All news with #aws tag

🤖 AWS Support has restructured its support portfolio into three AI-driven plans: Business Support+, Enterprise Support, and Unified Operations. Each tier layers faster response times, proactive guidance, and AI-assisted operations while combining generative AI with AWS engineering expertise. Highlights include 24/7 contextual AI assistance, designated TAMs, integrated security incident response, and the preview AWS DevOps Agent for one-click context sharing and proactive incident prevention. These plans are available in all commercial AWS Regions.

🔍 AWS announced new AWS Transform for mainframe reimagine capabilities that add data and activity analysis, business logic extraction, and intelligent code decomposition to support migration to cloud-native architectures. The service provides a comprehensive reverse-engineering workflow including automated code and data structure analysis and technical documentation generation. An AI-powered chat interface lets users choose predefined job plans—full modernization, analysis focus, or business-logic focus—or compose custom workflows. These capabilities are available today in multiple AWS Regions including N. Virginia, Mumbai, Seoul, Sydney, Tokyo, Canada (Central), Frankfurt, and London.

🔧 AWS Transform expands its .NET modernization agent into a full-stack Windows modernization agent that automates 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. The agent scans SQL Server instances in EC2 or RDS and .NET code in GitHub, GitLab, Bitbucket, or Azure Repos to produce editable modernization plans. It updates Entity Framework and ADO.NET data access code, migrates schemas and data, commits transformed code to a new branch, and supports supervised validation and deployment. Available in US East (N. Virginia).

🔍 AWS Transform for mainframe adds data and activity analysis to extract detailed insights that drive the reimagining of legacy applications. The update provides automated code and data-structure analysis, activity analysis, technical documentation generation, business logic extraction, and intelligent code decomposition. An AI-powered chat interface lets users build flexible job plans—from full modernization workflows to analysis- or business-logic-focused jobs—so teams can prioritize and execute modernization more efficiently.

🚀 AWS Transform adds agentic AI capabilities to automate enterprise-scale VMware migrations, collaborating with migration teams to plan and move hundreds of applications and thousands of servers. The agent discovers on-prem environments using built-in discovery, third-party inventories, and unstructured data, maps dependencies, and generates prioritized migration waves. It also produces network designs, IP management options, multi-account deployment configurations, and supports diverse sources and targets while providing iterative progress updates and approval-ready reports.

🚀 AWS Transform Custom is now generally available, offering an agentic AI service to accelerate organization-wide code and application modernization at scale. The service automates repeatable transformations—version upgrades, runtime migrations, framework transitions, and language translations—often reducing execution time by over 80% while removing the need for specialist automation expertise. It provides out-of-the-box transformations for Python, Node.js, Lambda, AWS SDK updates, and Java 8→17, and supports custom transformation definitions using natural language, reference documents, and code samples. Teams can run autonomous transformations with a one-line CLI command, embed them into pipelines, and benefit from an agent that continuously learns from developer feedback and execution results. AWS Transform Custom is available in the US East (N. Virginia) region.

🧪 AWS Transform for mainframe now introduces integrated test planning and automation to accelerate and de-risk modernization projects. The release includes automated test plan generation, test data collection scripts, and test case automation to stage environments, run functional tests, and validate results against expected outcomes. These tools reduce upfront planning and execution effort, cut dependency on scarce mainframe expertise, and support continuous delivery and regression testing. The new testing capabilities are available today in multiple AWS Regions.

🔧 AWS Transform is now generally available with expanded .NET modernization features that let customers convert .NET Framework and .NET code to .NET 10 or .NET Standard. New capabilities include automated UI porting from ASP.NET Web Forms to Blazor on ASP.NET Core and Entity Framework ORM porting. An enhanced IDE workflow via the AWS Toolkit for Visual Studio 2026 or 2022 provides an editable transformation plan, real‑time progress, repeatable iterations, detailed logs, and a Next Steps markdown for AI code companions.

🔒 CrowdStrike and AWS announced new integrations and consumption options to accelerate cloud security operations. Falcon Next‑Gen SIEM correlates AWS telemetry with endpoints, identities, and third‑party telemetry, offering out‑of‑the‑box dashboards, embedded AI, and over 200 CloudTrail correlation rules. A Quick Start, Amazon Athena federated search, and pay‑as‑you‑go pricing in the AWS Marketplace are intended to speed onboarding, lower storage costs, and simplify investigations.

🔗 Google Cloud and Amazon Web Services have jointly previewed the Cross‑Cloud Interconnect for AWS, a managed, on‑demand service that provisions private, secure connections between Google Cloud VPCs and AWS VPCs in minutes. The collaboration is published under an open specification to enable partner contributions and wider industry adoption. Preview bandwidth begins at 1 Gbps and will scale to 100 Gbps at GA, with MACsec encryption and managed key rotation as default security controls. The offering emphasizes simplicity, quad‑redundancy, and managed operations to reduce setup from days to minutes.

🔗 AWS and Google Cloud announced a jointly engineered multicloud networking solution that integrates AWS Interconnect - multicloud with Google Cloud’s Cross-Cloud Interconnect. The collaboration introduces an open API specification to automate private, high-speed connectivity and shifts multicloud setup from physical circuits to a managed, cloud-native experience. Customers can provision dedicated bandwidth in minutes via console or API, while the service enforces quad redundancy and MACsec encryption for secure, highly available links. The APIs are published openly for other providers and partners to adopt.

📊 Amazon Connect now delivers built‑in analytics and monitoring for AI agents across self‑service and agent assist experiences. Administrators can use customizable dashboards to track key metrics such as number of AI‑led interactions, hand‑off rates, conversation turns, and average handle time, and to compare agent versions to find optimal configurations. The release also exposes AI agent traces via APIs and enables rule‑based automation to trigger alerts or actions when conditions like low sentiment transfers occur.

🤖 Amazon Connect now supports the Model Context Protocol (MCP), enabling AI-driven customer self-service and employee assistance agents to invoke standardized tools to fetch information and perform actions during interactions. Amazon Connect offers out-of-the-box MCP tools for tasks like updating contact attributes and retrieving case information, and allows flow modules to be exposed as MCP tools so business logic is reusable across deterministic and generative workflows. Organizations can also integrate custom or third-party tools via flow modules or the Amazon Bedrock AgentCore Gateway to automate actions such as order lookups, refunds, and customer-record updates without human intervention.

🤖 Amazon Connect has introduced AI-powered predictive insights in public preview, adding five recommendation algorithms to its Customer Profiles. The capabilities analyze interaction history and behavior to power suggestions across self-service and agent interactions, supporting cross-sell, complementary product suggestions, and intelligent product discovery. The preview is available in multiple AWS regions and uses pay-as-you-go pricing for utilized profiles.

🤖 Amazon Connect now offers real-time AI agent assistance and automated contact summarization for Salesforce Contact Center with Amazon Connect (SCC-AC). The capability surfaces customer CRM records and knowledge-base articles to AI agents across voice and chat and provides agents with live transcripts and contextual recommendations. Supervisors gain enhanced call monitoring inside Salesforce, and automated post-contact summaries help agents quickly update cases, reducing administrative burden. Administrators can deploy and configure the integrated solution in minutes; it is available in all AWS Regions where Amazon Connect operates.

🤖 Amazon Connect introduces agentic self-service capabilities that enable AI agents to understand, reason, and take action across voice and messaging channels to automate routine and complex customer-service tasks. Nova Sonic speech models deliver more natural, expressive, and adaptive voice interactions that respond to customer tone, sentiment, and pacing across languages and accents. The feature supports blending deterministic and agentic experiences, automating tasks like order lookup, refunds, and troubleshooting while allowing escalation to live agents and is commercially available in US East (N. Virginia) and US West (Oregon) in English and Spanish, with previews for French, Italian, and German.

🔗 Amazon Connect now lets agents link related contacts — including email replies, call transfers, persistent chats, and queued callbacks — to an existing case using configurable flows. By enabling follow-up contacts to attach automatically, Amazon Connect Cases removes the need for custom logic or manual linking and helps present a unified customer journey to agents. The capability is available in multiple AWS regions; see the Amazon Connect Cases documentation to get started.

🔍 Amazon Connect introduces configurable criteria to automatically select relevant contacts for performance evaluations, helping managers target specific interactions for review. Managers can specify attributes such as inbound contacts with no connectivity issues and agent department to trigger a chosen evaluation form. New metric-driven criteria — including agent call avoidance, contact handling efficiency, and audibility — can also automatically populate evaluation fields. This capability is available in all regions where Amazon Connect is offered.

🎙️ Amazon Connect now supports integrating third-party speech providers for end-customer self-service. You can directly use Deepgram for speech-to-text and ElevenLabs for text-to-speech alongside Amazon Connect’s native speech capabilities, orchestration, analytics, and compliance controls. The feature is available with Amazon Connect unlimited AI in all commercial AWS regions. This gives contact center teams more flexibility to tailor voice experiences and choose models that fit accuracy, latency, customization, and cost priorities.

📈 Amazon Connect now enables contact center supervisors to create custom metrics using a simple, no-code interface that applies mathematical operations (for example, addition, subtraction, sum, average) to existing Connect data. Nontechnical users can build tailored KPIs and immediately surface them in dashboards and via APIs without engineering support. Use cases include segmented average handle time, total agent outbound time by product, and queue performance filtered by contact type. The feature is available in all AWS regions offering Amazon Connect.