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.

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.

Join this session where Shopify engineers will discuss how they leverage the latest Google Kubernetes Engine (GKE) innovations to build robust, scalable platforms that not only handle everyday traffic with ease but also gracefully absorb unpredictable spikes during peak events like Black Friday and Cyber Monday. Learn key architectural patterns, smart infrastructure choices, and proven best practices. Discover how to optimize resource utilization, control costs, and deliver cost-effective performance every time.

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.

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.

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.

Transform your developer experience by integrating Backstage with Google Cloud. Learn how to implement essential platform engineering practices applicable to any industry or size. Discover how you can achieve remarkable results by building a self-service developer platform on Backstage for your multi-tenant Google Kubernetes Engine infrastructure like HCA Healthcare did. Learn firsthand how they transformed developer onboarding: slashing the process from months to just minutes, improving developer satisfaction, and accelerating innovation at scale.

To stay competitive against cloud-native disruptors, Carrefour Spain launched a cloud-first strategy with Google Cloud, transforming IT for agility, scalability, and cost-efficiency. In this session, learn how NTT DATA helped Carrefour leverage IaaS, PaaS, and serverless tools, migrating 382 workloads and deploying SAP Hana across 200+ hypermarkets. Discover how Carrefour's new e-commerce platform powered by Kubernetes accelerates innovation and drives online growth, helping them outpace competitors.

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.

Scaling Google Kubernetes Engine (GKE) effectively can be complex. This session dives into the challenges and solutions for managing GKE at scale, from cost optimization and security to AI workloads. Learn how enterprises like Dun & Bradstreet leverage GKE as a secure and scalable platform for their generative AI initiatives.

This session explores Yahoo Mail’s successful implementation of OpenTelemetry within their globally distributed Google Kubernetes Engine (GKE) environment on Google Cloud. Discover how they achieved seamless integration with Google Cloud Observability and established a centralized observability platform for multiple teams. Learn best practices and gain their top tips and tricks for building enterprise-level observability.

Join fellow Google Kubernetes Engine and ML engineers to share experiences building scalable, flexible, and resource-efficient machine learning platforms on GKE. Let's discuss strategies to best leverage GKE's features for serving open LLM models and orchestrating TPU/GPU’s at scale. Come prepared to share, ask questions, connect with others, and help each other succeed with GKE for ML.

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!

Join us as we reveal how the AURA AI Suite—AURA-SECURE, AURA-FLEX, and AURA-OMNI—is transforming enterprise AI. Experience bespoke conversational solutions for both structured and unstructured data. Discover how private GPT models secure sensitive information and dynamic insights boost productivity, decision-making, and customer engagement. Plus, see how Google Cloud services like Vertex AI, BigQuery, and Kubernetes ensure seamless integration, accelerated performance, and robust 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.

This technical deep dive explores how small IT teams can leverage Google Kubernetes Engine (GKE) and AI Hypercomputer to build, refine, and optimize a cutting-edge, scalable, and secure container platform for AI workloads.

Ten years ago, Google Kubernetes Engine (GKE) was born! Since then, it has become the industry-leading managed Kubernetes platform, powering mission-critical workloads across all industries. But the innovations have just begun. Join this session to learn about the latest GKE features and upcoming innovations – such as next-generation autoscaling, lightning-fast node startup, and multi-cluster fleet management – that make GKE the best Kubernetes platform for the next generation of AI and modern workloads.

There are cases when you can’t use Google Cloud services but still want to get all benefits of AlloyDB integration with AI and serve a local model directly to the database. In such cases, AlloyDB Omni deployed in a Kubernetes cluster can be great solution, serving for edge cases and keeping all communications between database and AI model local.

This technical deep dive explores how small IT teams can leverage Google Kubernetes Engine (GKE) and AI Hypercomputer to build, refine, and optimize a cutting-edge, scalable, and secure container platform for AI workloads.

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!