AWS Builder ID, your profile for accessing AWS applications including AWS Builder Center, AWS Training and Certification and Kiro, now supports two new social logins: GitHub and Amazon. This expansion of sign-in options builds on the existing Google Apple social sign-in capabilities, providing GitHub and Amazon users with a streamlined way to access AWS resources without managing separate credentials on AWS.
With Sign in with Github and Amazon integration, developers and builders can now enjoy access to their AWS Builder ID profile using their GitHub or Amazon Account credentials. This enhancement eliminates password management complexity, reduces forgotten password issues, and provides a frictionless experience for both new user registration and returning user sign-ins. Whether you’re accessing development resources in AWS Builder Center, enrolling in certification programs or using Kiro to code your next app, your GitHub and Amazon Accounts can now serve as a secure gateway to your builder AWS journey.
To learn more about AWS Builder ID and get started with Sign in with GitHub and Amazon, visit the AWS Builder ID documentation.
AWS Builder ID, your profile for accessing AWS applications including AWS Builder Center, AWS Training and Certification and Kiro, now supports two new social logins: GitHub and Amazon. This expansion of sign-in options builds on the existing Google Apple social sign-in capabilities, providing GitHub and Amazon users with a streamlined way to access AWS resources without managing separate credentials on AWS.
With Sign in with Github and Amazon integration, developers and builders can now enjoy access to their AWS Builder ID profile using their GitHub or Amazon Account credentials. This enhancement eliminates password management complexity, reduces forgotten password issues, and provides a frictionless experience for both new user registration and returning user sign-ins. Whether you’re accessing development resources in AWS Builder Center, enrolling in certification programs or using Kiro to code your next app, your GitHub and Amazon Accounts can now serve as a secure gateway to your builder AWS journey.
To learn more about AWS Builder ID and get started with Sign in with GitHub and Amazon, visit the AWS Builder ID documentation.
Chequeo de salud: Cómo la gente utiliza Copilot para la salud
Por: Pavel Tolmachev, Bea Costa-Gomes, Viknesh Sounderajah.
No hay nada más importante que la salud.
Nuestro Informe de Uso de Copilot 2025 reveló que la gente habla de su salud y del estado de sus seres queridos más que de cualquier otro tema en el móvil.
Inspirados por este hallazgo, decidimos realizar un análisis en profundidad de más de medio millón de conversaciones relacionadas con la salud y el bienestar que las personas mantuvieron con Copilot durante enero de 2026.
Esta investigación muestra no solo la amplitud y profundidad del compromiso de las personas con la IA para su salud, sino también cómo la IA puede aparecer a través de las crecientes grietas en nuestros sistemas sanitarios. Muestra a personas que cambian de tema a lo largo del día, cómo la IA apoya a los familiares presionados y ayuda a superar la complejidad de la gestión de las decisiones sanitarias. En todo esto, destaca la importancia crítica de la precisión, la fiabilidad y la confianza.
Como ocurre con todos nuestros informes de uso y análisis de conversaciones, adoptamos un enfoque estricto para preservar la privacidad. Todas las conversaciones se desidentifican en la fuente y dependemos de un flujo de trabajo automatizado que extrae temas e intenciones. Ningún humano lee las conversaciones de los usuarios como parte de este proceso.
Aunque esta investigación subestima la importancia de la salud en la IA, lo que encontramos desafió muchas suposiciones: la gente no se limita a hacer preguntas generales sobre salud. En casi 1 de cada 5 conversaciones, las personas describen sus propios síntomas, reciben ayuda para interpretar sus propios resultados de pruebas o para gestionar sus propias condiciones. Y la gente no solo lo pide por sí misma, sino por quienes dependen de ellos. A continuación algunos puntos destacados:
Lo que la gente pregunta
La gente acude a Copilot sobre todo para obtener información. Quieren los hechos, rápidos y adaptados a ellos. Alrededor del 40% de las preguntas se centran en comprender los síntomas, las condiciones médicas y los tratamientos. Las preguntas formuladas en términos generales pueden reflejar la preocupación de salud del usuario más que la curiosidad casual, y la proporción real de preguntas personales de salud puede ser mayor. En un entorno donde la asimetría de la información y la desinformación sanitaria son generalizadas, la gente quiere explicaciones fiables y fáciles de entender extraídas de fuentes creíbles.
Las interacciones significativas van mucho más allá del conocimiento general. Una de las razones más comunes por las que la gente recurre a Copilot (el 10,9% de las preguntas de salud) es para interpretar síntomas (a menudo nuevos o inesperados) y para entender resultados de laboratorio o de imagen. Aunque la interpretación segura todavía depende de clínicos cualificados, estas son preguntas prácticas, a menudo urgentes, en las que la gente siente que necesita explicaciones claras y creíbles antes de dar los siguientes pasos.
El estilo de vida personalizado y el coaching de fitness generan una participación significativa (9% de las consultas), siendo la nutrición y el ejercicio las dos principales subcategorías. Lo que destaca aquí es el cambio de consejos genéricos a una guía personalizada y continua, el tipo de apoyo personalizado que las herramientas tradicionales de búsqueda en internet no ofrecen.
La gente también utiliza Copilot para navegar por el sistema sanitario (el 5,8% de las preguntas de salud abordan la navegación sanitaria, el seguro o los beneficios). Los usuarios quieren encontrar profesionales locales que se adapten a sus preocupaciones médicas, ubicación y cobertura de seguro. Quieren ayuda para entender los beneficios, comparar opciones de atención y gestionar la documentación médica. En estos momentos de estrés, Copilot actúa como guía a través de un sistema a menudo opaco, para ayudar a las personas a sentirse más preparadas y seguras en sus decisiones.
Distribución del porcentaje de intención de salud en todas las conversaciones.
La información general sobre la salud es la principal, pero casi 1 de cada 5 conversaciones implica evaluación personal de síntomas o manejo de la condición.
Cuándo pregunta la gente
Las conversaciones cambian a lo largo del día. Aunque las emociones y el bienestar representan una proporción más o menos pequeña de las consultas de salud en general, su proporción aumenta a medida que avanza el día: pasa del 3,4% de todas las consultas de salud por la mañana y durante el día al 4,3% por la tarde y el 5,2% por la noche. También encontramos un aumento nocturno de preguntas relacionadas con la comprensión de los síntomas médicos, lo que sugiere que las personas recurren a la IA cuando no pueden contactar con facilidad con un clínico, un farmacéutico o incluso amigos y familiares.
Cambios temporales en el uso de la intención, en relación con la mañana.
Los temas de salud personal surgen de manera constante durante la noche y hasta altas horas de la noche, mientras que las preguntas de investigación y académicas disminuyen.
Sobre quién pregunta la gente
Nuestros usuarios preguntan por otros, no solo a sí mismos. En las preguntas sobre manejo de síntomas y condiciones, 1 de cada 7 conversaciones es en nombre de otra persona. Estas preguntas suelen implicar el bienestar de los niños, la medicación de los padres mayores o los resultados de pruebas de la pareja.
Cada vez más personas se encuentran con la crianza de sus hijos, apoyan a padres mayores y gestionan las decisiones de salud de otros a la vez. Esta «generación sándwich» se conecta en línea para responder a las dudas, coordinar la atención y preparar preguntas cuando el tiempo y el acceso son limitados. El uso de proxys cambia la naturaleza de las consultas: más solicitudes implican resumir historiales, comparar opciones de tratamiento o traducir el lenguaje clínico para cuidadores no médicos. Todo esto requiere una orientación más clara sobre consentimiento, privacidad y una dirección clara sobre las vías de escalada.
Porcentaje de conversaciones sobre preguntas de síntomas relacionadas con un usuario, un dependiente, otro o un desconocido.
El móvil es donde ocurren la mayoría de las conversaciones personales sobre salud. Las preguntas sobre síntomas y las consultas sobre bienestar emocional son mucho más comunes en los teléfonos, mientras que el ordenador se inclina mucho hacia la investigación y el trabajo académico.
Dónde pregunta la gente
Según el dispositivo, la gente usa Copilot de forma muy diferente. En el móvil, la gente pregunta sobre síntomas y gestión de la condición al doble de ritmo que en el ordenador. Las conversaciones sobre bienestar emocional son un 75% más frecuentes. El móvil es donde se producen las conversaciones más personales e inmediatas sobre la salud.
El uso en el ordenador, en cambio, tiende a tareas relacionadas con el trabajo como la investigación en salud y el trabajo académico (tres veces más común), que tal vez reflejan un uso más profesional por parte de estudiantes, investigadores y clínicos.
Porcentaje medio de conversaciones por intención en el escritorio.
La mayoría de las conversaciones sobre síntomas son sobre los propios usuarios, pero uno de cada siete es en nombre de otra persona.
Por qué esto importa y cómo respondemos
A medida que los modelos existentes de prestación sanitaria luchan por seguir el ritmo de la demanda, cada vez más personas recurren a la inteligencia artificial y cada vez más en línea. Hasta hace poco, muchas personas confiaban en la búsqueda en internet para navegar preguntas de salud. El problema es que esto puede ofrecer una ayuda limitada para distinguir entre explicaciones simples y posibilidades alarmantes. Con la creciente presión sobre los servicios sanitarios, creemos que las personas necesitan mejores herramientas para comprender la información sanitaria cuando el acceso es complicado.
La IA generativa puede intervenir para ayudar. Ofrece respuestas más personalizadas a las consultas de los usuarios, hace preguntas específicas de seguimiento y guía a las personas hacia una siguiente mejor acción recomendada a cualquier hora del día. Si se hace bien, esto tiene el potencial de ampliar el acceso oportuno a una orientación fiable y marcar la diferencia en un momento de necesidad.
En los productos de consumo de Microsoft AI, incluidos Bing y Copilot, ya gestionamos más de 50 millones de preguntas de salud al día. Nos tomamos esta responsabilidad muy en serio. En noviembre de 2024, formamos un equipo dedicado a la salud del consumidor para centrarnos en las áreas que abordan las preguntas más urgentes de los usuarios, incluida:
Información sanitaria fiable
Las respuestas de salud de Copilot se basan en miles de fuentes creíbles, identificadas mediante principios publicados de forma independiente por la Academia Nacional de Medicina. Proporcionamos citas claras sobre la procedencia de la información mediante enlaces de un solo clic hacia el material fuente. Junto con las respuestas generativas, también presentamos tarjetas de respuestas escritas por expertos en colaboración con organizaciones respetadas como Harvard Health.
Navegación de cuidados
En Estados Unidos, Copilot ahora se conecta a directorios de proveedores en tiempo real, por lo que los usuarios pueden encontrar proveedores de alta calidad por especialidad, ubicación y preferencias personales. Con esta información, los usuarios pueden reservar citas y continuar su camino hacia la salud. Trabajamos de manera activa para expandir este servicio a nivel global.
Nuestra investigación sobre el uso respalda la importancia de estas áreas. Acertar la respuesta es en verdad importante para su salud y bienestar. Por eso el equipo de Microsoft AI Health trabaja para ofrecer un contexto clínico más rico y un razonamiento clínico más sólido en conversaciones que profundicen nuestra capacidad para dar respuestas claras, relevantes y seguras. Un contexto más rico significa que Copilot puede entender patrones y explicar lo que podría ocurrir en lugar de responder de forma aislada. Un razonamiento más sólido permite a Copilot desglosar preguntas complejas paso a paso, destacar lo importante y ayudar a las personas a prepararse para conversaciones más productivas con los clínicos.
La IA debe cumplir con la salud. Continuaremos con nuestro trabajo para que así sea.
Copilot no está destinado para diagnosticar, tratar u prevenir enfermedades u otras condiciones y no sustituye el asesoramiento médico profesional.
Today, Amazon Connect is announcing enhancements to AI-powered predictive insights that make it easier for businesses to deliver proactive, personalized customer experiences at scale. Building on the five recommendation algorithms launched at re:Invent 2025, AI-powered predictive insights now support up to 40 million product catalog items (8X increase), are available in message templates for trigger-based campaigns, and deliver up to 14% improved model accuracy. These enhancements enable businesses to automatically engage customers with the right message at the right time, while reducing the time required to deploy AI-powered personalization.
Businesses can now deliver trigger-based campaigns to initiate personalized outreach based on customer behavior and predictive signals – such as sending product recommendations when a customer abandons their cart or offering complementary services after a purchase. Businesses can now deliver targeted campaigns for specific customer cohorts based on predicted preferences and behaviors. Improved model accuracy and reduced training time mean businesses can deploy personalized experiences faster with greater confidence in the recommendations provided to customers.
With Amazon Connect Customer Profiles, you only pay-as-you-go for utilized profiles. Public preview for AI-powered predictive insights enhancements is available in Europe (Frankfurt), US East (N. Virginia), Asia Pacific (Seoul), Asia Pacific (Tokyo), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central).
Today, Amazon Connect is announcing enhancements to AI-powered predictive insights that make it easier for businesses to deliver proactive, personalized customer experiences at scale. Building on the five recommendation algorithms launched at re:Invent 2025, AI-powered predictive insights now support up to 40 million product catalog items (8X increase), are available in message templates for trigger-based campaigns, and deliver up to 14% improved model accuracy. These enhancements enable businesses to automatically engage customers with the right message at the right time, while reducing the time required to deploy AI-powered personalization.
Businesses can now deliver trigger-based campaigns to initiate personalized outreach based on customer behavior and predictive signals – such as sending product recommendations when a customer abandons their cart or offering complementary services after a purchase. Businesses can now deliver targeted campaigns for specific customer cohorts based on predicted preferences and behaviors. Improved model accuracy and reduced training time mean businesses can deploy personalized experiences faster with greater confidence in the recommendations provided to customers.
With Amazon Connect Customer Profiles, you only pay-as-you-go for utilized profiles. Public preview for AI-powered predictive insights enhancements is available in Europe (Frankfurt), US East (N. Virginia), Asia Pacific (Seoul), Asia Pacific (Tokyo), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central).
To learn more, visit our webpages for Customer Profiles and explore the AI-powered predictive insights documentation.
Amazon OpenSearch Service now extends in-place cluster volume size increases to volumes exceeding 3 TiB. With this enhancement, you can scale storage capacity across all volume sizes without requiring a blue/green deployment.
Previously, you could perform volume increases up to 3 TiB on your clusters without a blue/green deployment. This release removes that limitation, making it easier for you to scale up quickly even beyond 3 TiB when required. Domains that already have a volume size above 3 TiB will require a blue/green deployment the first time a volume increase is made; subsequent volume increases will not require a blue/green deployment.
Decreasing storage volume size, or making volume increases within short intervals, will still require a blue/green deployment. You can use the dry-run option to check whether your change requires a blue/green deployment.
This feature is available in all AWS Commercial and AWS GovCloud (US) Regions where Amazon OpenSearch Service is available. See here for a full list of our Regions. To learn more about Amazon OpenSearch Service configurations, visit the documentation page.
Amazon OpenSearch Service now extends in-place cluster volume size increases to volumes exceeding 3 TiB. With this enhancement, you can scale storage capacity across all volume sizes without requiring a blue/green deployment. Previously, you could perform volume increases up to 3 TiB on your clusters without a blue/green deployment. This release removes that limitation, making it easier for you to scale up quickly even beyond 3 TiB when required. Domains that already have a volume size above 3 TiB will require a blue/green deployment the first time a volume increase is made; subsequent volume increases will not require a blue/green deployment. Decreasing storage volume size, or making volume increases within short intervals, will still require a blue/green deployment. You can use the dry-run option to check whether your change requires a blue/green deployment. This feature is available in all AWS Commercial and AWS GovCloud (US) Regions where Amazon OpenSearch Service is available. See here for a full list of our Regions. To learn more about Amazon OpenSearch Service configurations, visit the documentation page.
Today, AWS announced the general availability of Amazon Route 53 Global Resolver, an internet-reachable anycast DNS resolver that delivers easy, secure, and reliable DNS resolution for authorized clients from anywhere. Global Resolver is now available across 30 AWS Regions, with support for both IPv4 and IPv6 DNS query traffic.
Previewed at re:Invent 2025 in 11 AWS Regions, Global Resolver gives authorized clients in your organization anycast DNS resolution of public internet domains and private domains associated with Route 53 private hosted zones — from any location. It also provides DNS query filtering to block potentially malicious domains, not-safe-for-work domains, and domains associated with advanced DNS threats such as DNS tunneling and Domain Generation Algorithms (DGA), along with centralized query logging. With general availability, Global Resolver adds protection against Dictionary DGA threats.
New customers can explore Global Resolver with a 30-day free trial. For pricing and feature details, visit the service page. To see supported AWS Regions, see the region table. To get started, see the documentation.
Today, AWS announced the general availability of Amazon Route 53 Global Resolver, an internet-reachable anycast DNS resolver that delivers easy, secure, and reliable DNS resolution for authorized clients from anywhere. Global Resolver is now available across 30 AWS Regions, with support for both IPv4 and IPv6 DNS query traffic. Previewed at re:Invent 2025 in 11 AWS Regions, Global Resolver gives authorized clients in your organization anycast DNS resolution of public internet domains and private domains associated with Route 53 private hosted zones — from any location. It also provides DNS query filtering to block potentially malicious domains, not-safe-for-work domains, and domains associated with advanced DNS threats such as DNS tunneling and Domain Generation Algorithms (DGA), along with centralized query logging. With general availability, Global Resolver adds protection against Dictionary DGA threats. New customers can explore Global Resolver with a 30-day free trial. For pricing and feature details, visit the service page. To see supported AWS Regions, see the region table. To get started, see the documentation.
Amazon Connect now supports conversational analytics for email contacts, enabling contact center managers to automatically categorize emails, redact personally identifiable information (PII), and generate contact summaries. This allows you to quickly identify emerging trends, better maintain compliance by protecting sensitive information, and reduce the time spent reviewing agent performance. For example, when customers email about account issues, Amazon Connect automatically categorizes the email, redacts sensitive information, and generates a summary for supervisor review.
To enable this feature, add the Set recording, analytics and processing behavior block to your flows before an email contact is assigned to your agent or sent to your end customer. You can customize which PII types to redact, choose whether redacted content shows specific PII type indicators e.g., [SSN] or generic markings ([PII]), opt to store both original and redacted versions in separate storage, as well as enable contact summaries. Using these analytics, you can quickly create rules to automatically trigger actions such as assigning categories, creating tasks, or updating cases.
Amazon Connect conversational analytics is available in the US East (N. Virginia), US West (Oregon), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London) regions. To learn more and get started, please refer to the help documentation or visit the Amazon Connect website.
Amazon Connect now supports conversational analytics for email contacts, enabling contact center managers to automatically categorize emails, redact personally identifiable information (PII), and generate contact summaries. This allows you to quickly identify emerging trends, better maintain compliance by protecting sensitive information, and reduce the time spent reviewing agent performance. For example, when customers email about account issues, Amazon Connect automatically categorizes the email, redacts sensitive information, and generates a summary for supervisor review. To enable this feature, add the Set recording, analytics and processing behavior block to your flows before an email contact is assigned to your agent or sent to your end customer. You can customize which PII types to redact, choose whether redacted content shows specific PII type indicators e.g., [SSN] or generic markings ([PII]), opt to store both original and redacted versions in separate storage, as well as enable contact summaries. Using these analytics, you can quickly create rules to automatically trigger actions such as assigning categories, creating tasks, or updating cases. Amazon Connect conversational analytics is available in the US East (N. Virginia), US West (Oregon), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London) regions. To learn more and get started, please refer to the help documentation or visit the Amazon Connect website.
Today, Amazon Connect announces the preview of an AI-powered assistant that enables contact center managers to get instant answers to operational questions using natural language. You can query across 150+ Amazon Connect metrics, including agent scheduling, self-service experience, and performance evaluations, with historical data for all of these, and receive results in seconds—eliminating hours of manual data gathering. The assistant can also diagnose underlying issues, such as identifying which queues are at risk of missing service level targets and recommending specific recovery actions.
This feature is available as a preview. To request access, contact your AWS account team or an AWS Representative. To learn more about Amazon Connect, the AWS cloud-based contact center, visit the Amazon Connect website.
Today, Amazon Connect announces the preview of an AI-powered assistant that enables contact center managers to get instant answers to operational questions using natural language. You can query across 150+ Amazon Connect metrics, including agent scheduling, self-service experience, and performance evaluations, with historical data for all of these, and receive results in seconds—eliminating hours of manual data gathering. The assistant can also diagnose underlying issues, such as identifying which queues are at risk of missing service level targets and recommending specific recovery actions.
This feature is available as a preview. To request access, contact your AWS account team or an AWS Representative. To learn more about Amazon Connect, the AWS cloud-based contact center, visit the Amazon Connect website.
We are announcing User Preferences in Amazon Quick Suite – a new feature that gives users greater control over how Quick looks, feels, and works for them. With User Preferences, users can now customize their Chat panel layout by setting it to open expanded or collapsed by default; Quick also automatically remembers their last used setting and resumes from where they left off. Users can select a default chat agent and pre-select a default knowledge scope for My Assistant, so their preferred agent is ready each time they return to Quick. Users can also personalize their experience by letting Quick know what to call them and sharing their area of focus at work – Quick uses this context to personalize responses and make interactions more relevant. Finally, users can view and manage their memories directly from User Preferences.
Previously, users had no way to persist their preferred Chat settings, agent selection, or personal context across sessions. User Preferences addresses this by giving users a single place to configure how Quick works for them, saving time and making every interaction feel more personalized from the start.
User Preferences is available in all AWS Regions where Amazon Quick Suite is available. To learn more, visit the Amazon Quick Suite User Guide.
We are announcing User Preferences in Amazon Quick Suite – a new feature that gives users greater control over how Quick looks, feels, and works for them. With User Preferences, users can now customize their Chat panel layout by setting it to open expanded or collapsed by default; Quick also automatically remembers their last used setting and resumes from where they left off. Users can select a default chat agent and pre-select a default knowledge scope for My Assistant, so their preferred agent is ready each time they return to Quick. Users can also personalize their experience by letting Quick know what to call them and sharing their area of focus at work – Quick uses this context to personalize responses and make interactions more relevant. Finally, users can view and manage their memories directly from User Preferences. Previously, users had no way to persist their preferred Chat settings, agent selection, or personal context across sessions. User Preferences addresses this by giving users a single place to configure how Quick works for them, saving time and making every interaction feel more personalized from the start. User Preferences is available in all AWS Regions where Amazon Quick Suite is available. To learn more, visit the Amazon Quick Suite User Guide.
Amazon Cognito is now available in the AWS Asia Pacific (Taipei) and Asia Pacific (New Zealand) Regions. This launch introduces all Amazon Cognito features and tiers, allowing customers to implement secure sign-in and access control for users, AI agents, and microservices in minutes.
Amazon Cognito is now available in the AWS Asia Pacific (Taipei) and Asia Pacific (New Zealand) Regions. This launch introduces all Amazon Cognito features and tiers, allowing customers to implement secure sign-in and access control for users, AI agents, and microservices in minutes.
For a full list of regions where Amazon Cognito is available, refer to the AWS Region Table. To learn more about Amazon Cognito, refer to Developer Guide, Product Detail Page, and Pricing Detail Page.
AWS Identity and Access Management (IAM) Roles Anywhere now supports the FIPS 204 Module-Lattice Digital Signature Standard (ML-DSA), a quantum-resistant digital signature algorithm standardized by the National Institute of Standards and Technology (NIST) to help protect against threat actors in possession of a large-scale quantum computer. ML-DSA is particularly valuable for IAM Roles Anywhere customers who authenticate workloads to AWS using X.509 certificates issued by certificate authorities, where a weakened signature algorithm could allow an unintended user to issue certificates and obtain unauthorized access.
IAM Roles Anywhere enables workloads running outside of AWS to obtain temporary AWS credentials using X.509 certificates to access AWS resources. You establish trust between your AWS environment and your public key infrastructure (PKI) by creating a trust anchor, either by referencing your AWS Private Certificate Authority or registering your own certificate authorities (CAs) with IAM Roles Anywhere. You can now use ML-DSA-signed CA certificates as IAM Roles Anywhere trust anchors, and issue end entity certificates bound to ML-DSA keys.
This feature is available in all AWS Regions where IAM Roles Anywhere is available, including the AWS GovCloud (US) Regions, AWS European Sovereign Cloud (Germany) Region, and China Regions. To learn more, see the IAM Roles Anywhere User Guide.
AWS Identity and Access Management (IAM) Roles Anywhere now supports the FIPS 204 Module-Lattice Digital Signature Standard (ML-DSA), a quantum-resistant digital signature algorithm standardized by the National Institute of Standards and Technology (NIST) to help protect against threat actors in possession of a large-scale quantum computer. ML-DSA is particularly valuable for IAM Roles Anywhere customers who authenticate workloads to AWS using X.509 certificates issued by certificate authorities, where a weakened signature algorithm could allow an unintended user to issue certificates and obtain unauthorized access. IAM Roles Anywhere enables workloads running outside of AWS to obtain temporary AWS credentials using X.509 certificates to access AWS resources. You establish trust between your AWS environment and your public key infrastructure (PKI) by creating a trust anchor, either by referencing your AWS Private Certificate Authority or registering your own certificate authorities (CAs) with IAM Roles Anywhere. You can now use ML-DSA-signed CA certificates as IAM Roles Anywhere trust anchors, and issue end entity certificates bound to ML-DSA keys. This feature is available in all AWS Regions where IAM Roles Anywhere is available, including the AWS GovCloud (US) Regions, AWS European Sovereign Cloud (Germany) Region, and China Regions. To learn more, see the IAM Roles Anywhere User Guide.
