Jason Polites discusses advances in serverless computing with Cloud Run, including increased resource access, global load balancing, and support for bigger and more complicated software. Cost-saving tips for projects, like committed use discounts and auto-scaling limits, are also shared. The use of open source build packs and the portability of containers on Cloud Run are highlighted. Recent enhancements, such as serverless VPC access and increased concurrency limit, are discussed.

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 Erwin Huizenga is a Data Scientist at Google specializing in TensorFLow, Python, and ML. Cool things of the week 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 Interview 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 What’s something cool you’re working on? 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 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 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. Cool things of the week 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 Interview 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 Buffaloe Bryce is the Assured Workloads Product Manager at Google. Mikaela Misaka 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. Cool things of the week 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 Interview 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 What’s something cool you’re working on? 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 Jennings 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 Conkling Joel is the Product Manager for both Earth Engine and Environmental Insights Explorer and has worked at Google since 2010. Cool things of the week 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 Interview 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 Schmidt 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 Aziza 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. Cool things of the week 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 Interview 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 What’s something cool you’re working on? 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 Hall 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 Brazeal Forrest is a cloud educator, author, speaker, and Pwnie Award-winning songwriter based in Charlotte, NC. Cool things of the week Cloud Next site Solving for What’s Next blog Training more than 40 million new people on Google Cloud skills blog Interview 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 What’s something cool you’re working on? 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. Perry Pierce 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 Brereton JoAnn loves baseball and tech, so she’s happy to be working at a job where she gets to do both. Cool things of the week Cloud NAT explained! blog Build your data analytics skills with the latest no cost BigQuery trainings blog Introducing Workflows callbacks blog Interview MLB site MLB Draft site Kubernetes site Grafana site Inside Baseball: How MLB Transactions Actually Get Done blog LBi Software site What’s something cool you’re working on? 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 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 Nandan Sridhar works in the Product Management team at Google Cloud, Apigee. Nandan’s expertise includes API design standards, API security and microservices. Cool things of the week What’s your org’s reliability mindset? Insights from Google SREs blog Climate TRACE site Interview 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 What’s something cool you’re working on? 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 Schwarz 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 Derrington Sean has spent 20 years in storage product management. Before Google, he spent time at Veritas, Exablox, and StorageCraft. Cool things of the week 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 Interview 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 What’s something cool you’re working on? Jenny is working on Google Cloud Reader and further audio formats for all your favorite cloud content.