Die Telekom soll die Kupferabschaltung nicht alleine aushandeln dürfen. Bundesdigitalminister Karsten Wildberger setzt sich vom bisherigen Kurs der Regierung ab. (Bundesministerium für Digitalisierung un, DSL)
Quelle: Golem
Amazon Managed Workflows for Apache Airflow (MWAA) now supports Apache Airflow version 3.0, the latest major release of the workflow orchestration platform. This release enhances your ability to author, schedule, and monitor complex workflows with greater efficiency and control. Amazon MWAA is a managed service for Apache Airflow that enables seamless workflow orchestration using the familiar Apache Airflow platform. The availability of Apache Airflow v3.0 on MWAA introduces substantial improvements to workflow orchestration, including a completely redesigned interface for enhanced usability and advanced event-driven scheduling capabilities. This new scheduling system triggers workflows based on external events directly, eliminating the need for separate asset update pipelines. The newly introduced Task SDK in Apache Airflow v3.0 on MWAA help you simplify DAGs by reducing boilerplate code, making workflows more concise, readable, and consistent. Security and isolation are strengthened through the Task Execution API, which restricts direct access to the metadatabase and manages all runtime interactions. This release also features scheduler-managed backfill functionality, providing you better control over historical data processing. Additionally, MWAA now supports Python 3.12, while incorporating critical security improvements and bug fixes that enhance the overall reliability and security of your workflows in Amazon MWAA environments. You can launch a new Apache Airflow 3.0 environment on Amazon MWAA with just a few clicks in the AWS Management Console in all currently supported Amazon MWAA regions. To learn more about Apache Airflow 3.0 visit the Amazon MWAA documentation, and the Apache Airflow 3.0 change log in the Apache Airflow documentation. Apache, Apache Airflow, and Airflow are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.
Quelle: aws.amazon.com
Unbekannte erbeuten Identifizierungsdaten von Bonify-Nutzern. Darunter sind auch Ausweisdaten und Fotos. (Schufa, Security)
Quelle: Golem
Mit Fire-TV-Geräten und fünf Echo-Lautsprechern lässt sich neuerdings bequem ein Heimkinosystem aufbauen. Dabei gibt es einiges zu beachten. (Amazon, Streaming)
Quelle: Golem
Der Open Printer verwendet einen Raspberry Pi Zero W und kommt ohne DRM aus – ein simpler Drucker ohne viel Drumherum. (Drucker, Epson)
Quelle: Golem
Die Anker-Mehrfachsteckdose mit 12 Anschlüssen, USB-C-Schnellladen und 7-fach-Schutzsystem ist jetzt günstig wie nie. (Anker, USB)
Quelle: Golem
Disney+ hat eine neue Serie aus dem Riverdale-Universum bestellt. Sie ist apokalyptisch und es gibt Zombies. (Zombie, Disney)
Quelle: Golem
Amazon Detective now supports Amazon Virtual Private Cloud (VPC) endpoints via AWS PrivateLink, enabling you to securely initiate API calls to Detective from within your VPC without requiring Internet traversal. AWS PrivateLink support for Detective is available in all AWS Regions where Detective is available (see the AWS Region table). To try the new feature, you can create a VPC endpoint for Detective through the VPC console, API, or SDK. This creates an elastic network interface in your specified subnets. The interface has a private IP address that serves as an entry point for traffic destined for Detective. You can read more about Detective’s integration with PrivateLink here. Amazon Detective automatically collects log data from your AWS resources and uses machine learning, statistical analysis, and graph theory to build interactive visualizations that enable you to conduct faster and more efficient security investigations. Detective analyzes trillions of events from multiple data sources like Amazon Virtual Private Cloud (Amazon VPC) Flow Logs, AWS CloudTrail logs, Amazon Elastic Kubernetes Service (Amazon EKS) audit logs, and findings from multiple AWS security services to create a unified, interactive view of security events. Detective also automatically groups related findings from Amazon GuardDuty, AWS Security Hub and Amazon Inspector to show you combined threats and vulnerabilities to help security analysts identify and prioritize potential high-severity security risks. To get started, see the Amazon Detective User Guide
Quelle: aws.amazon.com
Today, AWS announces the v1.0.0 release of the AWS API model context protocol (MCP) server enabling foundation models (FMs) to interact with any AWS API through natural language by creating and executing syntactically correct CLI commands. The v1.0.0 release of the AWS API MCP Server contains many enhancements that make the server easier to configure, use, and integrate with MCP clients and agentic frameworks. This release reduces startup time and removes several dependencies by converting the suggest_aws_command tool to a remote service rather than relying on local installation. Security enhancements offer improved secure file system controls, and better input validation. Customers using AWS CloudWatch agent can now collect logs from the API MCP Server for improved observability. In order to support more hosting and configuration options, the AWS API MCP Server now offers streamable HTTP transport in addition to the existing stdio. To make human-in-the-loop workflows requiring iterative inputs more reliable, the AWS API MCP Server now includes elicitation in supported MCP clients. To provide additional safeguards the API MCP Server can be configured to deny certain types of actions or require human oversight and consent for mutating actions. This release also includes a new experimental tool called get_execution_plan to provide prescriptive workflows for common AWS tasks. The tool can be enabled by setting the EXPERIMENTAL_AGENT_SCRIPTS flag to true. Customers can configure the AWS API MCP Server for use with their MCP-compatible clients from several popular MCP registries. The AWS API MCP Server is also available packaged as a container in the Amazon ECR Public Gallery. The AWS API MCP Server is open-source and available now. Visit the AWS Labs GitHub repository to view the source, download, and start experimenting with natural language interaction with AWS APIs today.
Quelle: aws.amazon.com
Today, AWS announces the general availability (GA) of the AWS Knowledge Model Context Protocol (MCP) Server. The AWS Knowledge server gives AI agents and MCP clients access to authoritative knowledge, including documentation, blog posts, What’s New announcements, and Well-Architected best practices, in an LLM-compatible format. With this release, the server also includes knowledge about the regional availability of AWS APIs and CloudFormation resources. AWS Knowledge MCP Server enables MCP clients and agentic frameworks supporting MCP to anchor their responses in trusted AWS context, guidance, and best practices. Customers can now benefit from more accurate reasoning, increased consistency of execution, reduced manual context management so they can focus on business problems rather than MCP configurations. The server is publicly accessible at no cost and does not require an AWS account. Usage is subject to rate limits. Give your developers and agents access to the most up-to-date AWS information today by configuring your MCP clients to use the AWS Knowledge MCP Server endpoint, and follow the Getting Started guide for setup instructions. The AWS Knowledge MCP Server is available globally.
Quelle: aws.amazon.com
