Kategorie: Amazon AWS

Ornith-1.0-9B and Ornith-1.0-35B models now available on Amazon SageMaker JumpStart

DeepReinforce AI’s Ornith-1.0-9B and Ornith-1.0-35B models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These two models are part of the Ornith 1.0 family of open-source, self-scaffolding agentic coding models released under the MIT license, achieving state-of-the-art performance among open-source models of comparable size on coding benchmarks such as Terminal-Bench 2.1, SWE-Bench, NL2Repo, and OpenClaw.
These models address different agentic coding challenges with specialized capabilities:
Ornith-1.0-9B is a lightweight 9B-parameter dense model post-trained on Qwen 3.5 9B, designed for efficient single-GPU deployment. With a 256K-token context window and 32 decoder layers, it is well-suited for individual developers and small teams running agentic coding workflows on a single GPU — including laptops with consumer-grade hardware. Its self-improving training framework uses reinforcement learning to jointly optimize scaffold generation and solution rollouts, enabling the model to discover better search trajectories and generate higher-quality code solutions.
Ornith-1.0-35B is a 35B-parameter Mixture-of-Experts (MoE) model post-trained on Qwen 3.5, delivering stronger agentic coding performance while remaining deployable on a single 24GB consumer GPU. Like its smaller sibling, it employs reinforcement learning to jointly optimize the scaffolds that drive coding tasks and the resulting solution rollouts, discovering superior code trajectories. Its MoE architecture activates only a subset of parameters per token, providing a strong balance of quality and efficiency for production agentic coding workloads.
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 SageMaker JumpStart model catalog in the SageMaker console 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

AWS Quick apps are now available in Asia Pacific (Singapore)

The AWS Quick desktop app for macOS and Windows and the Quick mobile app for iOS and Android are now available in the Asia Pacific (Singapore) Region. This launch builds on the recent availability of Quick in Singapore.
The desktop app works with your local files and connects to your calendar, email, and business apps. The mobile app lets you chat with Quick, review your activity feed, and open dashboards. Your conversations, context, and agents stay in sync across web, desktop, and mobile, so you can start an agent on your desktop, check on it from your phone, and let it keep running after you close your computer. 
To get started, download the desktop app from the AWS Quick download page or the mobile app from the Apple App Store or Google Play. To learn more, see AWS Quick on mobile in the AWS Quick User Guide and the AWS Quick product page.
Quelle: aws.amazon.com

Amazon EKS Auto Mode now supports security groups for Pods

Amazon EKS Auto Mode now supports security groups for Pods, letting you apply dedicated Amazon EC2 security group rules to individual Pods. Different workloads on the same node can carry different security groups, giving your Pods network-level segmentation without creating separate node pools for each application.
Security groups for Pods extends your existing AWS network controls to the Pod level, so your Pods can reach resources such as Amazon RDS and Amazon ElastiCache databases that authorize connections by security group under the same rules the rest of your VPC uses. You define which Pods receive which security groups with a SecurityGroupPolicy resource, and Pods not matched by a policy keep using their node’s security groups.
Security groups for Pods is included as part of EKS Auto Mode at no additional charge and is available on clusters running Kubernetes version 1.36 or later, in all AWS Regions where EKS Auto Mode is supported. To learn more, see Security groups for Pods in the Amazon EKS User Guide and the Amazon EKS Auto Mode product page.
Quelle: aws.amazon.com

AWS Lambda MicroVMs now supports the x86 CPU architecture

AWS Lambda MicroVMs now supports the x86 CPU architecture, so you can run your existing x86 applications, tools, and software dependencies without recompiling or porting them. When you create a MicroVM image, you can now choose between x86 and Arm (AWS Graviton) to give each user or job an isolated MicroVM on the architecture your workload uses.
Lambda MicroVMs is a serverless compute primitive that provides VM-level isolation, near-instant launch and resume, and state preservation for running user or AI-generated code, in applications such as AI coding assistants, CI/CD runners, interactive development environments, and vulnerability scanners. Today’s launch enables you to run x86-based workloads on Lambda MicroVMs as-is. For workloads that run on Arm, you can continue using AWS Graviton processors which is the default CPU architecture option.
To start building x86 workloads on Lambda MicroVMs, choose the x86 architecture when you create a MicroVM image from your Dockerfile, then launch MicroVMs from that image. You can use MicroVMs through the AWS Lambda console, AWS CloudFormation, AWS Cloud Development Kit, or with your preferred agentic development tools using the Agent Toolkit for AWS.
Support for the x86 CPU architecture is available in all AWS Regions where Lambda MicroVMs is available, except Asia Pacific (Hong Kong), Asia Pacific (Malaysia), Asia Pacific (Thailand), and Europe (Spain). To learn more, visit the AWS Lambda MicroVMs developer guide. For information on pricing, see Lambda MicroVMs pricing.
Quelle: aws.amazon.com

Amazon RDS for PostgreSQL announces Extended Support minor versions 13.23-rds.20260819, 12.22-rds.20260820 and 11.22-rds.20260822

Amazon Relational Database Service (RDS) for PostgreSQL announces Amazon RDS Extended Support minor versions 13.23-rds.20260819, 12.22-rds.20260820 and 11.22-rds.20260822.
Amazon RDS Extended Support provides up to three additional years of fixes for critical Common Vulnerabilities and Exposures (CVE) and bugs beyond a major version’s end of standard support date, giving you more time to upgrade to a new major version.
You can upgrade your database using Amazon RDS Blue/Green Deployments, in-place upgrade, or restore from a snapshot. Learn more about performing version upgrades in the Amazon RDS for PostgreSQL User Guide.
Amazon RDS for PostgreSQL makes it simple to set up, operate, and scale PostgreSQL deployments in the cloud. Create or update a fully managed Amazon RDS database in the Amazon RDS Management Console or by using the AWS Command Line Interface (AWS CLI).
Quelle: aws.amazon.com

Amazon RDS for MySQL 26.10 is now available in Amazon RDS Database Preview Environment

Starting today, Amazon RDS for MySQL 26.10 is available in the Amazon RDS Database Preview Environment, allowing you to evaluate the pre-release of MySQL 26.10 on Amazon RDS for MySQL.
MySQL 26.10 includes bug fixes, security patches, and some improvements to READ COMMITTED workload performance and purge lag warnings in the error log. On busy READ COMMITTED workloads, NUMA systems performance could be impacted as each read view that closed required a global mutex. Read-view objects can now be reused which eliminates the global mutex on closure. The error log now reports warnings when the history-list length (HLL) crosses innodb_max_purge_lag and when purge lag begins delaying DML, so you can detect purge backlogs before they affect performance. To learn more, please refer to the MySQL 26.10 release notes.
Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the Preview Environment can only be used to create or restore database instances within the Preview Environment. Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.
Quelle: aws.amazon.com

Amazon OpenSearch Service announces managed cross-Region disaster recovery

Amazon OpenSearch Service now offers managed cross-Region disaster recovery, so you can meet strict availability and business continuity requirements for mission-critical search, AI, and analytics workloads without building or maintaining replication yourself. After you create domains in two Regions, you can pair them with a single API call or a few steps in the AWS Management Console.
Managed disaster recovery delivers a recovery point objective (RPO) of under one minute and a recovery time objective (RTO) of under 20 minutes. The secondary domain stays continuously in sync with the primary. For planned events such as maintenance or Region rotation, a switchover swaps the two domains’ roles with zero data loss. If your primary domain becomes unavailable, a failover promotes the secondary, with data loss limited to the replication lag. After a failover, you restore protection by pairing the new primary with a secondary domain. You can monitor replication health and lag with Amazon CloudWatch metrics.
Managed disaster recovery requires OpenSearch 3.7 or later and supports domains in the same AWS account, including domains encrypted with customer managed AWS Key Management Service (AWS KMS) keys. Domains that use UltraWarm storage or OpenSearch Optimized instances (OR1 or OR2) aren’t supported. If you’re on an earlier version, clone-based upgrades let you test OpenSearch 3.7 against your workload, cut over when you’re ready, and roll back if needed.
There’s no additional charge for managed disaster recovery. You pay standard rates for the secondary domain and cross-Region data transfer. For details, see Amazon OpenSearch Service pricing.
Managed disaster recovery is available today in all commercial AWS Regions where Amazon OpenSearch Service is available (Region list). To get started, see the disaster recovery documentation.
Quelle: aws.amazon.com

Amazon EC2 G7 instances now available in additional regions

Amazon Elastic Compute Cloud (Amazon EC2) G7 instances powered by NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs are now available in Europe (London), Asia Pacific (Mumbai, Sydney) and South America (Sao Paulo) Regions. G7 instances deliver up to 4.6x AI inference performance and up to 2.1 graphics performance compared to G6 instances. G7 instances also deliver faster performance for GPU-accelerated data analytics workloads.
Customers can use G7 instances for deploying AI models for language translation, video and image analysis, speech recognition and recommender systems. They also accelerate graphics workloads such as creating and rendering real-time, cinematic-quality graphics and game streaming. Additionally, G7 instances support video transcoding, spatial computing, and data analytics workloads. G7 instances feature up to 8 NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs with 32 GB of memory per GPU and custom Intel Xeon 6 processors. They support up to 192 virtual CPUs (vCPUs) and up to 700 Gbps of Elastic Fabric Adapter (EFA) networking bandwidth. They also support up to 768 GiB of system memory, and up to 7.6 TB of local NVMe SSD storage.
You can use G7 instances for Amazon EC2 in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio) , Europe (London, Spain, Frankfurt, Stockholm) , Asia Pacific (Mumbai, Sydney) and South America (Sao Paulo). You can purchase G7 instances as On-Demand Instances, Spot Instances, or as part of Savings Plans.
To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit the G7 instance page.
Quelle: aws.amazon.com

AWS Billing and Cost Management now supports AWS Billing Conductor and AWS Billing Transfer views as source views for custom billing views

Custom billing views now support AWS Billing Conductor and AWS Billing Transfer views as source views. These are the views AWS maintains per billing group and per billing transfer relationship. You can combine them into a single custom billing view, apply filters, and use that view in Cost Explorer, AWS Budgets, and the Billing and Cost Management console. There are three source view types. Billing group views contain the cost of each Billing Conductor billing group, which you can combine for chargeback and showback across business units. Billing transfer views contain the cost transferred to you for each end customer, and transfer showback views contain the cost that end customer sees. Aggregating each type gives you your total transferred cost and the total bill your end customers see.
Your access does not change: you can use an AWS-managed view as a source only where you can already access it. Once created, you can share a custom billing view using AWS Resource Access Manager with accounts inside or outside your organization, so your finance team or a downstream seller works with the data in their own account. Whether you are an AWS Partner reselling AWS services or an organization using billing groups for pro forma billing, you get one consolidated view instead of one per customer or group.
This feature is available in all commercial AWS Regions at no additional cost. To get started, navigate to Billing Views in the AWS Billing and Cost Management console or view the user guide.
Quelle: aws.amazon.com

Amazon OpenSearch Service now lets you validate and roll back version upgrades

Amazon OpenSearch Service now supports clone-based upgrades, which let you validate a new OpenSearch version alongside your current one and cut over to it only when you’re satisfied. If you find a problem, you can cancel before you cut over or roll back afterward. With clone-based upgrades, you can move to new versions with more confidence.
When you start a clone-based upgrade, OpenSearch Service copies the data from your existing cluster (the primary cluster) to a second cluster running the new version (the cloned cluster). While the primary cluster keeps serving your workload, you can run the same search queries on both clusters and compare their performance using Amazon CloudWatch metrics. After you finish validating, you can cut over to the cloned cluster. If you keep the previous version for a retention period you choose, you can roll back to it at any time during that period. You can start and manage a clone-based upgrade from the AWS Management Console, the AWS CLI, or the OpenSearch Service APIs.
Clone-based upgrades are available for domains running OpenSearch 1.1 or later, or Elasticsearch 7.10, in AWS Commercial Regions where Amazon OpenSearch Service is offered, except Asia Pacific (New Zealand), Asia Pacific (Taipei), Asia Pacific (Thailand), and Mexico (Central). For a complete list of Regions, see the AWS Region Table.
To learn more, see Upgrading Amazon OpenSearch Service domains in the Amazon OpenSearch Service Developer Guide. To get started, visit the Amazon OpenSearch Service product page.
Quelle: aws.amazon.com