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.

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.

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.

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.

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.

Simulate the carbon footprint of your VMs, GKE Autopilot clusters and Cloud Run services. Learn how to improve your contribution to environment.

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.

Are you sold on dbt, but unsure as to how you’ll handle deployment, orchestration and job scheduling? Are you evaluating dbt and looking for an easy way to spin up a proof of concept while seeking buy in from stakeholders? Look no further! In this workshop we will show you how to containerize your dbt project and execute jobs using GCP’s serverless computing products Cloud Run, Build and Scheduler. If you have an interest in dbt orchestration, devops, or serverless cloud architecture, this workshop is for you!

Check the slides here: https://docs.google.com/presentation/d/1NiG0MFkOvw5MNpCZFF74VDuX-jHZpO4a8bHUadukoPI/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines

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!

Join us to discuss serverless computing and event-driven architectures with Cloud Run functions. Learn a quick and secure way to connect services and build event-driven architectures with multiple trigger types (HTTP, Pub/Sub, and Eventarc). And get introduced to Eventarc Advanced, centralized access control to your events with support for cross-project delivery.

Simplify AI inference using Cloud Run with GPUs and Google Axion Processors. Experience fast instance starts, rapid autoscaling, and scaling to zero with Cloud Run and optimize cost efficiency with Axion.

Continuously deploy Angular and Next.js web apps to Google Cloud from a connected GitHub repository on each commit. Firebase App Hosting detects your framework, builds your app in Cloud Build, and deploys to Cloud Run behind Cloud CDN.

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.