Join us to explore the next generation of in-car experiences. Discover how leading automakers are leveraging Automotive AI Agent and Google Cloud’s Gemini model to build cutting-edge, multimodal automotive assistants. Learn how to create unique brand experiences with customized voice assistants, complete data ownership, and personalized in-car interactions. This session will showcase the power of hybrid voice assistance and how you can unlock the potential for differentiated driver experiences through custom features and granular control.

Production-ready apps, including GenAI apps, demand robust telemetry. Explore the full lifecycle: from data generation to consumption. See how OpenTelemetry, scaled by BindPlane, delivers enterprise-grade observability within Google Cloud. Learn to centralize data, cut costs, and achieve proven customer success!

Developers love Cloud Run. In this demo-driven talk, you’ll discover why Cloud Run offers simplicity alongside flexibility for running your code. We’ll begin with a couple of basic getting-started concepts. Then we’ll go into “How do I” scenarios that cover every feature from Virtual Private Cloud (VPC) access to startup probes. Too much info? We’ll have codelabs for you to do at your own pace.

This hands-on lab empowers you to build a cutting-edge multimodal question answering system using Google's Vertex AI and the powerful Gemini family of models. By constructing this system from the ground up, you'll gain a deep understanding of its inner workings and the advantages of incorporating visual information into Retrieval Augmented Generation (RAG). This hands-on experience equips you with the knowledge to customize and optimize your own multimodal question answering systems, unlocking new possibilities for knowledge discovery and reasoning.

If you register for a Learning Center lab, please ensure that you sign up for a Google Cloud Skills Boost account for both your work domain and personal email address. You will need to authenticate your account as well (be sure to check your spam folder!). This will ensure you can arrive and access your labs quickly onsite. You can follow this link to sign up!

Are you ready to get hands-on with Google Cloud’s AI tools? In this 2 hour gHack, you will work in teams of 4. Together you will build a Formula E Race Analysis System from scratch using a variety of our AI and Data tools. Teams will work together to build the solution by searching, learning and collaborating together to find the answers needed. 3-2-1 lights out and away we go!

Transform your Google Workspace experience with the power of Gemini. This fast-paced session dives into practical integrations using Apps Script, Vertex AI, Python, and Node.js to automate workflows and unlock new levels of efficiency. Discover how to leverage Gemini for intelligent task management, data-driven insights, and building custom AI solutions. Leave with actionable strategies and code snippets to immediately boost your productivity.

Accelerate Android development in your company with the new Gemini in Android Studio Standard and Enterprise tiers. These new tiers bring together the best of Google AI coding assistance, AI capabilities for Android development, and the enterprise-readiness of Gemini Code Assist. In this session, you’ll learn about the benefits of Gemini in Android Studio and how to use the wide array of features – such as compose preview generation, transforms, chat, and more – to take your company’s Android development to the next level.

Go under the hood to understand how the database features of Gemini Code Assist are giving application developers exciting new superpowers. Learn how Gemini powers the industry’s leading automated database querying, smarter application code wrangling in the integrated development environment (IDE), and entirely new agentic AI application features powered by enterprise data. Learn from Google Cloud engineers, and industry experts about how these features are having an impact today. And discover the secret sauce that makes these superpowers possible.

Boost your productivity with Gemini Code Assist tools. This session demonstrates how to seamlessly integrate your daily tools – source code management, task management, Google Drive, and more – directly into your integrated development environment with Gemini Code Assist chat. Discover the latest Gemini Code Assist features and capabilities, learn best practices for integrating AI into your software development workflow, gain insights into modernizing legacy codebases, and learn how to improve code quality and accelerate development cycles.

Jeff, Head of Product at Hugging Face, will walk you through the latest and greatest from Hugging Face to build your own AI models, agents and applications using open models, open source and Google Cloud. Learn how to easily deploy the latest LLM on Vertex AI and GKE, how to accelerate and scale your models on TPU.

Are you ready to get hands-on with Google Cloud’s AI tools? In this 2 hour gHack, you will work in teams of 4. Together you will build a Formula E Race Analysis System from scratch using a variety of our AI and Data tools. Teams will work together to build the solution by searching, learning and collaborating together to find the answers needed. 3-2-1 lights out and away we go!

In this hands-on lab, you'll explore the power of Kubernetes and learn how to orchestrate cloud applications with ease. Using Google Kubernetes Engine, you’ll provision a fully managed Kubernetes cluster and deploy Docker containers using kubectl. Break down a monolithic application into microservices using Kubernetes Deployments and Services, and gain insights into the latest innovations in resource efficiency, developer productivity, and automated operations. By the end, you'll be ready to streamline application management in any environment.

If you register for a Learning Center lab, please ensure that you sign up for a Google Cloud Skills Boost account for both your work domain and personal email address. You will need to authenticate your account as well (be sure to check your spam folder!). This will ensure you can arrive and access your labs quickly onsite. You can follow this link to sign up!

This hands-on lab equips you with the practical skills to build and deploy a real-world AI-powered chat application leveraging the Gemini LLM APIs. You'll learn to containerize your application using Cloud Build, deploy it seamlessly to Cloud Run, and explore how to interact with the Gemini LLM to generate insightful responses. This hands-on experience will provide you with a solid foundation for developing engaging and interactive conversational applications.

If you register for a Learning Center lab, please ensure that you sign up for a Google Cloud Skills Boost account for both your work domain and personal email address. You will need to authenticate your account as well (be sure to check your spam folder!). This will ensure you can arrive and access your labs quickly onsite. You can follow this link to sign up!

Join this session to learn how to ground your AI with relevant data with retrieval-augmented generation (RAG) from Firebase Data Connect, which brings rapid development and intelligent context from your Cloud SQL database to your generative AI experiences. Data Connect makes it easy to connect your app, data, and AI all together, and seamlessly integrates Vertex AI and Cloud SQL to make RAG easy and ready for AI agents.

Learn how Firebase App Hosting simplifies deploying and managing Next.js and Angular web apps on Google Cloud infrastructure. With seamless GitHub integration, global scalability, and built-in observability, App Hosting is designed for production-ready deployments. In this session, you’ll watch live demos and explore streamlined workflows to elevate your web app deployment process.

Come join us as we take a deep dive into using Cloud Run for high-availability applications that are resilient to regional outages with no additional costs or complexity. Learn how you can minimize service disruptions to ensure your business continues to operate smoothly, even during a regional outage, with minimal toil on Cloud Run. This session covers a range of topics, including fault tolerant design, multi-region deployment, automated failover, and more.

Platform engineering is revolutionizing software delivery. Discover how leading organizations leverage it to accelerate time to market and reduce operational overhead. This panel of experts will share real-world implementation strategies, lessons learned from common challenges, and insights into the future of this rapidly evolving field. Together, we’ll also explore new research findings on best practices and the key pillars for successful platform engineering adoption. Join the session to gain actionable strategies to enhance the developer experience, foster collaboration, and attract top talent to your team.

Are you an Amazon Web Services (AWS) developer exploring Google Cloud for the first time, or looking to deepen your multi-cloud skills? Join us for a whirlwind tour exploring the ins and outs of Google Cloud, from resource and access management, to networking and SDKs. We’ll cover Google Cloud’s framework for hyperscaler migrations. Then, we will demonstrate migrating an AWS application to Google Kubernetes Engine (GKE) and Cloud SQL, including Database Migration Service (DMS), GKE cluster creation, container image migration, and CI/CD. You'll leave with a core understanding of how Google Cloud works, key similarities and differences with AWS, and resources to get started.

Google Cloud’s Sensitive Data Protection service is a highly effective capability that can discover and classify sensitive data in your environment, helping to prevent data leakage. But it also has features useful to developers to minimize the exposure of confidential customer information when handling large volumes of sensitive data. By taking advantage of Sensitive Data Protection transformation techniques, you can de-identify sensitive information in a dataset through redaction, replacement, masking, tokenization, bucketing, date shifting, and time extraction. Developers retain the ability to test applications using functional data while still meeting security requirements put in place to protect customer information. By using pseudonymization, which is reversible and provides an easier path for troubleshooting, developers will have a more useful dataset for functional testing than they would if they used data anonymization. In this talk, you’ll learn how to use the Cloud Data Loss Prevention API (DLP API) of Sensitive Data Protection to inspect data for sensitive information and build an automated data transformation pipeline to create de-identified copies of your dataset.

This talk explores practical strategies for creating effective AI agents. Drawing insights from recent research, this talk focuses on enhancing LLMs with tools, memory, and control mechanisms, transitioning from static workflows to dynamic, goal-driven systems. Learn how simplicity, thoughtful augmentation, and robust frameworks can lead to smarter, more reliable agents ready for real-world challenges.