Firestore with MongoDB compatibility is a serverless database service  designed to maximize scalability, high availability and performance without the hidden costs of capacity planning. This session demonstrates the new Firestore with MongoDB compatibility capabilities and discusses how Dialpad has built an Ai-powered customer communications platform leveraging Firestore over the last 14 years to grow a successful, performant, reliable business.

In this session, you’ll learn how to build an AI agent using MongoDB Atlas on Google Cloud in just 15 minutes. We’ll cover how to embed and store your data along with vectors in a single database; build a vector search index and run search queries; and implement an AI agent.

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.

Discover how some of the world’s most innovative companies modernized and transformed their applications with the power of Firestore, Firebase, and cutting-edge generative AI. Learn how they leveraged the latest technologies, such as edge computing and AI, to enhance customer experiences at every stage of the customer journey. Explore their innovative architecture and gain insights into building modern, engaging applications that deliver exceptional customer experiences.

This session explores the evolution of data management on Kubernetes for AI and machine learning (ML) workloads and modern databases, including Google’s leadership in this space. We’ll discuss key challenges and solutions, including persistent storage with solutions like checkpointing and Cloud Storage FUSE, and accelerating data access with caching. Customers Qdrant and Codeway will share how they’ve successfully leveraged these technologies to improve their AI, ML, and database performance on Google Kubernetes Engine (GKE).

Experience the power of AlloyDB Omni, a cutting-edge PostgreSQL-compatible database designed for multicloud and hybrid cloud environments. This session explores how AlloyDB Omni accelerates the development of modern applications, enabling generative AI experiences, efficient vector search, real-time operational analytics, and scalable transactional performance. We’ll also showcase how to run your applications on multiple clouds using Aiven’s seamless managed service, and how to supercharge hybrid cloud deployments with cloud-ready partners.

Explore the latest advancements in the open source software (OSS) world of in-memory data management and the launch of Memorystore for Valkey. Discover the exciting new features and enhancements in Valkey 8.0, including a preview of upcoming open source innovations on the roadmap. Join us for a deep dive with a customer who will share their real-world experience using Valkey within their architecture. Learn how they leverage the power of in-memory data to achieve exceptional performance and scalability.

This session explores building sensitive data protection directly into Retrieval-Augmented Generation (RAG) architectures. We'll demonstrate how to leverage Cloud Data Loss Prevention (Cloud DLP) and the Faker Library to anonymize sensitive data within the RAG pipeline. The session will cover techniques for reversible transformations using Memorystore and Firestore for data mapping, and discuss integrating these methods with Large Language Models (LLMs) like Gemini via LangChain and Vertex AI Search. Learn how to create secure and compliant AI solutions that protect sensitive data and adhere to regulations like the EU AI Act.

This session dives into building a modern data platform on Google Cloud with AI-powered data management. Explore how to leverage data mesh architectures to break down data silos and enable efficient data sharing. Learn how data contracts improve reliability, and discover how real-time ingestion empowers immediate insights. We'll also examine the role of data agents in automating data discovery, preparation, and delivery for optimized AI workflows.

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.

Analyze BigQuery logs with SQL using Log Analytics. This hands-on lab covers enabling Log Analytics, querying BigQuery logs within Cloud Logging, and visualizing results for in-depth usage analysis and troubleshooting.

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!

Time to make generative AI a reality for your application. This session is all about how to build high-performance gen AI applications fast with Cloud SQL for MySQL and PostgreSQL. Learn about Google Cloud’s innovative full-stack solutions that make gen AI app development, deployment, and operations simple and easy – even when deploying high-performance, production-grade applications. We’ll highlight best practices for getting started with Vertex AI, Cloud Run, Google Kubernetes Engine, and Cloud SQL, so that you can focus on gen AI application development from the get-go.

Migrations can feel daunting, especially for small teams. This session offers practical tips, tools, and strategies to plan and execute migrations efficiently, minimizing downtime and maximizing your existing resources. You’ll view a live demo of Google’s migration tools and learn from TRIARQ Health about how they successfully navigated their own migration to Google Cloud.

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.

Embark on a journey to enhance your Oracle applications by migrating and modernizing them on Google Cloud. This session delves into real-world customer success stories and showcases the latest advancements. Discover best practices for seamless migrations and explore how Google Cloud optimizes performance and scalability for your Oracle applications. Uncover valuable insights from your Oracle databases and app-powered integrations with Google advanced AI, analytics, and monitoring tools.

Unlock the full potential of your mission-critical workloads on Google Cloud. Discover how our platform is purpose-built for Microsoft, Oracle, OpenShift, and more, enabling you to optimize total cost of ownership (TCO) and accelerate modernization. Learn firsthand from customers who have successfully transformed their businesses by bringing their workloads to Google Cloud.

The next generation of intelligent business applications is here and powered by generative AI. In this session, you will learn about Spanner's latest graph capabilities and how GraphRAG can help you deliver richer contextual generative AI applications. Discover how to leverage a consolidated data platform to create smarter, more intuitive applications and drive business innovation.

You name it, we’ll build it. If a demo feels too polished without enough opportunities for things to go wrong, then let’s throw out the script and do it live. We’ll pick a JavaScript framework and a database, and then build a full-stack application from scratch. If you’re a full-stack application developer or a frontend or backend developer wondering how everything ties together in a modern application, this will be an exciting ride worth joining – no Google Cloud experience required.

Build resilient, scalable applications that thrive in the face of increasing demands. Cloud SQL offers new features designed to optimize performance, availability, and cost efficiency for MySQL and PostgreSQL databases, managed replica pools, and connection pooling. Learn how to make downtime a thing of the past, implement advanced disaster recovery strategies, and maximize your application’s performance. Join our demo-packed session for a deep dive into these new Cloud SQL capabilities and best practices.

This session offers a technical deep dive of the state-of-art AlloyDB AI capabilities for building highly accurate and relevant generative AI applications using real-time data. We’ll cover vector search using Google Research’s ScaNN index technology and cover how you can utilize Gemini from AlloyDB operators to seamlessly integrate into your application. Discover AlloyDB AI natural language feature, a new way to interact with databases and how it accurately and securely answers your questions. Also learn about the latest research between Google and NVIDIA on GPU-accelerated vector index builds in databases.

Visionaries from Virgin Media O2, TCS and Google Cloud share insights on their data modernization journey. Explore how a cloud-first data strategy enabled Virgin Media O2 to reimagine their business by enhancing agility, speed and scalability, automating operations, optimizing costs, and driving AI-readiness.

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.

AI applications that use the retrieval augmented generation (RAG) architecture can be a lot more accurate than those built with just the AI model’s built-in knowledge. But RAG introduces additional processing steps which need to be monitored. We’ll show you how.

Unlock the power of lightning-fast vector search for your generative AI applications. This session dives deep into Memorystore vector search, demonstrating how to achieve single-digit millisecond latency on over a billion vectors. Explore cutting-edge gen AI application architectures that leverage vector search and other Google Cloud services to deliver exceptional user experiences.

Learn how Database Migration Service can help you modernize your SQL Server databases to unleash the power of cloud databases and open source PostgreSQL! Convert your SQL Server schema and T-SQL code to PostgreSQL dialect with a click of a button in the DMS Conversion Workspace. Some objects could not be fully converted? Gemini can suggest a fix. Not yet familiar with PostgreSQL features? Ask Gemini to teach you how to convert SQL Server features to PostgreSQL equivalent ones. While Gemini is there - ask it to optimize the converted code or add some comments to explain the business logic. Once your database is fully converted and optimized you can migrate the data with minimal downtime using the change data capture powered migration job and complete your migration journey.

AI is revolutionizing observability. Learn about Cloud SQL AI-powered Database Insights and how it can help you optimize your queries and boost database performance. We’ll dive deep into the new Insights capabilities for MySQL, PostgreSQL, and SQL Server, including the Gemini-powered chat agent. Learn how to troubleshoot those tricky database performance issues and get practical tips to improve the performance of your applications.

Generative AI agents have emerged as the leading architecture for implementing complex application functionality. Tools are the way that agents access the data and systems they need. But building and deploying tools at scale brings new challenges. Learn how MCP Toolbox for Databases, an open source server for gen AI tool management, enables platforms like LangGraph and Vertex AI to easily connect to enterprise databases.

This talk demonstrates a fashion app that leverages the power of AlloyDB, Google Cloud’s fully managed PostgreSQL-compatible database, to provide users with intelligent recommendations for matching outfits. User-uploaded data of their clothes triggers a styling insight on how to pair the outfit with matching real-time fashion advice. This is enabled through an intuitive contextual search (vector search) powered by AlloyDB and Google’s ScaNN index to deliver faster vector search results, low-latency querying, and response times. While we’re at it, we’ll showcase the power of the AlloyDB columnar engine on joins required by the application to generate style recommendations. To complete the experience, we’ll engage the Vertex AI Gemini API package from Spring and LangChain4j integrations for generative recommendations and a visual representation of the personalized style. This entire application is built on a Java Spring Boot framework and deployed serverlessly on Cloud Run, ensuring scalability and cost efficiency. This talk explores how these technologies work together to create a dynamic and engaging fashion experience.