#Aws

Amazon Location Service announces enhanced map styling with contour line density, traffic visualization, and 3D terrain Amazon Location Service today announced new map styling capabilities, providing developers with greater control over terrain visualization, traffic display, and immersive 3D experiences. This release introduces customizable contour line density levels, a traffic congestion-only mode, 3D Terrain and Globe View features, and expands support for existing features across multiple map styles. These capabilities enable you to customize maps for diverse use cases. Choose from three contour line density levels (Low, Medium, and High) to control elevation data visualization, with Low density emphasizing major elevation changes, Medium density providing balanced detail, and High density showing double the contour lines for intricate terrain views. Display traffic strategically with the new traffic congestion-only mode, which filters out free-flowing traffic to highlight incidents and congestion. Create immersive experiences with 3D Terrain and 3D Globe View with Atmosphere, featuring realistic elevation and atmospheric effects. Additionally, existing features like full traffic visualization, Transit and Truck travel modes, and dark and light color schemes are now available across more map styles, including Monochrome, Hybrid, and Satellite. Amazon Location Service is available in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Malaysia), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Spain), Europe (Stockholm), South America (São Paulo), and AWS GovCloud (US-West). To get started, visit the Amazon Location Service Developer Guide or try the hands-on how to code samples.

1 hour ago

🆕 Amazon Location Service now features improved map styling with contour lines, traffic, and 3D terrain. Customizable contour levels, traffic modes, and immersive 3D are available. Existing features are expanded across multiple styles. Available in multiple AWS regions.

#AWS #AmazonLocationService

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Amazon Location Service announces enhanced map styling with contour line density, traffic visualization, and 3D terrain Amazon Location Service today announced new map styling capabilities, providing developers with greater control over terrain visualization, traffic display, and immersive 3D experiences. This release introduces customizable contour line density levels, a traffic congestion-only mode, 3D Terrain and Globe View features, and expands support for existing features across multiple map styles. These capabilities enable you to customize maps for diverse use cases. Choose from three contour line density levels (Low, Medium, and High) to control elevation data visualization, with Low density emphasizing major elevation changes, Medium density providing balanced detail, and High density showing double the contour lines for intricate terrain views. Display traffic strategically with the new traffic congestion-only mode, which filters out free-flowing traffic to highlight incidents and congestion. Create immersive experiences with 3D Terrain and 3D Globe View with Atmosphere, featuring realistic elevation and atmospheric effects. Additionally, existing features like full traffic visualization, Transit and Truck travel modes, and dark and light color schemes are now available across more map styles, including Monochrome, Hybrid, and Satellite. Amazon Location Service is available in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Malaysia), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Spain), Europe (Stockholm), South America (São Paulo), and AWS GovCloud (US-West). To get started, visit the https://docs.aws.amazon.com/location/latest/developerguide/maps-concepts.html or try the hands-on https://docs.aws.amazon.com/location/latest/developerguide/dynamic-maps-how-to.html.

1 hour ago

Amazon Location Service announces enhanced map styling with contour line density, traffic visualization, and 3D terrain

Amazon Location Service today announced new map styling capabilities, providing developers with greater control over terrain visualization, traff...

#AWS #AmazonLocationService

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Amazon IVS Real-Time Streaming now supports redundant ingest Amazon Interactive Video Service (Amazon IVS) Real-Time Streaming now supports redundant ingest, helping protect your live streams against source encoder failures and first-mile network issues. With redundant ingest, you can stream from two encoders simultaneously to a single stage with automated failover, ensuring uninterrupted delivery to your viewers. Redundant ingest is ideal for live events, 24/7 live streams, or any scenario where uninterrupted delivery is essential. This capability helps you maintain viewer engagement during unexpected disruptions and enables continuous 24/7 streaming. Amazon IVS is a managed live streaming solution designed to make low-latency or real-time video available to viewers around the world. Visit the AWS region table for a full list of AWS Regions where the Amazon IVS console and APIs for control and creation of video streams are available. To learn more, please visit the Amazon IVS Real-Time Streaming RTMP ingest documentation page.

2 hours ago

🆕 Amazon IVS now supports redundant ingest for real-time streaming, enabling dual encoders with automated failover to protect against failures, ensuring uninterrupted live streams for events and 24/7 broadcasts.

#AWS

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Amazon WorkSpaces Advisor now available for AI-powered troubleshooting Amazon WorkSpaces Advisor is a new AI-powered tool that helps administrators quickly troubleshoot and resolve issues with Amazon WorkSpaces Personal. Using generative AI capabilities, it analyzes WorkSpace configurations, identifies problems, and provides actionable recommendations to restore service and optimize performance. WorkSpaces Advisor streamlines administrative workflows by reducing the time needed to investigate and fix common issues. Administrators can leverage AI-driven insights to proactively maintain their virtual desktop infrastructure, improve end-user experience, and minimize downtime across their WorkSpaces. Amazon WorkSpaces Advisor is now available in all AWS commercial regions where Amazon WorkSpaces is offered. Visit the Amazon WorkSpaces console to access WorkSpaces Advisor and begin troubleshooting your environment. Learn more in the feature blog and user guide.

2 hours ago

🆕 Amazon WorkSpaces Advisor, now available in all commercial regions, uses AI to quickly troubleshoot and resolve issues with Amazon WorkSpaces Personal, offering actionable recommendations to optimize performance and reduce downtime.

#AWS #AmazonWorkspaces

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Amazon WorkSpaces Advisor now available for AI-powered troubleshooting Amazon WorkSpaces Advisor is a new AI-powered tool that helps administrators quickly troubleshoot and resolve issues with Amazon WorkSpaces Personal. Using generative AI capabilities, it analyzes WorkSpace configurations, identifies problems, and provides actionable recommendations to restore service and optimize performance. WorkSpaces Advisor streamlines administrative workflows by reducing the time needed to investigate and fix common issues. Administrators can leverage AI-driven insights to proactively maintain their virtual desktop infrastructure, improve end-user experience, and minimize downtime across their WorkSpaces. Amazon WorkSpaces Advisor is now available in all AWS commercial regions where Amazon WorkSpaces is offered. Visit the Amazon WorkSpaces console to access WorkSpaces Advisor and begin troubleshooting your environment. Learn more in the https://aws.amazon.com/blogs/desktop-and-application-streaming/troubleshoot-amazon-workspaces-personal-issues-faster-with-workspaces-advisor/ and https://docs.aws.amazon.com/workspaces/latest/adminguide/workspaces-advisor.html.

2 hours ago

Amazon WorkSpaces Advisor now available for AI-powered troubleshooting

Amazon WorkSpaces Advisor is a new AI-powered tool that helps administrators quickly troubleshoot and resolve issues with Amazon WorkSpaces Personal. Using generative AI capabilities, it analyzes Wor...

#AWS #AmazonWorkspaces

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Amazon IVS Real-Time Streaming now supports redundant ingest Amazon Interactive Video Service (Amazon IVS) Real-Time Streaming now supports redundant ingest, helping protect your live streams against source encoder failures and first-mile network issues. With redundant ingest, you can stream from two encoders simultaneously to a single stage with automated failover, ensuring uninterrupted delivery to your viewers. Redundant ingest is ideal for live events, 24/7 live streams, or any scenario where uninterrupted delivery is essential. This capability helps you maintain viewer engagement during unexpected disruptions and enables continuous 24/7 streaming. https://aws.amazon.com/ivs/ is a managed live streaming solution designed to make low-latency or real-time video available to viewers around the world. Visit the https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ for a full list of AWS Regions where the Amazon IVS console and APIs for control and creation of video streams are available. To learn more, please visit the https://docs.aws.amazon.com/ivs/latest/RealTimeUserGuide/rt-rtmp-publishing.html page.

2 hours ago

Amazon IVS Real-Time Streaming now supports redundant ingest

Amazon Interactive Video Service (Amazon IVS) Real-Time Streaming now supports redundant ingest, helping protect your live streams against source encoder failures and first-mile network issues. With redundant ingest, you can ...

#AWS #

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Reality Ausetkmt

@ausetkmt.bsky.social

2 hours ago

What about Choice 3. which he's already doing

3. setting it up to make more money for #Insider-stock-trading for his #oil and #Munitions barons.
Oh let us not forget #AWS, Bezos baby.
Scammin, while the griftin easy

#25/47NOW

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Cisco conversational AI powered by Amazon Lex The new open-source Amazon Lex connector for Cisco Webex Contact Center enables organizations to deploy AI-powered virtual agents within their existing Cisco environment without costly rebuilds, delivering natural voice interactions across 25+ languages while maintaining current workflows and systems. This integration combines AWS AI services including Amazon Lex, Amazon Polly, and Amazon Bedrock with Cisco’s contact center platform to provide immediate customer responses, reduce wait times, and allow agents to focus on complex interactions that require human expertise.

2 hours ago

📰 New article by Satish Subramanian, Aaron Keeton, Jessica Smith, Soundarya Muthuvel, Ravi Thakur

Cisco conversational AI powered by Amazon Lex

#AWS #AWSPartnerNetwork

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Amazon EKS managed node groups now support EC2 Auto Scaling warm pools Amazon Elastic Kubernetes Service (Amazon EKS) managed node groups now support Auto Scaling warm pools, enabling you to maintain pre-initialized EC2 instances ready for rapid scale-out. This reduces node provisioning latency for applications with burst traffic patterns, time-sensitive workloads, or long instance boot times due to complex initialization scripts and software dependencies. With warm pools enabled, your EKS managed node group maintains a pool of instances that have already completed OS initialization, user data execution, and software configuration. When demand increases and the Auto Scaling group scales out, instances transition from the warm pool to active service without repeating the full cold-start sequence. You can configure instances in the warm pool as Stopped (lower cost, longer transition) or Running (higher cost, faster transition). You can also enable reuse on scale-in, which returns instances to the warm pool during scale-down instead of terminating them. Warm pools work with Cluster Autoscaler without requiring any additional configuration. You can enable warm pools through the EKS API, AWS CLI, AWS Management Console, or AWS CloudFormation by adding a warmPoolConfig to your CreateNodegroup or UpdateNodegroupConfig requests. Existing managed node groups that do not enable warm pools are unaffected. This feature is available in all AWS Regions where Amazon EKS is available, except for the China (Beijing) Region, operated by Sinnet and the China (Ningxia) Region, operated by NWCD. To get started, see the Amazon EKS managed node groups documentation.

3 hours ago

🆕 Amazon EKS now supports Auto Scaling warm pools for managed node groups, cutting latency with pre-initialized EC2 instances for rapid scale-out, perfect for burst traffic and time-sensitive workloads. Available worldwide except China (Beijing) and China (Ningxia).

#AWS #AmazonEks

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SageMaker HyperPod now supports gang scheduling for distributed training workloads Amazon SageMaker HyperPod task governance now supports gang scheduling, which ensures all pods required for a distributed training job are ready before training begins. Administrators can configure gang scheduling to prevent wasted compute from partial job runs and avoid deadlocks from jobs waiting for resources. Data scientists running distributed AI/ML training jobs on Amazon SageMaker HyperPod clusters using the EKS orchestrator require multiple pods to work together across nodes with pod-to-pod communication. When some pods start but others do not, jobs can hold onto resources without making progress, block other workloads, and increase costs. Gang scheduling resolves this by monitoring all pods in a workload and pulling the workload back if not all pods are ready within a set time. Pulled-back workloads are automatically requeued to prevent stalling. Administrators can adjust settings on the HyperPod Console, such as how long to wait for pods to be ready, how to handle node failures, whether to admit workloads one at a time to avoid deadlocks on busy clusters, and how retries are scheduled. This capability is currently available for Amazon SageMaker HyperPod clusters using the EKS orchestrator across the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Asia Pacific (Jakarta), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), Europe (Spain), and South America (São Paulo). To learn more, visit SageMaker HyperPod webpage, and HyperPod task governance documentation.

3 hours ago

🆕 SageMaker HyperPod now supports gang scheduling for distributed training, ensuring all pods are ready before starting, preventing resource deadlocks, and minimizing wasted compute. Available in multiple AWS regions.

#AWS #AmazonSagemaker

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Amazon EKS managed node groups now support EC2 Auto Scaling warm pools Amazon Elastic Kubernetes Service (Amazon EKS) https://docs.aws.amazon.com/eks/latest/userguide/managed-node-groups.html now support https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-warm-pools.html, enabling you to maintain pre-initialized EC2 instances ready for rapid scale-out. This reduces node provisioning latency for applications with burst traffic patterns, time-sensitive workloads, or long instance boot times due to complex initialization scripts and software dependencies. With warm pools enabled, your EKS managed node group maintains a pool of instances that have already completed OS initialization, user data execution, and software configuration. When demand increases and the Auto Scaling group scales out, instances transition from the warm pool to active service without repeating the full cold-start sequence. You can configure instances in the warm pool as Stopped (lower cost, longer transition) or Running (higher cost, faster transition). You can also enable reuse on scale-in, which returns instances to the warm pool during scale-down instead of terminating them. Warm pools work with Cluster Autoscaler without requiring any additional configuration. You can enable warm pools through the EKS API, AWS CLI, AWS Management Console, or AWS CloudFormation by adding a warmPoolConfig to your CreateNodegroup or UpdateNodegroupConfig requests. Existing managed node groups that do not enable warm pools are unaffected. This feature is available in all AWS Regions where Amazon EKS is available, except for the China (Beijing) Region, operated by Sinnet and the China (Ningxia) Region, operated by NWCD. To get started, see the https://docs.aws.amazon.com/eks/latest/userguide/managed-node-groups.html.

3 hours ago

Amazon EKS managed node groups now support EC2 Auto Scaling warm pools

Amazon Elastic Kubernetes Service (Amazon EKS) docs.aws.amazon.com/eks/latest/userguide/man... now support docs.aws.amazon.com/autoscaling/ec2/userguid...

#AWS #AmazonEks

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SageMaker HyperPod now supports gang scheduling for distributed training workloads Amazon SageMaker HyperPod task governance now supports gang scheduling, which ensures all pods required for a distributed training job are ready before training begins. Administrators can configure gang scheduling to prevent wasted compute from partial job runs and avoid deadlocks from jobs waiting for resources. Data scientists running distributed AI/ML training jobs on Amazon SageMaker HyperPod clusters using the EKS orchestrator require multiple pods to work together across nodes with pod-to-pod communication. When some pods start but others do not, jobs can hold onto resources without making progress, block other workloads, and increase costs. Gang scheduling resolves this by monitoring all pods in a workload and pulling the workload back if not all pods are ready within a set time. Pulled-back workloads are automatically requeued to prevent stalling. Administrators can adjust settings on the HyperPod Console, such as how long to wait for pods to be ready, how to handle node failures, whether to admit workloads one at a time to avoid deadlocks on busy clusters, and how retries are scheduled. This capability is currently available for Amazon SageMaker HyperPod clusters using the EKS orchestrator across the following https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Asia Pacific (Jakarta), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), Europe (Spain), and South America (São Paulo). To learn more, visit https://aws.amazon.com/sagemaker-ai/hyperpod/, and https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-hyperpod-eks-operate-console-ui-governance-tasks-gang-scheduling.html.

3 hours ago

SageMaker HyperPod now supports gang scheduling for distributed training workloads

Amazon SageMaker HyperPod task governance now supports gang scheduling, which ensures all pods required for a distributed training job are ready before training begins. Administrators can ...

#AWS #AmazonSagemaker

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@detoxima2025.bsky.social

3 hours ago

AWS의 OpenAI와 앤스로픽 동시 투자, 왜 가능한 걸까? - IT Mania 도전인생 클라우드 시장의 거인 AWS가 앤스로픽에 80억 달러를 쏟아붓고, 동시에 OpenAI에 500억 달러라는 천문학적인 자금을 투자하며 업계의 이목이 쏠리고 있습니다. 경쟁 관계인 두 기업을 동시에 지원하는 행보를 두고 시장에서는 이해 상충 논란이 끊이지 않는데요. 과연 AWS는 어떤

AWS의 OpenAI와 앤스로픽 동시 투자, 왜 가능한 걸까?

https://bit.ly/4cyI9LW

#AWS #OpenAI #Anthropic #인공지능투자 #클라우드시장 #기술뉴스 #해킹과드래곤

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Pure Tech

@puretech.news

3 hours ago

AWS boss explains why investing billions in both Anthropic and OpenAI is an OK conflict | TechCrunch AWS has an ingrained culture of handling coopetition, he explained, because the cloud giant also competes with its partners.

AWS boss explains why investing billions in both Anthropic and OpenAI is an OK conflict #Technology #Business #Other #AWS #OpenAI #Anthropic

techcrunch.com/2026/04/08/aws-boss-expl...

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Troubleshoot Amazon WorkSpaces Personal issues faster with WorkSpaces Advisor When end users reports that their Amazon WorkSpace is slow or unable to connect, what happens next? Administrators work through various diagnostic tools, analyzing Amazon CloudWatch metrics, reviewing logs, and correlating signals across multiple sources to identify the root cause. While manageable at small scale, this approach does not scale across hundreds or thousands of WorkSpaces leading to increased time to resolution and frequent escalation [...]

3 hours ago

📰 New article by Pete Fergus, Denton He, Robert Fountain

Troubleshoot Amazon WorkSpaces Personal issues faster with WorkSpaces Advisor

#AWS #DesktopStreaming #ApplicationStreaming

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Amazon Bedrock AgentCore Browser adds OS-level interaction capabilities Amazon Bedrock AgentCore Browser now supports OS-level interaction capabilities, enabling automation of browser workflows that require direct operating system control beyond Chrome DevTools Protocol (CDP) capabilities. This enhancement addresses automation scenarios where CDP alone is insufficient, such as mouse operations, print dialogs, native system alerts, and keyboard shortcuts. The feature serves AI agent developers, test automation engineers, and organizations building LLM-powered web interaction tools. The new capabilities provide automation through mouse operations (click, move, drag, scroll), keyboard operations (type, press, shortcuts like ctrl+a and ctrl+p), and full desktop screenshots, all at OS-level coordinates extending beyond the browser viewport. Key use cases include automated testing with system dialog handling, document management workflows, complex UI interactions with right-click menus, and vision-based AI agents that require complete browser environment visibility. This feature is available by default on all browser instances in all 14 AWS Regions where Amazon Bedrock AgentCore Browser is available: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Canada (Central). To learn more, visit the AgentCore Browser documentation.

4 hours ago

🆕 Amazon Bedrock AgentCore Browser now supports OS-level interaction, automating workflows needing OS control beyond CDP, including mouse, keyboard, and screenshots. Available in 14 AWS regions. For details, see documentation.

#AWS #AmazonBedrock

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Amazon Bedrock AgentCore Browser adds OS-level interaction capabilities Amazon Bedrock AgentCore Browser now supports OS-level interaction capabilities, enabling automation of browser workflows that require direct operating system control beyond Chrome DevTools Protocol (CDP) capabilities. This enhancement addresses automation scenarios where CDP alone is insufficient, such as mouse operations, print dialogs, native system alerts, and keyboard shortcuts. The feature serves AI agent developers, test automation engineers, and organizations building LLM-powered web interaction tools. The new capabilities provide automation through mouse operations (click, move, drag, scroll), keyboard operations (type, press, shortcuts like ctrl+a and ctrl+p), and full desktop screenshots, all at OS-level coordinates extending beyond the browser viewport. Key use cases include automated testing with system dialog handling, document management workflows, complex UI interactions with right-click menus, and vision-based AI agents that require complete browser environment visibility. This feature is available by default on all browser instances in all 14 https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/agentcore-regions.html where Amazon Bedrock AgentCore Browser is available: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Canada (Central). To learn more, visit the https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/browser-tool.html.

4 hours ago

Amazon Bedrock AgentCore Browser adds OS-level interaction capabilities

Amazon Bedrock AgentCore Browser now supports OS-level interaction capabilities, enabling automation of browser workflows that require direct operating system control beyond Chrome DevTools Protocol (C...

#AWS #AmazonBedrock

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Build a multi-tenant configuration system with tagged storage patterns In this post, we demonstrate how you can build a scalable, multi-tenant configuration service using the tagged storage pattern, an architectural approach that uses key prefixes (like tenant_config_ or param_config_) to automatically route configuration requests to the most appropriate AWS storage service. This pattern maintains strict tenant isolation and supports real-time, zero-downtime configuration updates through event-driven architecture, alleviating the cache staleness problem.

4 hours ago

📰 New article by Koshal Agrawal, Ishita Gupta, Vijit Vashishtha

Build a multi-tenant configuration system with tagged storage patterns

#AWS #Architecture

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Customize Amazon Nova models with Amazon Bedrock fine-tuning In this post, we’ll walk you through a complete implementation of model fine-tuning in Amazon Bedrock using Amazon Nova models, demonstrating each step through an intent classifier example that achieves superior performance on a domain specific task. Throughout this guide, you’ll learn to prepare high-quality training data that drives meaningful model improvements, configure hyperparameters to optimize learning without overfitting, and deploy your fine-tuned model for improved accuracy and reduced latency. We’ll show you how to evaluate your results using training metrics and loss curves.

4 hours ago

📰 New article by Bhavya Sruthi Sode, David Rostcheck

Customize Amazon Nova models with Amazon Bedrock fine-tuning

#AWS #AI #MachineLearning

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Human-in-the-loop constructs for agentic workflows in healthcare and life sciences In healthcare and life sciences, AI agents help organizations process clinical data, submit regulatory filings, automate medical coding, and accelerate drug development and commercialization. However, the sensitive nature of healthcare data and regulatory requirements like Good Practice (GxP) compliance require human oversight at key decision points. This is where human-in-the-loop (HITL) constructs become essential. In this post, you will learn four practical approaches to implementing human-in-the-loop constructs using AWS services.

4 hours ago

📰 New article by Pierre de Malliard

Human-in-the-loop constructs for agentic workflows in healthcare and life sciences

#AWS #AI #MachineLearning

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Building intelligent audio search with Amazon Nova Embeddings: A deep dive into semantic audio understanding This post walks you through understanding audio embeddings, implementing Amazon Nova Multimodal Embeddings, and building a practical search system for your audio content. You’ll learn how embeddings represent audio as vectors, explore the technical capabilities of Amazon Nova, and see hands-on code examples for indexing and querying your audio libraries. By the end, you’ll have the knowledge to deploy production-ready audio search capabilities.

4 hours ago

📰 New article by Madhavi Evana, Dan Kolodny, Fahim Sajjad

Building intelligent audio search with Amazon Nova Embeddings: A deep dive into semantic audio understanding

#AWS #AI #MachineLearning

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Reinforcement fine-tuning on Amazon Bedrock: best practices You can use reinforcement Fine-Tuning (RFT) in Amazon Bedrock to customize Amazon Nova and supported open source models by defining what “good” looks like—no large labeled datasets required. By learning from reward signals rather than static examples, RFT delivers up to 66% accuracy gains over base models at reduced customization cost and complexity. This post [...]

4 hours ago

📰 New article by Nick McCarthy, Sapana Chaudhary, Shreyas Subramanian, Jennifer Zhu

Reinforcement fine-tuning on Amazon Bedrock: best practices

#AWS #AI #MachineLearning

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AWS Community Builder Blog Posts

@awscmblogposts.bsky.social

5 hours ago

Design Cost-Optimized Database Solutions Exam Guide: Solutions Architect - Associate ⚡ Domain 4: Design Cost-Optimized Architectures 📘 Task...

✍️ New blog post by Ntombizakhona Mabaso

Design Cost-Optimized Database Solutions

#aws #certification #cloud #solutionsarchitect

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Amazon OpenSearch Service now supports Graviton4 based i8ge instances Amazon OpenSearch Service now supports i8ge instances, which is the latest generation of storage optimized instances offering the best performance for storage-intensive workloads. Powered by AWS Graviton4 processors, I8ge instances deliver up to 60% better compute performance compared to previous generation Graviton2-based storage optimized Im4gn instances. I8ge instances use the latest third generation AWS Nitro SSDs, local NVMe storage that deliver up to 55% better real-time storage performance per TB while offering up to 60% lower storage I/O latency and up to 75% lower storage I/O latency variability compared to previous generation Im4gn instances. Built on the AWS Nitro System, these instances oﬄoad CPU virtualization, storage, and networking functions to dedicated hardware and software enhancing the performance and security for your workloads. I8ge instances are available of sizes up to 18xlarge and 45 TB instance storage. At 112.5 Gbps, these instances have the highest networking bandwidth among storage optimized instances available in Amazon OpenSearch Service. I8ge instances support all OpenSearch versions & Elasticsearch (open source) versions 7.9 and 7.10. Amazon OpenSearch Service supports i8ge instances in following AWS Regions : US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm), Asia Pacific (Malaysia), Asia Pacific (Mumbai), Asia Pacific (Singapore) and Asia Pacific (Sydney). For region specific availability & pricing, visit our pricing page. To learn more about Amazon OpenSearch Service and its capabilities, visit our product page.

5 hours ago

🆕 Amazon OpenSearch Service now supports Graviton4-based i8ge instances, delivering up to 60% better compute and 55% better storage per TB, with lower latency and higher bandwidth. Available in multiple regions. For pricing, check AWS.

#AWS #AmazonOpensearchService

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Amazon OpenSearch Service now supports Graviton4 based i8ge instances Amazon OpenSearch Service now supports i8ge instances, which is the latest generation of storage optimized instances offering the best performance for storage-intensive workloads. Powered by AWS Graviton4 processors, I8ge instances deliver up to 60% better compute performance compared to previous generation Graviton2-based storage optimized Im4gn instances. I8ge instances use the latest third generation AWS Nitro SSDs, local NVMe storage that deliver up to 55% better real-time storage performance per TB while offering up to 60% lower storage I/O latency and up to 75% lower storage I/O latency variability compared to previous generation Im4gn instances. Built on the https://aws.amazon.com/ec2/nitro/, these instances oﬄoad CPU virtualization, storage, and networking functions to dedicated hardware and software enhancing the performance and security for your workloads. I8ge instances are available of sizes up to 18xlarge and 45 TB instance storage. At 112.5 Gbps, these instances have the highest networking bandwidth among storage optimized instances available in Amazon OpenSearch Service. I8ge instances support all OpenSearch versions & Elasticsearch (open source) versions 7.9 and 7.10. Amazon OpenSearch Service supports i8ge instances in following https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ : US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm), Asia Pacific (Malaysia), Asia Pacific (Mumbai), Asia Pacific (Singapore) and Asia Pacific (Sydney). For region specific availability & pricing, visit our https://aws.amazon.com/opensearch-service/pricing/. To learn more about Amazon OpenSearch Service and its capabilities, visit our https://aws.amazon.com/opensearch-service/.

5 hours ago

Amazon OpenSearch Service now supports Graviton4 based i8ge instances

Amazon OpenSearch Service now supports i8ge instances, which is the latest generation of storage optimized instances offering the best performance for storage-intensive workloads.

Powered ...

#AWS #AmazonOpensearchService

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How to build unified JSON search solutions in AWS Using a movie streaming reference architecture, this post shows how to implement and sync operational, analytical, and search JSON workloads across AWS services. This pattern provides a scalable blueprint for any use case requiring multi-modal JSON data capabilities.

5 hours ago

📰 New article by Ezat Karimi, Jon Handler

How to build unified JSON search solutions in AWS

#AWS #Databases

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