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Today at the AWS Summit in New York City, Swami Sivasubramanian, AWS VP of Agentic AI, provided the day’s keynote on how we’re enabling customers to deliver production-ready AI agents at scale. Here’s our roundup of the biggest announcements from the event:
Introducing Amazon Bedrock AgentCore: Securely deploy and operate AI agents at any scale (preview)
Amazon Bedrock AgentCore enables rapid deployment and scaling of AI agents with enterprise-grade security. It provides memory management, identity controls, and tool integration—streamlining development while working with any open-source framework and foundation model.
Announcing Amazon Nova customization in Amazon SageMaker AI
AWS now enables extensive customization of Amazon Nova foundation models through SageMaker AI across all stages of model training. Available as ready-to-use SageMaker recipes, these capabilities allow customers to adapt Nova understanding models across pre-training and post-training, including fine-tuning and alignment recipes to better address business-specific requirements across industries.
AWS Free Tier update: New customers can get started and explore AWS with up to $200 in credits
AWS is enhancing its Free Tier program with up to $200 in credits for new users: $100 upon sign-up and an additional $100 earned by completing activities with services like Amazon EC2, Amazon Bedrock, and AWS Budgets.
TwelveLabs video understanding models are now available in Amazon Bedrock
TwelveLabs video understanding models are now available on Amazon Bedrock and enable customers to search through videos, classify scenes, summarize content, and extract insights with precision and reliability.
Amazon S3 Metadata now supports metadata for all your S3 objects
Amazon S3 Metadata now provides comprehensive visibility into all objects in S3 buckets through live inventory and journal tables, enabling SQL-based analysis of both existing and new objects with automatic updates within an hour of changes.
Introducing Amazon S3 Vectors: First cloud storage with native vector support at scale (preview)
Amazon S3 Vectors is a new cloud object store that provides native support for storing and querying vectors at massive scale, offering up to 90% cost reduction compared to conventional approaches while seamlessly integrating with Amazon Bedrock Knowledge Bases, SageMaker, and OpenSearch for AI applications.
Streamline the path from data to insights with new Amazon SageMaker capabilities
Amazon SageMaker has introduced three new capabilities—Amazon QuickSight integration for dashboard creation, governance, and sharing, Amazon S3 Unstructured Data Integration for cataloging documents and media files, and automatic data onboarding from Lakehouse—that eliminate data silos by unifying structured and unstructured data management, visualization, and governance in a single experience.
Monitor and debug event-driven applications with new Amazon EventBridge logging
Amazon EventBridge now offers enhanced logging capabilities that provide comprehensive event lifecycle tracking, helping users monitor and troubleshoot their event-driven applications with detailed logs that show when events are published, matched against rules, delivered to subscribers, or encounter failures.
Amazon EKS enables ultra scale AI/ML workloads with support for 100K nodes per cluster
Amazon EKS now scales to 100,000 nodes per cluster, enabling massive AI/ML workloads with up to 1.6M AWS Trainium accelerators or 800K NVIDIA GPUs. This allows organizations to efficiently train and run large AI models while maintaining Kubernetes compatibility and existing tooling integration.
