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Amazon Athena Spark adds support for AWS PrivateLink

Amazon Athena Spark now supports AWS PrivateLink so that you can access APIs and endpoints from your Amazon Virtual Private Cloud (VPC) without traversing the public internet. This feature can help you meet compliance requirements by allowing you to access and use Athena Spark APIs and endpoints entirely within the AWS network. You can now create AWS PrivateLink interface endpoints to connect from clients in your VPC. The Athena VPC endpoint supports all Athena Spark APIs and endpoints, including the Spark Connect, Spark Live UI and Spark History Server endpoints. Communication between your VPC and Athena Spark APIs and endpoints is then conducted entirely within the AWS network, providing a secure pathway for your data. To get started, you can create an interface VPC endpoint to connect to Amazon Athena Spark using the AWS Management Console or AWS Command Line Interface (AWS CLI) commands or AWS CloudFormation. This new feature is available in all AWS Regions where Amazon Athena Spark and AWS PrivateLink are available. For more information, refer to the AWS PrivateLink documentation and Athena Spark documentation.
 
Quelle: aws.amazon.com

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Introducing the Amazon EKS Hybrid Nodes gateway for hybrid Kubernetes networking

Amazon Elastic Kubernetes Service (EKS) now offers the Amazon EKS Hybrid Nodes gateway, a feature that automates networking between your Amazon EKS cluster VPC and Kubernetes Pods running on Amazon EKS Hybrid Nodes. The Amazon EKS Hybrid Nodes gateway eliminates the need to make on-premises pod networks routable or coordinate network infrastructure changes when running in hybrid Kubernetes environments. Networking in hybrid Kubernetes environments can be complex, often requiring changes to on-premises routing configurations, coordination with network teams, and ongoing maintenance as workloads scale. The Amazon EKS Hybrid Nodes gateway addresses these challenges by automatically enabling Kubernetes control plane-to-webhook communication, pod-to-pod traffic across cloud and on-premises environments, and connectivity for AWS services such as Application Load Balancers, Network Load Balancers, and Amazon Managed Service for Prometheus. Customers deploy the Amazon EKS Hybrid Nodes gateway to Amazon EC2 instances using Helm, and the gateway automatically maintains VPC route tables as workloads scale. The Amazon EKS Hybrid Nodes gateway codebase is open source. The Amazon EKS Hybrid Nodes gateway is available in all AWS Regions where Amazon EKS Hybrid Nodes is available, except the China Regions. The Amazon EKS Hybrid Nodes gateway is offered at no additional charge. You pay for the underlying AWS infrastructure used to run the gateway, including Amazon EC2 instance charges and any associated data transfer fees. To get started, visit the Amazon EKS Hybrid Nodes gateway documentation.
Quelle: aws.amazon.com

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Five new Qwen models for coding agents and efficient reasoning are now available in Amazon SageMaker JumpStart

Today, AWS announced the availability of Qwen3-Coder-Next, Qwen3-30B-A3B, Qwen3-30B-A3B-Thinking-2507, Qwen3-Coder-30B-A3B-Instruct, and Qwen3.5-4B in Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These five models from Qwen bring specialized capabilities spanning agentic coding, efficient reasoning, extended thinking, and multimodal understanding, enabling customers to build sophisticated AI applications across diverse use cases on AWS infrastructure.
These models address different enterprise AI challenges with specialized capabilities:
Qwen3-Coder-Next excels at long-horizon reasoning, complex tool use, and recovery from execution failures, making it ideal for powering coding agents in CLI/IDE platforms.
Qwen3-30B-A3B uniquely supports seamless switching between thinking and non-thinking modes, making it well suited for general-purpose assistant tasks like multilingual dialogue, math reasoning, and tool calling.
Qwen3-30B-A3B-Thinking-2507 delivers significantly improved performance on complex reasoning tasks in math, science, and coding, with enhanced long-context understanding.
Qwen3-Coder-30B-A3B-Instruct is designed for agentic coding workflows with a custom function call format and repo-scale context understanding.
Qwen3.5-4B supports unified vision-language training and  201 languages, making it ideal for lightweight multimodal deployments.
With SageMaker JumpStart, customers can deploy any of these models with just a few clicks to address their specific AI use cases.
To get started with these models, navigate to the Models section of SageMaker Studio or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the Amazon SageMaker JumpStart documentation.
Quelle: aws.amazon.com

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Amazon SageMaker now supports multi-region replication from IAM Identity Center

Amazon SageMaker now supports multi-region replication from IAM Identity Center (IdC), enabling you to deploy SageMaker Unified Studio domains in different regions from your IdC instance. This new capability empowers enterprise customers, particularly those in regulated industries like financial services and healthcare, to maintain compliance while leveraging centralized workforce identity management. As an Amazon SageMaker Unified Studio administrator, you can deploy SageMaker domains closer to your workforce based on data residency needs while maintaining seamless single sign-on (SSO) access. Organizations can address use cases such as maintaining IdC in one region while processing sensitive data in compliance-required regions, supporting global operations with centralized identity management, and meeting data sovereignty requirements without compromising SSO capabilities.
To get started see the SageMaker Unified Studio documentation and to learn about setting up IAM Identity Center multi-Region support see the IAM Identity Center User Guide.
Quelle: aws.amazon.com