AI-driven Scaling Default in Amazon Redshift Serverless Expands Access
Amazon Redshift Serverless employed machine learning to auto-scale resources, enhancing query performance and cost efficiency across a wider range of workloads.
THE TECHNOLOGY BRIEFING
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Amazon Redshift Serverless employed machine learning to auto-scale resources, enhancing query performance and cost efficiency across a wider range of workloads.
Amazon CloudWatch RUM improved its App Monitors overview page to consolidate critical application health and observability data for DevOps teams.
AWS Key Management Service added features to track the last cryptographic use of keys, simplifying management and policy enforcement for administrators.
Amazon Elastic VMware Service expanded instance options by adding a newer generation i7i.metal-24xl bare-metal EC2 instance to enhance performance and cost-effectiveness.
Redshift Serverless expanded regional availability, offering scalable analytics without manual infrastructure management in new AWS locations.
Amazon Connect increased file attachment size limits up to 100 MB and enabled administrator-defined custom file extensions across communication channels.
A managed pricing plan was launched to unify and clarify billing data visibility for customers using AWS Billing Transfer.
Amazon FSx for OpenZFS enhanced regional coverage, delivering low-latency, high-throughput file storage with native ZFS data management in new locations.
SageMaker HyperPod infrastructure extended to include state-of-the-art GPU and memory-optimized instances for scalable AI model development and deployment.
New EC2 instance families M8in and M8ib introduced network and storage optimized options powered by custom 6th gen Intel Xeon processors.
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