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Cloud Run

Google Cloud Run

serverless containers google_cloud

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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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

session
by Jeenal Shah (Google Cloud) , Jordan DeBeer (Google Cloud) , Todd Hall (Ford Motor Company) , James Ma (Google Cloud)

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.”

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

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.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

Do you want to know your options for running Java on Google Cloud? We’ll explore various options for running workloads written using the latest Java and Jakarta EE versions on serverless offerings like Google App Engine and Google Cloud Run. Furthermore, we'll look at optimizing your run time performance using various frameworks.

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We'll explore how integrating AI, serverless computing, data analytics, and APIs can revolutionize the retail landscape. Learn how Google Cloud Run, Apigee, BigQuery, and Vertex AI collaborate to create personalized shopping experiences, streamline operations, and drive sustainability. Key takeaways include implementing conversational AI for enhanced customer interaction, leveraging BigQuery for data-driven insights, and using Cloud Run for efficient, scalable retail solutions.

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U.S. floods cause ~$3B in damage annually. The National Oceanic and Atmospheric Administration predicts changing water levels, giving scientists and managers time to act. However, the massive archive of forecasts is too complex for typical users. Learn how BYU and U of Alabama, with SADA and Google, are using BigQuery, Cloud Run, DataFlow, and API Gateway to make these forecasts accessible for mobile apps, flood-warning systems, and more, addressing crucial concerns like rising river levels or the likelihood of flooding.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.