Schlagwort: cloud computing

Amazon Neptune Database now supports R7g and R8g instances in 5 additional regions

Amazon Neptune Database now supports Graviton3-based R7g and Graviton4-based R8g instances for Amazon Neptune engine versions 1.4.5 or above, in Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Singapore), Canada (Central) and US West (N. California). R7g and R8g instances are priced -16% vs R6g. Graviton3-based R7g are the first AWS database instances to feature the latest DDR5 memory, enabling high-speed access to data in memory. R7g database instances offer up to 30Gbps enhanced networking bandwidth and up to 20 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Graviton4-based R8g instances offer larger instance sizes, up to 48xlarge and features an 8:1 ratio of memory to vCPU, and the latest DDR5 memory. AWS Graviton4 processors are up to 40% faster for databases than AWS Graviton3 processors. You can launch R7g and R8g instances for Neptune using the AWS Management Console or using the AWS CLI. Upgrading a Neptune cluster to R7g or R8g instances requires a simple instance type modification for Neptune engine versions 1.4.5 or higher. For more information on pricing and regional availability, refer to the Amazon Neptune pricing page.
Quelle: aws.amazon.com

Amazon Lex launches configurable voice activity detection sensitivity

Amazon Lex now provides three VAD sensitivity levels that can be configured for each bot locale: Default, High, and Maximum. The Default setting is suitable for most environments with typical background noise levels. High is designed for environments with consistent but moderate noise levels, such as busy offices or retail spaces. Maximum provides the highest tolerance for very noisy environments such as manufacturing floors, construction sites, or outdoor locations with significant ambient noise. You can configure VAD sensitivity when creating or updating a bot locale in the Amazon Connect’s Conversational AI designer.
This feature is available in all AWS commercial regions where Amazon Connect and Lex operate. To learn more, visit the Amazon Lex documentation or explore the Amazon Connect website to learn how Amazon Connect and Amazon Lex deliver seamless end-customer self-service experiences.
Quelle: aws.amazon.com

Amazon SageMaker HyperPod now validates service quotas before creating clusters on console

Amazon SageMaker HyperPod console now validates service quotas for your AWS account before initiating cluster creation, enabling you to confirm sufficient quota availability before provisioning begins. SageMaker HyperPod helps you provision resilient clusters for running AI/ML workloads and developing state-of-the-art models such as large language models (LLMs), diffusion models, and foundation models (FMs). When creating large-scale AI/ML clusters, you need to ensure your account has sufficient quotas for instances, storage, and networking resources, but quota validation previously required manual checks across multiple AWS services, often resulting in failed cluster creation attempts and wasted time if you miss requesting quota limit increases. The new quota validation capability in the SageMaker HyperPod console automatically checks your account-level quotas against your cluster configuration, including instance type limits, EBS volume sizes, and VPC-related quotas when creating new resources. The validation displays a clear table showing expected utilization, applied quota values, and compliance status for each quota. When quotas may be exceeded, you receive a warning alert with direct links to the Service Quotas console to request increases. This feature is available in all AWS Regions where Amazon SageMaker HyperPod is supported. For a complete list of service quota validation checks performed, refer to the Amazon SageMaker HyperPod User Guide.
Quelle: aws.amazon.com