Kategorie: Amazon AWS

AWS launches AWS Transform custom to accelerate organization-wide application modernization

AWS Transform custom is now generally available, accelerating organization-specific code and application modernization at scale using agentic AI. AWS Transform is the first agentic AI service to accelerate the transformation of Windows, mainframe, VMware, and more—reducing technical debt and making your tech stack AI-ready. Technical debt accumulates when organizations maintain legacy systems and outdated code, requiring them to allocate 20-30% of their software development resources to repeatable, cross-codebase transformation tasks that must be performed manually. AWS Transform can automate repeatable transformations of version upgrades, runtime migrations, framework transitions, and language translations at scale, reducing execution time by over 80% in many cases while eliminating the need for specialized automation expertise.
The custom transformation agent in AWS Transform provides both pre-built and custom solutions. It includes out-of-the-box transformations for common scenarios, such as Python and Node.js runtime upgrades, Lambda function modernization, AWS SDK updates across multiple languages, and Java 8 to 17 upgrades (supporting any build system including Gradle and Maven). For organization-specific needs, teams can define custom transformations using natural language, reference documents, and code samples. Users can trigger autonomous transformations with a simple one-line CLI command, which can be scripted or embedded into any existing pipeline or workflow. Within your organization, the agent continually learns from developer feedback and execution results, improving transformation accuracy and tightly aligning the agent’s performance with your organization’s preferences. This approach enables organizations to systematically address technical debt at scale, with the agent continually improving while developers can focus on innovation and high-impact tasks.
AWS Transform custom is now available in the US East (N. Virginia) AWS Region.
To learn more, visit the user guide, overview page, and pricing page.
Quelle: aws.amazon.com

AWS Transform expands .NET transformation capabilities and enhances developer experience

Today, AWS announces the general availability of expanded .NET transformation capabilities and an enhanced developer experience in AWS Transform. Customers can now modernize .NET Framework and .NET code to .NET 10 or .NET Standard. New transformation capabilities include UI porting of ASP.NET Web Forms to Blazor on ASP.NET Core and porting Entity Framework ORM code. The new developer experience, available with the AWS Toolkit for Visual Studio 2026 or 2022, is customizable, interactive, and iterative. It includes an editable transformation plan, estimated transformation time, real-time updates during transformation, the ability to repeat transformations with a revised plan, and next steps markdown for easy handoff to AI code companions. With these enhancements, AWS Transform provides a path to modern .NET for more project types, supports the latest releases of .NET and Visual Studio, and gives developers oversight and control of transformations.
Developers can now streamline their .NET modernization through an enhanced IDE experience. The process begins with automated code analysis that produces a customizable transformation plan. Developers can customize the transformation plan, such as fine-tuning package updates. Throughout the transformation, they benefit from transparent progress tracking and detailed activity logs. Upon completion, developers receive a Next Steps document that outlines remaining tasks, including Linux readiness requirements, which they can address through additional AWS Transform iterations or by leveraging AI code companion tools such as Kiro.
AWS Transform is available in the following AWS Regions: US East (N. Virginia), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London).
To get started with AWS Transform, refer to the AWS Transform documentation.
Quelle: aws.amazon.com

AWS Transform for mainframe now supports application reimagining

AWS Transform for mainframe delivers new data and activity analysis capabilities to extract comprehensive insights to drive the reimagining of mainframe applications. These insights can be combined with business logic extraction to inform decomposition of legacy applications into logical business domains. Together, these form the basis of a comprehensive specification for coding agents like Kiro to reimagine applications into cloud-native architectures. The new capabilities empower organizations to reimagine legacy workloads, providing a comprehensive reverse engineering workflow that includes automated code and data structure analysis, activity analysis, technical documentation generation, business logic extraction, and intelligent code decomposition. Through in-depth data and activity analysis, AWS Transform helps identify application components with high utilization or business value, allowing teams to optimize their modernization efforts and make data-informed architectural decisions. In the AI-powered chat interface, users can customize their modernization approach through flexible job plans that allow them to select predefined comprehensive workflows—full modernization, analysis focus, or business logic focus—or create their own combination of capabilities based on specific objectives. The reimagine capabilities in AWS Transform for mainframe are available today in US East (N. Virginia), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London) Regions. To learn more about reimagining mainframe applications with AWS Transform for mainframe, read the AWS News Blog post or visit the AWS Transform product page. 
Quelle: aws.amazon.com

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