Google Cloud Platform Podcast

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