Cloud Computing Köln

Amazon Redshift Serverless is now available in the AWS Asia Pacific (Melbourne) and Canada West (Calgary) regions

Amazon Redshift Serverless, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Asia Pacific (Melbourne) and Canada West (Calgary) regions. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications. With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift Serverless. There is no need to choose node types, node count, workload management, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, Apache Iceberg in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs. To get started, see the Amazon Redshift Serverless feature page, user documentation, and API Reference.
Quelle: aws.amazon.com

Amazon Redshift Serverless AI-driven scaling is now the default for new workgroups

Amazon Redshift Serverless now makes AI-driven scaling and optimization the default for all new workgroups. AI-driven scaling uses machine learning to predict compute needs and automatically adjust resources before queries queue, delivering better price-performance without manual tuning. This release also expands support to workloads with a Base RPU range of 8–512 RPU, up from the previous 32–512 RPU, reducing the entry cost for AI-driven scaling. With AI-driven scaling and optimization, Amazon Redshift monitors your workload patterns and automatically adjusts compute resources based on query complexity, data volume, and expected data scan size. You can use the price-performance slider to choose whether to prioritize cost, performance, or a balance of both. Amazon Redshift also applies additional optimizations, including automatic materialized views and automatic table design optimization, to meet your selected target. To configure price-performance targets, use the AWS Management Console or Amazon Redshift API operations. You can also modify the target after you create the workgroup. Amazon Redshift Serverless AI-driven scaling and optimization is available in all AWS Regions where Amazon Redshift Serverless is available. For more information, see Amazon Redshift Serverless product page and AI-driven scaling and optimization documentation.
Quelle: aws.amazon.com

Amazon WorkSpaces Personal Supports Rocky 9, Red Hat Enterprise Linux 9, and Ubuntu 24.04

AWS announces availability of new Linux bundles for Amazon WorkSpaces Personal, including Rocky Linux 9, Red Hat Enterprise Linux 9, and Ubuntu 24.04. With these bundles, customers can launch WorkSpaces powered by the latest enterprise-grade Linux operating systems and take advantage of modern versions of Linux packages only available in these updated releases. While Rocky Linux 8, Red Hat Enterprise Linux 8, and Ubuntu 22.04 powered WorkSpaces bundles remain available, the new OS options bring access to the latest software ecosystems, improved security postures, and extended long-term support lifecycles offered by each respective distribution. These new bundles also provide a migration path for Amazon Linux 2 customers ahead of its end of life in June 2026. You can get started using managed Rocky Linux 9, Red Hat Enterprise Linux 9, or Ubuntu 24.04 WorkSpaces bundles by selecting one when creating a new Linux WorkSpace. These new bundles are available in all AWS Regions where Amazon WorkSpaces is available. For pricing information, visit the Amazon WorkSpaces pricing page.
Quelle: aws.amazon.com

Amazon SageMaker HyperPod now supports G7e and r5d.16xlarge instances

Amazon SageMaker HyperPod now supports G7e and r5d.16xlarge instances. SageMaker HyperPod is a purpose-built infrastructure for developing, training, and deploying foundation models at scale. It provides a resilient and performant environment with built-in fault tolerance, automated cluster recovery, and optimized distributed training libraries, reducing the undifferentiated heavy lifting of managing large-scale AI/ML infrastructure. 
G7e instances are powered by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs and deliver up to 2.3x better inference performance than G6e instances, allowing you to process more requests per second while reducing latency. With up to 768 GB of total GPU memory, G7e instances let you deploy larger language models or run multiple models on a single endpoint. You can use these instances for deploying LLMs, agentic AI, multimodal generative AI, and physical AI models. G7e instances are also well suited for cost-efficient single-node fine-tuning or training of NLP, computer vision, and smaller generative AI models, with up to 1.27x the TFLOPs and up to 4x the GPU-to-GPU bandwidth compared to G6e. In addition, HyperPod now supports r5d.16xlarge as well. The r5d.16xlarge instance provides 64 vCPUs, 512 GB of memory, and 5 x 600 GB NVMe SSD instance storage, powered by Intel Xeon Platinum 8000 series processors with a sustained all-core turbo frequency of up to 3.1 GHz. This instance is well suited for distributed training data preprocessing especially with frameworks such as Ray, large-scale feature engineering, and running memory-heavy orchestration services alongside GPU compute. G7e instances are available in US East (N. Virginia), US East (Ohio), Asia Pacific (Tokyo), and US West (Oregon) and r5d.16xlarge is available in all regions Amazon SageMaker HyperPod is available in. 
Quelle: aws.amazon.com