Kategorie: Amazon AWS

AWS Transform launches an AI agent for full-stack Windows modernization

AWS Transform is expanding its capability from the .NET modernization agent to now include the full-stack Windows modernization agent that handles both .NET applications and their associated databases. The new agent automates the transformation of .NET applications and Microsoft SQL Server databases to Amazon Aurora PostgreSQL and deploys them to containers on Amazon ECS or Amazon EC2 Linux. AWS Transform accelerates full-stack Windows modernization by 5x across application and database layers, while reducing operating costs by up to 70%. With AWS Transform, customers can accelerate their full-stack modernization journey through automated discovery, transformation, and deployment. The full-stack Windows modernization agent scans Microsoft SQL Server databases in Amazon EC2 or Amazon RDS instances, and it scans .NET application code from source repositories (GitHub, GitLab, Bitbucket, or Azure Repos) to create customized, editable modernization plans. It automatically transforms SQL Server schemas to Aurora PostgreSQL and migrates databases to new or existing Aurora PostgreSQL target clusters. For .NET application transformation, the agent updates database connections in the source code and modifies database access code written in Entity Framework and ADO.NET to be compatible with Aurora PostgreSQL—all in a unified workflow with human supervision. All the transformed code is committed to a new repository branch. Finally, the transformed application along with the databases can be deployed into a new or existing environment to validate the transformed applications and databases. Customers can monitor transformation progress through worklog updates and interactive chat, and they can use the detailed transformation summaries for next steps recommendations and for easy handoff to AI code companions. AWS Transform for full-stack Windows modernization is available in the US East (N. Virginia) AWS Region. To learn more, visit the overview page and AWS Transform documentation.
Quelle: aws.amazon.com

Amazon Connect now streams messages for AI-powered interactions

Amazon Connect now supports message streaming for AI-powered chat interactions. This new capability shows Connect AI agent responses as they’re being generated, which reduces perceived wait times and improves the customer experience. When using Amazon Connect AI agents, customers see status updates like “One moment while I review your account” during processing, and watch responses appear progressively. This experience gives customers confidence their request is actively being worked on while AI agents reason, invoke tools, and craft comprehensive solutions. Message streaming for AI-powered interactions is now available in the following regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (London) and Africa (Cape Town). To learn more, visit the Amazon Connect documentation.
Quelle: aws.amazon.com

Amazon Connect now simplifies linking related contacts to cases using flows

Amazon Connect now makes it easier to link related contacts such as email replies, call transfers, persistent chats, and queued callbacks to the same case so agents can view the complete customer journey and resolve issues faster. You can use flows to link a follow-up contact to an existing case, eliminating the need for custom logic or manual linking. Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.
Quelle: aws.amazon.com

Amazon Connect launches AI-powered predictive insights (Preview)

Today, Amazon Connect is launching AI-powered predictive insights that transform how businesses understand and serve their customers. This new feature set builds upon Connect’s existing customer profiles, introducing five recommendation algorithms that leverage AI to analyze customer behavior patterns and interaction history. These AI-powered insights are available for both self-service and agent interactions, enabling businesses to transform all customer touchpoints – from suggesting complementary products during service calls to providing smart product discovery through intelligent chat experiences by leveraging their existing customer data within Connect Customer Profiles. Businesses can also leverage these AI-powered insights to build their Connect AI agent for specialized for sales. The five recommendation algorithms are as follows: “Recommended for You” provides tailored suggestions based on individual user interactions patterns with any catalog; “Similar Items” uses generative AI to suggest alternative products or services; “Frequently Paired Items” powers cross-selling by identifying complementary product or service combinations, “Popular Items” surfaces top-performing product recommendations, and “Trending Now” captures real-time customer interest for timely engagement. With Amazon Connect Customer Profiles, you only pay-as-you-go for utilized profiles. Public preview for AI-powered predictive insights is available in Europe (Frankfurt), US East (N. Virginia), Asia Pacific (Seoul), Asia Pacific (Tokyo), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central). To learn more, visit our webpages for Customer Profiles.
Quelle: aws.amazon.com

Amazon Connect now provides AI-powered case summaries

Amazon Connect now provides AI-powered case summaries for complete context into customer issues, reduce manual wrap-up work, and help resolve cases faster. With a single click, agents can generate a concise case summary even when the case spans multiple interactions, follow-up tasks, and teams, capturing key details such as issue background, actions taken, and next steps. Administrators can configure custom prompts and guardrails to ensure that summaries align with organizational style and preferences. Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.
Quelle: aws.amazon.com

Amazon Connect introduces new criteria to automatically select relevant contacts for performance evaluation

Amazon Connect provides managers with new criteria while setting up automated evaluations, making it easier to identify relevant contacts for evaluation, and providing additional insights to automatically populate evaluation forms. For example, managers can specify that inbound contacts with no connectivity issues, handled by agents in a specific department, should be automatically evaluated using a particular evaluation form. Additionally, managers can use new metrics criteria on agent call avoidance, contact handling efficiency, and audibility, to automatically fill the selected form. This feature is available in all regions where Amazon Connect is offered. To learn more, please visit our documentation and our webpage. 
Quelle: aws.amazon.com

Amazon SageMaker HyperPod now supports programmatic node reboot and replacement

Today, Amazon SageMaker HyperPod announces the general availability of new APIs that enable programmatic rebooting and replacement of SageMaker HyperPod cluster nodes. SageMaker HyperPod helps you provision resilient clusters for running machine learning (ML) workloads and developing state-of-the-art models such as large language models (LLMs), diffusion models, and foundation models (FMs). The new BatchRebootClusterNodes and BatchReplaceClusterNodes APIs enable customers to programmatically reboot or replace unresponsive or degraded cluster nodes, providing a consistent, orchestrator agnostic approach to node recovery operations. The new APIs enhance node management capabilities for both Slurm and EKS orchestrated clusters complementing existing node reboot and replacement workflows. Existing orchestrator-specific methods, such as Kubernetes labels for EKS clusters and Slurm commands for Slurm clusters, remain available alongside the newly introduced programmatic capabilities for reboot and replace operations through these purpose-built APIs. When cluster nodes become unresponsive due to issues such as memory overruns or hardware degradation, recovery operations such as node reboots and replacements maybe be necessary and can be initiated through these new APIs. These capabilities are particularly valuable when running time-sensitive workloads. For instance, when a Slurm controller, login or compute node becomes unresponsive, administrators can trigger a reboot operation using the API and monitor its progress to get nodes back to operational status. Similarly, EKS cluster administrators can replace degraded worker nodes programmatically. Each API supports batch operations of up to 25 instances, enabling efficient management of large-scale recovery scenarios. The reboot and replace APIs are currently supported in three AWS regions where SageMaker HyperPod is available: US East (Ohio), Asia Pacific (Mumbai), and Asia Pacific (Tokyo).The APIs can be accessed through the AWS CLI, SDK, or API calls. For more information, see the Amazon SageMaker HyperPod documentation for BatchRebootClusterNodes and BatchReplaceClusterNodes.
Quelle: aws.amazon.com

The AWS API MCP Server is now available on AWS Marketplace

AWS announces the availability of the AWS API MCP Server on AWS Marketplace, enabling customers to deploy the Model Context Protocol (MCP) server to Amazon Bedrock AgentCore. The marketplace entry includes step-by-step configuration and deployment instructions for deploying the AWS API MCP Server as a managed service with built-in authentication and session isolation to Bedrock Agent Core Runtime. The AWS Marketplace deployment simplifies container management while providing enterprise-grade security, scalability, and session isolation through Amazon Bedrock AgentCore Runtime. Customers can deploy the AWS API MCP Server with configurable authentication methods (SigV4 or JWT), implement least-privilege IAM policies, and leverage AgentCore’s built-in logging and monitoring capabilities. The deployment lets customers configure IAM roles, authentication methods, and network settings according to their security requirements. The AWS API MCP Server can now be deployed from AWS Marketplace in all AWS Regions where Amazon Bedrock AgentCore is supported. Get started by visiting the AWS API MCP Server listing on AWS Marketplace or explore the deployment guide on AWS Labs GitHub repository. Learn more about Amazon Bedrock AgentCore in the AWS documentation.
Quelle: aws.amazon.com

Amazon Aurora now supports PostgreSQL 17.6, 16.10, 15.14, 14.19, and 13.22

Amazon Aurora PostgreSQL-Compatible Edition has added support for PostgreSQL versions 17.6, 16.10, 15.14, 14.19, and 13.22. The update includes the PostgreSQL community’s product improvements and bug fixes, and also includes Aurora-specific enhancements.
Dynamic Data Masking (DDM) (16.10 and 17.6 only) is a new database-level security feature that protects sensitive data like personally identifiable information by masking column values dynamically at query time based on role-based policies, without altering the actual stored data. This release also includes a shared plan cache, improved performance and recovery-time-objective (RTO) and improvement for Global Database switchovers. To use the new versions, create a new Aurora PostgreSQL-compatible database with just a few clicks in the Amazon RDS Management Console. You can also upgrade your existing database. Please review the Aurora documentation to learn more about upgrading. Refer to the Aurora version policy to help you to decide how often to upgrade and how to plan your upgrade process. These releases are available in all commercial AWS Regions and the AWS GovCloud (US) Regions. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.
Quelle: aws.amazon.com

Amazon Kinesis Video Streams now supports a new cost effective warm storage tier

AWS announces a new warm storage tier for Amazon Kinesis Video Streams (Amazon KVS), delivering cost-effective storage for extended media retention. The standard Amazon KVS storage tier, now designated as the hot tier, remains optimized for real-time data access and short-term storage. The new warm tier enables long-term media retention with sub-second access latency at reduced storage costs. The warm storage tier enables developers of home security and enterprise video monitoring solutions to cost-effectively stream data from devices, cameras, and mobile phones while maintaining extended retention periods for video analytics and regulatory compliance. Moreover, developers now have the flexibility to configure fragment sizes based on their specific requirements — selecting smaller fragments for lower latency use cases or larger fragments to reduce ingestion costs. Both hot and warm storage tiers integrate seamlessly with Amazon Rekognition Video and Amazon SageMaker, enabling continuous data processing to support the creation of computer vision and video analytics applications. Amazon Kinesis Video Streams with the new warm storage tier is available in all regions where Amazon Kinesis Video Streams is available, except the AWS GovCloud (US) Regions. To learn more, refer to the getting started guide.
Quelle: aws.amazon.com