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Network Flow Monitor provides near real-time visibility into network performance, such as packet loss and latency, for traffic between Amazon EC2 instances, as well as traffic toward other AWS services, such as Amazon S3 and Amazon DynamoDB, or to the edge of another AWS Region. Network Flow Monitor receives data from lightweight software agents that you install on your instances. The agents gather performance statistics from TCP connections.

Start your Cloud Practitioner learning journey in AWS Cloud Quest: https://skillbuilder.aws/learn/FU5WCYVGKY/aws-cloud-quest-cloud-practitioner/JF9TKU68GT The next generation of cloud builders needs to know how to design, not just how to build. AWS Cloud Quest is a role-based learning experience on AWS Skill Builder where you explore customer needs, clarify requirements in AI-powered conversations, choose an AWS solution, and build and validate it in a live AWS environment.

Enterprises are exploring ways to scale their AI agent implementations beyond initial use cases. Learn how Prudential Financial is moving beyond single-purpose deployments with a scalable, microagent architecture powered by Amazon Bedrock and MCP agent-to-agent (A2A) communication.

From sunrise alerts to sunset cost reports, the AWS WAF administrator’s day is never dull. Join us as we follow a fictional (but all-too-relatable) admin navigating setup, fine-tuning rules, building dashboards, and taming budgets - while outsmarting emerging threats before they bite. You’ll see how to adapt quickly to shifting traffic, uncover hidden risks, and make data-driven decisions without breaking the bank - or the application.

Building on our advancements unveiled at the New York Summit, this session explores the evolution of Nova Agents beyond conventional web browsing, human-in-the-loop (HITL) oversight, and standard tool use. We will dive into hybrid approaches, innovative LLM-tool interactions, and API-driven strategies that boost efficiency, reliability, and autonomy in agentic AI systems.

Are you looking to take your AWS cost management to the next level? In this live coding session, discover how to leverage AWS Cost and Usage Reports (CUR) alongside Amazon Q to streamline query development and automate code generation for detailed cost allocation. Learn best practices for breaking down costs, access control of your data access and optimization discoveries.

Ross Richards, Senior Product Marketing Manager at AWS, used to be the bottleneck. Now, with Amazon Quick, he's the enabler — helping anyone across the company create confident, on-message content in minutes. Learn more: https://go.aws/4lborsp Ross leads AI category messaging for AWS — a small team supporting thousands of marketers, sellers, and stakeholders across the company. Before Quick, keeping up meant endless meetings and manual reviews. Quick changed that.

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/organizations-scp-tag-policies The AWS Knowledge Center contains trusted, expert-reviewed answers to frequently asked questions across AWS services — including EC2, S3, IAM, Lambda, Bedrock, and more.

Amazon Web Services (AWS) delivers the most secure, reliable, and extensive global cloud infrastructure so that customers can build, run, and scale their applications with confidence. Learn about the comprehensive AWS Global Infrastructure offerings that enable you to run your applications wherever you need. Learn more about AWS Global Infrastructure: http://go.aws/47p29wU Subscribe to AWS: https://go.aws/subscribe Create a free AWS account: https://go.

AI coding agents are transforming how developers build and operate modern cloud-native applications. With tools such as Kiro CLI, Kiro IDE, or any MCP-compatible AI coding assistant, developers are embracing AI to move faster and scale smarter. This session explores how Model Context Protocol (MCP) servers for AWS services like ECS and EKS provide real-time, contextual code assistance to AI-powered coding agents.

AI is creating new opportunities, and organizations need speed-to-market, scalability, performance, and cost efficiency to bring ideas to life. Amazon EKS provides the trusted and flexible foundation for your AI journey as you build new experiences using AI inference, agents, and model fine-tuning.

Learn how Amazon SageMaker AI transforms model development with a unified environment for all your AI workloads - from interactive model development on IDEs to maximizing task and compute resource utilization across training and inference workloads. We'll demonstrate how to use SageMaker Studio as the familiar IDE to develop, submit, and monitor ML jobs, while leveraging the scalability and resiliency of HyperPod environment for computationally intensive tasks like training and deploying large...