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.

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!

Developers love Cloud Run, Google Cloud’s serverless runtime. Join this session for a deep dive into new Cloud Run capabilities that make it even simpler to deploy your applications and enable you to deploy new types of workloads, including AI inference. Discover how Cloud Run can power your most demanding workloads with unparalleled efficiency and flexibility.

This session showcases an end-to-end generative AI application on Google Cloud. We’ll demonstrate how to use Gemini 2.0 Flash to analyze user-uploaded images, extract features, and generate descriptions stored in AlloyDB. Then we’ll show you how to fine-tune Gemini 2.0 Flash with BigQuery and generate outfit recommendations with AlloyDB low-latency querying. Finally, we’ll use the output from Gemini 2.0 Flash and Imagen 3 to create visuals of the outfits and deploy the entire solution on Cloud Run.

What if gameplay evolved with each player? GenAI + Gemma makes it real! This open model creates dynamic experiences through fine-tuning & flexible deployment (local/Cloud Run GPU). See natural conversations & adapted gameplay via live demos, possibly live coding. Discover practical implementation & architecture insights. Let's skip the slides and jump to the fun.

According to a 2023 Stack Overflow survey, the combination of Firebase and Google Cloud is the #1 choice for learning how to develop apps. Join this session to learn why this is true and how you can best leverage Firebase and Google Cloud together. Whether you’re a startup or a world’s leading retailer, you can easily get started with Firebase, and grow your business with Google Cloud. In this session, hosted by product leaders from both teams, they’ll discuss across products including Firebase, Vertex AI, and Cloud Run.

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Ford Motor Company has leveraged Cloud Run as its first-choice platform for its Google Cloud migration. By taking advantage of the Cloud Run serverless container platform, Ford’s migration of thousands of services has improved developer productivity, application scalability, and operational efficiency. In this talk, we’ll discuss the how, the why, and the results of Ford's massive replatforming to Google Cloud with Cloud Run.

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Deploying an application can be intimidating, so let's make it fun. The JavaScript ecosystem moves so quickly that it can leave you wondering: Can I deploy [JavaScript framework] to Google Cloud Run? Yes. Let's prove it by deploying as many JavaScript Frameworks as we can, as quickly as possible.

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Ready to supercharge your Java skills with cutting-edge generative AI? Dive into this immersive hands-on workshop and learn how to build and deploy powerful gen AI applications in Cloud Run using gen AI with Vertex and Gemini models. We'll explore fast Java development, leverage the scalability of Cloud Run, and tackle real-world gen AI use cases. Get ready and unleash the power of AI in your next application!

Work with a complete end-to-end sample application, guided at all times by the power of Gemini.

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Come to this fireside chat with Seth Vargo to learn more about the ultimate hybrid cloud use case. We'll explore use cases where Alphabet products run on some of your favorite Google Cloud offerings such as Google Kubernetes Engine (GKE). Why don't we run everything at Alphabet on Google Cloud? Why do some products run partially on cloud? How do Alphabet engineers take advantage of products like GKE, Cloud Run, Vertex AI, and Gemini exposed over hybrid channels? We'll shed light on how our internal innovation influences the products available to our customers and vice-versa.

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Embark on a journey through the diverse landscape of website deployment options available on Google Cloud. In this session, we’ll guide you through various ways to deploy a website, offering insights into the array of tools and services Google Cloud provides for hosting, scaling, and optimizing web applications. From traditional virtual machine instances to containerized solutions with Kubernetes, and serverless deployment with Cloud Functions and Cloud Run, this session will cover the entire spectrum of deployment strategies.

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In this session we’ll create an Apigee proxy that will talk to our containerized workload on Google Cloud Run and Google Cloud SQL, where our business logic will be stored. We’ll explore Apigee capabilities like security and monetization, and build developer resources. We will also cover the concept of “treating your APIs as products.”

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Discover modern cloud migration strategies. Learn to leverage Google Cloud for cost optimization and easy transitions from on-premise infrastructure or competing cloud providers. Get real demos of top migration methods to Google Cloud environments like, Google Cloud VMware Engine, Google Compute Engine, Google Kubernetes Engine, and Cloud Run. Learn to migrate an application across Google Cloud infrastructure levels, fine-tuning for cost and performance. Plus, get insights from Global Payments, with a real-world Google Cloud migration success story.

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Looking to start a new application or better yet allow your frontend development team to own more of their tech stack? With the power of Google Cloud and Dart, it’s possible to get up and running quickly with code sharing between your frontend and backend. In this session we will bring up a full stack project and have it running on device and in Cloud Run in a matter of minutes so you can focus on your users feature requests instead of infrastructure nightmares.

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Cloud Run is Google Cloud's serverless runtime. It’s the simplest way to deploy a website or web API or perform streaming and batch data processing. In this session, we’ll cover what's new for two major areas of Cloud Run: Enterprise architectures and streamlined application management.

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Adequately testing systems that use Google Cloud services can be a serious challenge. In this session we’ll show you how to shift testing to an API-first approach using Testcontainers. This approach helps us improve the feedback cycle and reliability for both our inner-dev loop and our competitive intelligence cycle. We’ll go through an end-to-end example that uses BigQuery and PubSub, Cloud Build, and Cloud Run. Examples will use Kotlin but it could be accomplished with other languages including Rust, Go, JavaScript, Python, Java, and more.

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In this session, you’ll learn how to deploy a fully-functional Retrieval-Augmented Generation (RAG) application to Google Cloud using open-source tools and models from Ray, HuggingFace, and LangChain. You’ll learn how to augment it with your own data using Ray on Google Kubernetes Engine (GKE) and Cloud SQL’s pgvector extension, deploy any model from HuggingFace to GKE, and rapidly develop your LangChain application on Cloud Run. After the session, you’ll be able to deploy your own RAG application and customize it to your needs.

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Follow along as two Developer Relations Engineers work in real-time to develop a minimal viable Flutter app, backed by Firestore database through a Google Cloud Run-powered API. We'll see the Cloud Run developer experience, focusing on automation and error recovery to deploy a REST API. Based on this API, see how to develop a Flutter application showing the latest UI features.

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In our session, learn how MSCI uses machine learning with Vertex AI, BigQuery and Cloud Run to enrich its datasets to help our clients gain insight into around 1 million asset locations to help manage climate-related risks. We’ll demonstrate how MSCI Geospatial can achieve an increase of 100 times in data processing efficiency, utilizing the scalability and cost-effectiveness of Google Cloud solutions.

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LangChain is the most popular open-source framework for building LLM-based apps. Google Cloud is the easiest place to deploy LangChain apps to production. In this session technical practitioners will learn how to combine LangChain on Cloud Run with Cloud SQL's pgvector for vector storage and Vertex Endpoints to create generative AI applications.

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