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Should governance be centralized or decentralized? The truth is — you need both. In this episode, we discuss how to find the right balance for your organization, empowering teams while maintaining consistency, interoperability, and control. You’ll also learn how to avoid over-centralization bottlenecks and redundant systems that often come from over-decentralization. Learn more about Amazon SageMaker Catalog - http://go.aws/47TFHgN Subscribe to AWS: https://go.

This session demonstrates building Generative AI agents that operate fully offline using the AWS Strands Agents SDK. The presentation covers deploying lightweight local models with Ollama and integrating custom tools for remote manufacturing, field operations, and data sovereignty scenarios. Explore how these edge-deployed agents seamlessly scale to leverage cloud capabilities, transitioning to powerful models like Claude on Amazon Bedrock when connectivity is available.

詳細について、動画の関連ナレッジセンター記事をご参照ください：https://repost.aws/ja/knowledge-center/rds-mysql-max-connections Kito さんは、Amazon RDS for MySQL インスタンスの最大接続数パラメータを、確認および設定する方法をご紹介します。 早速始めましょう。 The AWS Knowledge Center contains trusted, expert-reviewed answers to frequently asked questions across AWS services — including EC2, S3, IAM, Lambda, Bedrock, and more. Subscribe to AWS: https://go.aws/subscribe Sign up for AWS: https://go.aws/signup AWS free tier: https://go.aws/free Explore more: https://go.

Pharmaceutical companies are under pressure to move from data overload to trusted, actionable insights. This session explores how Agentic AI is transforming pharma data and analytics — tackling structured data challenges, integrating technologies end to end, and reimagining how insights flow across the enterprise. Learn how combining AI for data and data for AI enables governed analytics at scale, unlocks hidden value, and delivers efficiency and trust.

Amazon file storage services continue to deliver innovations to help enterprise customers and storage admins manage their file data more effectively. Dive into the latest capabilities designed to enhance file data accessibility and integration with modern cloud applications. Discover how shared file storage from Amazon EFS and Amazon FSx is evolving to meet the needs of compute-intensive and data-heavy workloads.

VideoCX.io is an enterprise-grade platform that helps financial institutions digitize customer interactions, from onboarding and KYC verification to branch and at-home banking services. In this video, Rudrajeet Desai, Founder, CEO, and Product Head of VideoCX.io, shares how the company uses AWS to deliver scalable, multilingual banking experiences across geographies.

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For more details on this topic, visit the AWS Knowledge Center on AWS re:Post and read the full article associated with this video: [https://repost.aws/knowledge-center/aurora-postgresql-max-connections] The AWS Knowledge Center contains trusted, expert-reviewed answers to frequently asked questions across AWS services — including EC2, S3, IAM, Lambda, Bedrock, and more. Ankita shows you how to increase maximum connections for an Aurora DB instance.

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​Agentic applications interpret inputs and take actions within a customer’s enterprise environment, and model customization enables agents that understand the business and provides responses or actions that are appropriate for the use case. In this session, we will cover recent advancements like Nova customization on SageMaker AI and on-demand inferences on custom models, which lower the cost and effort needed for model customization.

Enterprise applications are evolving beyond simple chat assistants to intelligent agentic systems that can reason, plan, and execute complex workflows. In this session, you'll learn about the core model capabilities needed to build production-ready agents. We'll cover specialized use cases, including browser-forward agents and multi-agent systems, sharing frameworks for model selection and how to apply them to your use case.

Learn how to scale generative AI experiments into production-ready solutions. This session provides a strategic and technical framework for accelerating AI deployment while managing risks and maintaining governance. We'll cover practical approaches to align AI initiatives with business goals, establish evaluation criteria, and build effective teams. Through real-world examples, discover proven methods for fast-tracking implementation while ensuring security and quality.