluster Use Cases docs
• CNCF Kubernetes Overview site
• Anthos site
• Anthos Technical Overview docs
• Anthos Config Management site
• Config Sync Overview docs
• Guide To GitOps site
• Policy Controller Overview docs
• Kustomize site
• Cloud Code site
• Config Connector Overview docs
• Crossplane site
• Skaffold site
• Open Policy Agent site
• Backstage site

Anthony shared info about GKE on the podcast last week and he’s been working on his video series on GKE cost optimization. The solutions guide and white paper are great resources for this topic.

Kaslin Fields and Mark Mirchandani host this week’s episode of the podcast as we celebrate one of our favorite Google products, Google Kubernetes Engine! Anthony Bushong and Gari Singh join the party to talk about GKE’s life journey, what’s new, and what’s coming up for the service.

Each guest brings their unique perspective to the show starting with their definitions of Kubernetes and GKE, tailored to a six year old. How does Kubernetes relate to cookies, Disney World, and Pokemon? Kaslin, Anthony, and Gari break it down.

Next, each guest talks their favorite GKE features and what makes the service different. Kaslin loves the persistent storage feature, among others. Anthony appreciates the evolution of GKE to a place where it supports many different workloads and situations for clients and how easy it is to get started with GKE. GKE’s ability to connect easily to other GCP products and features and GKE Autopilot are some of Gari’s favorite things about the service.

Best practices and advice for new users are shared by our guests. From practical tips for project planning to encouragement with long-term problem solving, our guests offer listeners resources and ideas for a successful GKE project. Kaslin, Anthony, and Gari share their favorite customer stories with us and talk about the fun, interesting events Google has hosted for GKE customers.

The future of GKE looks bright, with new options for Windows containers, expanded Autopilot uses, and multicluster support. KubeCon is coming up soon, so keep an eye out for more Kubernetes and GKE news!

Anthony Bushong has been working in the field with production GKE users, both large and small, for almost 5 years now. In Kubernetes time, since Kubernetes v1.3!

Gari Singh is an Outbound Product Manager focused on GKE and Anthos. In this role, he has the opportunity to work with many customers and help align their needs with overall product direction.

Kaslin Fields is a Developer Advocate at Google Cloud, a Cloud Native Computing Foundation (CNCF) Ambassador, and a contributor to Open Source Kubernetes. As a Developer Advocate, she engages with Open Source communities both as a member, and as an advocate for their needs as users (or potential users) of Google Cloud’s products. She is passionate about making technology accessible to a broad audience through making the information available in many forms, such as videos, blogs, documentation, and even comics which she illustrates herself!

• Try a tutorial in the Google Cloud Console blog
  • GCP Podcast Episode 180: Firebase with Jen Person podcast
• Migrate, Manage & Modernize: Windows Workloads Powered by GKE and Anthos site

• GKE site
• Kubernetes site
• Explain Like I’m 5: Containers VS VMs blog
• Introducing GKE Autopilot: a revolution in managed Kubernetes blog
• Best practices for running cost-optimized Kubernetes applications on GKE docs
• Discover and invoke services across clusters with GKE multi-cluster services blog
• The evolution of Kubernetes networking with the GKE Gateway controller blog
• Bringing Pokémon GO to life on Google Cloud blog
• Bayer Crop Science seeds the future with 15000-node GKE clusters blog
• Helping researchers at CERN to analyze powerful data and uncover the secrets of our universe blog
• Optimize costs in GKE with monitoring systems video
• Monitoring for efficient cluster binpacking in GKE video
• Monitoring for app right-sizing in GKE video
• Cloud Next 2021 site
• KubeCon site
• GCP Podcast Episode 210: Kubernetes Config Connector with Emily Cai podcast
• GCP Podcast Episode 234: GKE Turns Five with Alex Zakonov and Drew Bradstock podcast
• GCP Podcast Episode 252: GKE Cost Optimization with Kaslin Fields and Anthony Bushong podcast
• GCP Podcast Episode 257: GKE Autopilot with Yochay Kiriaty and William Denniss podcast

Kaslin is working on a ton of things, including Kube Essentials and GKE Essentials (coming soon), KubeCon panel and keynote addresses, and Fields Tested - CNCF Twitch - CTF.

Guest Ryan Przybyl is back this week to tell hosts Lorin Price and Stephanie Wong more about service networking and what the future holds for the networking field. Picking up from last week, Ryan starts by detailing the products and features Google has developed to help enterprise customers shift to a service networking architecture. He walks us through an example scenario and explains how a company might work with Google to gradually shift.

Google continues to grow in the service networking space. As client requirements are identified or changed, Google continually develops products to satisfy the varying networking needs. Ryan talks about tools like Network Intelligence Center, which allows network visibility and aims to ease the transition for traditional networking specialists. He talks about the Grow with Google Model, a term he coined to describe the step-by-step path his team helps enterprises take in the journey to full service networking. The process can take years and Ryan encourages clients to revisit their models periodically to take full advantage of new Google product offerings. He addresses the financial aspects of the networking shift as well.

Ryan offers advice for companies looking to move to the cloud and tells our listeners his thoughts on the future of networking.

Ryan Przybyl is a Networking Specialist at Google Chicago, and has held roles in both Cloud Customer Engineering and Google’s Network Operations. Prior to Google, Ryan was the Senior Director of Sales Engineering for Level 3 Communications. Ryan’s focus is on helping customers understand Google Cloud’s networking technologies while ensuring customers make use of Google Cloud best practices. When not talking with customers, Ryan is usually working with product and engineering teams to ensure Google Cloud is developing the right networking products for the future.

• Consume services faster, privately and securely - Private Service Connect now in GA blog
• Elevate your security with new Secret Manager features and integrations blog
• Google named a Leader in 2021 Gartner Magic Quadrant for Cloud Infrastructure and Platform Services again blog

• Google Cloud Networking Products site
• Private Service Connect docs
• Private Service Connect and Service Directory: A revolution to connect your application in Cloud video
• Migration to Google Cloud: Getting Started docs
• What’s New in Networking videos
• The future of service networking video
• Traffic Director site
• Envoy Proxy site
• Network Intelligence Center site

Lorin is working on Private Service Connect docs.

Stephanie is working on new episodes of What’s New in Networking.

This week on the show, Lorin Price and Stephanie talk about the differences between traditional and service networking with guest Ryan Przybyl. Ryan starts the show telling us how customer needs and advancing cloud technologies have shifted the conversations he has with customers from a traditional networking focus to an emphasis on cloud services.

Ryan describes how he helps different sized companies approach networking, whether they’re cloud native or shifting to a cloud approach from a traditional background. For example, companies that take advantage of Google Cloud and its services can deploy environments quickly, allowing developers to work without infrastructure constraints. Enterprise companies using more traditional networking that move into the cloud will need to make some changes, Ryan says, comparing apples to oranges. They want to move in a way that takes advantage of the cloud without negatively impacting performance.

Later, Ryan tells us all about service-oriented networking and how it’s possible for companies to choose pieces to shift to a service-oriented architecture without re-doing the entire project. We learn about Google’s Private Service Connect which handles things like routing for companies connecting to third party services. Ryan offers some advice for companies considering this move and regales us with interesting anecdotes from his time helping clients.

Ryan Przybyl is a Networking Specialist at Google Chicago, and has held roles in both Cloud Customer Engineering and Google’s Network Operations. Prior to Google, Ryan was the Senior Director of Sales Engineering for Level 3 Communications. Ryan’s focus is on helping customers understand Google Cloud’s networking technologies while ensuring customers make use of Google Cloud best practices. When not talking with customers, Ryan is usually working with product and engineering teams to ensure Google Cloud is developing the right networking products for the future.

• Private Service Connect is GA blog
• Securing the software development lifecycle with Cloud Build and SLSA blog
  • Container Security: Building trust in your software supply chain site
• Introducing Cloud Build private pools: Secure CI/CD for private networks blog

• Google Cloud Networking Products site
• Private Service Connect docs
• Private Service Connect and Service Directory: A revolution to connect your application in Cloud video
• Migration to Google Cloud: Getting Started docs
• What’s New in Networking videos

Lorin is working on Private Service Connect docs.

Philip O’Toole and Reed Taylor talk with Stephanie and guest host Terry Ryan all about the new features in Google Cloud Logging on this episode of the podcast. Cloud Logging provides users with management and analyzation of project logs, the reports that describe the state of every system in a project.

Reed walks us through Cloud Logging, including a list of features and how other GCP products integrate well with Logging. Once logs are sorted, Cloud Logging also provides tools for detailed query and analysis of log data. But storage and management of logs is as important as sorting and analyzing, and Reed tells us why this third component is vital.

New features in storage and management promise to streamline the process. Log Buckets, for example, allow the separation of routing and storage, while Log Views make secure field-level access possible. Log Retention means users can dictate how long different types of logs are stored. These new features help users comply with standards and regulations in the data space. Our guests give more examples of how these tools improve logging tasks.

Philip O’Toole is an Engineering Manager at Google Pittsburgh, leading development teams working on GCP’s Cloud Logging Platform. Prior to Google he led development teams at InfluxDB, Loggly, and Riverbed Technology. You can find him on the web at https://www.philipotoole.com.

Reed Taylor is a Senior Product Manager at Google Pittsburgh, just last week marked his 10th “Googleversary” since starting at the office. In that time he’s worked on a range of products including Google Search, Google Shopping, and AdWords. Reed joined GCP just this Spring, and is now focused on Logging products within the Cloud Operations suite.

• Grow your ML skills with free offer from Coursera blog
• Advancing our trusted cloud with engineered-in, invisible security blog

• Google Cloud Logging site
• Google Cloud Logging Documentation docs
• Managing log buckets docs
• Managing log views on your log buckets docs
• Data Governance for Log Data Whitepaper site
• Principles for Security and Managing Logs Whitepaper site

Terry has been working on tutorials for the Cloud Ops team. His recent Cloud Logging tutorial is available now.

This week on the podcast, hosts Stephanie Wong and Bukola Ayodele speak with Nikhil Kaul and Victor Szalvay about security in the software supply chain. Cloud OnAir will be offering a virtual event on supply chain software security on July 29th, and our guests start the show by telling us more about it.

The recent cyber attacks on US companies have brought to light the importance of cyber security. A new set of guidelines for securing these components and software as a whole will be released soon, impacting not just software developers but the users as well. The Cloud OnAir event will breakdown these new guidelines and educate attendees on steps to take to ensure more secure software and software components. Internally, Google has been optimizing their software supply chain security for years with solutions like BeyondCorp and internally developed solutions that Google has since adapted for their clients. These solutions will be discussed in detail in the Cloud OnAir event.

Victor goes on to explain the three areas of supply chain security and how they fit into the overall security of online platforms. Software projects are often built using many small pieces of software sourced from third parties, which can create vulnerabilities. The new guidelines will help ensure quality and security at all levels of development for software and its pieces, thus strengthening security at every level of the supply chain. Nikhil and Victor talk about issues that contribute to supply chain security, including the risks that a microservices architecture can introduce and the use of open source software and their dependencies. We hear about Google’s contributions to the supply chain security effort, like OpenSSF that strives to bring the open source community together toward the goal of cyber security. Our guests give listeners tips on starting the supply chain security journey.

Join the Cloud OnAir talk to learn more!

Nikhil leads a team of product marketers focused on driving and building messaging, positioning, and go-to-market strategy for Google Cloud’s DevOps portfolio.

Victor is an Outbound Product Manager with Google Cloud focused on helping customers get the most from the cloud. Previously he has been a tech entrepreneur and leader, with a concentration on DevOps and app dev team productivity.

• Helping you pick the greenest region for your Google Cloud resources blog
• Optimizing your Google Cloud spend with BigQuery and Looker blog

• Container Security: Building trust in your software supply chain site
• OpenSSF site
• Deps site
• SLSA site
• Cloud Build site
• BeyondCorp site
• Binary Authorization for Borg docs
• GKE Autopilot docs
• GCP Podcast Episode 251: BeyondCorp with Kiran Nair and Ameet Jani podcast

Bukola is working on the new season of Security Command Center set to be released next month!

Brian Dorsey and Mark Mirchandani are talking intro to Firestore this week with fellow Googler Allison Kornher. Allison, a Cloud Technical Resident, starts the show telling us about the program and how it brought her to Firestore.

Allison takes us through the differences between SQL and NoSQL databases and describes the four categories of NoSQL databases: family, document, key value, and graph. Firestore is a scalable, flexible NoSQL document database. To illustrate the uses and benefits of Firestore, Allison walks us through a delicious pizza example. Each document in the database belongs to a collection, which is used to organize these documents. Firestore documents are assigned an identifier and can be quickly changed and called within their collections. Because these documents are stored in an implicit schema in key value pairs, developers have control over the details of database organization and data change and growth are easy to manage. The availability of subcollections further adds to the flexibility of Firestore database design.

Choosing a database type will depend on the situation, and Allison suggests this starts with a look at CAP theorem. If a document database is your database of choice, Allison gives our listeners tips for getting started with Firestore and clearing any hurdles along the way.

Allison is a Cloud Technical Resident and has worked helping startups looking to join GCP and in the Premium Tier Cloud Support organization with a focus on Storage.

• BigQuery admin reference guide: Tables & routines blog
• Top 25 Google Search terms, now in BigQuery blog
• Three security and scalability improvements for Cloud SQL for SQL Server blog
• GCP Podcast Episode 247: Cloud SQL Insights with Nimesh Bhagat podcast
• GCP Podcast Episode 163: Cloud SQL with Amy Krishnamohan podcast

• Cloud Firestore site
• Cloud Firestore Documentation docs
• Cloud Firestore explained: for users who never used Firestore before blog
• Gabi on Twitter site
• Datastore site
• BigTable site
• Firebase Realtime Database site
• Memorystore site
• Cloud Spanner site
• GCP Podcast Episode 248: Cloud Spanner Revisited with Dilraj Kaur and Christoph Bussler podcast
• All you need to know about Firestore: A cheatsheet blog

Brian has been working on sharing a persistent disk between Google Compute Engine VMs.

• Cloud Storage site
• Cloud Filestore site
• Cloud SQL site

Stephanie Wong and Jenny Brown are your hosts this week, discussing data analytics with the yin and yang of the field, Bruno Aziza and Eric Schmidt. Our guests introduce us to three new Google offerings, BigQuery Omni, Dataplex, and the Analytics Hub, and discuss the uses and implications of each and how they work together to achieve goals.

Bruno and Eric describe challenges in data analytics and how Google uses these as opportunities to create problem-solving systems that solve real client problems. Through real-world examples from companies like Equifax, we see how companies are getting more information from their data in a way that creates actionable opportunities to improve customer experiences.

For multi-cloud companies, BigQuery Omni gets the most out of data that exists in multiple clouds. To accomplish this, Google takes the analytics to the data and is able to reach all appropriate data across clouds without having to move it. This allows for cheaper analysis with much less system downtime. Support for Azure was added this year.

The new Dataplex software helps customers intelligently manage data assets, especially in distributed systems. Dataplex lets companies automatically discover data, make data secure without having to move it, and apply governance and policies centrally so the data is accessible. Rather than sit unused, data can now be found easily, analyzed securely, and put to work for companies no matter where their data lives.

For analytic asset sharing, Analytics Hub lets companies coordinate with others to get the most use out of their data efficiently. Analytics Hub gets to data value as quickly and easily as possible. Companies can publish, discover, and subscribe to shared assets, create exchanges that combine data sets, and curate exchanges of data and insights for full information sharing.

Eric is the Head of Advocacy for Data Analytics at Google and has been with us for almost 8 years. He comes to us from Microsoft, where he led Advocacy and Evangelism there, too. Eric is an expert in products like BigQuery, Dataflow, Dataproc and leads a team of leaders who help customers turn data into value. In his downtime, Eric is also a Dj at KEXP 90.3 Seattel - KEPX.ORG where he guest hosts a modern global music show. You can find Eric on Twitter. His handle is @notthateric - not to be confused with the ‘other Eric Schmidt’ here at Google. In fact, internally, we affectionately call him “cloude”.

Bruno is the Head of Data & Analytics at Google Cloud and specializes in everything data, from data analytics, to business intelligence, data science, and artificial intelligence.

Before working at Google, Bruno worked at companies like Business Objects when it went IPO and Oracle, where his team led one of the fastest turnarounds in the business analytics industry. He led the launch of startups like Alpine Data (now part of Tibco), Sisense and AtScale and he helped Microsoft grow its Data unit into a $1B business. Bruno has been educated in the US, France, the UK, and Germany. He has written two books on Data Analytics and Performance Management. And he has a monthly column on Forbes.com on everything Data, AI and Analytics.

• BigQuery row-level security enables more granular access to data blog
• Expanding access to quantum today for a better tomorrow blog
• Expanding partner solutions at the network edge blog

• Data Cloud Summit site
• Bringing multi-cloud analytics to your data with BigQuery Omni blog
• Dataplex site
• Analytics Hub site
• Intelligent Data and Analytics Fabric video
• GCP Podcast Episode 253: Data Governance with Jessi Ashdown and Uri Gilad podcast
• Public Data Sets site
• Smart analytics reference patterns site
• Data and Analytics Sharing at Equifax: Immediate, Interconnected, Scalable, and Secure video
• BigQuery ML site
• Learn more about these launches site

Jenny has been working on Google Cloud Reader episodes on BigQuery Explained.

On the podcast this week, Stephanie Wong and Abdel Sghiouar are joined by guest Jan Harasym of Sharkmob Games, who starts the interview describing how he and his team designed the infrastructure for The Division. With the game’s sequel, The Division II, in development, Jan and his team made the decision to use a cloud provider. Jan describes the differences between on-prem and cloud, outlining the benefits of GCP for game development and hosting, including better reliability and development environments. Scaling a cloud project can be much more efficient, and Jan tells us some tricks for doing it well. We talk about the process of migrating this large game to Google Cloud and how they choose the software and development tools they used.

When Sharkmob migrated to the cloud, Jan worked to convince the company that GCP was the way to go. He tells us more about how he persuaded the team, how they planned the migration, and the overall success of the process. Sharkmob is working on two new projects for the future and soon will be releasing a new game, Vampire Masquerade Blood Hunt.

Jan has helped make online games work for eight years. Most recently, he helped release Tom Clancy’s The Division 2 with online infrastructure on top of GCP.

• New Tau VMs deliver leading price-performance for scale-out workloads blog
• Introducing container-native Cloud DNS: Global DNS for Kubernetes blog
• Google for Games Developer Summit 2021 site

• Sharkmob site
• The Division 1 site
• The Division 2 site
• Massive site
• Unreal site
• Zookeeper site
• Agones site
• Kubernetes site
• GKE site
• Blood Hunt site

Abdel is working on GKE Network Recipes.

Our old pal Mark Mirchandani is back this week, joining Stephanie Wong and our guests Steve McGhee and Yuri Grinshteyn to talk about Site Reliability Engineering. SRE is Google’s way of helping companies of all sizes create consistent, predictable, and functional projects. It helps clients approach operations from a software engineering stand point so that growing systems can be managed efficiently.

We talk about the challenges of implementing best SRE practices and how companies can overcome these. Though the benefits of SRE are many, it can be difficult for clients to grasp. Steve and Yuri tell us the process they go through with customers to help them set realistic goals and work to make reliable, scalable projects with little downtime. By starting small and taking wins early, Steve says clients reap the rewards of SRE and are encouraged to push forward. Yuri’s customer-centric approach encourages companies to prioritize alerts that affect the user experience, thus limiting inbox mayhem and keeping customers happy. Alerts based on symptoms, Steve says, help accomplish this goal.

Later, Yuri and Steve describe the best ways for companies to get started with SRE. Realistic goals and specific detailed plans can make the journey less bumpy for clients, and Google’s SRE team can help.

Steve was an SRE at Google for about 10 years, then left to help a company build reliable systems on the Cloud. Now he’s back at Google, helping more companies do that.

Yuri works with Google Cloud Platform customers to help them design, architect, build, and operate reliable applications and services. He also advocates for SRE principles and practices on YouTube and elsewhere.

• Fresh updates: Google Cloud 2021 Summits blog
• Why you need to explain machine learning models blog
  • GCP Podcast Episode 260: Responsible AI with Craig Wiley and Tracy Frey podcast
  • GCP Podcast Episode 249: ML Lifecycle with Dale Markowitz and Craig Wiley podcast
  • GCP Podcast Episode 214: AI in Healthcare with Dale Markowitz podcast

• Site Reliability Engineering site
• Reliability Architecture Framework site
• Site Reliability Engineering: Measuring and Managing Reliability on Coursera site
• Developing a Google SRE Culture on Coursera site
• How Lowe’s meets customer demand with Google SRE practices blog
• GCP Podcast Episode 68: The Home Depot with William Bonnell podcast
• GCP Podcast Episode 213: The Art of SLOs with Alex Bramley podcast
• GCP Podcast Episode 127: SRE vs Devops with Liz Fong-Jones and Seth Vargo podcast
• GCP Podcast Episode 72: Customer Reliability Engineering with Luke Stone podcast
• GCP Podcast Episode 38: Site Reliability Engineering with Paul Newson podcast
• GCP Podcast Episode 59: SRE II with Paul Newson podcast

Yuri has been working on Engineering for Reliability.

Stephanie has been working on her new series What’s New in Networking.

Max Saltonstall and Carter Morgan co-host the podcast this week and talk APIs with our guests, Dave Feuer and Benjamin Schuler. Apigee, an API management platform that is a part of Google Cloud, focuses on all steps of the digital product life cycle to make API management easy for clients. The software company SAP provides data storage and other business support for different types of companies across the world. Together, Apigee and SAP allow data to be collected, stored, organized, and securely accessed and shared with other applications.

The shift to e-commerce and the desire for tailored experiences has driven the need for more API usage and therefore better API management. SAP and Apigee, with their myriad features, allow businesses to keep up with these increasing demands efficiently. We hear examples of how companies are leveraging these tools and use cases where the power of SAP and Apigee benefit customers most. Our guests describe the developer experience as well. We talk about the process of creating a project with both SAP and Apigee and why both tools working together makes the developer’s job easier. Planning your project with an “API first” mindset means choosing APIs and SAP software early in the planning process to better align your project with your business goals. Apigee can help you manage these APIs securely, letting you choose the data that is shared. The use of both SAP and Apigee helps companies to realize long-term efficiency and streamlined operations as development becomes easier with each additional API.

Benjamin Schuler is a Solution Manager for SAP at Google Cloud with a focus on topics around application modernization. Prior to joining Google, he was working directly for SAP’s consulting unit and helped companies move parts of their SAP landscape to the cloud. When he is not busy populating spreadsheets or adding yet another //TODO: to his demo apps, he likes to get out onto the water for some freeride kitesurfing.

Dave Feuer is Senior Product Manager at Apigee, a part of Google Cloud Platform. Previously, Dave ran the Platforms & Strategies practice at a boutique consulting firm, designing and implementing developer programs for Fortune 100 companies. Prior to that, Dave ran enterprise telecommunications product development and software engineering at IDT and Net2Phone, a telecommunications and payments company. Dave started his career as an embedded software development engineer, and frequently questions how he ended up spending so much time in Google Slides.

• AI Simplified: Managing ML data sets with Vertex AI blog
• Create your own journaling app without writing code blog
  • AppSheet Journal site

• Apigee site
• Apigee Setup site
• SAP site
• Apigee: Your gateway to more manageable APIs for SAP blog
• Accelerate the time to value of your SAP data with Apigee video
• GCP Podcast Episode 54: API Lifecycle with Alan Ho podcast
• GCP Podcast Episode 219: Spotify with Josh Brown podcast
• Conrad Electronic: Powering next-gen retail with BigQuery and Apigee API management site
• Schlumberger chooses GCP to deliver new oil and gas technology platform blog
• Schlumberger Selects Google Cloud for its Enterprise-Wide SAP Migration and Modernization site

Max is documenting how Google & Alphabet made the move to SAP. He’s also working on a Discord bot on Google Cloud and ITRP series launch.

Carter is working on a SAP content video series and teaching in the Equity Through Technology program.

Stephanie Wong and cohost Gabi Ferrara talk about the exciting launch of Database Migration Service at Google. Our guests this week, Shachar Guz and Gabe Weiss, start the show explaining DMS, focusing on the ease of infrastructure management for cloud users.

Migration is made simpler with DMS, and Shachar and Gabe walk us through the process of using this powerful new service. Our guests outline some hurdles to migration and how DMS and the DMS documentation help developers overcome them. Shacher tells us the steps companies should take before and after running DMS to ensure projects run correctly and business logic is preserved as well, and Gabe stresses the importance of testing.

Database Migration Service focuses on open source, and we talk about why this is an important benefit. In addition, the thorough explanations embedded in DMS help users navigate easily, serverless technology means projects are fast and efficient, and native applications are leveraged for better transparency. And it’s free.

Shachar is a product manager at Google Cloud, he works on the Cloud Database Migration Service. Shachar worked in various product and engineering roles and shares a true passion about data and helping customers get the most out of their data. Shachar is passionate about building products that make cumbersome processes simple and straightforward and helping companies adopt Cloud technologies to accelerate their business.

Gabe works on the Google Cloud Platform team ensuring that developers can make awesome things, both inside and outside of Google. Prior to Google he’s worked in virtual reality production and distribution, source control, the games industry and professional acting.

• Unlock the power of change data capture and replication with new, serverless Datastream blog
  • Introducing Dataplex—an intelligent data fabric for analytics at scale blog
  • Data Cloud Summit site
  • Google Cloud’s New 2021 Analytics Launches video
  • Bringing multi-cloud analytics to your data with BigQuery Omni blog
• Applied ML Summit site

• Database Migration Service site
• DMS Documentation docs
• Cloud SQL site
• Network Intelligence Center site
• Introducing Database Migration Service video
• Best practices for homogeneous database migrations blog
• Database Migration Service Connectivity—A technical introspective blog
• Migrating MySQL data to Cloud SQL using Database Migration Service Qwiklab site

Gabbi is going to CrimeCon for fun!

On the podcast this week, we’re diving into what full stack development looks like on Google Cloud. Guests Tony Pujals and Kevin Moore join your hosts Stephanie Wong and Grant Timmerman to help us understand how developers can leverage Dart and Google Cloud to create powerful and effective front end and back end systems for their projects.

Kevin takes us through the evolution of Dart and Flutter and how they have become a way to allow developers an experience-first solution. Developers can focus on the experience they want to create, then decide which platforms to run on. With Dart, Google provides business logic that allows developers to provide the front end and back end experience for users in one programming language. Our guests talk about the types of projects that will benefit most from the use of Dart and how Dart is expanding to offer more features and better usability. Flutter offers a high fidelity, rich framework that supports mobile and can be deployed on any platform. When paired with Dart on Docker Hub, developers can easily build optimized front and back end systems.

Tony and Kevin tell us about the new Functions Framework for Dart and how it helps developers handle deploying to serverless technologies. We hear more about how Dart, Flutter, and Cloud Run working together can make any project easy to build and easy to deploy and use.

Tony is a career engineer who’s now on the serverless developer relations team and focused on helping full stack developers succeed building their app backends.

Kevin is the Product Manager of Dart & Flutter at Google.

• What is Vertex AI? Developer advocates share more blog
• Google Cloud launches from Google I/O 2021 blog
• Secure and reliable development with Go | Q&A video
  • Google CloudEvents - Go site

• Flutter site
• Dart site
• Go site
• Datastore site
• Dart on Docker site
• Functions Framework for Dart on GitHub site
• Cloud Run site
• Dart Documentation docs
• Google APIs with Dart docs
• App Engine site
• Dart Functions Qwiklab site
• Flutter Startup Namer Qwiklab site
• Cloud, Dart, and full-stack Flutter | Q&A video
• Go full-stack with Kotlin or Dart on Google Cloud | Session video

Grant has been working on libraries for CloudEvents.

Stephanie Wong and Priyanka Vergadia host the podcast this week as we talk responsible AI with guests Craig Wiley and Tracy Frey.

Vertex AI, the newly released AI platform from Google, is where Craig starts, telling us that it helps seamlessly integrate AI best practices into AI projects. When designing and building machine learning projects, it’s important to plan and integrate functions that support a responsible model as well. Tracy and Craig help us understand the process of designing and building these responsible, efficient projects, from problem identification and data set collection and refinement to ethical model considerations and finally project construction.

Part of Responsible AI is considering all the stakeholders of a project and how they will be impacted. Through examples, Tracy demonstrates how businesses can decide if the software solution affects stakeholders in a way the business would be proud of. Starting in the planning stages and continuing through data collection and model training, companies employing responsible AI techniques will consider input from groups that may use or be affected by the model, from social scientist who specialize in human behavior, and others. Craig elaborates on these principles in the context of Vertex AI and how the time savings of Vertex could be used to make thoughtful, responsible AI decisions.

Craig teaches us more about Vertex as we wrap up the interview. Its ability to analyze data and perform ongoing model monitoring make for richer, more accurate projects. Tracy talks about the future of Responsible AI and how the marriage of tech and humanity will continue to produce ethical, effective AI projects.

Craig is the Director of Product for Google Cloud’s AI Platform. Previous to Google, Craig spent nine years at Amazon as the General Manager of Amazon SageMaker, AWS’ machine learning platform as well as in Amazon’s 3rd Party Seller Business. Craig has a deep belief in democratizing the power of data, and he pushes to improve the tooling for experienced users while seeking to simplify it for the growing set of less experienced users. Outside of work he enjoys spending time with his family, eating delicious meals, and enthusiastically struggling through small home improvement projects.

Tracy Frey is Google Cloud AI & Industry Solution’s Managing Director of Outbound Product Management, Incubation and Responsible AI and is dedicated to ensuring Google Cloud AI & Industry Solutions is responsible, thoughtful, and collaborative as it continues to advance artificial intelligence and machine learning. She has been at Google for more than 10 years where she has worked on many different products and areas. Before joining Google she worked at multiple early-stage tech startups where she held multiple functions including product management, developer relations, product marketing, business development and strategy. Prior to her life in tech she taught children traditional wilderness survival skills, taught in a traditional classroom, studied private reserves in Costa Rica and has been a professional hip hop dancer.

• Cloud CISO Perspectives: May 2021 blog
• The cloud developer’s guide to Google I/O 2021 blog

• Vertex AI site
• Responsible AI site
• Staying ahead of the curve – The business case for responsible AI article
• Building responsible AI for everyone site
• Cloud Storage site
• BigQuery site
• Data Cloud Summit site
• Applied ML Summit site
• GCP Podcast Episode 249: ML Lifecycle with Dale Markowitz and Craig Wiley podcast
• AI Edition Google’s Tracy Frey: Creating Responsible AI podcast
• TensorFlow Responsible AI Toolkit site

Priyanka has been working on the Vertex AI video series. Episode 1 and episode 2 are available now!

This week on the show, our guests Anu Srivastava and Sudheera Vanguri talk about Document AI with hosts Stephanie Wong and Dale Markowitz. Document AI uses artificial intelligence to improve the way businesses create and manage things like paystubs, tax forms, contracts, and virtually any other business document. Data normally stored on paper can be parsed, enriched, and structured, then stored securely with the use of Document AI. Data becomes more accessible and more manageable.

Our guests go on to describe the process of using this powerful tool and instances where developers and enterprise companies could benefit. We talk about Lending DocAI and Procurement DocAI and how offerings like Google Vision and Knowledge Graph enhance these powerful tools. Users of Document AI can take advantage of these tools as well as bring their own expertise to create custom models.

Later, we learn about the developer experience when using the Document AI Platform. Our guests talk specifically about the use of Knowledge Graph and how the advanced search capabilities allow Document AI users to collect data from myriad sources, filling in missing information and enhancing the search with other useful data to make your results more usable. To demonstrate the use of the platform and integrated Google AI tools, we hear about the real-world examples of Workday and Mr. Cooper and their document processing and model training.

Sudheera Vanguri is the head of Product Management at Google Cloud Document AI.

Anu Srivastava is an Applied AI Engineer for ML on Google Cloud. Before that, she was a software engineer in Android Google Cloud Infrastructure.

• A handy new Google Cloud, AWS, and Azure product map blog
  • Compare AWS and Azure services to Google Cloud docs
• Google Cloud and Seagate: Transforming hard-disk drive maintenance with predictive ML blog

• Document AI site
• BigQuery site
• Lending DocAI site
• Procurement DocAI site
• Cloud Natural Language site
• Google Vision AI site
• Google Knowledge Graph site
• Cloud Translation site
• Workday site
• Mr. Cooper site
• AODocs site
• Processors overview site
• Python Codelab site
• Getting started with the Document AI platform video

We’ve been working hard on Google I/O.

On the show this week, Mark Mirchandani joins Stephanie Wong to talk about serverless computing and the Cloud OnAir Serverless event with our guests. Aparna Sinha and Philip Beevers start the show giving us a thorough definition of serverless infrastructures and how this setup can help clients run efficient and cost-effective projects with easy scalability and observability.

Serverless has grown exponentially over the last decade, and Aparna talks about how that trajectory will continue in the future. At its core, the serverless structure allows large enterprise companies to do what they need to do, from analyzing real time information to ensuring dinner is delivered piping hot. Aparna describes the three aspects of next generation serverless, developer centricity, versatility, and built-in best practices, and how Google is using these to empower developers and company employees to create robust projects efficiently and economically. Phil tells us about the experience of using serverless products and the success of the three pillars in Google serverless offerings.

Enterprise customers like MediaMarktSaturn and Ikea are taking advantage of the serverless system for e-commerce, data processing, machine learning, and more. Our guests describe client experiences and how customer feedback is used to help improve Google serverless tools. With so many serverless tools available, our guests offer advice on choosing the right products for your project.

We also hear all about the upcoming Cloud On Air event and what participants can expect, from product announcements and live demos to thorough reviews of recently added serverless features.

Aparna Sinha is Director of Product at Google Cloud and the product leader for Serverless Application Development and DevOps. She is passionate about transforming businesses through faster, safer software delivery. Previously, Aparna helped grow Kubernetes into a widely adopted platform across industries. Aparna holds a PhD in Electrical Engineering from Stanford. She is Chair of the Governing Board of the Cloud Native Computing Foundation (CNCF). She lives in Palo Alto with her husband and two kids.

Phil has been at Google for seven years. He currently leads the Serverless Engineering teams and previously ran the Site Reliability Engineering team for Google Cloud and Google’s internal Technical Infrastructure. Phil holds a BA in Mathematics from Oxford University.

• The evolution of Kubernetes networking with the GKE Gateway controller blog
• Network Performance for all of Google Cloud in Performance Dashboard site
• Go from Database to Dashboard with BigQuery and Looker blog
• Introducing Open Saves: Open-source cloud-native storage for games blog

• Cloud Run site
• Cloud Functions site
• Serverless Computing site
• The power of Serverless: Get more done easily site
• App Engine site
• Building Serverless Applications with Google Cloud Run book
• MediaMarktSaturn site
• Ikea site
• Airbus site
• Veolia site

• “Fanfare1” by N2P5 of Freesound.org
• “Banjo Opener” by Simanays of Freesound.org

Kaslin Fields joins Stephanie Wong hosting the podcast this week as we talk all about GKE Autopilot with our guests Yochay Kiriaty and William Denniss. GKE Autopilot manages tasks like quantity and size of nodes so deploying workloads is faster and machines are used efficiently. Autopilot also offers cluster management options, including monitoring the health of nodes and other components.

William and Yochay explain that GKE Autopilot was built to aid companies in the efficient use of resources and give clients more time to focus on their projects. Important efficiency features that are optional in GKE, like multidimensional pod autoscaling, are employed automatically for clients in Autopilot, giving clients peace of mind. Kubernetes best practices are auto-deployed for projects so clients can rest assured things will run as quickly and smoothly as possible without extra work.

Kubernetes is a great way to manage containers, and our guests describe cases where this tool is best suited. We compare GKE standard mode and Autopilot, and Yochay tells us when developers might choose standard mode to allow for more specific customization. He talks about migrating between standard and Autopilot clusters with the goal of easy migration by the end of this year. Security is important for GKE, and we talk about the Autopilot security configurations and why they were chosen.

Later, our guests walk us through the process of a Kubernetes project on Autopilot, highlighting decisions this tool makes automatically for you and why. Though Autopilot sounds very much like a serverless offering, William explains the differences between tools like Cloud Run and GKE Autopilot. We also hear about the future of Autopilot, including some exciting new features coming soon.

Yochay is a Product Manager for GKE responsible for security.

William is a Product Manager for GKE Autopilot. He’s currently writing a book called Kubernetes Quickly.

• Google Cloud Region Picker site
  • Faster, cheaper, greener? Pick the Google Cloud region that’s right for you blog
• 5 resources to help you get started with SRE blog

• Kubernetes site
• GKE site
• Autopilot Overview docs
• GCP Podcast Episode 252: GKE Cost Optimization with Kaslin Fields and Anthony Bushong podcast
• Multidimensional Pod Autoscaling docs
• Docker site
• Cloud Run site
• Introducing GKE Autopilot: a revolution in managed Kubernetes blog
• Creating an Autopilot cluster docs

Kaslin has been working on KubeCon EU as a volunteer and will be presenting there as well.

This week on the podcast, Stephanie Wong and Alexandrina Garcia-Verdin are diving into an important topic for our global community: sustainability and carbon aware computing. Kendal Smith, program manager for Carbon Intelligent Computing, and Chris Talbott, leader of the sustainability product marketing efforts at Google Cloud, start the show telling us why sustainability is so important in the tech world.

Environmentally conscious data centers are an important part of Google Cloud sustainability efforts. Using computing in the smartest way possible, Kendall tells us, is the root of green computing. Wind, solar, and other low or carbon-free energy sources are employed at Google Cloud data centers to accomplish this goal. Kendall and Chris detail the green goals Google has met or exceeded, including carbon neutrality in 2007, and future goals for Google.

Chris explains how Google Cloud customers have taken advantage of Google’s sustainability practices and been inspired in their own businesses. Kendall details the Carbon Intelligent Computing Platform and how they adjust compute times to align with available carbon-free energy. We hear about Google’s sustainability metrics, including the Carbon Free Energy Percentage, and how these measurements can help Google and its customers run environmentally friendly applications. Chris describes the process he and his team go through when helping Google clients design their carbon aware strategy.

To wrap up the show, our guests talk about the future of de-carbonized computing at Google.

Kendal is the Program Manager for Carbon Intelligent Computing at Google, which reduces the carbon footprint of Data Centers by exploiting flexibility in compute workloads. She also helps Google engineers build products efficiently, as well as advise other Bets on carbon measurement and tracking.

Chris leads sustainability product marketing and customer engagement efforts for Google Cloud, and works on opening new Google Cloud data centers throughout the globe. He helps customers improve the environmental impact of their IT operations and identify new opportunities to tackle climate change challenges with cloud technology.

• Active Assist’s new feature, predictive autoscaling, helps improve response times for your applications site
• Maximizing developer productivity video

• Google Carbon Aware Computing Workshop 2021 site
• Our data centers now work harder when the sun shines and wind blows blog
• How carbon-free is your cloud? New data lets you know blog
• Google Cloud Region Picker site

Alexandrina is working on a new series called People & Planet AI. The first episode, Recovering global wildlife populations using ML is out now. She’s also been working on internal websites to share climate information.

Stephanie has been working on a blog post about AppSheet Automation, which we talked about in-depth last week on the podcast.

Stephanie Wong and co-host Carter Morgan learn all about the no-code experience of AppSheet Automation this week. Guests Jennifer Cadence and Prithpal Bhogill introduce us to AppSheet, a platform that empowers anyone to build applications without code. The strong focus on openness means AppSheet offers support for all manner of APIs and services, making it easy to use and customize.

Jennifer starts by telling us how AppSheet increases productivity and satisfaction at work. She describes how people’s individual characteristics and use of time affect productivity and explains that tasks that can be automated free people up to work on higher value tasks or focus on important issues. Employees are not only more productive but happier in their jobs when mundane or frustrating tasks are automated.

Later, Prithpal describes using the software. The AppSheet Unified Platform supports any application creator so users can build their apps and automations without ever leaving the AppSheet dashboard. Data stays where it is, with no upload requirements, further easing the build process. We hear some real-world uses of AppSheet Automation, including employee onboarding, customer support, and more. Prithpal takes us behind the scenes, using examples to explain the inner workings of AppSheet and walks us through the steps of using this powerful tool. Jennifer tells us how the AppSheet Community helps shape the platform and talks about the future of AppSheet Automation.

Jennifer is the Product Marketing Manager for AppSheet. She’s also a dog lover, community builder, and curious human.

Prithpal is the Lead Product Manager for AppSheet, frequent blogger, and featured speaker on several tech conferences.

• Choose your own cloud adventure video
• Recovering global wildlife populations using ML blog
  • Introduction to AI Platform (Unified) docs

• AppSheet site
• AppSheet Community site
• Invisible Woman book
• Apps Script site
• Workspace site

Stephanie and Carter are working on some new features for the podcast!

Stephanie will be speaking at CTC.

• “Applause 1” by Ichapman1980 of Freesound.org

Brian Dorsey joins Stephanie Wong this week for an in-depth discussion on Workflows. Guests Kris Braun and Guillaume Laforge introduce us to Google Cloud Workflows, explaining that this fully managed serverless product helps connect services in the cloud. By facilitating the creation of an end-to-end schema, Workflows lets developers specify what microservices or other software respond when certain events occur in a detailed, visual format.

Kris and Guillaume list the benefits of using Workflows and detail the many uses for this powerful tool. The ability to add detailed descriptors, for example, helps companies avoid errors in calling up other pieces of software. New employees have an easier time getting acquainted when the steps are clearly defined as well. Our guests use real-world examples to illustrate the three main uses for Workflows: event-driven, batch, and infrastructure automation. Workflows are flexible and customizable.

Later, we hear about Cloud Composer and its relation to Workflows, and our guests help us understand which product is right for each client type. The Workflows team continues to expand offerings. More connectors are being added to allow developers to call other GCP services. Working with lists will soon be easier, allowing Workflows to run steps in parallel. And Kris details other exciting updates coming soon, including Eventarc.

Kris Braun is the Product Manager for three Google Cloud products that connect services to build applications: Workflows, Tasks, and Scheduler. Before Google, Kris’ adventures include founding and growing startups, leading a team of network security researchers investigating threats like Stuxnet, and writing the original BlackBerry simulator for app development. He’s a passionate advocate for opening job opportunities to skilled refugees displaced by war and disaster.

Guillaume Laforge is a Developer Advocate for Google Cloud, focusing on serverless technologies. More recently, he dived head first in Workflows, and started presenting the product at online events, wrote articles, tips and tricks, and videos on the topic.

• How sweet it is: Using Cloud AI to whip up new treats with Mars Maltesers blog
• Turbo boost your Compute Engine workloads with new 100 Gbps networking blog
  • Benchmarking higher bandwidth VM instances docs

• Workflows site
• Spanner site
• Cloud SQL site
• Cloud Composer site
• Pub/Sub site
• Cloud Run site
• Eventarc site
• Eventarc Documentation docs
• Workflows Insiders site
• Quickstarts site
• How-To Guides site
• Syntax Reference site
• Guillaume’s Workflow Tips and Tricks blog
• A first look at serverless orchestration with Workflows blog
• Orchestrating the Pic-a-Daily serverless app with Workflows blog
• Better service orchestration with Workflows blog
• Get to know Workflows, Google Cloud’s serverless orchestration engine blog
• 3 common serverless patterns to build with Workflows blog
• Introduction to serverless orchestration with Workflows codelab
• Pic-a-Daily Serverless Workshop codelab
• Pic-a-daily: Lab 6—Orchestration with Workflows codelab

Brian is working on use cases around VMs.

Stephanie has been writing about database migration.

Hosts Stephanie Wong and Priyanka Vergadia learn about data governance this week in an interesting chat with Jessi Ashdown and Uri Gilad. While data governance includes security measures, the overarching term also means knowing your data, where it is, and how to use it. In their book, Jessi, Uri, and their co-authors hope to make data governance more accessible by sharing the knowledge Google has developed over twenty plus years.

We talk about the challenges companies of all sizes face implementing data governance frameworks and Uri shares a few tips for streamlining the process. Communication and prioritization are important no matter the size of your team. Companies must also understand the sensitivity of the data, how it’s protected and managed, and why it’s collected.

Having a thoughtful, thorough understanding of what data gives you the most bang for your buck can help companies prioritize certain data collection, make better decisions, scale efficiently, and save money. When communicating with team members, it’s important to share vital information about the data. Knowing who’s in charge of what data, for example, makes accessing that data faster. With proper communication and thorough prioritization, teams can begin to think about how developing automated tools can increase functional data utilization.

Later, we discuss the ways companies can support employees on the data governance journey by clearly communicating the best practice rules. Uri describes how Google uses data governance principles and shares resources Google has published that detail these steps further. Tools like BigQuery and Data Catalog are Google-built products meant to provide companies with more automated data governance solutions.

Jessi and Uri wrap up the show with some more best practices in the data governance sphere, like proper metadata to increase the trustworthiness of data. And Uri details the tools Google Cloud has developed to make your data life easier, giving examples of companies putting these tools into practice.

Jessi Ashdown is a User Experience Researcher for Google Cloud who conducts user studies with customers from all over the world and uses the findings and feedback from these studies to help inform and shape Google’s data governance products to best serve those users’ needs.

Uri is leading the Data Governance efforts, within the Data Analytics area in Google Cloud. As part of his role, Uri is spearheading a cross-functional effort to create the relevant controls, management tools and workflows that enable a GCP customer to apply Data Governance policies in a unified fashion wherever your data may be in your GCP deployment.

Prior to Google, Uri served as an executive in multiple Data Security companies: most recently as the VP of product in MobileIron, a public Zero Trust/Endpoint security platform. Uri was an early employee and a manager in CheckPoint and Forescout - two well known Security brands. Uri holds an M.sc from Tel Aviv University and a B.sc from the Technion, Israel’s Institute of Technology. You can find him on Linkedin.

• Batter up! Anthos on bare metal helps MLB gear up for upcoming season blog
• Introducing Network Connectivity Center: A revolution in simplifying on-prem and cloud networking blog

• Data Governance: The Definitive Guide: People, Processes, and Tools to Operationalize Data Trustworthiness book
• Goods White Paper doc
• Dremel White Paper doc
• BigQuery site
• Data Catalog site
• Identity and Access Management site
• Strata Data Superstream Series event

Priyanka has been working on GCP Comics and new GCPSketchnotes.

Stephanie is working on an animated series about data centers.

This week on the podcast, fellow Googlers Kaslin Fields and Anthony Bushong chat with hosts Mark Mirchandani and Stephanie Wong about how to optimize your spending with Google Kubernetes Engine.

Cost optimization doesn’t necessarily mean lower costs, Kaslin explains. It means running your application the best possible way and accommodating things like traffic spikes while keeping costs as low as possible. As our guests tell us, standard best practices can aid in optimization, but when it comes to efficiently running on a budget, there are more tips and tricks available in GKE. One of GKE’s newest operation modes, Autopilot, means Kubernetes nodes are now managed by Google. Customers pay by the pod so the focus can be on the application rather than the details of clusters and their optimization. Best practices for resource utilization and autoscaling are included with Autopilot.

Kaslin and Anthony break up Google’s GKE cost optimization tips into four categories: multi-tenancy, autoscaling, infrastructure choice, and workload best practices and tell us how company culture effects these decisions. Proper education around Kubernetes and GKE specifically is the first step to using resources the most efficiently, Anthony tells us. Keeping tenants separate and resources well managed on multi-tenant clusters is made easier with Namespaces. Scaling pods and the infrastructure around them is an important part of optimization as well, and Anthony helps us understand the best practices for fine tuning the autoscaling features in GKE. Scaling infrastructure to handle spikes or lulls is an automatic feature with Autopilot, helping projects run smoothly. To control workloads efficiency, GKE now offers a host of features, including horizontal, vertical, and multidimensional pod autoscaling.

Later, we walk through the steps for implementing some of these optimizations decisions while keeping your application running. GKE Usage Metering is a useful tool for measuring tenant usage in a cluster so resource distribution can be managed easier.

Kaslin is a Developer Advocate at Google Cloud where she focuses on Google Kubernetes Engine.

Anthony is a Specialist Customer Engineer at Google Cloud, where he focuses on Kubernetes.

• A2 VMs now GA—the largest GPU cloud instances with NVIDIA A100 GPUs blog
• How carbon-free is your cloud? New data lets you know blog
  • Our third decade of climate action: Realizing a carbon-free future blog

• Kubernetes site
• GKE site
• Best practices for running cost-optimized Kubernetes applications on GKE docs
• Docker site
• Autopilot overview docs
• Namespaces docs
• Kubernetes best practices: Organizing with Namespaces blog
• Optimize cost to performance on Google Kubernetes Engine video
• Using node auto-provisioning docs
• Scaling workloads across multiple dimensions in GKE blog
• Enabling GKE usage metering docs
• Kubernetes in Google Cloud Qwiklabs site
• Kubernetes Engine Qwiklabs site
• Cloud Operations for GKE Qwiklabs site
• Earn the new Google Kubernetes Engine skill badge for free blog
• Beyond Your Bill videos
• Cloud On Air Webinar: Hands-on Lab: Optimizing Your Costs on Google Kubernetes Engine site
• Cloud OnBoard site
• Adopting Kubernetes with Spotify video

Stephanie Wong joins our old pal Mark Mirchandani this week to chat about BeyondCorp Enterprise and the way enterprise companies are using this security software.

Ameet starts the show explaining BeyondCorp’s three pillars of security, including how detailed customer and client knowledge aid in security. Kiran elaborates, stressing the importance of the web browser’s contribution to a secure experience. With BeyondCorp Enterprise offerings, companies can layer additional protections in the cloud, supplementing the often lacking network model and adding better security protections across devices. BeyondCorp offers a simpler implementation structure as well. Things like monitoring can be switched on with a click. We hear about the features of BeyondCorp, including how users help shape the way BeyondCorp protects their projects. Ameet walks us through how a client could add BeyondCorp to their current security infrastructure and the specific benefits of doing so.

BeyondCorp Enterprise, an easy off-the-shelf offering, was inspired by Google’s own security measures. With automatic added protections in Chrome, BeyondCorp Enterprise takes the most secure browser in the world and ups the game for enterprise employees working from any device. Kiran describes these additional measures and why they’re important for enterprise users. Ameet and Kiran tell us the steps required to set up the software and the customizations available. Enterprise customers should think through groups of users and what will be allowed by each. On the browser side, the three tiers of security features, including invisible features, can be implemented and changed easily.

With the new BeyondCorp Enterprise, enterprise clients are now able to take advantage of the advanced security of the cloud. Through real company examples, Ameet and Kiran share with us the ways this software is already changing the enterprise security game.

Kiran Nair is a product manager on Google Chrome. His focus area is security, and keeping Chrome users safe from web based threats. Besides spending the last 12 years building software and hardware products, Kiran is a certified yoga trainer and enjoys a casual game of tennis in the evening

Ameet is the product manager for BeyondCorp Enterprise.

• Introducing #AskGoogleCloud: A community driven YouTube live series blog
• Cloud On Air: Build the future with Google Kubernetes Engine (GKE) event
• Google Cloud Born-Digital Summit: Inspiring the next generation of technology leaders blog

• BeyondCorp site
• BeyondCorp Enterprise on Google site
• GCP Podcast Episode 221: BeyondCorp with Robert Sadowski podcast
• An overview: “A New Approach to Enterprise Security” research paper
• How Google did it: “Design to Deployment at Google” research paper
• Google’s frontend infrastructure: “The Access Proxy” research paper
• Migrating to BeyondCorp: “Maintaining Productivity while Improving Security” research paper
• The human element: “The User Experience” research paper
• Secure your endpoints: “Building a Healthy Fleet” research paper

Can you clearly explain GCP policy resource inheritance? What does it mean when the policy is effectively a union or additive?

• Resource Manager
• Understanding hierarchy evaluation
• Guide to Cloud Billing Resource Organization & Access Management

Jenny Brown and Mark Mirchandani are back this week to celebrate a special anniversary! This year marks ten years since the launch of the first Chromebooks, and our guests, Angela Gosz and Courtney Harrison, are here to reflect on the past and talk about the future Chrome OS. Chromebooks powered by Intel allow users to get the most out of their endpoints, serving as a secure and stable entrypoint to the Cloud.

Our guests describe the key groups of Chromebook users and how the security, ease of use, and portability of Chrome OS benefits each group. The Google Admin Console allows more than 500 customizable security features to tailor the experience for employees or end customers, Angela explains. The changes brought on by the pandemic meant more companies had to support a distributed business, and Chrome OS has been able to facilitate this transition easily. With zero-touch enrollment, Chromebooks can be sent directly to employees, bypassing IT. Chromebooks can be configured through the Google Admin Console without any physical contact.

Courtney tells us about her experiences with Chrome OS at Intel and how the automatic updates, computing speed, and other features have made her job easier. She explains the process of working with Google to develop Chromebook hardware and how the cloud comes into play for maximum performance. We talk about the many Chromebook options offered and what options will be available in the future.

Angela Gosz is a Customer Success Manager on the Chrome Enterprise Team, based out of Google Chicago. With 17 years of experience in the IT Industry, Angela has been on the leading edge of digital transformation implementations, supporting Enterprise organizations and partners to adopt and optimize their endpoint computing strategy - especially in Healthcare. Today she ensures customers realize the full potential of their investment in Chrome OS as a cloud-first endpoint. Outside of work, she has been meditating daily for 5 years, teaches yoga and is a certified Reiki practitioner. Angela holds a Bachelor’s Degree in Journalism from the University of Wisconsin-Madison.

Courtney is an Account Director with Intel Corporation based in the San Francisco Bay area. Currently Courtney leads a team that supports all of the Intel business interactions with Alphabet and Google. A twenty-one year Intel veteran, Courtney has spent the past fifteen years in field sales working with top multi-national customers and local OEMs. Courtney began her career at Intel in CPU operations. Courtney has both a Bachelor’s and Master’s Degree from Stanford University in Industrial Engineering.

• A new podcast explores the unseen world of data centers blog
• Back by popular demand: Google Cloud products in 4 words or less (2021 edition) blog
• Save the date for Google Cloud Next ‘21: October 12-14, 2021 blog

• Intel site
• Chromebook site
• Chrome OS site
• Chromebook turns 10 site
• Building the future of business computing: 10 years of Chrome OS blog
• Form Factor Portfolio site
• Deploy devices with zero-touch enrollment site
• Thunderbolt site
• WiFi 6 site
• CloudReady site
• MCA site

Mark is working on Costs meet code with programmatic budget notifications.

• “LeDancing” by Frankum of Freesound.org
• “Jingle Romantic” by Jay_You of Freesound.org

Jenny Brown co-hosts with Mark Mirchandani this week for a great conversation about the ML lifecycle with our guests Craig Wiley and Dale Markowitz. Using a real-life example of bus cameras detecting potholes, Dale and Craig walk us through the steps of designing, building, implementing, and improving on a piece of machine learning software.

The first step, Craig tells us, is to identify the data collected and determine its viability in an ML model. He describes how to get the best data for your project and how to keep the data, code, and libraries consistent to allow better analysis by your ML models. He talks about the importance of a Feature Store to aid in data consistency. Craig explains how machine learning pipelines like TensorFlow are great tools to improve consistency in the ML environment as well, making it easier to improve your model and even to build new ones using the same data. Keeping this consistency from data scientist analyzation to ML developer to model deployment means a more efficient process and product.

Evaluating models after production is an important step in the lifecycle as well to ensure accuracy, validity, and performance of the model. Craig gives us some examples and tips on monitoring models after they’ve been deployed. We talk about the challenges of scaling ML projects and Craig offers advice for developers and companies looking to build ML projects.

Dale Markowitz is an Applied AI Engineer for ML on Google Cloud. Before that, she was a software engineer in Google Research and an engineer at the online dating site OkCupid.

Craig is the Director of Product for Google Cloud’s AI Platform. Previous to Google, Craig spent nine years at Amazon, as the General Manager of Amazon SageMaker, AWS’ machine learning platform as well as in Amazon’s 3rd Party Seller Business. Craig has a deep belief in democratizing the power of data, he pushes to improve the tooling for experienced users while seeking to simplifying it for the growing set of less experienced users. Outside of work he enjoys spending time with his family, eating delicious meals, and enthusiastically struggling through small home improvement projects.

• Introducing GKE Autopilot: a revolution in managed Kubernetes blog
• At your service! With schedule-based autoscaling, VMs are at the ready blog

• Google Cloud AI and Machine Learning Products site
• GCP Podcast Episode 240: reCAPTCHA Enterprise with Kelly Anderson + Spring ML Potholes with Eric Clark podcast
• Using machine learning to improve road maintenance blog
• Key requirements for an MLOps foundation blog
• TensorFLow site
• Kubeflow Pipelines site
• TensorBoard site
• How to dub a video with AI video
• Can AI make a good baking recipe? video
• Machine learning without code in the browser video

Jenny started a new podcast that reads interesting Google blog posts over at Google Cloud Reader.

Our friend Dr. Anton Chuvakin started the Cloud Security Podcast by Google. Read more about it and listen here. Follow the show and hosts on Twitter Cloud Security Podcast Anton and Tim

And listen to Anton on the GCP Podcast Episode 218: Chronicle Security with Dr. Anton Chuvakin and Ansh Patniak.

Mark Mirchandani and Stephanie Wong are back this week as we learn about all the new things happening with Google Cloud Spanner. Our guests this week, Dilraj Kaur and Christoph Bussler, describe Cloud Spanner as a fully managed relational database that boasts unlimited scaling and advanced consistency and availability.

Unlimited scaling truly means unlimited, and Chris explains why Cloud Spanner offers this feature and how it’s making database design and development easier. Dilraj and Chris tell us all about the cool new features Spanner has developed, like generated columns and foreign keys, and how customer needs influenced these developments. Chris walks us through the process of using some of these new features, including how developers can monitor their database systems.

Managed backups and multi-region configuration are additional recent additions to Cloud Spanner, and our guests explain how these are used by current enterprise clients. Dilraj and Chris explain the automatically managed features of Spanner versus the customer managed features and how people set up and manage database projects. We hear examples of companies using Cloud Spanner and how it has improved their businesses.

Dilraj Kaur is an Enterprise Customer Engineer with specialization in Data Management. She has been with Google for about 2.5 years and is based in Atlanta.

As a Solutions Architect Chris is focusing on databases, data migration and data integration in enterprise customer settings. See his professional work and background on his website.

• New to Google Cloud? Here are a few free trainings to help you get started blog
  • Start your skills challenge today site
• Service Directory is generally available: Simplify your service inventory blog

• Google Cloud Spanner site
• GCP Podcast Episode 62: Cloud Spanner with Deepti Srivastava podcast
• Using the Cloud Spanner Emulator docs
• Cloud Spanner Ecosystem site
• Cloud Spanner Qwiklabs site
• Google Cloud Platform Community On Slack site
• Creating and managing generated columns docs
• WITH Clause docs
• Foreign Keys docs
• Numeric Data Type docs
• Information schema docs
• Overview of introspection tools docs
• Backup and Restore docs
• Multi-region configurations docs
• ShareChat: Building a scalable data-driven social network for non-English speakers globally site
• Blockchain.com: Streamlining infrastructure for the world’s most dynamic financial market site
• What is Cloud Spanner? video

Mark has been working on budgeting blog posts, including Protect your Google Cloud spending with budgets.

Stephanie is working on her data center animation series

This week on the podcast, Mark Mirchandani and Gabi Ferrara talk with Nimesh Bhagat about Cloud SQL Insights. This powerful tool enables developers to diagnose database issues for faster, smoother performance.

Nimesh tells us the inspiration for Cloud SQL Insight’s development and describes its biggest benefits. One of the important aspects of Insights is the ability for developers to gain an application-centric view by allowing them to tag database queries with SQL comments. These tags are aggregated in Insights and give developers a visual of the database queries. Here, developers can see load patterns and use that information to improve database efficiency. Cloud SQL Insights offers managed database analysis that helps developers understand the past and predict the future.

Simplifying the journey of database debugging, Nimesh explains, was the goal of creating Cloud SQL Insights. He takes us through the process of using the software, pointing out the improvements Insights makes over the old way. Cloud SQL Insights only launched in January, but it’s already helping numerous clients with their projects. Nimesh describes these real-world uses, including Major League Baseball experience as part of Insights Early Access Program.

Nimesh is a product manager at Google Cloud, he leads Cloud SQL Insights. He has worked across engineering and product roles, building highly available and high performance enterprise infrastructure used by Fortune 500 companies. His passion lies in combining powerful infrastructure with simple user experience so that every business and developer can build software at scale and velocity.

• A new collaboration with Google Cloud blog
• Don’t fear the authentication: Google Drive edition blog

• Cloud SQL Insights docs
• Cloud SQL Documentation docs
• GCP Podcast Episode 163: Cloud SQL with Amy Krishnamohan podcast
• Google Cloud Monitoring site
• Database observability for developers: introducing Cloud SQL Insights blog
• Introduction to Cloud SQL Insights codelab
• Boost your query performance troubleshooting skills with Cloud SQL Insights blog
• Introducing Sqlcommenter: An open source ORM auto-instrumentation library blog
• Introducing Cloud SQL Insights video
• Cloud SQL Github site

Gabi is working on several things, including Schema Migrations with CI/CD pipelines. She is always available on Twitter and she offers free office hours!

• “Small Audience Laugh” by Tim Kahn of Freesound.org

Former GCP Podcast host Mark Mandel is our guest this week. He’s talking Google Cloud Game Servers, Agones, and more with Mark Mirchandani and guest host Stephanie Wong.

Mark explains how dedicated game servers work and why gaming has embraced the idea of dedicated servers. Online multiplayer gaming with its need for fast, consistent state sharing among players benefits from dedicated servers and offers cheating mitigation and reduced latency, as well as development flexibility. He tells us a little about the history of the open source project, Agones, and how it has helped Kubernetes run memory-state games efficiently on these dedicated servers.

Google Cloud Game Servers work with layers of products to create a seamless multiplayer environment. Mark details this process and how Kubernetes, GKE, and Agones work together with these servers to accomplish this goal at scale. This situation is ideal for developers looking for the customizability and flexibility of a self-controlled system rather than a fully managed lift and shift model. Mark talks about the features of GCGS, including the versioning configuration system that allows you to create multiple configurations, and roll outs that give you control over distribution.

We also learn a little about game building best practices and how Mark and his team advise and educate other game developers.

Mark Mandel is a Developer Advocate for the Google Cloud Platform. Hailing from Australia, Mark built his career developing backend web applications which included several widely adopted open source projects, and running an international conference in Melbourne for several years. Since then he has focused on becoming a polyglot developer, building systems in Go, JRuby and Clojure on a variety of infrastructures. In his spare time he plays with his dog, trains martial arts, and reads too much fantasy literature.

• Google Cloud Docs Samples docs
• Limiting public IPs on Google Cloud blog

• Google Cloud Game Servers site
• Agones site
• Agones Prerequisite Knowledge docs
• Kubernetes site
• GKE site
• Online Game Technology, Drawn Badly videos
• GCP Podcast Episode 142: Agones with Mark Mandel and Cyril Tovena podcast
• GCP Podcast Episode 202: Supersolid with Kami May podcast
• Multiplay site
• Accelbyte site
• Improbable site
• Find the right Google Cloud partner site
• Game Developers Conference site
• Agones on Slack site
• Agones on Twitter site
• Mark Mandel on Twitch site
• Mark Mandel on YouTube site

Stephanie is working on Season of Scale season 5 and a data center animated series that will launch in a few weeks!

• “TrumpetBrassFanfare.wav” by ohforheavensake of Freesound.org
• “8-bit Video Game Sounds.wav” by ProjectsU012 of Freesound.org
• “music elevator.wav” by Jay_You of Freesound.org

Dustin Dye and Alex Seegers of Botcopy are on the show today, chatting with hosts Mark Mirchandani and Priyanka Vergadia. Botcopy uses advanced AI technology along with excellent copy writing to create better chat bots. The software works directly on a company website and doesn’t require a login, allowing chats to stay anonymous.

Our guests explain that their chat bots are treated like virtual employees, built and trained to function and speak appropriately for their specific job. Copy writing is an important part of this, as the conversational AI should continue to support the brand being represented and conversations should flow naturally. The bot personalities are developed through written copy and interactions with customers in instances like customer service, lead generation, and even some internal employee management needs.

Later, we talk about how Dialogflow and Botcopy work together, including how Botcopy adds important user context to the conversation to facilitate more accurate bot responses. We hear more about Dialogflow CX and how the modular builder makes designing and controlling bot conversations easier. CX has also made managing multiple bots on a single account easier and team collaboration more efficient. The visual builder available in CX offers a better chatbot design experience, especially when multiple teams are working on the same bot. We hear examples of great use-cases for Botcopy, like restaurant menus, clinical trials, and more.

Alex and Dustin give developers valuable advice about working with clients to build their bots. Test early and often to build a robust bot capable of handling many situations. It’s important to have an analytics system in place to identify possible improvement areas as well.

Dustin Dye is co-founder and CEO of Botcopy. After developing branded character and dialogue content for the #1 business bots on Messenger and Slack, Dustin launched Botcopy in 2017. Before co-founding Botcopy, Dustin had co-founded Expert Dojo, one of Silicon Beach’s largest startup incubator, serving, mentoring, and securing funding for some of the most exciting businesses coming out of LA. Dustin is a frequent keynote speaker at leading Chatbot conferences in the US and abroad.

Alexander Seegers is a co-founder and COO of Botcopy and heads up the product team. He holds a Business degree from Northeastern and UX certification from General Assembly. Alex has consulted tech leaders at Fortune 500 companies worldwide, spearheading their forays into conversational AI for multiple use cases at the enterprise level. In addition to big-picture leadership and vision, Alex is adept at numerous coding languages and complex systems architecture.

• Introducing WebSockets, HTTP/2 and gRPC bidirectional streams for Cloud Run blog
• Take the first step toward SRE with Cloud Operations Sandbox blog

• Botcopy site
• Botcopy Blog blog
• Contact Botcopy email
• Dialogflow site
• Miro site

Priyanka is working on Dialogflow CX episodes for the Deconstructing Chatbots series.

Welcome back to a new year of Google Cloud Platform Podcasts! Mark Mirchandani and Emma Iwao host the first show of 2021 with special guest Rebecca Weekly of Intel. She joins us to talk about the partnership between Google Cloud and Intel. Describing the company’s goals of gathering, storing, managing, and analyzing data in all its forms to unlock the power of technology and information, Rebecca points out how well these align with Google’s own goals and why the partnership is such a natural fit.

Rebecca explains the four pillars of the Google-Intel partnership, including the focus on infrastructure and app modernization to elevate the user experience. Through their work with Google, Intel has been able to optimize the move from on prem to cloud for those clients who choose to make the shift, using their thorough client knowledge and Google Cloud expertise to facilitate a smooth transition. Rebecca walks us through the process of crafting this client experience, from choosing products and tools to identifying and solving any bottlenecks and optimizing the configuration using benchmarks.

Later, we talk about the value of open source software in both the hardware and software worlds and why Intel believes so strongly in open source projects. Rebecca offers examples of clients successfully using Intel hardware and Google Cloud software, including Climacell and Kinsta. We get the inside scoop on future projects at Intel, like the next generation of scalable Xeon processors, and Rebecca talks about the future of data analyzation and computing.

Intel and the Intel logo are trademarks of Intel Corporation or its subsidiaries.

Rebecca leads the team that influences nearly every aspect of our cloud platform solutions across strategic planning, hardware and software enabling, marketing and sales. Together they shape the development, production, and business strategy of Intel’s cloud platforms to ensure differentiation and platforms that enable TAM expansion with enthusiasm, collaboration, and urgency. She drives strategic collaborations with key partners including top cloud service providers, OxMs, ISVs & OSVs to ensure platform requirements meet our customer needs.

In her “spare” time, she’s the lead singer of a funk & soul band, Sinister Dexter, was professionally trained in dance (tap, modern, and jazz), and is an experienced choreographer. She has two amazing little boys and loves to run (after them, and on her own).

Rebecca graduated from MIT with a degree in Computer Science and Electrical Engineering.

• 97 Things Every Cloud Engineer Should Know Book
• Introducing Google Cloud Workflows video

• Intel site
• Google Cloud withe Intel site
• TensorFlow site
• Anthos site
• Intel Select Solutions site
• PerfKit Benchmarker site
• Google Cloud Functions site
• Climacell site
• Blue Skies Ahead: ClimaCell Delivers Innovative Weather Prediction Solutions doc
• Kinsta site
• Benchmarking GCP’s Compute-Optimized VMs (C2) blog
• Arcules site
• Descartes Labs site
• DAOS site
• Optane site

Emma was a guest on GCP Podcast Episode 167: World Pi Day with Emma Haruka Iwao.

Emma is working on the Ruby 3.0 support and release and deprecation policy. Ruby is now available on Google Cloud Functions!

• “Partyhorn” by Milton of Freesound.org
• “ToiletFlush” by EminYildirim of Freesound.org

This week, four of the podcast’s greatest hosts come together to celebrate all of the fun and informative episodes we’ve been privileged to do this year! Join Mark Mirchandani, Jon Foust, Priyanka Vergadia, and Brian Dorsey as we talk about our favorite guests and shows, some cool things that happened this year, and what we’re looking forward to in 2021!

• A Giant List of Google Cloud Resources blog
• Google Cloud 4 Words site

• Jon’s Favorites

  • GCP Podcast Episode 212: Data Management with Amy Krishnamohan podcast
  • GCP Podcast Episode 237: NVIDIA with Bryan Catanzaro podcast

• Priyanka’s Favorite

  • GCP Podcast Episode 240: reCAPTCHA Enterprise with Kelly Anderson + Spring ML Potholes with Eric Clark podcast

• Mark’s Favorites

  • GCP Podcast Episode 242: NASA and FDL with James Parr and Madhulika Guhathakurta podcast
  • GCP Podcast Episode 217: Cost Optimization with Justin Lerma and Pathik Sharma podcast
  • GCP Podcast Episode 228: Fastly with Tyler McMullen podcast

• Brian’s Favorites

  • GCP Podcast Episode 223: Voice Coding with Emily Shea and Ryan Hileman podcast
  • GCP Podcast Episode 233: Bare Metal Solution with James Harding and Gurmeet Goindi podcast
  • GCP Podcast Episode 212: Data Management with Amy Krishnamohan podcast

• “Bad Beep” by RicherLandTV of Freesound.org
• “Small Group Laugh 6” by Tim.Kahn of Freesound.org
• “It’s Always Night in Space” by JamesSilvera of HDInteractive.com
• “Easy Cheesy” by LoboLoco of FreeMusicArchive.org

Guest host Sara Ford joins our old favorite Mark Mirchandani this week for a special interview with NASA and FDL. Our guests, James Parr and Madhulika Guhathakurta, give us a super cool, in-depth look at how NASA and FDL do what they do. Lika explains the important scientific studies she has worked on during her years at NASA and how she came to understand and appreciate Machine Learning. James introduces us to the Frontier Development Lab, a project collaborated on by private and public companies to leverage AI and Machine Learning in the research of science, exploration, and many other disciplines.

From saving Earth from asteroids to conducting research on our sun, James describes the process of solving these solar system sized problems, starting with creating a solid team. Machine Learning is a team sport, he says, and like making a Hollywood film, it takes many people from different backgrounds to find these solutions. The cloud has been integral in facilitating this meeting of the minds and the analyzing of data at FDL.

Later, we talk about the process of astronomical research before the current technological age and how techniques have advanced into the 21st century. James tells us the origin story of FDL and how they were tasked with applying Machine Learning to complex problems like planetary defense and space weather. Lika describes space weather and details how it impacts our planet. We talk about the role of data engineers in the team sport of astro-research and how data is collected and analyzed. Lika emphasizes the benefits of building a working system and how the processes can be applied to many other disciplines.

James and Lika wrap up the show with a look at what cool things they expect in the future.

James is Director of the Frontier Development Lab, in partnership with NASA ARC and the SETI Institute. FDL has successfully demonstrated that structured interdisciplinary problem solving, sprint methodologies, radical collaboration methods and partnering with leaders in commercial AI, such as Google Cloud, are powerful amplifiers in applying AI to the science and technology goals of space agencies.

For the past two decades, Lika has led the development of Heliophysics as an integrated scientific discipline from which fundamental discoveries about our universe provide direct societal benefits. As the Lead for the Living With a Star (LWS) program for 16 years (2001-2016), she made possible the flagship missions (e.g. the Solar Dynamics Observatory, Van Allen Probes, Solar Orbiter Collaboration and Parker Solar Probe) including STEREO that would revolutionize our understanding of how the Sun shapes space weather in the solar system.

To accelerate innovation and scientific discovery she created funding mechanisms to shepherd traditional domain scientists out of their comfort zones to create LWS system science known as Targeted Research & Technology program and Focused Science Teams that foster competitive, yet collaborative environments that promote the crosspollination of ideas and technology.

To nurture the next generation of leaders in Heliophysics, she created the Jack Eddy Fellowship Program which has become an important channel for the professional growth of promising researchers and has been successful at promoting the careers of many women scientists reaching 50% parity with men.

Since 2017, she was the driving force at NASA Headquarters and at NASA Ames behind the growth of Frontier Development Laboratory, both in terms of the breadth of problem areas tackled as well as in the number of agency and industry partners (e.g. Google, Nvidia, Intel, Lockheed Martin, Planet). The types of innovative solutions include virtual telescopes, data fusion, edge computing, and autonomy and this approach will have an enduring imprint on the way science and exploration is carried out by future generations.

• Prepare for Google Cloud certification with one free month of new Professional Certificates on Coursera blog
  • GCP Podcast Episode 239: Cloud Learning Services with Nandhini Rangan and Magda Jary podcast
• NASA’s OSIRIS-REx Spacecraft Collects Significant Amount of Asteroid site

• NASA site
• Frontier Development Lab (FDL) site
• Oort Information site

• “Bad Beep” by RicherLandTV of Freesound.org
• “Small Group Laugh 6” by Tim.Kahn of Freesound.org

Mark and Brian are together this week, hosting our guests Senanu Aggor and Ilias Katsardis as we discuss High Performance Computing with Google. HPC uses powerful computers to solve problems that would otherwise be too large or take too long for standard machines. Innovation and advances in cloud technology have made this resource more accessible, more scalable, and more affordable.

Senanu lists some great use cases for HPC, including vehicle manufacturing and the medical field and describes how these markets benefit from the extra power HPC offers. Ilias talks tech and helps us understand the evolution of the Google HPC offering and the architecture most often used with HPC. He explains the benefits of HPC on the cloud over the old way, emphasizing the flexibility of choosing machines based on your code rather than forcing your code onto small machines. Storage of data is flexible, scalable, and secure as well. Diminishing VM to VM latency has been an important advancement in HPC, and Ilias describes how Google has decreased latency.

Google Cloud customers are using the HPC offering for all kinds of large computing jobs, and Senanu details some of these real world instances. From Covid vaccine research to disaster evacuation planning, HPC on the cloud is changing the way we process data. Later, Ilias tells our listeners how to get started with their HPC project.

Senanu Aggor is the Product Marketing Manager for Google Cloud’s High Performance Computing (HPC) solution.

Ilias Katsardis is the HPC Solution Lead for the Customer Engineering team (EMEA) at Google. In this role, Ilias brings over 14 years of experience in the cloud computing and high-performance computing industries to promote Google Cloud’s state-of-the-art infrastructure for complex HPC workloads. Previously, he worked as an applications analyst at Cray Inc., where he was a dedicated analyst to the European Centre for Medium-Range Weather Forecasts (ECMWF), and, prior to that, was an HPC application specialist at ClusterVision. Ilias also founded two startups Airwire Networks in 2006 and Performance Hive in 2017.

• What’s happening in BigQuery: Time unit partitioning, Table ACLs and more blog
• BigQuery explained: Blog series blog
• BigQuery Spotlight videos
• Cloud Functions vs. Cloud Run video

• High Performance Computing site
• GCP Podcast Episode 237: NVIDIA with Bryan Catanzaro podcasdt
• GCP Podcast Episode 167: World Pi Day with Emma Haruka Iwao podcast
• Compute Engine site
• Compute Engine Machine Types site
• Cloud Storage site
• Cloud Firestore site
• Google Cloud with Intel site
• Cloud GPUs site
• Best practices for running tightly coupled HPC applications on Compute Engine site
• Super Computing Event site

This week, Max Saltonstall is talking cyber analytics with Eric Dull from Deloitte.

This week, your hosts Mark Mirchandani and Priyanka Vergadia are joined by Google Product Marketing Lead for Online Fraud Protection, Kelly Anderson, to talk about reCAPTCHA Enterprise. Kelly’s main focus at Google, reCAPTCHA, is a service that helps online companies determine if a user is a human or an automated system. With an advanced risk analysis engine, Google’s reCAPTCHA system has been defending sites from fraud for more than a decade. We talk about the evolution of reCAPTCHA and learn about the specific attributes of each version.

Later, we focus on reCAPTCHA Enterprise which caters this security software to enterprise companies. Like version three, Enterprise boasts detailed risk analysis and actions. Companies can also expect reason codes for high risk scores and the ability to use the risk analysis engine customized to their company. They are able to find bots impersonating users and neutralize them easily. reCAPTCHA Enterprise is easy to use, whether you’re a Google Cloud customer or not. With the handy API, any company can take advantage of this security feature. Kelly leads us through the steps of deploying the API and details instances where this software plays a vital role in the protection of your website across multiple devices.

Kelly takes us through the reCAPTCHA Enterprise dashboard and talks about the future as we conclude the show. reCAPTCHA hopes to move beyond behavioral protection to continue to stay ahead of malicious actors online. As Kelly explains, Machine Learning will become more and more important as fraud detection continues to grow and change.

Kelly Anderson currently leads product marketing for Google Cloud’s online fraud protection business. She devotes most of her time to working on reCAPTCHA Enterprise and Web Risk and is passionate about helping businesses and their customers stay protected from fraud and abuse. Prior to Google, she worked in product marketing for Microsoft in Azure, where she marketed a variety of security products and business continuity products. For more information about Kelly Anderson and her leather jacket, you can follow her on Twitter.

• Introducing HTTP/gRPC server streaming for Cloud Run blog
• Introducing Google Workspace blog

• reCAPTCHA Enterprise site
• reCAPTCHA enterprise product demo video
• Top 10 use cases for reCAPTCHA Enterprise to defend against OWASP Web-Automated Attacks site
• Google reCAPTCHA Enterprise: Frictionless, Flexible, and Effective Web App Security site

This week, Max Saltonstall is fixing potholes in Memphis with Eric Clark of SpringML.

Priyanka has been working on Google Cloud Whiteboard episodes Operations and CDN. She’s been working on new comic strips for zero trust and new GCPSketchnotes as well!

Jon Foust joins Mark this week as we talk with Nandhini Rangan and Magda Jary about Cloud Learning Services. The Cloud Learning Services team is passionate about helping technical practitioners elevate their careers and transform businesses by building and validating in-demand Google Cloud skills. Nandhini explains that a lack of technical practitioners with skills in the cloud is one of the biggest barriers to entry for companies considering the shift. But with the right knowledge, companies that take full advantage of cloud environments are proven to be more efficient, reach more of their goals, and overall, be more successful. Cloud Learning Services offerings empower technical practitioners and companies to learn new skills, put these skills into practice, and achieve their objectives.

Magda tells us that these training courses focus around job roles in the cloud. The cloud has necessitated a shift in the idea of development learning, she tells us, explaining that nowadays, the focus is on job roles, like Data Scientist, and the technological requirements of that job rather than learning one coding language.

We talk later about the specific offerings Cloud Learning Services provides. With a focus on hands-on learning, technical practitioners are put into the real Google Cloud environment with Qwiklabs, while videos and lectures accompany the material. Job-specific skill badges and certifications are earned as courses are completed, allowing technical practitioners and employers to better understand what proficiency in each job role looks like. Our guests tell us more about Qwiklabs and how its sandbox environment facilitates better learning without the added cost and commitment of services that they may not be ready to use. When the time for real-world development comes, this hands-on approach means no disconnect between learning and applying. We talk more about the Challenge Labs used to test learning and the skill badges earned on completion.

To wrap up, we discuss the future of Cloud Learning Services and how the team stays on top of new technologies and job roles to keep learning materials updated and fun. The team is working on new material for badging and certifying business professionals as well.

Resources to check out to learn more about Google Cloud training and certifications: https://cloud.google.com/training https://cloud.google.com/certification

Follow a learning path designed to help you prepare for the certification most suited to your role: https://g.co/cloud/getcertified

Nandhini Rangan works at Google Cloud Learning and is very passionate about the topic of upskilling, reskilling, and especially for cloud roles that are needed in organizations today, but also defining the roles and jobs of the future. She is based in Canada and works out of Toronto. She started her career as a Software Engineer, went on and got her MBA and then spent many years in operations and strategy including a stint as a management consultant. Learning was always top of mind for her and she decided to make the jump to join a learning organization full time in 2018 with Google Cloud. She launched the Google Cloud Technical Residency program, worked in the Higher Education learning space bringing programs to faculty and students globally, and currently works as a learning portfolio manager helping bring cloud training content closer to its audiences.

Magda Jary is responsible for all aspects of Google Cloud Certification and Digital Badges go-to market and her mission is to grow Cloud skill sets. She joined Google in 2008 after graduating with two Masters degrees: Media and Communications at Warsaw School of Economics and International Management at Rotterdam School of Management. Currently based in San Francisco, she has been leading global learning and engagement programs for Google Cloud customers and partners. Magda is a frequent guest speaker at events dedicated to skills development, diversity, and women in tech. She is a certified yoga teacher and has completed a mindfulness teacher certification. She teaches the Search Inside Yourself training at Google, a mindfulness-based emotional intelligence course for leaders.

• Announcing Google Cloud Public Sector Summit, a free global digital event: Dec. 8-9 blog
• 5 tips for more interactive meetings with Q&A and Polls, rolling out to Google Meet blog
• Add a more accurate sense of place to your applications using these five YouTube tutorials blog
  • GCP Podcast Episode 181: Google Maps Platform with Angela Yu podcast

• Google Cloud Training site
• Google Cloud Skill Badges site
• Qwiklabs site
• Deploy to Kubernetes in Google Cloud site
• Professional Machine Learning Engineer Certification site
• Coursera site
• Codelabs site
• TSIA Star Awards site

I’ve been interested in the Cloud Architect Certification and after listening to the interview, I’ve be inspired to look into taking it. What training material is available for preparing for the exam?

Check out the Google Cloud certification, Professional Cloud Architect certification, and the Preparing for the Professional Cloud Architect Examination Qwiklab.

Jon finished Game Summit last week and is back to creating Open Match content, specifically on submitting request from games and writing a match function in a language you may be familiar with!

ML in machinery is our main topic this week as Mark Mirchandani and Brian Dorsey talk with Arnaud Hubaux, development lead for ASML. Our good friend, fellow Googler, and ML specialist Dale Markowitz joins the conversation as well!

With a potent combination of physics and Machine Learning, ASML develops machines that build the chips powering our essential devices. These highly refined machines optimize production for each specific customer, detect defects, and make corrections quickly and accurately by harnessing the power of Machine Learning. The machines also effectively train themselves to ensure the intense accuracy required is sustained over time. Arnaud describes the process these machines go through in order to accomplish these goals, including how they build and train their ML models with the help of physics.

Arnaud tells us how the machine’s closed ML system works from zero to train the particular job it will do. By taking a minimum spec chip that has already been created, the machine learns the process for creating that chip and continues to improve that process. These machines are not only able to detect problems but can figure out why these issues are occurring, decreasing production downtime.

Recently, ASML moved to Google Cloud. We talk about the products they use, why they chose Google Cloud, and their journey to the cloud.

Arnaud Hubaux is development lead for Artificial Intelligence and Machine Learning products at ASML. He works with the world’s biggest chip manufacturers on AI-driven solutions to solve problems like optimizing production yield. As a trailblazer, Arnaud and his team implemented the first ASML AI application development pipeline on Google Cloud. With a PhD on applied constraint solving, Arnaud has deep experience as an architect of software platforms and product lifecycle management.

• Cloud migration: What you need to know (and where to find it) blog
• All together now: Fleet-wide monitoring for your Compute Engine VMs blog
• SRE Classroom: exercises for non-abstract large systems design blog
• gVisor: Protecting GKE and serverless users in the real world blog

• ASML site
• ASML in One Minute video
• Zoom in on the chip in your smartphone video
• KubeFlow site
• BigQuery site
• AI Platform Notebooks site
• Cloud Build site
• Introduction to Kubeflow video
• Intro to Kubeflow Pipelines video
• How to Build a Kubeflow Pipeline video

We have a super cool tip on combining AI and WTH with meetings and webcams! Check out the Level Up - AI Director and Level Up - Real-Time Video Translation with AR Subtitles videos!

Mark is working on some upcoming Kubernetes content.

Brian is working on an upcoming series of GCE videos with Carter Morgan.

Mark Mirchandani and Jon Foust are together again this week, speaking with NVIDIA VP of Applied Deep Learning Research Bryan Catanzaro. Bryan and his team focus on using deep learning to enhance NVIDIA’s offerings.

Since Bryan was last a guest on the show, NVIDIA has been doing some amazing things. We talk about the A100 Tensor Core GPU and the massive effort it took to create, the new RTX graphics cards great for gaming, and the differences between them. Bryan explains how the new A100 chips compare to the previous versions, saying the new chips are larger, but with almost three times the power, making them ideal for things like precise calculations. And, as Bryan says, with better computation and more insight, we can make discoveries that benefit humanity. While the new RTX graphic cards are cheaper than previous versions, they are faster and more powerful, making gaming and video streaming much more enjoyable. Background noises and objects can even be removed with the help of deep learning.

Jon and Bryan talk about The Black Box at NVIDIA and what demos Jon hopes to see on his next visit. With this as the catalyst, Bryan talks more about how the NVIDIA architecture and the deep learning they employ have created efficient 8k graphics rendering for truly powerful gaming experiences. Outside of gaming, DLSS could have farther reaching benefits as the model learns new purposes, and Bryan talks us through some fun examples.

With the acquisitions of Mellanox and ARM, Bryan explains that NVIDIA has been able to streamline networking and really take advantage of powerful performance at all stages. The future of AI and HPC is about the data center, Bryan explains, and NVIDIA is hoping to push the boundaries on latency reduction and more.

Bryan Catanzaro is VP of Applied Deep Learning Research at NVIDIA, where he leads a team finding new ways to use deep learning for graphics, speech, audio, and system design. His research led to the creation of the CUDNN library.

• Introducing interactive code samples in Google Cloud documentation blog
• GCP Podcast Episode 228: Fastly with Tyler McMullen podcast
• Fastly Offers First Partner Edge Cloud-Based Content Delivery Solution on Google Cloud Marketplace press release and marketplace

• NVIDIA site
• NVIDIA A100 site
• NVIDIA RTX 30 Series site
• Mellanox site
• ARM site
• Cuda site
• GCP Podcast Episode 119: NVIDIA and Deep Learning Research with Bryan Catanzaro podcast
• GCP Podcast Episode 168: NVIDIA T4 with Ian Buck and Kari Briski podcast
• Digital GTC site

Zack Akil is here this week with a tip about ML on the edge with Teachable Machine and AutoML.

Jon has been working on Open Match which went 1.0 recently! He’s been working on samples for matchfunctions, sending requests from game clients, and putting all that content out for the world to play with!

Matthew Lawson of IKEA Retail (Ingka Group) joins Mark Mirchandani and Priyanka Vergadia today, telling us all about IKEA Retail (Ingka Group)’s move to the cloud. Engineering Manager Matt and his team primarily focus on the early stages of development at IKEA Retail (Ingka Group), helping the company with research and planning as well as development. Lately, they have been focused on incrementally moving IKEA Retail (Ingka Group)’s digital presence to the cloud.

Matt explains the digital shift process for IKEA Retail (Ingka Group) and why they chose to modernize and move pieces to the cloud over time. By illustrating through examples, he details projects the team worked on during this digital transformation. Matt also talks about the changes to the IKEA Retail (Ingka Group) Digital DNA, emphasizing progress made in their digital culture to allow for the drastic change from on-prem to the cloud. Using managed services like Google Cloud Run, IKEA Retail (Ingka Group) has been able to adapt and grow in the cloud. Because IKEA Retail (Ingka Group)’s culture is developer-supportive, Matt and his team were able to research and convince the company that managed services in the cloud was the way to go, and developers were allowed some autonomy to choose things like GKE to create an effective cloud environment for IKEA Retail (Ingka Group).

Next year, Matt and his engineering team are hoping to run some online hackathons and other events.

Matthew Lawson is responsible for leading a small innovation team at IKEA Retail (Ingka Group) in southern Sweden. He has worked within the IT/Digital industry for 13 years and has deep experience and knowledge in application development, automation, DevOps and cloud technologies - especially serverless. He has a deep passion for enabling teams to quickly provide business value across the entire digital and physical customer journey.

• Next OnAir as it happens: All the announcements in one place blog
• A developer’s take: Get the most out of Cloud AI Week at Next OnAir blog
• BANDAI NAMCO Entertainment Inc. brings PAC-MAN to the real world in PAC-MAN GEO blog

• IKEA Retail (Ingka Group) site
• Matt’s Next Session: Serverless Functions (FaaS): Secure, Scalable, Resilient, Anywhere site
• ML Kit site
• Compute Engine site
• Cloud Run site
• Google Cloud Functions site
• Pub/Sub site
• BigQuery site
• GKE site
• Firestore site
• IKEA Retail (Ingka Group) is hiring! site

This week, we get a great tip from our friend Grant on using Google Cloud Functions! github

Priyanka is working on sketches like this summary of Google Cloud Next and more GCP Comics!

Max Saltonstall is back in the co-host seat, joining Mark for a fun chat about Active Assist. Chris Law is our guest this week, and he starts with the story of his arrival at Google and his path to the Active Assist team. Active Assist is Google’s way of helping clients learn about and take advantage of all the cloud features available.

Chris describes the main ways Active Assist helps customers in the real world, from troubleshooting tools that identify problems to analysis software that helps clients determine how changes will effect the project. Active Assist also provides recommendations for cost savings, better security, and performance boosters to help clients proactively build better projects. As companies scale, these features become even more important, Chris tells us, citing examples from real users.

Later, we talk about how machine learning is employed to create these recommendations. We talk transparency and learn how Chris and his team keep open communication with clients as they design and improve client security structures. In the future, the Active Assist team will continue to work with departments across Google Cloud and build more recommendations tools for customers. DataFlow and BigQuery are some of the recommendations projects coming soon. More automation will be introduced as well, helping clients do things like scale automatically based on machine learning analysis done behind the scenes.

Chris has helped to start several companies in the past, everything from Social Networking (Tribe.net) to Aggregate Knowledge, which started out as a Recommendations company and moved into Data Management Platform in the Ads space. He joined Google to see what it’s like to build things at scale.

• Cloud Next Week 9: Business Application Platform site
• From One to More: Why Sharing Our Narrative Matters site
• The 2020 Doodle for Google national finalists are here blog
• Explore Kids Space: A way to nurture your kid’s curiosity blog

• Active Assist site
• IAM Recommender Documentation site
• IAM Recommender Service Account Insights site
• Committed Use Discounts site

This week, we talk to Rob Hedgepeth about SkySQL.

Max is working on quite a few things, from fixing his dishwasher and teaching his family new board games to a new animated Google series with Jen Person.

This week on the podcast, we’re celebrating GKE’s fifth birthday! Mark Mirchandani is joined by special guest host Carter Morgan to talk all things Kubernetes and GKE with fellow Googlers and GKE experts Alex and Drew.

Drew starts the show with a thorough explanation of Kubernetes, telling our hosts that its a great way to manage containers as you scale. Because it is an open source offering, Kubernetes has grown and adapted quickly. Alex elaborates, pointing out that Kubernetes has helped redefine how people create cloud native applications. A year after Kubernetes was born, Google introduced Google Kubernetes Engine to help simplify things for developers while optimizing scalability and efficiency.

Our guests talk about the progression of GKE over its short life, what’s new with the latest version, and why reliability and scalability have become the focus for year six. Later, we hear examples of companies taking advantage of everything GKE has to offer and how the symbiotic relationship between Google and its customers has helped GKE grow. In the world of gaming, GKE’s global scaling capabilities have been vital. Drew talks about Anthos, explaining that it helps businesses run Kubernetes in their controlled on-prem system while leaving the option for an easy cloud migration in the future.

We wrap up the show with a look into the Kubernetes crystal ball where Drew sees a more adaptive Kubernetes and GKE. Alex hopes to continue to simplify GKE, making it easier and easier to use anywhere in the world.

Alex Zakonov leads Google Kubernetes Engine team being responsible for operations of Google K8S fleet and for driving innovation in the K8S management. Prior to Google, Alex led a portfolio of products for Azure Monitoring at Microsoft enabling Azure customers to reliably operate and scale their applications. Alex has co-founded two successful start-ups, one of which, AVIcode, was acquired by Microsoft. Alex brings experience and passion in building and operating large scale systems and enabling engineering teams to deliver innovation at scale.

Drew Bradstock leads product management for Google Kubernetes Engine. He previously worked on Google Ad Exchange and is based in Waterloo, Ontario in the Great White North of Canada.

• New GKE Dataplane V2 increases security and visibility for containers blog
• Week 8 of Cloud Next: Cloud AI site
  • Interpreting ML Models with Explainable AI site
• How I Launched This: A SaaS Story podcast

• Kubernetes site
• GKE site
• Bare Metal Solution site
• Optimize cost to performance on Google Kubernetes Engine video
• Best practices for running cost-optimized Kubernetes applications on GKE docs
• Anthos site
• Start your K8s learning journey with hands-on training at no cost site
• Kubernetes Podcast podcast

Anthony gives us a GKE tip on NodeLocal DNSCache this week!

Carter is working on the SaaS podcast. Mark and Carter are working on a Kubernetes series!

A wonky midi version of the Superman Theme was used comedically at the end of this episode. The powerful and moving original symphonic music composed by John Williams can be found here.

Mark and Brian Dorsey are together again this week as we learn all about Google’s Bare Metal Solution with our guests James Harding and Gurmeet “GG” Goindi. To start the show, GG introduces us to Bare Metal Solution, explaining that it allows client projects built on specialized, often outdated software to take advantage of the benefits of a cloud environment. Using Bare Metal Solution, clients can choose to migrate all or part of their projects for a fully customized experience.

We learn how Bare Metal Solution is able to support a partial or full native solution for clients and go through the steps to getting a project from completely on-prem to the cloud where latency is decreased, security is increased, and other cloud benefits can be leveraged. GG gives examples of situations where Bare Metal is a great option for clients, for instance an established company with an early 90s database that recently branched out into apps built in cloud native software. James outlines the benefits of Bare Metal Solution over other options, including real world examples of industries that have been able to modernize their offerings and adapt with the Bare Metal.

GG and James wrap up the show explaining why the open source aspect of Bare Metal is so important to the evolution and flexibility of the product, and we talk about the recent developments at Bare Metal.

James Harding leads the Data Management Practice for North America, with responsibility for the go-to-market strategy for all products and services data mangement. He also oversees marketing campaigns and sales field enablement.

Gurmeet Goindi (GG) is a product manager at Google, where he focuses on databases and attends meetings. Prior to joining Google, GG led product management for Exadata at Oracle, where he also worked on databases and attended meetings. GG has had various product management, management, and engineering roles for the last 20 years in Silicon Valley, but his favorite meetings have been at Google. He holds an MBA from the University of Chicago Booth School of Business.

• Google Cloud Next Week 7: Application Modernization site
• Brian’s Cloud Next Presentation: Where Should I Run My Stuff? Choosing Compute Options site
• Mark’s Cloud Next Presentation: What’s New in Google Cloud Cost Management site
• Announcing the general availability of Google Cloud Game Servers blog

• Bare Metal Solution site
• Bare Metal Solution Next Presentation site
• Bare Metal Solution on GitHub site
• Oracle site
• Oracle Rack Cabinets site

Max talks to Deloitte about how they built their system to help groups collect and respond to COVID-19 data on our Stack Chat Segment this week!

• NCAA bracket predictions on QwikLabs
• Here’s a hint for next week’s episode! GKE Turns 5: What’s New?

This week on the podcast, Mark and Max Saltonstall talk with Simen Svale Skogsrud and Knut Melvær of Sanity.io. Sanity.io started as a consulting company but organically morphed into a software company when they realized their content management solutions worked across many industries. By providing a managed system that includes search indexing and data hosting, Sanity.io allows customers to analyze and deliver content all over the world with ease. They also offer an open source kit that facilitates complete customization of the program to each client’s particular needs.

Simen explains headless CMS as compared to the conventional systems and how it benefits Sanity.io clients. Data is separate and much more flexible, allowing it to be used in any way on any platform. Knut tells us about the developer experience using Sanity, describing the dashboard of useful APIs and other features that make using the program a breeze. We talk about how real clients have influenced and built on the product and why customer service is so important to Sanity.

Later in the show, our guests go in-depth about specific features of Sanity, including how the system handles different types of data and data relationships. We get technical, talking about the importance of scaling and how Sanity is accomplishing this with Google Cloud and Kubernetes. Simen and Knut offer our listeners some valuable advice on product launching, time management, and more.

Knut Melvær is the Head of Developer Relations and Support at Sanity.io.

Simen Svale Skogsrud is Co-founder and CTO of Sanity.io.

• The Anywhere School: 50+ Google for Education updates blog
• It’s Week 6 of Next site
• Google Cloud and Spotify Demo at Next site
• Bare Metal Solution talk from GG site

• Sanity.io site
• Get Started with Sanity.io site
• Get Started with Sanity CLI site
• Sanity.io Careers site
• Sanity.io Docs site
• OMA site
• Bengler site
• Kubernetes site

Roger gives us a tip about Google Cloud’s Data Loss Prevention. Check out the demo here!

Max is blogging about identity and security and access control. Here’s his latest post with Jen Person, Zero Trust for Enterprise : Cooking up some access controls. Mark and Max have been working on turning their popular YouTube Series, Stack Chat, into a new addition to the podcast! Join us next week to hear the first installment!

Priyanka is back this week, joining Mark as we talk big data with our guests Prabhu Palanisamy and Jarrett Garcia. Iron Mountain, a data management company, securely stores hard-copy and online data for enterprise customers. SpringML aides enterprises in the use of data analytics and machine learning to transform their projects. With the help of SpringML and Google Cloud, Iron Mountain migrated much of their data to datalakes and cloud storage for easier access and manipulation of the data.

Jarrett and Prabhu talk about the process of migrating so much data, including the main goals of their partnership. First, they established systems that could be repeated and help Iron Mountain understand when data is moved, destroyed, migrated, and more. We discuss the next steps taken, learning how Iron Mountain moved so much data to the cloud. Using Google products like DataFlow, BigQuery, and Cloud Composer, SpringML was able to take the data from Iron Mountain’s landing zone and transform it. Prior planning meant that the system was optimized and ready from the beginning, complete with automation and tools to make a fast, effective migration of data without any restructuring. Later, the data visualization is done by GSuite, Google Data Studio, and Looker so Iron Mountain and their customers can use the data for analysis.

Later in the show, Jarrett describes real-life situations in which Iron Mountain has helped manage, migrate, and store data for customers. Prabhu details the lessons SpringML learned while working on this project and offers advice to other developers. He talks about the future of the project, explaining that now that the data has been migrated, more detailed analytics can be performed and machine learning projects added on to augment Iron Mountain’s offerings.

Jarrett Garcia recently joined Iron Mountain as the Director of Enterprise Data. At Iron Mountain, Jarrett is working closely with the executive leadership team to build a robust Enterprise Data Platform in the cloud. His partnership with Google Cloud is a critical component to the transformation journey. Before coming to Iron Mountain, Jarrett worked as a Lead Architect at Nielsen within their Technology R&D team to create an AI/ML platform in the cloud. Jarrett has been at the forefront in introducing modern technologies into the organization such as Docker, TensorFlow, and Kubernetes. Before that, he lead the Data Science technology team where he spent over a decade building analytic tools and ushering in new technology.

Prabhu Palanisamy is co-founder of SpringML. He has a long history of running data-driven consulting organizations from Software AG to Appirio. Building on relationships he created leading integration and analytics services, Prabhu co-founded SpringML, a next generation data analytics company that serves data intensive industries. Prabhu constantly questions the conventional way of doing things and finds ways to be creative and innovative for customer business problems.

• Google Cloud Next Week 5: Data Analytics site
• Best practices for performance and cost optimization for machine learning site
• Building smarter games with Machine Learning video
• Anthos in a Minute video
• What is BigQuery? video

• SpringML site
• Iron Mountain site
• BigQuery site
• Google Cloud Storage site
• Dataflow site
• Cloud Composer site
• GSuite site
• Data Studio site
• Looker site
• Scaling Data-Driven Insights Across a Complex Global Organization with Looker and BigQuery site

Nick Orlove tells us a bit more about what to think about when optimizing BigQuery:

• What is BigQuery? video
• Visualizing query results video

Priyanka has been working on GCP Comics and Sketchnote.

On the podcast this week, Mark Mirchandani and Brian Dorsey talk with fellow Googlers John Laham and Stewart Reichling about Traffic Director, a managed control plane for service mesh. Traffic Director solves many common networking problems developers face when breaking apart monoliths into multiple, manageable microservices. We start the conversation with some helpful definitions of terms like data plane (the plane that data passes through when one service calls on another) and service mesh (the art of helping these microservices speak with each other) and how Traffic Director and the Envoy Proxy use these concepts to streamline distributed services.

Envoy Proxy can handle all sorts of networking solutions, from policy enforcement to routing, without adding hundreds of lines of code to each project piece. The proxy can receive a request, process it, and pass it on to the next correct piece, speeding up your distributed system processes. But Envoy can do more than the regular proxy. With its xDS APIs, services can configure proxies automatically, making the process much more efficient. In some instances, the same benefits developers see with a distributed system can be gained from distributed proxies as well. To make distributed proxy configuration easy and manageable, a managed control plane system like Traffic Director is the solution. Traffic Director not only helps you facilitate communication between microservices, it also syncs distributed states across regions, monitors your infrastructure, and more.

Stewart is a Product Manager on Google Cloud Platform (GCP), based out of Cambridge, Massachusetts. Stewart leads Product Management for Traffic Director (Google’s managed control plane for open service mesh) and Internal HTTP(S) Load Balancing (Google’s managed, Envoy-based Layer 7 load balancer). He is a graduate of Georgia Institute of Technology and has worked across strategy, Marketing and Product Management at Google.

John is an infrastructure architect and cloud solutions architect that works with customers to help them build their applications and platforms on Google Cloud. Currently, he leads a team of consultants and engineers as part of the Google Cloud Professional Services organization, aligned to the telco, media, entertainment and gaming verticals.

• Week four sessions of Cloud Next: Security site
• Weekly Cloud Talks by DevRel Week 2 site
• Weekly Cloud Talks by DevRel Week 3 site
• Cost optimization on Google Cloud for developers and operators site
  • GCP Podcast Episode 217: Cost Optimization with Justin Lerma and Pathik Sharma podcast

• Traffic Director site
• Envoy Proxy site
• NGINX site
• HAProxy site
• Kubernetes site
• Cloud Run site
• Service Mesh with Traffic Director site
• Traffic Director Documentation site
• gRPC site
• Traffic Director and gRPC—proxyless services for your service mesh blog

This week, we’re talking about IAM Policy Troubleshooter.

Brian is working on the Weekly Cloud Talks by DevRel we mentioned in the cool things this week and continuing his Terraform studies.

Check out the Immutable Infrastructure video we talked about last week.

• “Jingle Romantic” by Jay_You of Freesound.org

Mark Mirchandani is joined again by Priyanka Vergadia this week for an ML-filled interview with Radu Miclaus of Lucidworks. Lucidworks, a company specializing in information retrieval, strives to make data searching easier for developers and users. Building off Solr, Lucidworks created Fusion, an environment more conducive to easy AI-enhanced query capabilities, better scalability, and more. With Fusion, developers can take advantage of the highly advanced relevance tuning tools such as query rewrites, which analyze user behavior and automatically rewrite queries based on that information.

On the tech side, Fusion was built with a combination of Java, Kubernetes to increase scalability, Solr management tools, and logging and reporting tools. The engineers at Lucidworks have created Fusion-specific system-enhancing pieces as well, including a machine learning service that allows data scientists to train their models elsewhere and plug them in for a completely customized experience. The team also created Smart Answers, which is a Q-And-A system built on a search engine that can connect to chatbots, virtual assistants, and others. Radu goes into detail explaining the Smart Answers system and how the layers of the project work together. We also learn about the customization capabilities and integration of Smart Answers.

Radu wraps up the show with interesting use-case stories and how Fusion is working in the real world. In the future, Lucidworks will be available right in the GCP marketplace!

Radu has over 12 years of experience in the data science space with applications in general machine learning architecture, search, customer analytics, risk and financial analysis. At Lucidworks, Radu focuses on low-code AI for search developers, pluggable machine learning for data scientists, and cloud managed services that offload the burden of operating search applications.

• Week 2 sessions on productivity and collaboration site
• Online shopping gets more personal with Recommendations AI blog
• Using new traffic control features in External HTTP(S) load balancer blog
• Optimizing your costs on Compute Engine video
• Google Cloud Talks by DevRel site
• Giving you better cost analytics capabilities—and a simpler invoice blog
• GCP Podcast Episode 217: Cost Optimization with Justin Lerma and Pathik Sharma podcast

• Lucidworks site
• Solr site
• Lucene site
• Fusion site
• Try Fusion site
• Smart Answers site
• Spark site
• Kubernetes site
• GKE site
• Dialogflow site
• Webinar: Smart Answers for Employee and Customer Support After COVID-19 site
• Deconstructing Chatbots video
• GCP Podcast Episode 227: Pandium with Cristina Flaschen and Kelly Sarabyn podcast
• GCP Podcast Episode 188: Conversation AI with Priyanka Vergadia podcast
• GCP Podcast Episode 195: Conversational AI Best Practices with Cathy Pearl and Jessica Dene Earley-Cha podcast

We’re talking to Dale Markowitz about Prototyping Machine Learning projects.

You can also hear more from Dale in GCP Podcast Episode 214: AI in Healthcare with Dale Markowitz and GCP Podcast Episode 194: ML with Dale Markowitz.

Priyanka has been working on GCP Comics and Sketchnote.

Tyler McMullen of Fastly is with us today, telling our hosts Mark Mirchandani and Brian Dorsey all about the company, CDNs, and more.

Fastly is an edge cloud platform, focusing on ways to improve the more customer-focused side of the cloud with things like latency reduction, efficient scaling, and more. Content Delivery Networks can be a part of this, due to their proximity to customers and better caching. Edge cloud takes pieces of normal cloud setups and moves them to the edge of the cloud, closer to the customer, to achieve better speed. Tyler explains what pieces make sense to move out to the edge and what he sees as the future of edge cloud platforms.

Later in the show, Tyler tells us how to analyze projects and make decisions on the use of edge cloud, CDNs, and microservices. He explains the technical process of using an edge cloud platform too, giving examples of situations that might benefit from a more edge cloud approach. WebAssembly, technology originally created for web browsers, actually plays a role in Fastly’s edge platforms, Tyler explains, going further into the technical side of how the engineers at Fastly have created this system to run smoothly while also being easy to build on.

In the future, Tyler hopes to see WebAssembly support more languages so compiling and distributing can be even easier.

Tyler McMullen is CTO at Fastly, a global edge cloud platform, where he is responsible for evolving the company’s system architecture and technology vision. He leads a team of experienced technology innovators focused on internet scale, and working on future-facing, ambitious projects and standards. As part of the founding team at Fastly, Tyler built the first versions of Fastly’s Instant Purging system, API, and Real-time Analytics. Prior to joining Fastly, Tyler worked on large scale web applications, text analysis, and performance. He can be found debating about edge computing, networking, and distributed systems all over the world.

• Week 1 recap of Google Cloud Next ‘20: OnAir blog
• Introducing Google Cloud Confidential Computing with Confidential VMs blog
• Next OnAir Sessions (Week 2) site
• Introducing your new home for work in G Suite blog

• Fastly site
• Reaching 100 Tbps of Capacity blog
• Fastly’s investment in WASM ecosystem blog
• Fastly’s Developer Hub site
• Fastly’s Developer Hub: Everything you need to build on Fastly is now in one place blog
• Bytecode Alliance site
• WebAssembly site
• BigQuery site
• Fastly Labs site
• Altitude site

We’re talking to Stephanie Wong about the Network Intelligence Center and her video series, GCP Networking End to End

Brian is learning Terraform!

Mark is working on more video content and his Next talk, CST103.

This week is all about business-to-business marketplace software with Pandium as Mark Mirchandani and Max Saltonstall talk with our guests Cristina Flaschen and Kelly Sarabyn. The Pandium platform helps companies build and support in-app marketplaces with a focus on software integration and flexibility.

Kelly and Cristina start by explaining how Pandium deals with scalability for clients with multiple users and partners. Cristina elaborates on Pandium’s role in facilitating integrations, helping customers build customized, flexible solutions. We discuss how APIs are handled and the way Pandium takes care of authentication, security, and other standard pieces.

We continue with a thorough discussion of ‘yes code’, ‘low code’, and ‘no code’ approaches, and the benefits and drawbacks of each system. With a combination approach of some ‘no code’ tools and other ‘yes code’ pieces, Pandium allows better customization in any code language, while keeping some functions easy for non-engineers.

Cristina Flaschen is the CEO and co-founder of Pandium. She has managed integration projects and technical implementation teams for over a decade, including at Handshake and Booker.

Kelly Sarabyn is a senior product marketer at Pandium. Previously, she was a partner at Woden and 2K North, where she crafted the positioning for dozens of SaaS companies.

• Choose the right Google Compute Engine machine type for you blog
• New gcloud cheat sheet available as free printable download blog
• Search for Racial Equity video

• Pandium site
• GKE site
• Google Sheets site
• Improving marketplace integrations with Pandium blog
• Scaling and support on GKE with Pandium video
• What’s Wrong with Low and No Code Platforms? blog
• “No Code”​ is great. But here’s why we need Yes Code blog

Alicia Williams is here to tell us about connecting Sheets to BigQuery.

A new video series called Season of Scale started just last week!

Max’s latest blog post is all about Pandium!

The Stack Chat series!

• “Laser Wrath 4.wav” by Marcuslee of Freesound.org

Mark Mirchandani and Priyanka Vergadia are here this week to talk about some cool things that are going on. Then, Mark brings us an interesting interview all about documentation in development with Technical Writing Manager Riona Macnamara. Riona specializes in technical documentation for DevOps at Google.

Having written technical documentation for both external and internal audiences, Riona starts the show comparing the two, explaining how the process can be very different. In external writing, she stresses the importance of engineers and technical writers working together. She details the challenges of documentation in code development culture and offers some solutions. Laying out goals can create better quality documents, while providing a simple documentation process for engineers can help bolster a culture of documenting. She talks about open source projects, stressing that documentation is possibly more necessary because of the diverse contributor base.

We wrap up the interview learning how to get started creating and maintaining useful documentation. Better trumps best with documentation; a lot of decent documentation is better than very few documents no one can find or use!

Riona is a 13-year Google veteran, and a documentation manager in Google Cloud. Previously at Google, she drove Google’s open source documentation strategy, led the team that developed Google’s internal engineering doc platform used by more than 20,000 projects, and supported Google’s Webmaster Tools (now Search Console). Before Google, she was a product manager at Amazon, and spent ten years at Microsoft as an editor on Encarta and mapping products, and a technical writer. She is a frequent speaker on documentation, open source, and diversity and inclusion, and is based in New York City.

• Google Cloud VMware Engine is now generally available blog
• I built an AI-powered moderation bot for Discord video

• Berlin Buzzwords 2019: Aizhamal Nurmamat Kyzy & Riona MacNamara - From User to Contributor video
• Documentation for Good: Knowledge as a tool for equity and inclusion video
• SREcon18 Asia/Australia - Do Docs Better: Practical Tips on Delivering Value to your Business video
• DevOps Days Galway videos
• Write the Docs Portland 2019 videos
• Write the Docs Australia 2019 videos
• Technical Writing Courses at Google site
• Docs Like Code on Amazon site

This week, we learn how to authenticate a REST API.

Riona will be the Keynote speaker for TCWorld India

Priyanka’s been working on new episodes of Cloud Bytes. App Engine in a Minute is now up! She’s also working on her series GCP Comics.

This week, Mark Mirchandani and Priyanka Vergadia learn all about Cloud Audit Logging with fellow Googlers Philip O’Toole and Oscar Guerrero. Our guests explain the importance of Cloud Audit Logs to keep track of your GCP resources so you know who, what, where, and when things were done. Our guests explain the types of logs GCP offers and why each is important for security. The interview continues with a discussion the various other benefits of audit logging, including proof of compliance and measuring of risk.

Because audit logs have the ability to create more data than some businesses can use, Philip and Oscar help our listeners understand how to choose the correct logging services for their needs, and we learn how Cloud Logging can help users digest their data. Philip describes how audit logs and event driven systems can benefit businesses, explaining how event driven systems can be built and pushed with GCP. Oscar continues the conversation with audit logging in G Suite. The Cloud Logging team is continuing to expand offerings, so be on the lookout!

Philip O’Toole is an Engineering Manager at Google Pittsburgh, leading development teams working on GCP’s Cloud Logging Platform, including Audit Logging. Prior to Google, he led development teams at InfluxDB, Loggly, and Riverbed Technology. You can find him on the web.

Oscar Guerrero is a Product Manager at Google New York, focused on Data Privacy and Compliance, in particular Audit Logging. Prior to Google, he consulted on Cloud based Financial Risk systems and was a Program Manager at Microsoft in Commerce, Xbox, and Cloud Recommendations.

• The new Google Cloud region in Jakarta is now open blog
• Cloud SQL database instances now discounted blog
  • Beyond Your Bill videos
  • Understanding and analyzing your committed use discounts video
• Now available: Next OnAir ‘20 schedule, sessions, learning, and resources blog

• Cloud Audit Logs site
• Cloud Audit Logs Documentation site
• Cloud Logging site
• Cloud Logging Documentation site
• BigQuery site
• Google Cloud Storage site
• Operations (formerly Stackdriver) site
• Chronicle site
• Splunk site
• G Suite audit logging information guide
• Google G Suite to Splunk HEC Configuration blog
• Anthos site

This week, we have a tip from our Customer Engineering friend, Anthony Bushong, about audit logging in Kubernetes. You can find great documentation on this here and here.

Cloud Bytes launched on Sunday and the 2nd episode of the Drawing Board launched late last week! Continuing to work on these.

Mark Mirchandani and Priyanka Vergadia host this week’s episode of the podcast, with a thorough discussion of Solutions Engineering at Google. Our guests, Grace Mollison and Ann Wallace, explain that the Solutions Engineering team is there to help customers choose appropriate products for things like security, analytics, data management, and more. The products are laid out in guides and blueprints so the client can easily understand why products are chosen and how to use them.

Grace and Ann talk later in the podcast about the Solutions Engineering blueprints that Solutions Engineering Architects have begun creating. They describe how the idea came about, how they’re built, as well as the types of blueprints that are available and how to use them. The team is still working to create more blueprints and make them even easier to use.

Based in London, UK, Grace Mollison leads the Cloud Solutions Architect team in EMEA, where she helps customers to understand how to architect and deploy applications “safely” on the Google Cloud platform. In her spare time she spends time attempting to teach her international team how to speak the Queen’s English! Before Google, Grace was a Solutions Architect at AWS where she worked with the AWS ecosystem and customers to ensure well architected solutions.

Ann Wallace (she/her) is Security Solutions Manager for Google Cloud where she develops, designs, and packages security solutions for Enterprise Customers. She co-wrote Google’s guidance for running PCI compliant workloads on GKE. Before Google, Ann spent 14 years at Nike in various engineering and architecture roles. She volunteers and leads workshops with Women Who Code Portland. When not working, Ann can be found traveling and ultra-trail running with her dog, Cedar.

• Father’s Day present of the past: 30 years of family videos in an AI archive blog
  • GCP Podcast Episode 214: AI in Healthcare with Dale Markowitz podcast
• Open Match is now 1.0 and ready for deployment in production blog
• Google Data Center Security: 6 Layers Deep video

• Cloud Solutions site
• Security blueprint: PCI on GKE site
• PCI and GKE Blueprint on GitHub site
• GCP Podcast Episode 116: Solution Architects with Miles Ward and Grace Mollison podcast
• GCP Podcast Episode 174: Professional Services with Ann Wallace and Michael Wallman podcast
• Terraform site
• Kubernetes site
• Anthos site
• Anthos security blueprint: Auditing and monitoring for deviation from policy site
• Anthos security blueprint: Enforcing policies site
• Anthos security blueprint: Enforcing locality restrictions for clusters on Google Cloud site
• OnlineBoutique on GitHub site

How can I get introduced to key products? With Priyanka’s new video series!

Our guests will be giving talks at virtual summits, including KubeCon and CISO Forum.

Priyanka has been working on a new video series called Google Cloud Drawing Board, as well as a new animation series that will launch next week!

Mark Mirchandani is back this week as he and co-host Brian Dorsey learn all about voice coding with some great guests! Emily Shea, senior software engineer at Fastly and user of Talon Voice, and Ryan Hileman, developer of Talon Voice, tell us about Repetitive Strain Injury and how it led to the design and use of Talon Voice. Talon allows not only straight voice input but includes eye tracking, noise recognition, and user customization to perform complex actions like moving windows, selecting text, and user-specific workflow customizations without touching any hardware.

Emily describes her experiences with Talon, including the process to get started and how she looked past voice recognition stereotypes to find how useful the product could be. She demos Talon for us, explaining how the alphabet system works. Ryan types a sentence using his voice then explains the process of developing the alphabet and other parts of Talon. Later, Ryan and Emily tell us how they write code using Talon and the logistics of using the software at home or in the office.

We end the show talking about how Talon and voice recognition software have helped people with and without debilitating injuries and given hope to those spending hours on computers every day. Emily stresses the importance of adding accessibility to websites to accommodate Talon users and others with disabilities.

Emily is a Senior Software Engineer at Fastly, where she works on the platform for delivering core Edge Cloud configurations. Because of a Repetitive Strain Injury, she develops using Talon’s speech recognition.

Ryan was a software engineer for over a decade and in 2017 quit his job due to hand pain. He has since worked full time on Talon with a mission of enabling anyone to be equally productive for any and all tasks on a computer without their hands.

• How to find—and use—your GKE logs with Cloud Logging blog
  • The Stack Doctor videos
• Using Recommenders to keep your cloud running optimally blog

• Talon Voice site
• Talon Slack site
• Talon Patreon site
• Hammerspoon site
• AutoHotkey site
• Whale Quench site
• The Accessibility Project site
• Web Content Accessibility Guidelines site
• Perl Conference video
• Demo from The Perl Conf video
• Strange Loop video
• Demo from Strange Loop video
• Ryan’s demo video
• Street Fighter video

We’re discussing security operations on the podcast this week with your hosts Priyanka Vergadia and Mark Mirchandani. They’re joined by Elliott Abraham and Jason Bisson who start the interview explaining that they created the CLAM framework to help customers use Google Cloud security features to their fullest potential to create safe projects and relaxed clients.

The CLAM (Cloud Logging Alerting and Monitoring) framework came about specifically to help customers transition products to, and run products securely in, the cloud. Using the Mitre GCP Matrix, the security team addressed each element with GCP product solutions, from initial access to persistence and beyond. CLAM is GCP specific, taking into account the default security measures GCP already provides and supplementing these measures with appropriate procedures for each client. Once the framework is in place and things are secure, clients can build on that with operational controls, such as SRE best practices.

Elliott explains the shared security model and how clients can shift more of the security responsibility to the cloud service provider by employing more managed services. Jason tells us about VPC Service Controls and how they allow clients to set specific security rules such as from where data can be accessed. They go on to describe the GCP Security Command Center and the tools available there.

We wrap up the interview with some tips from our guests, including what to do if you are compromised.

Elliott Abraham is a Security and Compliance Specialist based in Atlanta. Elliott works with Financial Services, Healthcare and Life Sciences and other Select Accounts migrating to or expanding their footprint on the Google Cloud Platform. Elliott has helped many customers to operationalize GCP Security solutions in alignment with their security, compliance, and regulatory requirements.

Jason Bisson is a Security and Compliance Specialist based in NYC. He works with Financial Services, Healthcare, Government, and Retail customers to explain the security, compliance, and regulatory abilities of Google Cloud Platform.

• Announcing Google Cloud Next ‘20: OnAir blog
• Celebrating a decade of data: BigQuery turns 10 blog
  • A very special BigQuery Day (The Data Show, w/ Felipe Hoffa & Yufeng Guo) video

• CLAM Framework pdf
• Mitre site
• Mitre ATT&CK site
• Mitre GCP Matrix site
• SRE Handbook site
• VPC Service Controls site
• Cloud Audit Logs site
• Cloud Data Loss Prevention site
• GCP Podcast Episode 218: Chronicle Security with Dr. Anton Chuvakin and Ansh Patniakpodcast
• GCP Podcast Episode 221: BeyondCorp with Robert Sadowski podcast

Yuri Grinshteyn talks about the new logging feature.

Priyanka is working on Building an Unbreakable DevOps Pipeline with Google Cloud.

Mark is working on more videos and will be speaking at Next.

On this episode of the podcast, our old pal Mark Mirchandani is joined by special guest host Max Saltonstall to talk trust and security with fellow Googler Rob Sadowski. BeyondCorp is Google’s answer to allowing employees to use company networks on any device while outside the building in a way that is both secure and efficient. Users are authenticated per session and per device to give access only to the specific person, on the specific device, for the specific job each time. In addition to the thorough authentication process, BeyondCorp continues to monitor device metadata during use as part of the system’s decision to continue to trust (or not trust) a user. With this information, if a user accidentally exposes the system to malware, for example, access can be revoked quickly.

Max and Rob explain the steps Google went through to create such a state-of-the-art security program and give tips on how companies can build something similar. Codifying your employees’ needs and preferences, detailing the levels of trust you’ll allow, and thinking ahead about where in the world your employees will be when they access the system are some of their tips. Rob stresses how complicated the system was to build from scratch and emphasizes that with BeyondCorp Remote Access, companies don’t have to build a whole new system.

BeyondCorp Remote Access offers automatic scaling and world-wide points of presence for a fast user experience anywhere in the world. Companies can define access rules for each user, setting trust levels and parameters for who can access what parts of the network. Rob points out that this is a great solution, not only for employees who find themselves working from home due to the current global climate, but also for freelance or contract workers who only need access to parts of the internal system.

Rob Sadowski is the Trust & Security Product Lead for Google Cloud at Google. He is responsible for creating and delivering Google Cloud’s security message, spanning platforms, applications, and connected devices.

• Using Bigtable’s monitoring tools, meant for a petabyte-scale database, to… make art blog
  • GCP Podcast Episode 192: Cloud Bigtable with Billy Jacobson podcast
• A simple, secure way for teams to meet and work: G Suite Essentials is here blog

• BeyondCorp site
• BeyondCorp Remote Access site
• BeyondCorp: A New Approach to Enterprise Security paper
• BeyondCorp: Design to Deployment at Google paper
• BeyondCorp: The Access Proxy paper
• Migrating to BeyondCorp: Maintaining Productivity While Improving Security paper
• BeyondCorp: The User Experience paper
• BeyondCorp 6: Building a Healthy Fleet paper
• NYC Cyber Command site

This week, Max talks about 2-step verification, security keys, and why you need them!

Max is working on Stack Chat at Home (coming soon!), BeyondCorp in a Bottle, as well as Ring Fit Adventure and Just Dance video games.

• “Clarinet Multiphonics” by jfcharles of Freesound.org

Priyanka Vergadia hops back into the host seat this week, joining Mark Mirchandani to talk to Marit Rødevand of Strise. Strise is an AI-driven enterprise company using knowledge graphs to gather and analyze massive amounts of information, depositing it into a web-based interface to help large clients such as banks solve data-driven problems. Strise’s web-based data platform is customizable, flexible, and capable of keeping up with the fast-paced world of technology so enterprise companies aren’t constantly putting time and resources into reworking old or building new software. To do this, Strise uses knowledge graphs rather than typical databases to create what Marit calls a future-proof data model.

Marit explains knowledge graphs in detail, emphasizing that they can reduce training of machine models, allow new data to be input easily, and make analyzing unstructured data much easier. Knowledge graphs take data that would normally only make sense to humans and in effect translate it for computers. Using banking as an example, she details how information about customers can be collected and analyzed thoroughly to help the bank come to conclusions about credit-worthiness or possible criminal activity.

On Strise’s platform, Marit tells us that the information is now available to the end user who provides feedback to the system, marking things as relevant or irrelevant, rather than leaving those decisions to a data scientist outside of the client’s field. This means that massive amounts of information could be stored in the knowledge graph, across many industries, and each user only gets the data he or she needs.

Google Cloud tools such as Kubernetes Engine, Dataproc, and Pub/Sub have played an integral roll in the creation of the Strise data pipeline. Marit explains how Strise gets their data, how it’s input into the knowledge graph, and how these Google tools help to keep Strise running.

Marit Rødevand is the CEO & co-founder of Strise, an AI startup from Norway who is signaling a new era of enterprise software.

Strise makes the world’s information useful across the enterprise. Their novel approach by utilizing a knowledge graph to power their data platform, allows Strise to break data silos, end customization projects, and bring new insights from unstructured data. Strise is currently helping leading Nordic banks and financial institutions to solve their hardest data-driven problems within KYC/AML, risk, and sales.

Strise recently announced their Seed round from Maki.vc, the leading Nordic early stage investor, who invests in deep tech & brand-led startups.

Marit has a background from Cybernetics & Robotics at the Norwegian University of Science and Technology (NTNU). In university, she co-founded Rendra, a construction SaaS, who was later acquired. Marit started as Entrepreneur in Residence at NTNU where she spun Strise out of a research project that focused on new data models as a foundation for better AI.

• BakeML site
  • David East’s Firebase Podcast podcast
• Automating BigQuery exports to an email blog
• Cloud OnBoard site

• Strise site
• A world in text — Strise blog
• GKE site
• Helm sote
• Dataproc site
• Operations site
• Cloud Run site
• Cloud Pub/Sub site
• Cloud DNS site
• Cloud Storage site
• GCP Podcast Episode 198: SeMI Technologies with Laura Ham podcast
• Building on Google Cloud with SeMI Technologies - Stack Chat video
• Knowledge graphs with Weaviate - Stack Chat video
• Natural Language Data Processing with Mito.ai - Stack Chat video

Zach answers the question “What’s a cool thing in Cloud that many people may not have thought about?” GSuite and Apps Script

Priyanka wrote this post on 13 Most Common Google Cloud Reference Architectures and her parents were on the news for the vegetable garden they’ve been working on. She’s also been working with material design components and firebase hosting. And The Data Show with Yufeng and Felipe is going strong!

Josh Brown, Developer Advocate at Spotify, is on the podcast this week with your hosts Mark and Brian. Working in the Open Developer Platform department, Josh supports third-party developers as they create music experiences for users using the Spotify APIs and SDKs. The most popular of these, the Spotify Web API, lets developers access metadata about music and facilitates library management for users.

We talk later in the episode about the types of applications developers are creating using the Spotify Web API and how it’s changing the way people listen. Using developer feedback, Spotify has continued to improve on the API, now offering podcast support, for example. With the new podcast support, hobby developers especially are developing apps that make podcast listening easier and more social.

To create these open platform APIs, Josh tells us they relied heavily on Google Cloud products like GKE and Cloud Storage. To manage the GCP products they use, Spotify created an internal portal called Backstage. Independent developers are encouraged to make use of Backstage to help with their Spotify projects as well.

Josh wraps up the episode explaining the lessons learned in creating these APIs and how developer feedback became so important for them.

Josh Brown is a developer advocate for Spotify, focusing on APIs. In his spare time, Josh enjoys running and writing.

• Google Cloud training available at no cost for 30 days blog
• Cost optimization for serverless workloads blog
• Understanding forwarding, peering, and private zones in Cloud DNS blog
  • Stephanie Wong’s video series on networking videos
  • Stephanie Wong’s blog on Medium blog

• Spotify site
• Backstage site
• Spotify for Developers site
• Spotify Community site
• Spotify Web API site
• Search, browse and follow podcasts using the new Podcast APIs news
• Kubernetes site
• GKE site
• Cloud SQL site
• Google Cloud Storage site
• Spotify Platform Documentation site
• Adopting Kubernetes with Spotify - Stack Chat video
• Updates on future Spotify events twitter

Podcasts and hosting static files: how does the GC Podcast do it? Cloud Storage of course! GC Podcast on GitHub.

The Google Cloud livestreams we talked about a few weeks ago have expanded into a new Meetup group!

It’s cyber security week on the podcast as Priyanka Vergadia joins Mark Mirchandani to talk with the folks of the Chronicle Security Team. Our guests Ansh Patniak and Dr. Anton Chuvakin start the show off with a brief explanation of Chronicle, which is a security analytics platform that can identify threats and correct them.

Anton details the threats facing clients today and why it’s important to continue to guard against old threats as well. Cyber security developers must constantly examine the landscape, adjust tools used, and think ahead to try to predict possible future problems. Ansh elaborates, pointing out that sometimes, all the security needed to protect against old, current, and potentially new threats can create a data overload that causes some threats to be lost in a jungle of notifications. Analyzing this data to gain insights about the health of a company’s cyber security is an important part of the process, and Chronicle can help with that. We discuss other challenges in the security analytics world and learn tips and tricks to help overcome them.

Our guests wrap up the show explaining how Chronicle, as part of GCP, benefits Google Cloud customers.

Dr. Anton Chuvakin is now involved with security solution strategy at Google Cloud, where he arrived via Chronicle Security (an Alphabet company) acquisition in July 2019. Anton was, until recently, a Research Vice President and Distinguished Analyst at Gartner for Technical Professionals (GTP) Security and Risk Management Strategies team. Anton is a recognized security expert in the field of log management, SIEM and PCI DSS compliance.

Ansh Patnaik is responsible for product marketing at Chronicle. Previously, he was VP of Product Management at Oracle where he defined and launched their Security Analytics Cloud service. Ansh has held product management, marketing and sales engineering roles at several cybersecurity and data segment market leaders including Delphix, ArcSight (acquired by HP), and BindView (acquired by Symantec).

• UEFI, Shielded VM now the default for Google Compute Engine customers—no additional charge blog
• Anthos—driving business agility and efficiency blog
• Anthos 101 videos

• Chronicle Security site
• Chronicle Security Blog blog
• Chronicle Security Resources site
• Why Your Security Data Lake Project Will FAIL! blog

Whats one thing you have seen users ask about security on Google Cloud?

Our guests be doing the SANS Webinar on April 30th.

13 days of GCP Architecture series! We’re on day nine now, but you can catch up on Twitter with posts like Day 6 on Data Lake and join us for the next few!

Our guests Justin Lerma and Pathik Sharma join Brian and Mark this week to talk cost optimization techniques for internet projects. Justin and Pathik, both of the Professional Services Organization, work to help customers get the most out of GCP while maintaining their project budgets. They help customers take business success metrics and track them from a cost perspective, allowing the client to get an understanding of how much each business goal actually costs, rather than an aggregate of how much has been spent in total. This information is used to tailor GCP product usage and cost optimization to each client project.

Pathik explains how the Recommender API can help with VM usage by suggesting shrinking or removing a VM altogether for cost savings. With thorough analysis, clients can also benefit from cost savings by paying for longterm usage of GCP products rather than month-to-month. For storage and analysis, BigQuery can offer better performance at a lower cost with partitioning and clustering.

Throughout the episode, Justin and Pathik offer up other tips and tricks to help our listeners save money with GCP, as well as suggested reading materials, videos, and labs to get you started on your cost optimization adventure.

Pathik Sharma is a Technical Account Manager with Google Cloud, focusing on proactively guiding enterprise customers to operate effectively and efficiently in the cloud. He loves helping customers to maximize their business value by optimizing their cloud spend. 

Justin Lerma is a Technical Account Manager with Google Cloud. He has a passion for sharing best practices in operational efficiency as it allows for the proliferation of more experimentation and breeds new ideas.

• Get started with Google Cloud Training & Certification site

• Compute Engine site
• BigQuery site
• BigQuery Reservations docs
• Cloud Storage site
• Operations site
• Recommenders docs
• Google Cloud Support Plans site
• Cloud SQL site
• Use labels to gain visibility into GCP resource usage and spending blog
• GCP Advanced Billing Dashboard site
• Stack Doctor Series videos
• Cost Management Playlist videos
• Best practices for Cloud Storage cost optimization blog
• Best practices for optimizing your cloud costs blog
• Cost optimization best practices for BigQuery blog
• Networking cost optimization best practices: an overview blog
• 5 best practices for Compute Engine Cost Optimization blog
• Cloud Logging and Monitoring Cost Optimization Strategies docs
• Codelabs: BigQuery Pricing site
• Qwiklabs: Business Transformation with Google Cloud site
• Qwiklabs: Understand Your Google Cloud Costs site
• Qwiklabs: Optimizing Your GCP Costs site
• Business Learning Path site
• Cloud Platform Resource Hierarchy docs
• Cleaning up unused IP addresses docs
• Cleaning up unused and orphaned persistent disks docs
• Schedule VMs to auto start/stop with Cloud Scheduler docs