Schlagwort: cloud computing

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