AWS Atlas

As organizations scale AI agent development, robust enterprise architecture patterns become essential. In this advanced session, we'll explore how Amazon Bedrock AgentCore enables teams to build modular systems using their preferred frameworks while sharing tools through MCP gateways. Learn about A2A collaboration, shared memory, identity-based access controls, and integrated observability.

In this session, you will learn how Formula 1 is revving up fan experiences with cloud and generative AI technology. Discover how Formula 1 is revolutionizing motorsport entertainment through cutting-edge cloud and AI technology. Learn how real-time data analytics and generative AI are transforming race broadcasts and fan engagement, and how AWS Media Services is powering 1 TV Premium, F1's new streaming service that launched in 2025.

With an innovative architecture that decouples compute from storage and advanced features like Amazon Aurora Global Database and low-latency read replicas, Aurora reimagines what it means to be a relational database. Aurora is a built-for-the-cloud, serverless relational database service that delivers unparalleled performance and availability at global scale for MySQL, PostgreSQL, and DSQL.

In this session, explore Amazon Aurora and Amazon RDS cost components and learn important best practices that can help you improve the performance of your relational database workloads while reducing spend on cost components such as compute, storage, backup, and I/O.

Amazon Quick Suite is an agentic teammate for business users that quickly answers their questions at work and turns those insights into actions. Join this session to hear compelling customer stories and discover how organizations are transforming workplace productivity with AI agents for automation, research, and business intelligence in a unified experience.

Learn how organizations are modernizing their data architectures using the next generation of Amazon SageMaker to create AI-ready data platforms. This session covers how to design and build modern data architectures that enable both innovation and control, examining real-world patterns for data lake consolidation, cross-account governance, and AI integration.

The introduction of Amazon Bedrock AgentCore equips builders with a range of new tools and technologies. These tools enable a range of new strategies and techniques that will directly impact how teams build multi-tenant AI solutions and agents. This session will dig into working examples how tenancy is leveraged and landed in an intelligence-as-a-service environment, highlighting the multi-tenant nuances and possibilities that can built with the latest AI-powered AWS services.

Organizations running critical analytics on Apache Iceberg need multi-Region replication for compliance, business continuity, and global data sharing. However, replicating Iceberg tables requires maintaining snapshot chronology, rewriting metadata files, and coordinating multiple catalogs—complexity that goes far beyond simple object replication.

We will recap all re:Invent 2024 networking and content delivery launches, from IPv6 and VPC IPAM features, to VPC Lattice support for TCP Resources, cross-Region support for AWS PrivateLink endpoints, and Amazon CloudFront support for anycast IPs and private VPC Origins.

Design software pioneer Autodesk is transforming computer-aided design (CAD) by harnessing generative AI and Amazon Web Services (AWS). The company is developing advanced AI foundation models, like "Project Bernini," which can generate precise 2D and 3D geometric designs based on physical principles. By utilizing AWS technologies such as Amazon DynamoDB, Elastic MapReduce (EMR), Amazon SageMaker, and Elastic Fabric Adapter, Autodesk has significantly enhanced its AI development process.

Go behind the scenes of Amazon S3 performance architecture while learning practical optimization strategies. We'll explore how S3's internal systems manage massive throughput, handle concurrent requests, and balance loads across its distributed infrastructure. Dive deep into the technical foundations - from request routing and partitioning strategies to caching mechanisms - that enable S3 to power demanding workloads like real-time analytics and ML training.

Learn how AWS networking services are transforming AI/ML application performance. This session demonstrates approaches using AWS Network Load Balancer for ultra-low latency search and real-time AI/ML inference, plus Amazon API Gateway optimizations for low-concurrency LLM workloads. Through real-world case studies and production deployments, you'll discover practical techniques for minimizing network latency in AI/ML pipelines and architecture patterns for high-performance inference serving.