Kategorie: Amazon AWS

Amazon EC2 I8ge instances now generally available in Europe (Ireland) AWS region.

Amazon Web Services (AWS) announces the availability of Amazon EC2 I8ge instances in Europe (Ireland) AWS region. Designed for large storage I/O intensive workloads, these new instances are powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, offering up to 40% better compute performance and 20% better price performance over existing I3en instances. I8ge instances offer up to 120TB local NVMe storage density—the highest available in the cloud for storage optimized instances—and deliver up to twice as many vCPUs and memory compared to prior generation instances. Powered by 3rd generation AWS Nitro SSDs, these instances achieve up to 65% better real-time storage performance, up to 50% lower storage I/O latency, and 65% lower storage I/O latency variability compared to I3en instances. Additionally, the 16KB torn write prevention feature, enables customers to eliminate performance bottlenecks for database workloads. I8ge instances are high-density storage-optimized instances, for workloads that demand rapid local storage with high random read/write performance and consistently low latency for accessing large data sets. These versatile instances are offered in eleven different sizes including 2 metal sizes, providing flexibility to match customers computational needs. They deliver up to 180 Gbps of network performance bandwidth, and 60 Gbps of dedicated bandwidth for Amazon Elastic Block Store (EBS), ensuring fast and efficient data transfer for the most demanding applications. To begin your Graviton journey, visit the Level up your compute with AWS Graviton page. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs. To learn more, visit the I8ge instances page.
Quelle: aws.amazon.com

Database Savings Plans now supports Amazon OpenSearch Service and Amazon Neptune Analytics

Today, AWS announces expanded coverage for Database Savings Plans, with support for Amazon OpenSearch Service and Amazon Neptune Analytics. With Database Savings Plans, you can save up to 35% in exchange for a commitment to a consistent amount of usage (measured in $/hour) over a one-year term with no upfront payment. Database Savings Plans automatically applies to eligible serverless and provisioned instance usage regardless of supported engine, instance family, size, deployment option, or AWS Region. For example, with Database Savings Plans, you can change from m7i.large.search to c8g.2xlarge.search within OpenSearch Service, or scale Neptune Analytics workloads while continuing to benefit from the discounted pricing. Database Savings Plans for Amazon OpenSearch Service and Amazon Neptune Analytics is available starting today in all AWS Regions, except China Regions. You can get started with Database Savings Plans from the AWS Billing and Cost Management Console or by using the AWS CLI. To realize the largest savings, you can make a commitment to Savings Plans by using purchase recommendations provided in the console. For a more customized analysis, you can use the Savings Plans Purchase Analyzer to estimate potential cost savings for custom purchase scenarios. For more information, visit the Database Savings Plans pricing page and the AWS Savings Plans FAQs.
Quelle: aws.amazon.com

Introducing Amazon Connect Health, Agentic AI Built for Healthcare

Amazon Connect Health is now generally available, bringing purpose-built agentic AI to healthcare organizations to streamline patient engagement and point-of-care workflows. Amazon Connect Health delivers five AI agents designed to reduce administrative burden across the care continuum — enabling patients faster access to care and freeing clinicians from paperwork and administrative burden to focus on what matters most: their patients. These agents are ready to deploy within existing patient, clinician, and healthcare workflows — such as patient access centers (i.e., contact centers), Electronic Health Records (EHR) applications, and telehealth solutions — in days, not months. All the features follow responsible AI best practices, implement safety guardrails, are HIPAA-eligible, and deliver the same security and reliability standards as any AWS service.
Agents available at launch:

Patient verification (GA) – Confirms patient identity in real time against EHR records with appointment lookup, reducing inbound call-handling time.

Appointment management (Preview) – Books appointments via natural language voice interaction, 24/7, with real-time insurance eligibility checks, enabling after-hours scheduling, and relieving burden on human staff. 

Patient insights (Preview) – Surfaces relevant patient history and clinical context before the visit, so clinicians walk in prepared. Reduces the time clinicians spend piecing together information before a patient’s visit.

Ambient documentation (GA) – Captures patient-clinician conversations during the visit and generates clinical notes in real time.

Medical coding (Preview) – Automatically generates ICD-10 and CPT codes from clinical notes post-visit, with full audit trails.

Amazon Connect Health patient engagement capabilities are natively integrated with Amazon Connect, a complete AI-powered contact center solution delivering personalized customer experiences at scale. Clinical and administrative staff can configure and customize these AI capabilities in minutes using the Amazon Connect Health application, enabling rapid testing and seamless deployment into contact center workflows. The point-of-care capabilities — ambient listening, patient insight, and medical coding — are available via Amazon Connect Health unified SDK (SDK documentation), enabling developers to integrate the features directly into existing EHR and clinician-facing applications. 
 
Amazon Connect Health is available in US East (N. Virginia) and US West (Oregon). To get started, visit the Amazon Connect Health product page. For technical details, see the Amazon Connect Health documentation
Quelle: aws.amazon.com

Amazon OpenSearch Service introduces capacity optimized blue/green deployments

Amazon OpenSearch Service now offers a Capacity Optimized option for blue/green deployments, ensuring domain updates can complete even when available instance capacity is less than required. Updates are performed in incremental batches, reducing the number of additional instances needed during the process. Amazon OpenSearch Service uses a blue/green deployment process when updating domains — creating an idle copy of the original environment, applying updates, and routing traffic to the new environment once complete. This minimizes downtime and preserves the original environment as a fallback. Until now, blue/green deployments required 100% instance capacity upfront. For example, for a cluster with 100 data nodes, another 100 nodes were needed to proceed. If sufficient capacity was unavailable, customers had to wait and retry later. Now, customers can choose between two deployment strategies. The default Full Swap option maintains current behavior, requiring full capacity upfront for the fastest deployment. The new Capacity Optimized option attempts a full capacity deployment first, but automatically falls back to batch deployment if capacity is insufficient. OpenSearch Service determines the appropriate batch size based on cluster size and available instances. Because updates are applied in batches, this option may take longer than a full-swap deployment. Customers can select their preferred option in the deployment configuration settings via the OpenSearch Service console or API. We recommend choosing the Capacity Optimized deployment option for clusters with 30 or more nodes. The Capacity Optimized option is available for all OpenSearch and Elasticsearch versions, across all AWS Commercial Regions where OpenSearch Service is available. See here for a full listing of our Regions. To learn more, visit the documentation page.
Quelle: aws.amazon.com

AWS Shield network security director findings are now available in AWS Security Hub

Today, AWS Shield announces findings from network security director, currently in preview, are now available in AWS Security Hub. AWS Shield network security director identifies missing or misconfigured network security services like AWS WAF, VPC security groups, and VPC network access control lists (ACLs) in your AWS Organization and provides remediation recommendations. Network security director findings now also appear in the Inventory section of the Security Hub console. With network security director, you can continuously analyze your network across accounts or organizational units in your AWS Organization, and receive findings highlighting missing or misconfigured network security services per AWS best practices. The severity of each finding is determined based on a combination of the misconfiguration identified and the network topology of the resource the finding is associated with. To learn more, visit the overview page.
Quelle: aws.amazon.com

AWS Elastic Beanstalk now offers AI-powered environment analysis

AWS Elastic Beanstalk now offers AI-powered environment analysis to help you quickly identify root causes and get recommended solutions for environment health issues. When your environment experiences problems, Elastic Beanstalk collects recent events, instance health, and logs from your environment and sends them to Amazon Bedrock for analysis. This feature is designed for developers and operations teams who need to diagnose and resolve environment issues faster without manually reviewing logs and events. You can request an AI analysis directly from the Elastic Beanstalk console using the AI Analysis button when your environment’s health status is Warning, Degraded, or Severe. You can also use the AWS CLI with the RequestEnvironmentInfo and RetrieveEnvironmentInfo API operations. The analysis provides step-by-step troubleshooting recommendations tailored to your environment’s current state, helping you reduce mean time to resolution.
AI-powered environment analysis is available in all AWS Regions where both AWS Elastic Beanstalk and Amazon Bedrock are available. 
For more information about the AI-powered environment analysis and for a full list of supported platform versions, see the Elastic Beanstalk developer guide. To learn more about Elastic Beanstalk, visit the Elastic Beanstalk product page.
Quelle: aws.amazon.com

Multi-party approval now supports approval team baselining

Multi-party approval (MPA) now supports MPA administrators running test approvals to confirm that their approval team is set up correctly and that approvers are active and reachable. With this new capability, customers ensure their approval teams do not become unresponsive due to natural attrition, incorrect approver selection, or reduced engagement. MPA administrators and security teams can now proactively assess their approval configurations before relying on them for sensitive operations. The baseline feature enables proactive team health management by allowing manual initiation of test approval sessions through the AWS Organizations console. Customers can verify approver availability, identify inactive team members, and maintain compliance with internal governance requirements. Key use cases include regular team responsiveness verification, recommended every 90 days by AWS using the MPA Console, onboarding validation for new approval configurations, and operation health checks to ensure approval workflows function effectively when needed. This feature is available in all AWS commercial regions. To learn more about implementing baseline testing for your multi-party approval workflows, visit the Multi-party approval documentation.    
Quelle: aws.amazon.com

Amazon OpenSearch Ingestion now supports unified ingestion endpoint for OpenTelemetry data

Amazon OpenSearch Ingestion now supports a unified ingestion endpoint that can accept all three OpenTelemetry observability signals — logs, metrics, and traces — through a single pipeline. Previously, customers who wanted to ingest all three OpenTelemetry data types had to create and manage three separate pipelines, one for each signal type. With this launch, a single pipeline can now receive any combination of OpenTelemetry signals, simplifying pipeline architecture and reducing operational overhead. Customers can now build centralized observability pipelines that consolidate logs, metrics, and traces in one place, making it easier to correlate signals and gain a holistic view of application health. Teams operating at scale can reduce the number of pipelines they manage, lowering infrastructure costs and simplifying access control, monitoring, and lifecycle management. This also makes it easier to adopt OpenTelemetry incrementally as teams can begin with one signal type and add others over time without any pipeline reconfiguration. The unified ingestion endpoint for OpenTelemetry data is supported in all regions that Amazon OpenSearch Ingestion is currently available. Customers can get started by using the new unified OpenTelemetry source in their pipeline configuration via the AWS Management console or using the AWS CLI and point their OpenTelemetry clients to the new unified endpoint. To learn more and get started, visit the Amazon OpenSearch Ingestion documentation.
Quelle: aws.amazon.com

Amazon SageMaker HyperPod now provides comprehensive observability for Restricted Instance Groups

Amazon SageMaker HyperPod now offers comprehensive observability for Restricted Instance Groups (RIG), enabling teams training foundation models with Nova Forge to gain deep visibility into their compute resources and training workloads. This new capability eliminates the manual effort of collecting and correlating metrics across the infrastructure stack, providing a unified view of GPU performance, system health, network throughput, and Kubernetes cluster state through a pre-configured Amazon Managed Grafana dashboard backed by Amazon Managed Service for Prometheus.
You can now monitor GPU utilization, NVLink bandwidth, CPU pressure, FSx for Lustre usage, and pod lifecycle from a single Grafana dashboard, with metrics collected across four exporters covering GPU performance, host-level system health, network fabric, and Kubernetes object state. In addition, curated logs are automatically made available in these dashboards, covering epoch progress, step-level training logs, pipeline errors, and Python tracebacks, so you can quickly diagnose training failures. HyperPod Observability for Restricted Instance Group is automatically enabled when you create a new cluster using RIGs, or can be enabled for existing clusters in a few clicks in the HyperPod cluster management console.
Amazon SageMaker HyperPod RIG observability is available in all AWS Regions where SageMaker HyperPod RIG is supported. To learn more, visit the documentation.
Quelle: aws.amazon.com

AWS simplifies IAM role creation and setup in service workflows

AWS Identity and Access Management (IAM) now makes it easier to create and configure IAM roles directly within service workflows, allowing you to customize role permissions without switching between browser tabs. Now, when you are performing console tasks that involve role configuration, a new panel will appear to set the permissions required. IAM roles enable secure AWS cross-service connections using temporary credentials, eliminating the need for hardcoded access keys. This launch integrates role creation capabilities with custom permissions directly into service workflows, allowing you to configure roles and permissions without navigating to the IAM console. You can use default policies or the simplified statement builder to customize your permissions, streamlining your resource setup while maintaining the full functionality of IAM role management. This feature is available when working with Amazon EC2, AWS Lambda, Amazon EKS, Amazon ECS, AWS Glue, AWS CloudFormation, AWS Database Migration Service, AWS Systems Manager, AWS Secrets Manager, Amazon Relational Database Service, and AWS IoT Core in the US East (N. Virginia) Region. The feature will gradually become available across additional AWS services and regions. To learn more, refer to individual service User Guide or IAM documentation.
Quelle: aws.amazon.com