Amazon EC2 P6-B200 instances are now available in the AWS GovCloud (US-East) Region

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) P6-B200 instances accelerated by NVIDIA Blackwell GPUs are available in AWS GovCloud (US-East) Region. These instances offer up to 2x performance compared to P5en instances for AI training and inference. P6-B200 instances feature 8 Blackwell GPUs with 1440 GB of high-bandwidth GPU memory and a 60% increase in GPU memory bandwidth compared to P5en, 5th Generation Intel Xeon processors (Emerald Rapids), and up to 3.2 terabits per second of Elastic Fabric Adapter (EFAv4) networking. P6-B200 instances are powered by the AWS Nitro System, so you can reliably and securely scale AI workloads within Amazon EC2 UltraClusters to tens of thousands of GPUs. P6-B200 instances are now available in p6-b200.48xlarge size in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), AWS GovCloud (US-West) and AWS GovCloud (US-East) Region. To learn more about P6-B200 instances, visit Amazon EC2 P6 instances.
Quelle: aws.amazon.com

Amazon EC2 M9g and M9gd general purpose instances are now available

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M9g and M9gd instances, powered by AWS Graviton5 processors, are generally available. AWS Graviton5 processors are the fifth generation of custom-designed AWS processors, delivering the best price performance for general purpose workloads running on Amazon EC2.
​​M9g instances serve a broad range of general-purpose workloads including application servers, microservices, gaming, caching, and containers, while also delivering the performance needed for agentic AI use cases like real-time reasoning, code generation, and multi-step orchestration.  
​​M9gd instances offer local NVMe-based SSD block-level storage for customers that require high-speed, low-latency local storage, such as media processing, batch and log processing, and applications that need access to temporary storage including caches and scratch files.​
​​​M9g and M9gd instances deliver up to 25% better compute performance compared to AWS Graviton4-based M8g and M8gd instances. They are up to 30% faster for databases, up to 35% faster for web applications, and up to 35% faster for machine learning. These instances are built on the sixth-generation AWS Nitro System and are the first to feature the Nitro Isolation Engine, harnessing formal verification to provide mathematical assurance that customer workloads are isolated from each other and AWS operators, pioneering a new standard for mathematically proven cloud security​​.
M9g and M9gd instances are available in US East (N. Virginia, Ohio), US West (Oregon), and EU (Frankfurt) regions. M9g and M9gd instances are available for purchase via Savings Plans, On-Demand, Spot instances, Dedicated instances, or Dedicated hosts.
Level up your compute with AWS Graviton and get started today.
Quelle: aws.amazon.com

AWS Backup support for Amazon EKS is now available in the AWS European Sovereign Cloud (Germany) Region

AWS Backup support for Amazon Elastic Kubernetes Service (EKS) is now available in the AWS European Sovereign Cloud (Germany) Region. This expansion brings fully-managed, policy-based data protection and recovery to your Amazon EKS clusters in this newly supported Region — including automated scheduling, retention management, immutable vaults, and cross-Region and cross-account copies.
You can use AWS Backup for Amazon EKS to protect entire EKS clusters, specific namespaces, or individual persistent volumes using a centralized, agent-free solution that replaces custom scripts or third-party tools. Use AWS Backup to protect your clusters for disaster recovery, compliance requirements, or before EKS cluster upgrades.
To get started, visit the AWS Backup console, refer to the AWS Backup documentation, or read the AWS News Blog.
Quelle: aws.amazon.com

Amazon S3 Access Grants are now available in the AWS European Sovereign Cloud (Germany) Region

You can now create Amazon S3 Access Grants in the AWS European Sovereign Cloud (Germany) Region.
Amazon S3 Access Grants map identities in directories such as Microsoft Entra ID, or AWS Identity and Access Management (IAM) principals, to datasets in S3. This helps you manage data permissions at scale by automatically granting S3 access to end users based on their corporate identity.
Visit the AWS Region Table for complete regional availability information. To learn more about Amazon S3 Access Grants, visit our product page.
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Amazon SageMaker Unified Studio Notebooks now support EMR Serverless

Amazon SageMaker Unified Studio Notebooks now support Amazon EMR Serverless with Apache Spark Connect, giving data engineers and analysts more flexibility in choosing their Spark runtime for interactive analytics and data engineering workloads. In addition to Amazon Athena Spark, users can now leverage Amazon EMR Serverless as their Spark runtime, selecting the optimal engine based on their requirements.
With this launch, you can run PySpark and Spark SQL on an EMR Serverless Spark Application in Notebook cells. Users can select their Spark runtime from the Notebook side panel, and the selected runtime applies to both Python and SQL cells. Additionally, users can leverage SageMaker Data Agent, the built-in AI assistant, to generate code and execution plans from natural language prompts, accelerating Spark development workflows with EMR Serverless. Organizations can leverage pre-initialized capacity to improve session start times, while benefiting from unified Spark UI monitoring across all supported engines for consistent visibility into job execution and performance. Additionally, EMR Serverless provides VPC connectivity support for workloads requiring network isolation.
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available, supporting both SageMaker Unified Studio notebooks and JupyterLab IDE environments. To get started, see Amazon SageMaker Unified Studio User Guide.
Quelle: aws.amazon.com

Run Interactive Workloads on Amazon EMR Serverless with Spark Connect

Amazon EMR Serverless now supports interactive sessions with Spark Connect, enabling you to develop and run Apache Spark applications from managed notebooks in Amazon SageMaker Unified Studio, as well as your favorite notebook environments and IDEs such as Jupyter and Visual Studio Code. You can also monitor and debug active and completed sessions in the EMR console, and get granular cost and usage visibility for individual sessions. 
 
An interactive session provides a persistent Spark context that seamlessly spans across cells and scripts, enabling you to blend local Python code execution with remote Spark operations within a unified environment. This is enabled by Spark Connect’s client-server architecture, which decouples your application client from the Spark driver and allows you to maintain your preferred development environment and tooling while Spark infrastructure runs independently on EMR Serverless. This architecture unlocks workflows including ad hoc data exploration, iterative step-by-step debugging, and incremental PySpark job development before deploying to production.  For observability, you get real-time session monitoring via the Spark UI, history tracking through the Spark History Server, and session management from the EMR console or API/CLI/SDK.
 
Spark Connect on Amazon EMR Serverless is available with EMR release 7.13 in all AWS Regions where Amazon EMR Serverless is available. The SageMaker Unified Studio experience is available in supported regions. To get started, visit the EMR Serverless Interactive Sessions User Guide or the Amazon SageMaker Unified Studio Getting Started guide.
Quelle: aws.amazon.com

AWS announces Claude Fable 5, the first generally available Mythos-class model

Claude Fable 5 is generally available on AWS and makes Mythos-level capabilities available to all customers, with strong safeguards designed to make it safe for broader use. Fable 5 is state-of-the-art on nearly all tested benchmarks and delivers a step-change in autonomous knowledge work and coding for developers and enterprises building production AI applications. Claude Mythos 5, the same model without those safety classifiers, is available to a small group of customers who currently have access to Claude Mythos Preview.
Claude Fable 5 can run for extended periods on complex knowledge work and coding tasks without intervention, representing a fundamental shift in the types of problems customers can solve with AI. It is built for professional tasks in finance, legal, marketing, sales, data, and engineering — proactively self-updating skills based on learnings, developing its own evaluation harnesses, and verifying its work before delivery. 
Customers have two ways to access Claude Fable 5: Amazon Bedrock and Claude Platform on AWS. Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Fable 5 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see Amazon Bedrock documentation and regional availability. 
Claude Platform on AWS, operated by Anthropic, gives you direct access to Anthropic’s native Claude platform experience with unified AWS billing and authentication. To get started, see the Claude Platform on AWS documentation.
Quelle: aws.amazon.com

AWS FinOps Agent is now available in preview

Today, AWS announces the preview of AWS FinOps Agent, a frontier agent for FinOps practitioners and engineering teams that answers cost questions, surfaces optimization opportunities, automatically investigates cost anomalies, and runs recurring FinOps workflows on a schedule you define.
With the AWS FinOps Agent, you can ask questions about your AWS costs and generate cloud cost reports for finance and engineering teams. The agent surfaces rightsizing, idle resource, and Savings Plans recommendations from AWS Cost Optimization Hub and AWS Compute Optimizer, and can open Jira tickets on your behalf. When a cost anomaly is detected, FinOps Agent can automatically investigate the root cause and can post the findings to a Slack channel, so engineering teams are notified without manual triage.
AWS FinOps Agent (preview) is available in the US East (N. Virginia) Region and includes cost and usage data covering all AWS Regions, except AWS GovCloud (US) Regions and AWS China (Beijing and Ningxia) Regions. AWS FinOps Agent is offered at no additional charge during the preview.
Learn more about AWS FinOps Agent in the User Guide, product details page, and the blog. Get started by visiting the AWS FinOps Agent page in the AWS Management Console.
Quelle: aws.amazon.com

Amazon CloudWatch Logs Insights adds 23 new query commands and functions

Amazon CloudWatch Logs Insights query language now supports 23 new commands and functions that give you new ways to query, parse, transform, and analyze your logs. Customers analyzing logs in CloudWatch Logs Insights often need to do conditional processing, string conversions, process IP addresses, parse different file formats, and execute complex stats commands. With this launch, CloudWatch Logs Insights provides new hash functions (md5, sha256), string functions (strcontains supporting case-insensitive search, split), conditional logic (if statement), and conversion functions (toNumber, toInt, toLong, toDouble). It also adds IP functions (ipv4ToNumber, isPrivateIP, isPublicIP, isReservedIP), analytics functions (rate, count_over_time, sum_over_time, offset, histogram), and parse functions (parse CSV, parse XML, parse multi, values, addtotals). Additionally, queries now support “limit any N” to fetch the first N results, and can use up to 10 stats commands. These commands and functions are available today in all commercial AWS Regions. To learn more, see the Amazon CloudWatch Logs documentation.
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Amazon DocumentDB now supports engine minor version starting with 5.0.1

Amazon DocumentDB (with MongoDB compatibility) now supports engine minor versions, starting with 5.0.1. This release delivers enhanced aggregation capabilities with new operators ($rand, $pow, $dateToParts, $dateFromParts), the active connections metric to monitor instances, and granular command-level performance metrics in CloudWatch (find, insert, findAndModify, update, etc.). For a full list of what’s included, see release notes. Minor versions provide new features and bug fixes within the same major version, giving you more control over when and how you upgrade your clusters. We recommend upgrading to the latest minor version to benefit from these performance enhancements, bug fixes, and new capabilities. You can specify minor version 5.0.1 when creating a new cluster, or manually upgrade an existing 5.0.0 cluster to 5.0.1 using the AWS Management Console or AWS CLI (via the modify-db-cluster command with –engine-version 5.0.1). Once you upgrade to a newer minor version, you cannot downgrade back to a previous minor version. Upgrading from 5.0.0 (LTS) to 5.0.1 gives you access to the latest features and fixes, but you will no longer be on the LTS track. If minimizing upgrades is your priority, you should remain on LTS. For more information, see Using a long-term support (LTS) release. Amazon DocumentDB engine minor version 5.0.1 is available in all AWS Regions where Amazon DocumentDB 5.0 is available. Learn more about minor version upgrades and version support dates in the Amazon DocumentDB Developer Guide. Create or update a fully managed Amazon DocumentDB cluster in the Amazon DocumentDB Management Console.
Quelle: aws.amazon.com