Cloud Computing Köln

Amazon Redshift streaming can now ingest 10MiB records from Amazon Kinesis Data Streams

Amazon Redshift  now supports Amazon Kinesis Data Streams (KDS) record sizes up to 10 MiB—a 10x increase from the previous 1 MiB limit—fully matching the expanded maximum record size in Amazon KDS. This means you can stream significantly larger payloads directly into Amazon Redshift without splitting records, simplifying your ingestion pipelines and unlocking new use cases for high-volume, large-record workloads.
Amazon Redshift support for 10MiB record size in Amazon KDS streams is now available in all commercial AWS regions where Amazon Redshift is available. For more information on direct streaming ingestion into Amazon Redshift, see the Amazon Redshift streaming documentation. For more information on 10MiB record support in Amazon KDS, see the Amazon KDS documentation.  
Quelle: aws.amazon.com

Muse-Glimmer-30B and Qwen 3.8-27B models now available on Amazon SageMaker JumpStart

Meta’s Muse-Glimmer-30B and Alibaba’s Qwen 3.8-27B models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These two models bring specialized capabilities spanning autonomous local agentic workflows and multimodal long-horizon reasoning, enabling customers to deploy high-performance, scalable AI solutions on AWS infrastructure.
These models address different enterprise AI challenges with specialized capabilities:
Muse-Glimmer-30B is engineered for autonomous agentic tasks with multi-step reasoning, tool use, and failure recovery. This 30B-parameter dense model from Meta Superintelligence Lab combines a dedicated ~1.8B ViT-G/14 perception encoder with interleaved text and image inputs, a 131K+ context window, and selectable reasoning strength (low through extra-high). Released under Apache 2.0, it handles sequential tool calls, recovers from failures, and operates entirely without cloud infrastructure which is ideal for always-on enterprise agents.
Qwen 3.8-27B excels in coding, multi-step agentic tasks, and multimodal understanding across text, images, and video. A dense 27B-parameter native vision-language model with a 262K context window (extendable to ~1M via YaRN scaling), it delivers substantial gains over its predecessor with adjustable reasoning effort levels. Scoring 61.7 on SWE-bench Pro and running at ~17GB quantized, it carries complex multi-step tasks through to completion with greater reliability.
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

Cosmos3-Edge, Cosmos3-Nano, and Cosmos3-Super models now available on Amazon SageMaker JumpStart

NVIDIA’s Cosmos3-Edge, Cosmos3-Nano, and Cosmos3-Super models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These three models form the Cosmos 3 family of open, frontier omnimodal world models for physical AI, enabling customers to build robots, autonomous vehicles, and vision AI that perceive, reason, plan, and act in the physical world.
These models address different physical AI challenges with specialized capabilities:
Cosmos3-Edge is engineered for on-device robot control and real-time visual reasoning on edge hardware. This 4B-parameter omni-model (with a 2B Nemotron-based reasoner) operates at robot-control resolution (640×360), delivering real-time reasoning and generating 32 actions per inference at 15 Hz on NVIDIA Jetson Thor. It supports 256p and 480p video at 12–30 FPS, bringing frontier physical AI capabilities directly to embedded systems.
Cosmos3-Nano excels in physics-aware world generation and physical reasoning as a compact 16B-parameter omnimodal model. It processes combinations of text, image, video, audio, and action trajectories to produce corresponding outputs, enabling robots and vision AI agents to reason using prior knowledge, physics understanding, and common sense. It supports chain-of-thought reasoning over text, images, and video with resolutions up to 720p.
Cosmos3-Super provides the highest-fidelity world generation and simulation in the Cosmos 3 family at 64B parameters. It jointly processes and generates language, images, video, audio, and action sequences within a unified Mixture-of-Transformers architecture, supporting resolutions up to 720p across multiple aspect ratios. Ideal for large-scale simulation, synthetic data generation, and policy learning workflows.
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

Amazon FSx for NetApp ONTAP now supports copying backups across AWS Regions and accounts

Amazon FSx for NetApp ONTAP, a fully managed shared storage service built on NetApp’s popular ONTAP file system, now supports copying backups within and across AWS Regions, and across trusted accounts in your AWS organization. You can now provide an additional layer of protection for your data by storing secondary backup copies in a different Region or account than your primary copies, making it easier to meet your business continuity, data protection, and compliance requirements.
Amazon FSx offers secure, highly durable, and incremental backups designed to support your data retention, archival, and compliance needs. Backups are point-in-time offline copies of your volumes, stored redundantly across multiple Availability Zones in the same Region as your file system. Previously, you could create and restore backups in the same Region and account as your file system. Starting today, you can copy backup data to multiple Regions and accounts for enhanced resilience, data isolation, and operational flexibility.
You can copy new and existing backups in all AWS Regions where Amazon FSx for NetApp ONTAP is available. To learn more, visit the FSx for NetApp ONTAP user guide and the Amazon FSx for NetApp ONTAP product page.
Quelle: aws.amazon.com

AWS Elastic Disaster Recovery introduces Recovery Plans for orchestrated application recovery

AWS Elastic Disaster Recovery (AWS DRS) now offers Recovery Plans, a capability that automates the sequential launch of multi-server applications during recovery and drills. Instead of launching servers one at a time and tracking dependencies manually, you define the recovery sequence once and run it with a single action when you need it. This addresses a common challenge for customers running applications made up of databases, application tiers, and supporting services that must come up in a specific order.
Recovery Plans let you group servers into sequential steps with configurable wait times between them, so your application recovers predictably and consistently every time. You can run plans in a non-disruptive drill mode to validate your procedures, add approval steps where you want a person in the loop, and monitor progress in real time. This automation reduces recovery time and eliminates common errors that occur when coordinating server launch order during high-stress disaster scenarios.
Recovery Plans are available in all AWS Regions where AWS DRS is offered, at no additional cost beyond standard DRS usage. To learn more, visit the AWS Elastic Disaster Recovery User Guide.
Quelle: aws.amazon.com