The AWS MCP Server now supports cross-account and cross-role access

Today, AWS announced cross-account and cross-role access for the AWS Model Context Protocol (MCP) Server, part of the Agent Toolkit for AWS. This feature allows developers using AI coding agents like Kiro, Claude Code, or Codex to work across multiple AWS accounts and AWS Identity and Access Management (IAM) roles within a single session, with no restarts required. Previously, switching profiles required stopping the AI coding session, updating local AWS credentials, and restarting the MCP server for every account change. Now, AI agents using the AWS MCP Server can specify a profile on each command, allowing users to switch between accounts and roles seamlessly.
Cross-account access helps developers move faster across multi-account environments. For example, a DevOps engineer can query CloudWatch logs across production and staging accounts to diagnose a performance issue, or an application developer can update a Lambda configuration in one account and adjust an S3 bucket policy in another, all within the same conversation. Each request specifies which profile to use, so there is no risk of commands reaching the wrong account.
To get started, see Multi-profile support in the Agent Toolkit for AWS user guide. The AWS MCP Server is available in the US East (N. Virginia) and Europe (Frankfurt) Regions.
Quelle: aws.amazon.com

Amazon ECS with AWS Fargate now supports 32vCPU compute configurations

Amazon Elastic Container Service (Amazon ECS) with AWS Fargate now supports 32vCPU compute configurations, enabling customers to run more demanding applications with greater flexibility and performance. AWS Fargate offers 32vCPU tasks with the following memory configurations: 60 GiB, 120 GiB, or 244 GiB, for both x86-based and ARM-based workloads on Linux. These new task sizes extend Amazon ECS’s capability to support high-performance computing use-cases, large-scale data processing, AI inference, and other compute-intensive workloads. With 32vCPUs and up to 244 GiB of memory, Amazon ECS customers can now deploy larger containers and scale applications beyond previous limits, all while leveraging the reliability, security, and scalability of AWS Fargate. To use the new 32vCPU task sizes, simply configure your task definitions to specify 32 as the vCPU value and select one of the new memory options (60, 120, or 244 GiB), then deploy your Amazon ECS services or tasks as usual via the AWS Management Console, CLI, or your infrastructure-as-code of choice. The new vCPU and memory configurations are available on both Fargate and Fargate Spot capacity providers, and existing Compute Savings Plans apply automatically. For pricing details, refer to AWS Fargate pricing page. The 32vCPU tasks are available with Amazon ECS and AWS Fargate in all AWS commercial and AWS GovCloud (US) Regions. To learn more, refer to the Amazon ECS documentation.
Quelle: aws.amazon.com

AWS Databases on Vercel now available in additional AWS Regions

Amazon Aurora PostgreSQL, Amazon Aurora DSQL, and Amazon DynamoDB serverless databases are now available on Vercel Marketplace and v0 by Vercel in additional AWS Regions, offering you more flexibility to build applications with Vercel and AWS databases from the Regions of your choice. To get started, you can describe your idea in v0 using natural language. The tool automatically generates a spec-driven design, deploys code and infrastructure, and stores your application data in the AWS database that best fits your needs with no hands-on coding or provisioning required. Vercel provides an end-to-end setup experience where you can create database resources in seconds under a new AWS account or link to an existing one, all without leaving Vercel. New AWS accounts created from Vercel include access to all three databases and $100 USD in credits, usable across any of these database options for up to six months. You can manage your plan, add payment information, and view usage details anytime from the AWS settings portal in the Vercel dashboard. To learn more, visit v0 or the AWS landing page on the Vercel Marketplace. You can now create an Aurora PostgreSQL database or Amazon DynamoDB table through Vercel from 17 AWS Regions enabled by default, and Aurora DSQL from 16 AWS Regions including: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), and South America (São Paulo). AWS Databases deliver security, reliability, and price performance without the operational overhead, whether you’re prototyping your next big idea or running production AI and data driven applications. For more information, visit the AWS Databases webpage.
Quelle: aws.amazon.com

Amazon EKS Capabilities now supports Amazon CloudWatch Vended Logs

Amazon Elastic Kubernetes Service (Amazon EKS) Capabilities can now be configured as log delivery sources using Amazon CloudWatch Vended Logs. This enables customers to monitor and troubleshoot their EKS Capabilities for Argo CD, AWS Controllers for Kubernetes (ACK), and kro (Kubernetes Resource Orchestrator) by monitoring logs collected from the managed controllers that run in AWS-managed infrastructure. Customers can enable log delivery for each capability using CloudWatch APIs or the AWS Console. Logs are configured as a CloudWatch Vended Logs delivery source, enabling reliable, secure log delivery to CloudWatch Logs, Amazon S3, or Amazon Kinesis Data Firehose destinations. This feature is available in all AWS Regions where the EKS Capabilities feature is supported. Standard CloudWatch Vended Logs pricing applies based on the chosen destination. There is no additional EKS charge. To learn more about EKS Capabilities, visit the Amazon EKS documentation.
Quelle: aws.amazon.com

Amazon SageMaker Data Agent integrates business context into conversations

Amazon SageMaker Data Agent now integrates with SageMaker Catalog business context and metadata, enabling data practitioners to discover datasets and generate more accurate SQL and Python code using business terminology instead of cryptic technical table names. This integration allows the Data Agent to leverage the business context that companies have invested months curating in their SageMaker Catalog, including those synced from Collibra, Atlan, and Alation, to deliver more accurate data discovery and code generation.
With this capability, data practitioners can ask questions like “Calculate customer retention rate” or “What data do I have on customer churn?” and the Data Agent will search glossary terms, custom metadata forms, asset summaries, and README content to identify the correct tables and columns. The agent generates more accurate code on first attempt by understanding business context, plans multi-step workflows with the correct sequence of tables and transformations, and respects data governance by checking subscription status and providing access request links when needed. Organizations maximize their existing catalog investment without changing the current data workflows, reducing time-to-insight, and enabling data teams to work in business language rather than deciphering technical table names.
This integration is available in SageMaker Unified Studio notebooks and Query Editor in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the Amazon SageMaker Unified Studio page and Amazon SageMaker Data Agent documentation.
Quelle: aws.amazon.com