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DAIVI is a reference solution with Terraform modules to accelerate development of Data, Analytics, AI and Visualization applications on AWS using the next generation "Amazon SageMaker" platform. The goal of the DAIVI solution is to provide engineers with sample Terraform modules to build their enterprise data platform on AWS. The solution is being developed working backward from customer priorities. The solution currently supports the following modules. 1.

Roll up your sleeves for this hands-on coding session where we'll build modern security analytics tools on top of Amazon Security Lake. Through interactive demos, we'll craft queries and visualizations to operationalize your security data using AWS services like Amazon OpenSearch Service, Amazon QuickSight, Amazon Athena, and Amazon Bedrock. Leave with practical code samples and architectures to analyze security data.

A leader in AI for cybersecurity, Darktrace detects subtle anomalous activity by learning about each customer to understand what’s normal for their unique business. On a mission to rapidly expand their presence in the United States, Darktrace sought strategic support and resources through the AWS Global Passport program. Having successfully built brand recognition in new markets and verticals, Darktrace is proving that it’s possible to offer unique security deployments at a vast scale.

Data product development is a complex multi team effort that often span several years even developing a minimum Bible product to prove business value often requires multiple quarters in this video. We will show you how to use strand agents to support with this process. Learn more at - http://go.aws/4otD3Vh 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.aws/more Contact AWS: https://go.

As cloud applications grow in complexity, optimizing costs becomes crucial for developers. This session explores AWS-native tools and coding practices that reduce expenses without compromising performance or scalability. Learn to identify resource inefficiencies using AI-powered recommendations and cost analysis tools. Discover how to implement cost-aware architectures across compute, serverless, and observability services.

Join Raf, Oksana, and Alex for "Your Guide to the AWS Agentic AI Microcredential," a 4-episode live streaming series designed to prepare you for the AWS Agentic AI Microcredential exam. This hands-on series goes beyond traditional multiple-choice testing by focusing on practical, real-world skills that demonstrate true mastery.

Consumer expectations are rapidly evolving, requiring brands and retailers to develop and launch innovative, new products quickly. In this session, you’ll learn how to use artificial intelligence (AI) to accelerate prototype development, create compelling content, and rapidly scale product launches, significantly reducing time-to-market and costs.

OBSESS OVER YOUR AI AGENTS LIKE YOUR CUSTOMERS. Built a distributed AI system? Here's how to ACTUALLY know if it's working. This demo shows real multi-agent observability using AWS Timestream + Grafana - because flying blind is NOT an option. What you'll see: - Live agent performance metrics - Token efficiency tracking - Real-time collaboration monitoring - Root cause analysis tools No more "hope and pray" deployments.

AWS Managed Microsoft AD (Hybrid Edition) allows you to extend your existing Active Directory to the AWS Cloud with AWS Managed Microsoft AD. This feature makes it easier to move your AD–dependent workloads to AWS, adopt AWS services, and increase your Active Directory redundancy. AWS will periodically run directory assessments on your hybrid directory which you can view in the Directory Service console. Learn more about AWS Managed Microsoft AD: https://go.

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

In this session, learn how AWS zero-ETL integrations remove the need to manage complex data movement pipelines across multiple source database engines and targets so data engineers, architects, & DBAs can eliminate maintenance overhead while ensuring near real-time data availability for analytics & ML workloads.

Learn how to build enterprise-grade generative AI security tools that unify security data and enable natural language investigations. This session demonstrates practical approaches for developing secure generative AI solutions, including implementation patterns for data privacy and compliance controls. Explore real-world architectures combining AWS foundation models with security orchestration. Hear how Trellix achieved 23x cost savings while maintaining 95% accuracy using Amazon Bedrock models.