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Discover how to enhance SAP workload resilience through AWS Support's comprehensive programs, featuring real-world implementation of AWS Resilience Hub, Fault Injection Simulator, and CloudWatch insights.
Discover how to integrate DevOps practices into ML workflows, focusing on automated building, training, and deployment of models while improving collaboration between data teams on AWS.
Explore multi-agent orchestration techniques using Tailwinds and Amazon Bedrock, focusing on practical GenAI use cases, workflow implementation, and prompt engineering best practices.
Discover how to build reliable global networks using Direct Connect SiteLink, featuring traffic engineering, routing configurations, and network segmentation for connecting offices and data centers worldwide.
Discover how SageMaker HyperPod's governance features optimize GPU resource allocation for AI model development, ensuring efficient task prioritization and cost management.
Discover how to rapidly build a language learning application using Amazon Q Developer, with step-by-step guidance on leveraging AI assistance in your IDE.
Discover how to accelerate ML and generative AI model development using SageMaker partner AI apps, featuring specialized applications that integrate seamlessly while maintaining security and privacy.
Discover how Amazon GuardDuty's Extended Threat Detection leverages AI/ML to identify and combat sophisticated multi-stage cloud attacks, enhancing your organization's security posture and response capabilities.
Discover how Amazon S3 Tables streamlines large-scale tabular data management, offering automated optimization, enhanced security controls, and improved performance for analytics and ML workloads.
Discover how Amazon SageMaker Lakehouse unifies data across S3 lakes and Redshift warehouses, enabling seamless querying with Apache Iceberg tools while maintaining robust security controls.
Discover Amazon's proven strategies and real-world insights for scaling generative AI applications, featuring a demo of their ad photo generator and practical lessons from successful enterprise deployments.
Master container-level metrics and enhanced observability in Amazon ECS to quickly identify anomalies, troubleshoot issues, and improve performance across clusters, services, tasks, and individual containers.
Discover how to safeguard sensitive data using Amazon Macie and S3 Object Lambda, featuring automated detection, access control implementation, and real-time data processing for enhanced cloud security.
Discover how Amazon Q's transformation capabilities streamline the modernization of .NET Framework applications from Windows to Linux, featuring hands-on demonstrations in web and IDE environments.
Discover how AWS Trainium2 and EC2 Trn2 instances accelerate generative AI model training, enabling faster iteration and real-time AI experiences with enhanced performance for billion-parameter models.
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