Kategorie: Amazon AWS

Amazon EventBridge Scheduler adds 619 new SDK API actions, including Lambda Managed Instances

Amazon EventBridge Scheduler expands its AWS SDK integrations with 13 additional services and 619 new API actions across new and existing AWS services, including AWS Lambda Managed Instances. You can now schedule direct invocations of a broader set of AWS services without writing custom integration code. EventBridge Scheduler is a serverless scheduler that allows you to create, run, and manage billions of scheduled events and tasks across more than 270 AWS services, without provisioning or managing the underlying infrastructure. With this expansion, you can now schedule a broader set of AWS API actions directly from Scheduler, including scaling Lambda managed instances up or down on a time-based schedule for precise control over capacity provisioning. These enhancements are now generally available in all AWS Regions where AWS EventBridge Scheduler is available. Specific services and API actions are subject to the availability of the target service in the AWS Region. To learn more about AWS EventBridge Scheduler SDK integrations, visit the Developer Guide.
Quelle: aws.amazon.com

Announcing Region Expansion of G6e instances on SageMaker Studio notebooks

We are pleased to announce general availability of Amazon EC2 G6e instances in the Middle East (Dubai), Asia Pacific (Tokyo, Seoul) and Europe (Frankfurt, Stockholm, Spain) on SageMaker Studio notebooks.
Amazon EC2 G6e instances are powered by up to 8 NVIDIA L40s Tensor Core GPUs with 48 GB of memory per GPU and third generation AMD EPYC processors. G6e instances deliver up to 2.5x better performance compared to EC2 G5 instances. Customers can use G6e instances to interactively test model deployment and for interactive model training use cases such as generative AI fine-tuning. You can use G6e instances to deploy large language models (LLMs) with up to 13B parameters and diffusion models for generating images, video, and audio.
Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio. For pricing information on these instances, please visit our pricing page.
Quelle: aws.amazon.com

Announcing Region Expansion of P4de instances on SageMaker Studio notebooks

We are pleased to announce general availability of Amazon EC2 P4de instances in Asia Pacific (Tokyo, Singapore) and Europe (Frankfurt) on SageMaker Studio notebooks. Amazon EC2 P4de instances are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, 2X higher than the GPUs in our current P4d instances. The new P4de instances provide a total of 640GB of GPU memory, which provide up to 60% better ML training performance along with 20% lower cost to train when compared to P4d instances. The improved performance will allow customers to reduce model training times and accelerate time to market. Increased GPU memory on P4de will also benefit workloads that need to train on large datasets of high-resolution data. Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio. For pricing information on these instances, please visit our pricing page.
Quelle: aws.amazon.com

Announcing Region Expansion of G6 instances on SageMaker Studio notebooks

We are pleased to announce general availability of Amazon EC2 G6 instances in the Middle East (Dubai) and Asia Pacific (Malaysia) on SageMaker Studio notebooks.
Amazon EC2 G6 instances are powered by up to 8 NVIDIA L4 Tensor Core GPUs with 24 GB of memory per GPU and third generation AMD EPYC processors. G6 instances offer 2x better performance for deep learning inference compared to EC2 G4dn instances. Customers can use G6 instances to interactively test model deployment and for interactive model training for use cases such as generative AI fine-tuning and inference workloads, natural language processing, language translation, computer vision, and recommender engines.
Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio. For pricing information on these instances, please visit our pricing page.
Quelle: aws.amazon.com

ENA Express for Amazon EC2 instances now supports traffic between Availability Zones

Elastic Network Adapter (ENA) Express now supports traffic between Amazon EC2 instances in different Availability Zones within a Region, delivering up to 25 Gbps single-flow bandwidth. ENA Express is a networking feature that uses the AWS Scalable Reliable Datagram (SRD) protocol to improve network performance. SRD is a reliable network protocol that delivers performance improvements through advanced congestion control and multi-pathing. Amazon Elastic Block Store (EBS) io2 Block Express and Elastic Fabric Adapter (EFA) for high performance computing and machine learning workloads also leverage SRD.
Workloads such as distributed storage, databases, and file systems require deployments spanning multiple Availability Zones for resilience, yet single flows between zones support up to 5 Gbps with ENA. ENA Express delivers up to 25 Gbps single-flow bandwidth for traffic between Availability Zones. To achieve this, ENA Express detects compatibility between your EC2 instances and establishes an SRD connection when both communicating instances have ENA Express enabled. Once established, SRD uses multi-pathing to route your traffic across the network and avoids head-of-line blocking as it does not need packets to arrive in order. Using these capabilities, ENA Express delivers the performance benefits transparently to your application with TCP and UDP protocols.
ENA Express for connections between Availability Zones within a Region is available for all supported instance types and sizes in Africa (Cape Town), Asia Pacific (Hong Kong, Hyderabad, Jakarta, Malaysia, Melbourne, Mumbai, New Zealand, Osaka, Seoul, Singapore, Sydney, Taipei, Thailand, Tokyo), Canada (Central), Canada West (Calgary), Europe (Frankfurt, Ireland, London, Milan, Paris, Spain, Stockholm, Zurich), Israel (Tel Aviv), Mexico (Central), US East (N. Virginia, Ohio), US West (N. California, Oregon), and AWS GovCloud (US) Regions. ENA Express comes at no additional cost. For a list of supported instances and configuration guidance, please review the latest EC2 documentation.
Quelle: aws.amazon.com

Announcing Region Expansion of P6-B200 instances on SageMaker Studio notebooks

We are pleased to announce general availability of Amazon EC2 P6-B200 instances in AWS US East (N. Virginia) on SageMaker Studio notebooks.
Amazon EC2 P6-B200 instances are powered by 8 NVIDIA Blackwell GPUs with 1440 GB of high-bandwidth GPU memory and 5th Generation Intel Xeon processors (Emerald Rapids). These instances deliver up to 2x better performance compared to P5en instances for AI training. Customers can use P6-B200 instances to interactively develop and fine-tune large foundation models, including LLMs, mixture of experts models, and multi-modal reasoning models. These instances enable efficient experimentation with larger models directly in JupyterLab or CodeEditor environments for generative AI applications such as enterprise copilots and content generation across text, images, and video.
Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio. For pricing information on these instances, please visit our pricing page.
Quelle: aws.amazon.com

AWS Transform adds containerization capability during migrations

AWS Transform now supports replatforming applications to containers during migration to AWS. This release extends AWS Transform’s agentic AI capabilities to automate the containerization of your source code, enabling you to migrate and modernize in parallel, reducing the time and complexity of moving from on-premises to cloud-native architectures. Migration teams can containerize source code from GitHub, Bitbucket, GitLab, or .zip files, generate Docker images, publish to Amazon Elastic Container Registry (Amazon ECR), and deploy to Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). This brings containerization into the same workflow your team uses to plan and execute rehost migrations. AWS Transform analyzes your source code repositories, generates Dockerfiles, and builds container images with integrated security scanning for common vulnerabilities and exposures (CVEs). It produces deployment-ready Terraform infrastructure-as-code and Helm charts for your target environment. The service supports monolithic repositories (monorepos) and multi-repo structures, private dependency resolution through AWS CodeArtifact, and containerization of thousands of applications at scale. During migration wave planning, you can assign applications to either a rehost or replatform-to-containers path, so you can move and realize the benefits of AWS faster. This new capability is available in all AWS Regions where AWS Transform is offered.
To learn more, please visit the AWS Transform User Guide.
Quelle: aws.amazon.com

Claude Platform on AWS is now generally available

Today, AWS announced the general availability of Claude Platform on AWS, a new service that gives customers direct access to Anthropic’s native Claude Platform experience through their existing AWS account. AWS is the first cloud provider to offer access to the native Claude Platform experience. Developers and organizations now have the choice to access Anthropic’s native Claude Platform experience, including APIs, console, and early-access beta features, directly through their existing AWS account, without managing separate accounts, billing, or tracking.
Claude Platform on AWS is operated by Anthropic, and customer data is processed outside the AWS security boundary. Claude Platform on AWS is designed for development teams and enterprises that want access to Anthropic’s native Claude Platform development experience and do not have specific regional data residency requirements. Customers still use existing IAM credentials and access controls, consolidated AWS billing, and CloudTrail audit logging for full security visibility. Features available through Claude Platform on AWS include Claude Managed Agents (beta), advisor strategy (beta), web search, web fetch, code execution, files API (beta), Skills (beta), MCP connector (beta), prompt caching, citations, batch processing, and the Claude Console for prompt development and evaluation. 
Claude Platform on AWS is available in US East (N. Virginia), US East (Ohio), US West (Oregon), Canada (Central), South America (São Paulo), Europe (Dublin), Europe (London), Europe (Frankfurt), Europe (Milan), Europe (Zurich), Europe (Paris), Europe (Stockholm), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Parcific (Melborune), Asia, Pacific (Jakarta), Asia Pacific (Sydney), and Asia Pacific (Melbourne). To learn more, visit the Claude Platform on AWS product page. To get started, see the Claude Platform on AWS documentation.
Quelle: aws.amazon.com

AWS HealthOmics now supports caching of cancelled workflow runs

AWS HealthOmics now supports caching completed task outputs of cancelled runs, enabling customers to reuse outputs and avoid recomputing previously completed tasks. When caching is enabled and a run is cancelled, HealthOmics automatically stores completed task outputs in the customer’s S3 bucket, allowing customers to restart runs from the point of cancellation. AWS HealthOmics is a HIPAA-eligible service that helps healthcare and life sciences customers accelerate scientific breakthroughs at scale with fully managed bioinformatics workflows.
Caching of cancelled runs helps researchers, bioinformaticians, and workflow developers debug and iteratively develop workflows efficiently by storing intermediate files and completed task outputs for inspection. This saves customers the cost of recomputing completed tasks that may have taken hours and accelerates subsequent runs by executing only the remaining incomplete tasks.
Caching cancelled runs is now available for Nextflow, WDL, and CWL runs in all AWS HealthOmics regions: US East (N. Virginia), US West (Oregon), Europe (Frankfurt, Ireland, London), Israel (Tel Aviv), and Asia Pacific (Singapore, Seoul). To learn more, visit the workflow cache documentation. 
Quelle: aws.amazon.com

IAM Policy Autopilot adds Java support and Terraform-aware policy generation

IAM Policy Autopilot now supports Java applications and Terraform-aware policy generation, expanding its language coverage and its ability to generate less permissive IAM policies from code. IAM Policy Autopilot is an open-source tool launched at re:Invent 2025 that helps builders quickly and deterministically create baseline IAM policies on AWS that you can refine as your application evolves, reducing the time you spend writing IAM policies and troubleshooting access issues.
Java has been one of the most requested languages from IAM Policy Autopilot users. With this release, Java developers can now analyze their application source code to generate AWS IAM policies, joining Python, TypeScript, and Go as supported languages. In addition, IAM Policy Autopilot can now cross-reference Terraform resource definitions with SDK calls in your application code to resolve actual resource ARNs for each IAM action. For example, a policy generated for an application that calls S3 GetObject will now reference the specific bucket defined in Terraform rather than defaulting to wildcard (*) resources. 
IAM Policy Autopilot is available at no additional cost and can be used from your own machine. To get started, visit the IAM Policy Autopilot GitHub repository. 
Quelle: aws.amazon.com