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!

Building AI solutions on Google Cloud? This session demystifies our AI infrastructure stack, from pretrained models like Gemini to the Vertex AI managed platform, and all the way down to DIY container runtimes and virtual machines (VMs). Learn how to choose the right level of abstraction for your AI and machine learning (ML) workloads, and leverage the full power of Google Cloud’s AI ecosystem.

There are a lot of amazing AI features being announced at Google Cloud Next. In order to take full advantage of these, you need to make sure your data is being managed in a secure, centralized way. In this talk, you’ll learn how to set up your lakehouse to get your data ready for downstream workloads. You’ll view a demo involving an architecture of Google Cloud products that includes managing permissions on your data, configuring metadata management, and performing transformations using open source frameworks.

Large AI, machine learning (ML), and analytics workloads can demand high-performance access to storage from thousands of nodes and to exabytes worth of data. Unblocking innovation requires having an efficient and sustainable storage infrastructure in place. In this session, you’ll learn about how customers can achieve this using Google Cloud Hyperdisk capabilities and offerings like Hyperdisk Storage Pools, Hyperdisk ML, Hyperdisk Throughput, and more. Learn from leading customers who have used Hyperdisk to achieve their business objectives.

Join us to learn about migrating to Google Workspace. In this session, you’ll learn how to set up your new Workspace domain. We’ll guide you through how you can migrate your data to Workspace and set up essential workflows for your business. Plus, you’ll learn best practices for migrating to Workspace from customers and partners who’ve already taken the journey.

In this session, we’ll describe how Google Cloud Consulting and Professional Service teams have partnered with enterprise customers on their large-scale innovation, transformation, and migration journeys and accelerated the paths to their business objectives. We’ll cover a number of customer and partner success stories, transforming their business via large scale migration, NVIDIA GPU technologies and other AI infrastructure innovations.

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.

Managing massive deployments of accelerators for AI and high performance computing (HPC) workloads can be complex. This talk dives into running AI-optimized Google Kubernetes Engine (GKE) clusters that streamline infrastructure provisioning, workload orchestration, and ongoing operations for tens of thousands of accelerators. Learn how topology-aware scheduling, maintenance controls, and advanced networking capabilities enable ultralow latency and maximum performance by default for demanding workloads like AI pretraining, fine-tuning, inference, and HPC.

This session provides strategies for maximizing business value with generative AI. We cut through the hype and offer actionable insights for building and deploying advanced gen AI business capabilities. We'll delve into strategies that our customers use to get the most out of their AI investment, explore the essential foundations for scaling up, and share a vision for the future of business operations transformed by agentic AI.

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.

Default service accounts in Google Cloud have been an area of interest for threat actors. Cloud administrators can sometimes grant unintentionally broad permissions through this mechanism to their workloads, such as virtual machines and Kubernetes clusters. In this talk, we will discuss the role of default service accounts in Google Cloud Compute Engine (GCE) and Google Cloud Kubernetes Engine (GKE), and best practices for managing and securing them.

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.

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.

Modern analytics and AI workloads demand a unified storage layer for structured and unstructured data. Learn how Cloud Storage simplifies building data lakes based on Apache Iceberg. We’ll discuss storage best practices and new capabilities that enable high performance and cost efficiency. We’ll also guide you through real-world examples, including Iceberg data lakes with BigQuery or third-party solutions, data preparation for AI pipelines with Dataproc and Apache Spark, and how customers have built unified analytics and AI solutions on Cloud Storage.

Spanner Graph provides graph database capabilities at virtually unlimited scale and allows you to seamlessly interoperate between relational and graph data models. Join this session to learn about the latest capabilities in Spanner Graph and how you can build intelligent applications with it.

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!

Leverage the best of Ray and Google Kubernetes Engine (GKE) to build your next-generation machine learning (ML) platform. Google and Anyscale are making Ray and Kubernetes the distributing operating system for AI/ML. Discover how on GKE, Ray enables you to deliver a unified platform to scale your workloads from development to large-scale production. Learn about GKE’s latest advancements for fast data access, intelligent scheduling, and optimized utilization of hardware accelerators, and how Ray and Anyscale RayTurbo are enhancing that with best-in-class performance, efficiency, and developer productivity. Leave this session equipped to build a scalable AI/ML platform to empower your researchers and engineers.

Join us to learn how to design and deploy mission-critical applications on Google Cloud, with a focus on reliability. We’ll cover common deployment architectures for traditional enterprise and AI and machine learning apps, Google Cloud product capabilities to improve reliability, and best practices for high availability and disaster recovery. And a Google Cloud customer will share their journey of running mission-critical applications on Google Cloud, including key lessons learned and how those connect back to Google Cloud architectural guidance and best practices.

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.

Master modern enterprise storage on Google Cloud. Optimize cloud-based file storage for diverse workloads with Filestore and Google Cloud NetApp Volumes, fully managed Network File System [NFS) and Server Message Block (SMB) solutions balancing performance, availability, and cost. Explore new features for modern workloads and discover how NetApp Volumes handles Windows and petabyte-scale enterprise demands. This session is a must for IT leaders seeking to future-proof their storage strategy. Learn from BlackLine’s success.