Google Cloud Platform Podcast

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