Learn how to simplify cloud migrations with real-world lessons from moving a client from AWS Batch to Google Cloud Batch. This session will cover key areas like translating batch job definitions, optimizing workflows for better performance, and integrating applications with the Google Cloud Batch API. Along the way, we’ll explore strategies to address client concerns and ensure a smooth transition. Whether you’re planning a similar move or just curious about the behind-the-scenes, this session will give you some practical insights.

Build & deploy with Google Cloud Deploy! This hands-on lab equips you to create delivery pipelines, deploy container images to Artifact Registry, and promote applications across GKE environments.

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!

AlloyDB for PostgreSQL is Google Cloud’s high-performance, PostgreSQL-compatible database service for your demanding online transaction processing (OLTP), hybrid transactional and analytical, and generative AI applications. In this session, we’ll cover what’s new with AlloyDB, including critical enterprise features across performance, availability, ease of use, and more. You’ll also learn how customers are quickly migrating to AlloyDB with Database Migration Service and how they’ve successfully scaled their workloads with AlloyDB, saving money while doing so.

We will delve into the practical applications of AI-assisted coding within a large organization, highlighting the specific ways Ulta Beauty's developers are utilizing Gemini Code Assist to streamline workflows. Understand how Ulta successfully gained buy-in from both management and engineering teams by demonstrating the tool's value and addressing potential concerns. Learn about Ulta's thoughtful approach to integrating new AI technologies while prioritizing security, responsible usage, and alignment with existing development processes. 

This hands-on lab guides you through importing real-world data from CSV files into a Cloud SQL database. Using a flight dataset from the US Bureau of Transport Statistics, you'll gain hands-on experience with data ingestion and basic analysis. You'll learn to create a Cloud SQL instance and database, effectively import your data, and build a foundational data model using SQL queries.

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!

Build, deploy, and monetize AI agents on Google Cloud. This session covers the full lifecycle — development on Vertex AI, packaging, publishing, and commercialization on Google Cloud Marketplace, deployment on GKE etc., and customer access, including via Google Agentspace. We'll demonstrate leveraging the Google Cloud partner ecosystem to build enterprise-grade agents.

Moving mission-critical applications to the cloud in a regulated industry? In this session, experts from CME Group share a roadmap for achieving operational resilience on Google Cloud. Learn how to implement enterprise-scale observability, proactively troubleshoot issues, and enhance reliability while meeting stringent compliance requirements. Leave equipped with practical knowledge and tools to ensure operational excellence for your critical applications.

In this session, we’ll build a functional generative AI application designed to solve a common IT challenge for small teams. We’ll start by defining a problem and exploring how gen AI can offer a solution. Next, we’ll select a pretrained model from Model Garden and use it to build a simple application with intelligent automation. Throughout the process, we’ll demonstrate testing and refinement techniques. This session is ideal for visual learners who want to see the power of gen AI in action and gain the confidence to build their own AI-powered solutions.

Discover how Renault transformed automotive software development (SDV) with Google Cloud. By replacing physical prototypes with Android-based virtualization, they accelerated their SDV life cycle and moved to a cloud-first, iterative approach. Learn how they leverage Cloud Workstations, Gemini Code Assist, and a continuous integration and continuous testing (CI/CT) pipeline powered by Google Kubernetes Engine and GitLab to boost developer productivity and bring new features to market faster.

Transforming your cloud security means understanding that traditional application security (AppSec) almost never effectively prevents risk, cloud posture is too complex to manage, cloud runtime protection is sparsely deployed, and the security operations center (SOC) doesn’t have the visibility, AI, and automation for real-time response. Join us to learn how to remediate your cloud exposures in minutes, not weeks, using real-time AI-powered risk reduction, investigation, and response – all fueled by unified data and advanced automation. See the future of fast, intelligent, scalable cloud security.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

Organizations excel at building software, but they often struggle with the complexity of delivering it to production. This session introduces Software Logistics, a crucial discipline within Platform Engineering, focusing on the journey from package to runtime. Learn how to build delivery pipelines that handle modern cloud-native applications through practical patterns, real-world examples, and essential frameworks. Discover how customers implement Software Logistics practices to achieve reliable, secure, and efficient delivery of applications.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

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!

Google is transforming its marketing workflows with AI, slashing task time from weeks to minutes. This session explores the business problem and the solution: a Gemini-powered product that embeds AI-assisted content creation directly into our publishing platform replacing over 10 disparate tools. We will share some key technical considerations when working with Gemini including API design, prompt engineering versus fine-tuning, and evaluation techniques to ensure high quality output. Learn how to achieve similar results by integrating AI into your marketing ecosystem.

Agentic workflows analyze vast amounts of data and generate insights in real-time, giving you a competitive advantage with your AI offering. But when should you use them and how do you get started? Join DataStax to learn what use cases are best for employing agentic workflows, best practices for assuring accuracy, and getting your agentic AI into production.

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

Unlock the power of generative AI and data. Join experts from LlamaIndex and Google Cloud databases and learn how to seamlessly integrate LlamaIndex with AlloyDB and Cloud SQL for PostgreSQL, enabling your apps to reason, act on your data, and leverage the performance of Google Cloud. We’ll share real-world examples and code. Discover new possibilities for building advanced gen AI applications.

Tired of building the same old software as a service (SaaS) features? AI and data agents are revolutionizing the SaaS landscape, and developers are at the forefront of this exciting shift. Imagine building applications that can autonomously learn, adapt, and execute complex tasks, all while providing a personalized user experience. This session equips you with the knowledge and tools to build the next generation of intelligent SaaS applications. Learn how leading companies are leveraging AI agents to automate workflows, personalize user interactions, and boost operational efficiency. Discover the latest trends in agent development, best practices for building agent-first applications, and the secrets to successful implementation. And leave with practical insights and a clear roadmap for harnessing the power of agentic AI to create truly innovative SaaS products.

As the number of distributed and generative AI applications grows in your organization, so will the number of APIs – presenting management and governance challenges. This session introduces API Hub, a solution for unified API management. Learn how to gain centralized observability over your APIs, use the API Hub on-ramp framework to connect to any API gateway, help developers access shared components and standards to build compliant APIs faster, and discover and manage shadow APIs.

This session explores patterns for productionizing AI applications on Google Kubernetes Engine (GKE). Learn to leverage open source frameworks, cloud AI services, and readily available models to train, deploy, and scale with GKE. We’ll share real-world customer stories and best practices for productionizing AI solutions on GKE.

Dive into the world of serverless GPUs with Cloud Run. This talk explores how Cloud Run delivers on-demand GPUs with unprecedented flexibility and cost efficiency. Learn how you can achieve optimal performance and resource utilization with rapid autoscaling and scaling to zero. And discover how Cloud Run GPUs can help you build AI inference apps with open models, high-performance computing, graphics rendering, and much more.