AWS Directory Service for Microsoft Active Directory, also known as AWS Managed Microsoft AD, and AD Connector are now available in the AWS Mexico – Central and in Thailand region.

Built on actual Microsoft Active Directory (AD), AWS Managed Microsoft AD enables you to migrate AD-aware applications while reducing the work of managing AD infrastructure in the AWS Cloud. You can use your Microsoft AD credentials to domain join EC2 instances, and also manage containers and Kubernetes clusters. You can keep your identities in your existing Microsoft AD or create and manage identities in your AWS managed directory.

AD Connector is a proxy that enables AWS applications to use your existing on-premises AD identities without requiring AD infrastructure in the AWS Cloud. You can also use AD Connector to join Amazon EC2 instances to your on-premises AD domain and manage these instances using your existing group policies.

Please see all AWS Regions where AWS Managed Microsoft AD and AD Connector are available. To learn more, see AWS Directory Service.
 

​AWS Directory Service for Microsoft Active Directory, also known as AWS Managed Microsoft AD, and AD Connector are now available in the AWS Mexico – Central and in Thailand region. Built on actual Microsoft Active Directory (AD), AWS Managed Microsoft AD enables you to migrate AD-aware applications while reducing the work of managing AD infrastructure in the AWS Cloud. You can use your Microsoft AD credentials to domain join EC2 instances, and also manage containers and Kubernetes clusters. You can keep your identities in your existing Microsoft AD or create and manage identities in your AWS managed directory. AD Connector is a proxy that enables AWS applications to use your existing on-premises AD identities without requiring AD infrastructure in the AWS Cloud. You can also use AD Connector to join Amazon EC2 instances to your on-premises AD domain and manage these instances using your existing group policies. Please see all AWS Regions where AWS Managed Microsoft AD and AD Connector are available. To learn more, see AWS Directory Service.    

Today, AWS announced support for 24 additional AWS services in the AWS Console Mobile App. AWS customers using the AWS Console Mobile App can now access 24 additional AWS services including Service Quotas, CloudFront, Amazon SES, AWS Cloud9, and AWS Batch via an integrated mobile web browser experience in the AWS Console Mobile App.

AWS customers who are on-the-go can use the AWS Console Mobile App to access a select set of native and in-app browser supported services. Customers benefit from the AWS Console Mobile App’s biometric authentication (sign-in), and mobile optimized customer experience. For AWS services not available natively, customers can access the AWS Management Console via an in-app browser to access service pages without additional authentication, manual navigation, or need to switch from the app to a browser.

Visit the product page for more information about the Console Mobile App, including a full list of supported services and regions.
 

​Today, AWS announced support for 24 additional AWS services in the AWS Console Mobile App. AWS customers using the AWS Console Mobile App can now access 24 additional AWS services including Service Quotas, CloudFront, Amazon SES, AWS Cloud9, and AWS Batch via an integrated mobile web browser experience in the AWS Console Mobile App. AWS customers who are on-the-go can use the AWS Console Mobile App to access a select set of native and in-app browser supported services. Customers benefit from the AWS Console Mobile App’s biometric authentication (sign-in), and mobile optimized customer experience. For AWS services not available natively, customers can access the AWS Management Console via an in-app browser to access service pages without additional authentication, manual navigation, or need to switch from the app to a browser. Visit the product page for more information about the Console Mobile App, including a full list of supported services and regions.    

AWS has enhanced Payment Profiles to allow customers to select their preferred currency for each AWS service provider (seller of record). This new capability builds upon the existing ability to set different payment methods per service provider, giving you more control over your currency preferences.

With Payment Profiles you can now customize both payment methods and currencies for each AWS service provider. For example, you can select to pay one AWS service provider in USD and another in EUR, aligning your AWS payment preferences with your business needs. If you prefer not to create specific Payment Profiles, AWS will continue using your default payment preferences.

This feature is now generally available to all AWS customers worldwide.

To start managing your currency preferences with Payment Profiles, visit the Payment Preferences page in the AWS Billing and Cost Management Console. For more information about configuring Payment Profiles, visit Using payment profiles.

​AWS has enhanced Payment Profiles to allow customers to select their preferred currency for each AWS service provider (seller of record). This new capability builds upon the existing ability to set different payment methods per service provider, giving you more control over your currency preferences. With Payment Profiles you can now customize both payment methods and currencies for each AWS service provider. For example, you can select to pay one AWS service provider in USD and another in EUR, aligning your AWS payment preferences with your business needs. If you prefer not to create specific Payment Profiles, AWS will continue using your default payment preferences. This feature is now generally available to all AWS customers worldwide. To start managing your currency preferences with Payment Profiles, visit the Payment Preferences page in the AWS Billing and Cost Management Console. For more information about configuring Payment Profiles, visit Using payment profiles.  

The post El nuevo Copilot for Gaming tiene como objetivo ahorrarles tiempo y ayudarlos a ser buenos appeared first on Source LATAM.

​The post El nuevo Copilot for Gaming tiene como objetivo ahorrarles tiempo y ayudarlos a ser buenos appeared first on Source LATAM.  

Amazon Bedrock RAG evaluation is now generally available. You can evaluate your retrieval-augmented generation (RAG) applications, either those built on Amazon Bedrock Knowledge Bases or a custom RAG system. You can evaluate either retrieval or end-to-end generation. Evaluations are powered by an LLM-as-a-judge, with a choice of several judge models. For retrieval, you can select from metrics such as context relevance and coverage. For end-to-end retrieve and generation, you can select from quality metrics such as correctness, completeness, and faithfulness (hallucination detection), and responsible AI metrics such as harmfulness, answer refusal, and stereotyping. You can also compare across evaluation jobs to iterate on your Knowledge Bases or custom RAG applications with different settings like chunking strategy or vector length, rerankers, or different content generating models.

*Brand new – more flexibility!* As of today, in addition to Bedrock Knowledge Bases, Amazon Bedrock’s RAG evaluations supports custom RAG pipeline evaluations. Customers evaluating custom RAG pipelines can now bring their input-output pairs and retrieved contexts into the evaluation job directly in their input dataset, enabling them to bypass the call to a Bedrock Knowledge Base («bring your own inference responses»). We also added citation precision and citation coverage metrics for Bedrock Knowledge Bases evaluation. If you use a Bedrock Knowledge Base as part of your evaluation, you can incorporate Amazon Bedrock Guardrails directly.

To learn more, visit the Amazon Bedrock Evaluations page and documentation. To get started, log into the Amazon Bedrock Console or use the Amazon Bedrock APIs.
 

​Amazon Bedrock RAG evaluation is now generally available. You can evaluate your retrieval-augmented generation (RAG) applications, either those built on Amazon Bedrock Knowledge Bases or a custom RAG system. You can evaluate either retrieval or end-to-end generation. Evaluations are powered by an LLM-as-a-judge, with a choice of several judge models. For retrieval, you can select from metrics such as context relevance and coverage. For end-to-end retrieve and generation, you can select from quality metrics such as correctness, completeness, and faithfulness (hallucination detection), and responsible AI metrics such as harmfulness, answer refusal, and stereotyping. You can also compare across evaluation jobs to iterate on your Knowledge Bases or custom RAG applications with different settings like chunking strategy or vector length, rerankers, or different content generating models. *Brand new – more flexibility!* As of today, in addition to Bedrock Knowledge Bases, Amazon Bedrock’s RAG evaluations supports custom RAG pipeline evaluations. Customers evaluating custom RAG pipelines can now bring their input-output pairs and retrieved contexts into the evaluation job directly in their input dataset, enabling them to bypass the call to a Bedrock Knowledge Base («bring your own inference responses»). We also added citation precision and citation coverage metrics for Bedrock Knowledge Bases evaluation. If you use a Bedrock Knowledge Base as part of your evaluation, you can incorporate Amazon Bedrock Guardrails directly. To learn more, visit the Amazon Bedrock Evaluations page and documentation. To get started, log into the Amazon Bedrock Console or use the Amazon Bedrock APIs.    

Today we’re excited to announce Research and Engineering Studio (RES) on AWS Version 2025.03. This release introduces the RES cost dashboard, supports custom instance lists by software stack, extends hibernation support to Linux virtual desktops, and supports virtual desktops running Windows 10 and 11.

Administrators now have access to the RES cost dashboard, which provides an overview of the Virtual Desktop Infrastructure (VDI) costs at a project level. Use the cost dashboard to get an overview of each project’s budget progress and view data related to historical spend.

RES 2024.08 introduced the ability to modify the list of allowable VDI instance types at the environment level. This release refines that feature by allowing administrators to assign any subset of allowed instances to specific software stacks. Assigning these software stacks to projects makes it possible to limit the instances available for VDIs at a project level.

RES 2025.03 also extends hibernation support to all supported Linux distributions and now supports launching VDIs with Windows 10 and 11. Software stacks now have an additional setting to launch VDIs with either shared, dedicated instance, or dedicated host tenancy to meet licensing requirements. Finally, the ability to create a software stack from a running session has returned. Use this as an alternative to EC2 Image Builder to streamline creation of custom Software Stacks and software images.

See the regional availability page for the list of regions where RES is available.

Check out additional release notes on Github to get started and deploy RES 2025.03.
 

​Today we’re excited to announce Research and Engineering Studio (RES) on AWS Version 2025.03. This release introduces the RES cost dashboard, supports custom instance lists by software stack, extends hibernation support to Linux virtual desktops, and supports virtual desktops running Windows 10 and 11. Administrators now have access to the RES cost dashboard, which provides an overview of the Virtual Desktop Infrastructure (VDI) costs at a project level. Use the cost dashboard to get an overview of each project’s budget progress and view data related to historical spend. RES 2024.08 introduced the ability to modify the list of allowable VDI instance types at the environment level. This release refines that feature by allowing administrators to assign any subset of allowed instances to specific software stacks. Assigning these software stacks to projects makes it possible to limit the instances available for VDIs at a project level. RES 2025.03 also extends hibernation support to all supported Linux distributions and now supports launching VDIs with Windows 10 and 11. Software stacks now have an additional setting to launch VDIs with either shared, dedicated instance, or dedicated host tenancy to meet licensing requirements. Finally, the ability to create a software stack from a running session has returned. Use this as an alternative to EC2 Image Builder to streamline creation of custom Software Stacks and software images. See the regional availability page for the list of regions where RES is available. Check out additional release notes on Github to get started and deploy RES 2025.03.    

Amazon Bedrock Model Evaluation’s LLM-as-a-judge capability is now generally available. Amazon Bedrock Model Evaluation allows you to evaluate, compare, and select the right models for your use case. You can choose an LLM as your judge from several available on Bedrock to ensure you have the right combination of evaluator models and models being evaluated. You can select quality metrics such as correctness, completeness, and professional style and tone, as well as responsible AI metrics such as harmfulness and answer refusal. You can evaluate all available models on Amazon Bedrock, including serverless models, Bedrock Marketplace models compatible with Converse API, customized and distilled models, imported models, and model routers. You can also compare results across evaluation jobs.

*Brand new – more flexibility!* Today, you can evaluate any model or system hosted anywhere by bringing your own inference responses you already fetched into your input prompt dataset for the evaluation job (“bring your own inference responses“). These responses can be from an Amazon Bedrock model or from any model or application hosted outside of Amazon Bedrock, enabling you to bypass calling an Amazon Bedrock model in the evaluation job, and allowing you to incorporate all the intermediate steps of your application into your final responses.

With LLM-as-a-judge, you can get human-like evaluation quality at lower cost, while saving weeks of time.

To learn more, visit the Amazon Bedrock Evaluations page and documentation. To get started, sign in to the AWS Console or use Amazon Bedrock APIs.
 

​Amazon Bedrock Model Evaluation’s LLM-as-a-judge capability is now generally available. Amazon Bedrock Model Evaluation allows you to evaluate, compare, and select the right models for your use case. You can choose an LLM as your judge from several available on Bedrock to ensure you have the right combination of evaluator models and models being evaluated. You can select quality metrics such as correctness, completeness, and professional style and tone, as well as responsible AI metrics such as harmfulness and answer refusal. You can evaluate all available models on Amazon Bedrock, including serverless models, Bedrock Marketplace models compatible with Converse API, customized and distilled models, imported models, and model routers. You can also compare results across evaluation jobs. *Brand new – more flexibility!* Today, you can evaluate any model or system hosted anywhere by bringing your own inference responses you already fetched into your input prompt dataset for the evaluation job (“bring your own inference responses“). These responses can be from an Amazon Bedrock model or from any model or application hosted outside of Amazon Bedrock, enabling you to bypass calling an Amazon Bedrock model in the evaluation job, and allowing you to incorporate all the intermediate steps of your application into your final responses. With LLM-as-a-judge, you can get human-like evaluation quality at lower cost, while saving weeks of time. To learn more, visit the Amazon Bedrock Evaluations page and documentation. To get started, sign in to the AWS Console or use Amazon Bedrock APIs.    

Amazon Redshift Serverless, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Mexico (Central) and Asia Pacific (Thailand) regions. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications.

With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift Serverless. There is no need to choose node types, node count, workload management, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs.

To get started, see the Amazon Redshift Serverless feature page, user documentation, and API Reference.

​Amazon Redshift Serverless, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Mexico (Central) and Asia Pacific (Thailand) regions. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications. With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift Serverless. There is no need to choose node types, node count, workload management, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs. To get started, see the Amazon Redshift Serverless feature page, user documentation, and API Reference.  

Amazon Braket, the quantum computing service from AWS, now offers IonQ’s latest 36-qubit Forte Enterprise quantum processing unit (QPU) in the US East (N. Virginia) Region. This new device joins IonQ’s existing quantum hardware portfolio on Braket, which includes Forte-1, Aria-1, and Aria-2, providing customers with additional capacity to run their quantum workloads on ion-trapped devices.

With this launch, customers can use the familiar Braket SDK and APIs to access Forte Enterprise, which maintains the same capabilities that customers value in Forte-1. The device features IonQ’s debiasing and sharpening error mitigation algorithms to enable advanced customers workloads. Forte Enterprise continues to use the native ZZ gate architecture, making it easy for customers to seamlessly migrate workloads between the Forte devices.

IonQ Forte Enterprise is physically located in Switzerland, but all customer traffic routes through US East (N. Virginia) region. Customers can access this new device using the ARN: arn:aws:braket:us-east-1::device/qpu/ionq/Forte-Enterprise-1.

To get started with IonQ Forte Enterprise, visit the Amazon Braket devices page in the AWS Management Console to explore device specifications and capabilities. For additional guidance, review the Amazon Braket documentation and pricing information to make the most of this new device.

​Amazon Braket, the quantum computing service from AWS, now offers IonQ’s latest 36-qubit Forte Enterprise quantum processing unit (QPU) in the US East (N. Virginia) Region. This new device joins IonQ’s existing quantum hardware portfolio on Braket, which includes Forte-1, Aria-1, and Aria-2, providing customers with additional capacity to run their quantum workloads on ion-trapped devices. With this launch, customers can use the familiar Braket SDK and APIs to access Forte Enterprise, which maintains the same capabilities that customers value in Forte-1. The device features IonQ’s debiasing and sharpening error mitigation algorithms to enable advanced customers workloads. Forte Enterprise continues to use the native ZZ gate architecture, making it easy for customers to seamlessly migrate workloads between the Forte devices. IonQ Forte Enterprise is physically located in Switzerland, but all customer traffic routes through US East (N. Virginia) region. Customers can access this new device using the ARN: arn:aws:braket:us-east-1::device/qpu/ionq/Forte-Enterprise-1. To get started with IonQ Forte Enterprise, visit the Amazon Braket devices page in the AWS Management Console to explore device specifications and capabilities. For additional guidance, review the Amazon Braket documentation and pricing information to make the most of this new device.  

Today, AWS announces a new flow management feature for AWS Network Firewall that enables customers to identify and control active network flows. This feature introduces two key functions: Flow Capture, which allows point-in-time snapshots of active flows, and Flow Flush, which enables selective termination of specific connections. With these new capabilities, customers can now view and manage active flows based on criteria such as source/destination IP addresses, ports, and protocols, providing enhanced control over their network traffic.

This new feature helps customers maintain consistent security policies when updating firewall rules and enables rapid response during security incidents. Network administrators can now easily validate security configurations and ensure that all traffic is evaluated against current policies. The flow management feature is particularly valuable for troubleshooting network issues and isolating suspicious traffic during security events. By providing granular control over active network flows, AWS Network Firewall enhances customers’ ability to maintain a secure and efficient network environment.

The new flow management feature is available in all regions where AWS Network Firewall is supported, allowing customers to benefit from these enhanced capabilities across their global infrastructure.

Customers can start using Flow Capture and Flow Flush at no additional cost. To get started, visit the AWS Network Firewall documentation, explore the new APIs in the Network Firewall API Reference guide, or learn more about AWS Network Firewall on the product page.
 

​Today, AWS announces a new flow management feature for AWS Network Firewall that enables customers to identify and control active network flows. This feature introduces two key functions: Flow Capture, which allows point-in-time snapshots of active flows, and Flow Flush, which enables selective termination of specific connections. With these new capabilities, customers can now view and manage active flows based on criteria such as source/destination IP addresses, ports, and protocols, providing enhanced control over their network traffic. This new feature helps customers maintain consistent security policies when updating firewall rules and enables rapid response during security incidents. Network administrators can now easily validate security configurations and ensure that all traffic is evaluated against current policies. The flow management feature is particularly valuable for troubleshooting network issues and isolating suspicious traffic during security events. By providing granular control over active network flows, AWS Network Firewall enhances customers’ ability to maintain a secure and efficient network environment. The new flow management feature is available in all regions where AWS Network Firewall is supported, allowing customers to benefit from these enhanced capabilities across their global infrastructure. Customers can start using Flow Capture and Flow Flush at no additional cost. To get started, visit the AWS Network Firewall documentation, explore the new APIs in the Network Firewall API Reference guide, or learn more about AWS Network Firewall on the product page.