Starting today, the general-purpose Amazon EC2 M8a instances are available in AWS Asia Pacific (Mumbai) region. M8a instances are powered by 5th Gen AMD EPYC processors (formerly code named Turin) with a maximum frequency of 4.5 GHz, deliver up to 30% higher performance, and up to 19% better price-performance compared to M7a instances.
M8a instances deliver 45% more memory bandwidth compared to M7a instances, making these instances ideal for even latency sensitive workloads. M8a instances deliver even higher performance gains for specific workloads. M8a instances are up to 60% faster for GroovyJVM benchmark, and up to 39% faster for Cassandra benchmark compared to Amazon EC2 M7a instances. M8a instances are SAP-certified and offer 12 sizes including 2 bare metal sizes. This range of instance sizes allows customers to precisely match their workload requirements.
M8a instances are built using the latest sixth generation AWS Nitro Cards and ideal for applications that benefit from high performance and high throughput such as financial applications, gaming, rendering, application servers, simulation modeling, mid-size data stores, application development environments, and caching fleets.
To get started, sign in to the AWS Management Console. Customers can purchase these instances via Savings Plans, On-Demand instances, and Spot instances. For more information visit the Amazon EC2 M8a instance page.
Starting today, the general-purpose Amazon EC2 M8a instances are available in AWS Asia Pacific (Mumbai) region. M8a instances are powered by 5th Gen AMD EPYC processors (formerly code named Turin) with a maximum frequency of 4.5 GHz, deliver up to 30% higher performance, and up to 19% better price-performance compared to M7a instances. M8a instances deliver 45% more memory bandwidth compared to M7a instances, making these instances ideal for even latency sensitive workloads. M8a instances deliver even higher performance gains for specific workloads. M8a instances are up to 60% faster for GroovyJVM benchmark, and up to 39% faster for Cassandra benchmark compared to Amazon EC2 M7a instances. M8a instances are SAP-certified and offer 12 sizes including 2 bare metal sizes. This range of instance sizes allows customers to precisely match their workload requirements. M8a instances are built using the latest sixth generation AWS Nitro Cards and ideal for applications that benefit from high performance and high throughput such as financial applications, gaming, rendering, application servers, simulation modeling, mid-size data stores, application development environments, and caching fleets. To get started, sign in to the AWS Management Console. Customers can purchase these instances via Savings Plans, On-Demand instances, and Spot instances. For more information visit the Amazon EC2 M8a instance page.
OpenAI GPT, OpenAI GPT OSS, and NVIDIA Nemotron models are now FedRAMP High and Department of Defense Cloud Computing Security Requirements Guide (DoD CC SRG) Impact Level (IL) 4 and 5 approved within Amazon Bedrock in the AWS GovCloud (US) Regions.
Federal agencies, public sector organizations, and other enterprises with FedRAMP High and DoD CC SRG IL-4/5 compliance requirements can now use these models on Amazon Bedrock to build and scale generative AI applications with confidence that they meet the security and compliance standards required for government workloads. These models are powered by Mantle, a next-generation distributed inference engine on Amazon Bedrock, which provides high-performance serverless inference with zero operator access, automated capacity management, and out-of-the-box compatibility with OpenAI API specifications.
OpenAI GPT, OpenAI GPT OSS, and NVIDIA Nemotron models are now FedRAMP High and Department of Defense Cloud Computing Security Requirements Guide (DoD CC SRG) Impact Level (IL) 4 and 5 approved within Amazon Bedrock in the AWS GovCloud (US) Regions.
Federal agencies, public sector organizations, and other enterprises with FedRAMP High and DoD CC SRG IL-4/5 compliance requirements can now use these models on Amazon Bedrock to build and scale generative AI applications with confidence that they meet the security and compliance standards required for government workloads. These models are powered by Mantle, a next-generation distributed inference engine on Amazon Bedrock, which provides high-performance serverless inference with zero operator access, automated capacity management, and out-of-the-box compatibility with OpenAI API specifications.
To learn more, visit the Amazon Bedrock product page, Amazon Bedrock documentation, and the AWS GovCloud (US) compliance page. To get started, visit the Amazon Bedrock console.
AWS Network Firewall now supports two new managed rule groups from VisionHeight, available through AWS Marketplace: Zero-Day Threat Protection, and Noisy Scanners and Tor Protection. These rule groups expand the managed rules offerings for AWS Network Firewall, giving customers access to proprietary threat intelligence built on VisionHeight’s Pulse telemetry.
Zero-Day Threat Protection proactively blocks malicious IP infrastructure before it appears on public blocklists. This rule group helps organizations get ahead of emerging threats by weeks, strengthening defense for workloads facing targeted attacks. Tor Protection reduces firewall log noise by blocking communication with active Tor exit nodes and filtering traffic from known high-volume scanning sources. With daily refresh cycles, this rule group suppresses noise at first packet —before events are generated—lowering SOC alert volume, reducing SIEM ingestion costs, and removing Tor as a path into or out of your environment.
Managed rules for AWS Network Firewall are available from AWS Marketplace sellers including Check Point, Fortinet, Infoblox, Lumen, Rapid7, ThreatSTOP, Trend Micro, and VisionHeight. For a full list of supported regions, visit the AWS Regional Services page.
To get started, visit the AWS Network Firewall console or browse available managed rules in AWS Marketplace. For more information, see the AWS Network Firewall product page and the service documentation.
AWS Network Firewall now supports two new managed rule groups from VisionHeight, available through AWS Marketplace: Zero-Day Threat Protection, and Noisy Scanners and Tor Protection. These rule groups expand the managed rules offerings for AWS Network Firewall, giving customers access to proprietary threat intelligence built on VisionHeight’s Pulse telemetry. Zero-Day Threat Protection proactively blocks malicious IP infrastructure before it appears on public blocklists. This rule group helps organizations get ahead of emerging threats by weeks, strengthening defense for workloads facing targeted attacks. Tor Protection reduces firewall log noise by blocking communication with active Tor exit nodes and filtering traffic from known high-volume scanning sources. With daily refresh cycles, this rule group suppresses noise at first packet —before events are generated—lowering SOC alert volume, reducing SIEM ingestion costs, and removing Tor as a path into or out of your environment. Managed rules for AWS Network Firewall are available from AWS Marketplace sellers including Check Point, Fortinet, Infoblox, Lumen, Rapid7, ThreatSTOP, Trend Micro, and VisionHeight. For a full list of supported regions, visit the AWS Regional Services page. To get started, visit the AWS Network Firewall console or browse available managed rules in AWS Marketplace. For more information, see the AWS Network Firewall product page and the service documentation.
Kiro is now FedRAMP High and Department of Defense Cloud Computing Security Requirements Guide (DoD CC SRG) Impact Level (IL) 4 and 5 authorized in the AWS GovCloud (US) Regions.
Federal agencies, public sector organizations, and other enterprises with FedRAMP High and DoD CC SRG IL-4/5 compliance requirements can now use Kiro as their agentic engineering partner with confidence that it meets the security and compliance standards required for sensitive workloads.
Kiro is an agentic AI with an integrated development environment (IDE) and command-line interface (CLI) that helps you build applications from prototype to production with spec-driven development. From simple to complex tasks, Kiro works alongside you to turn prompts into detailed specs, then into working code, docs, and tests — so what you build is exactly what you want and ready to share with your team. With native Model Context Protocol (MCP) support, Kiro connects to documentation, databases, APIs, and other enterprise resources, providing capability for mission-critical development workflows.
For more details about Kiro in AWS GovCloud (US), visit the GovCloud documentation or contact your AWS account team for more information. To learn more about Kiro, visit the Kiro product page.
Kiro is now FedRAMP High and Department of Defense Cloud Computing Security Requirements Guide (DoD CC SRG) Impact Level (IL) 4 and 5 authorized in the AWS GovCloud (US) Regions. Federal agencies, public sector organizations, and other enterprises with FedRAMP High and DoD CC SRG IL-4/5 compliance requirements can now use Kiro as their agentic engineering partner with confidence that it meets the security and compliance standards required for sensitive workloads. Kiro is an agentic AI with an integrated development environment (IDE) and command-line interface (CLI) that helps you build applications from prototype to production with spec-driven development. From simple to complex tasks, Kiro works alongside you to turn prompts into detailed specs, then into working code, docs, and tests — so what you build is exactly what you want and ready to share with your team. With native Model Context Protocol (MCP) support, Kiro connects to documentation, databases, APIs, and other enterprise resources, providing capability for mission-critical development workflows. For more details about Kiro in AWS GovCloud (US), visit the GovCloud documentation or contact your AWS account team for more information. To learn more about Kiro, visit the Kiro product page.
AWS GovCloud (US) customers now have their technical support cases routed to US-based, US-citizen cloud support engineers by default with no opt-in or special request required. This enhancement ensures that 24/7 technical support across both AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions is handled exclusively by full-time AWS employees who are US citizens on US soil, trained to maintain ITAR compliance and meet other applicable AWS GovCloud (US) requirements.
With this update, AWS GovCloud (US) customers benefit from cloud support engineers with the permissions and tools to work directly within their regulated environments, enabling faster diagnosis and resolution of technical issues. Support is available around the clock through the AWS GovCloud (US) Console, API access for automated workflows, click-to-call for urgent issues, and live chat for quick questions.
To learn more about AWS GovCloud (US), visit the product page and user guide; to learn more about the AWS GovCloud (US). For a deeper dive into this launch, read the full blog post.
AWS GovCloud (US) customers now have their technical support cases routed to US-based, US-citizen cloud support engineers by default with no opt-in or special request required. This enhancement ensures that 24/7 technical support across both AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions is handled exclusively by full-time AWS employees who are US citizens on US soil, trained to maintain ITAR compliance and meet other applicable AWS GovCloud (US) requirements. With this update, AWS GovCloud (US) customers benefit from cloud support engineers with the permissions and tools to work directly within their regulated environments, enabling faster diagnosis and resolution of technical issues. Support is available around the clock through the AWS GovCloud (US) Console, API access for automated workflows, click-to-call for urgent issues, and live chat for quick questions. To learn more about AWS GovCloud (US), visit the product page and user guide; to learn more about the AWS GovCloud (US). For a deeper dive into this launch, read the full blog post.
Starting today, customers can use Amazon OpenSearch Ingestion in the Europe (Paris) Region (eu-west-3) for ingesting data into their Amazon OpenSearch Service managed clusters or serverless collections.
Amazon OpenSearch Ingestion is a fully managed data ingestion tier that allows you to ingest and process data before indexing it in Amazon OpenSearch managed clusters or serverless collections. Amazon OpenSearch Ingestion provides a no-code experience to filter, transform, redact, and route data into Amazon OpenSearch Service. Amazon OpenSearch Ingestion automatically provisions and scales the underlying resources to meet the fluctuating demands of your workloads.
With this launch, Amazon OpenSearch Ingestion is now generally available in 17 AWS regions: US East (Ohio), US East (N. Virginia), US West (Oregon), US West (N. California), Europe (Ireland), Europe (London), Europe (Frankfurt), Europe (Spain), Europe (Paris), Asia Pacific (Tokyo), Asia Pacific (Sydney), Asia Pacific (Singapore), Asia Pacific (Mumbai), Asia Pacific (Seoul), Canada (Central), South America (Sao Paulo), and Europe (Stockholm).
Starting today, customers can use Amazon OpenSearch Ingestion in the Europe (Paris) Region (eu-west-3) for ingesting data into their Amazon OpenSearch Service managed clusters or serverless collections. Amazon OpenSearch Ingestion is a fully managed data ingestion tier that allows you to ingest and process data before indexing it in Amazon OpenSearch managed clusters or serverless collections. Amazon OpenSearch Ingestion provides a no-code experience to filter, transform, redact, and route data into Amazon OpenSearch Service. Amazon OpenSearch Ingestion automatically provisions and scales the underlying resources to meet the fluctuating demands of your workloads. With this launch, Amazon OpenSearch Ingestion is now generally available in 17 AWS regions: US East (Ohio), US East (N. Virginia), US West (Oregon), US West (N. California), Europe (Ireland), Europe (London), Europe (Frankfurt), Europe (Spain), Europe (Paris), Asia Pacific (Tokyo), Asia Pacific (Sydney), Asia Pacific (Singapore), Asia Pacific (Mumbai), Asia Pacific (Seoul), Canada (Central), South America (Sao Paulo), and Europe (Stockholm). To learn more, see the Amazon OpenSearch Ingestion webpage and the Amazon OpenSearch Ingestion Developer Guide.
Amazon Redshift announces the availability of All Upfront and Partial Upfront payment options for 1-year and 3-year reserved instances for RG instances. Reserved instances allow customers to benefit from significant savings over on-demand rates. The new payment options join the previously available No Upfront option, giving customers greater flexibility to optimize compute costs based on their financial preferences. All Upfront delivers the maximum discount by paying for the full reservation term at the start, while Partial Upfront splits the cost between an initial payment and lower monthly installments.
Amazon Redshift RG reserved instances with All Upfront and Partial Upfront payment options are now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Canada (Central), South America (São Paulo), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Milan), Europe (Spain), Africa (Cape Town), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Mumbai), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Malaysia), Asia Pacific (Hyderabad), Asia Pacific (Taiwan), Asia Pacific (Melbourne), Asia Pacific (Bangkok), and Mexico (Central).
Amazon Redshift announces the availability of All Upfront and Partial Upfront payment options for 1-year and 3-year reserved instances for RG instances. Reserved instances allow customers to benefit from significant savings over on-demand rates. The new payment options join the previously available No Upfront option, giving customers greater flexibility to optimize compute costs based on their financial preferences. All Upfront delivers the maximum discount by paying for the full reservation term at the start, while Partial Upfront splits the cost between an initial payment and lower monthly installments.
Amazon Redshift RG reserved instances with All Upfront and Partial Upfront payment options are now available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Canada (Central), South America (São Paulo), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Milan), Europe (Spain), Africa (Cape Town), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Mumbai), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Osaka), Asia Pacific (Malaysia), Asia Pacific (Hyderabad), Asia Pacific (Taiwan), Asia Pacific (Melbourne), Asia Pacific (Bangkok), and Mexico (Central).
For pricing details, visit the Amazon Redshift pricing page.
Por: Brian Jones, vicepresidente – Excel Product Group
Hay un patrón en cómo la nueva tecnología llega al mundo. Oleada tras oleada, desde el PC hasta la base de datos relacional y la nube, la nueva tecnología llega primero a los desarrolladores, y las finanzas suelen ser las siguientes. Para los profesionales de finanzas, una mejor herramienta es una ventaja y el trabajo es modelar la realidad con un poco más de precisión que ayer. Durante décadas, esa herramienta ha sido Excel: donde se cierra el trimestre y se discute la previsión línea por línea, donde cada número se remonta a una fuente.
Así que cuando la IA entra en finanzas, tiene que superar la misma barra: mostrar su trabajo, usar datos fiables y rastrear cada cálculo. Muchas herramientas de IA afirman estar diseñadas para finanzas; Microsoft 365 Copilot en Excel lo demuestra en la práctica.
En Planificación y Análisis Financiero (FP&A, por sus siglas en inglés), Contabilidad, Fiscalidad, Cumplimiento y Tesorería, Microsoft Finance ejecuta Copilot en Excel en flujos de trabajo reales, donde dedica menos tiempo a buscar información y reconstruir análisis, y libera a los equipos para aplicar juicio a las decisiones. Lo moldean tanto como lo usan, indicándonos dónde falla y empujan el producto hacia el estándar que su propio trabajo exige. Cuando llega a ustedes, ya ha sido sometido a pruebas de presión por una organización financiera que opera en la frontera.
Hoy presentamos nuevas funciones diseñadas para que los profesionales financieros puedan seguir haciéndolo, con habilidades para flujos de trabajo repetibles, nuevos conectores financieros para datos confiables y capacidades mejoradas para la trazabilidad.
Diseñado para la complejidad del trabajo financiero
Antes de que las nuevas capacidades de Copilot se envíen en Excel, las evaluamos en niveles graduados de complejidad de tareas y benchmarks que reflejan el trabajo diario de los equipos financieros, para asegurar que puedan ofrecer un flujo de trabajo en varios pasos con un resultado fiable y verificable, en lugar de completar solo una tarea. Para saber más sobre cómo evaluamos, den un vistazo interno a nuestro marco de evaluación, benchmarks y enfoque específico de cada sector para finanzas.
Alcanzar el alto nivel del trabajo profesional en finanzas no es algo que hayamos hecho solos. También nos hemos asociado con el Financial Modeling Institute (FMI), el organismo global que acredita a los modeladores más exigentes del sector. Su biblioteca de casos reales de modelización financiera se ha convertido en una parte fundamental de cómo evaluamos Copilot en Excel para trabajos financieros.
Ajustado a sus estándares
Hoy presentamos habilidades que permiten a los equipos definir cómo Copilot debe completar procesos comunes como construir un DCF, cerrar libros, actualizar un modelo mensual de informes o preparar un análisis de variaciones. En lugar de empezar desde cero cada vez, una habilidad guía a Copilot a través de los pasos, para aplicar la estructura y el formato adecuados, y ayudar a producir un resultado más fácil de revisar, reutilizar y confiar.
Ahora está disponible una biblioteca de habilidades de finanzas de ejemplo, y pueden crear sus propias habilidades personalizadas a través de un archivo de markdown de estándar abierto. Guarden un archivo SKILL.md en su OneDrive, y Copilot lo recogerá para construir un modelo de tres sentencias o un paquete de placa por medio del proceso que definan para él. Descubran más sobre cómo crear, usar y gestionar habilidades aquí.
Desarrolladores y socios podrán pronto desarrollar y desplegar habilidades a través de Microsoft Marketplace y Microsoft 365 Admin Center. Ya hemos empezado a trabajar con una primera oleada de socios, incluidas soluciones financieras y ERP como LSEG,Ramp, Rogo, samaya.ai, Velixo y Vena.
Copilot también puede adaptarse a cómo les gusta trabajar en Excel. Con laPersonalización, puede establecer preferencias una vez y que Copilot las aplique de manera consistente, mientras que las reglas del cuaderno capturan la estructura, el nombre y las convenciones de fórmulas como una hoja en el libro que sigue al archivo.
Basado en datos de confianza
Copilot en Excel se conecta directo con los datos en los que confían los profesionales financieros, al incorporar datos de mercado, fundamentos e investigación directo al cuaderno de trabajo, de modo que el análisis parte de las fuentes más recientes en lugar de obtener datos de manera manual. Además de los conectores LSEG y Moody’s que lanzamos en mayo, hoy ampliamos sus opciones con más conectores de datos financieros para incorporar datos de mercados públicos y privados a Copilot en Excel.
CB Insights aporta inteligencia predictiva sobre empresas y mercados privados a Excel. Los equipos lo utilizan para localizar empresas prometedoras, evaluar mercados emergentes y apoyar los flujos de trabajo de estrategia, fusiones y adquisiciones y desarrollo corporativo.
Daloopa proporciona fundamentos listos para auditoría obtenidos de documentos ante la SEC, presentaciones a inversores, comunicados de prensa y otros materiales de empresas públicas. Los analistas la utilizan para actualizar modelos operativos, construir tablas comparables, hacer análisis financieros complejos y reducir la entrada manual de datos en las presentaciones.
FactSet conecta flujos de trabajo de Excel con datos financieros y alternativos utilizados por profesionales de la inversión, instituciones financieras y empresas. Los equipos la utilizan para modelar, seleccionar, analizar el mercado y realizar flujos de trabajo de investigación que dependen de datos institucionales de confianza.
Morningstar incorpora la investigación y datos de inversión a Excel, incluidos análisis de analistas, calificaciones y análisis de carteras. Los equipos de inversión la utilizan para evaluar las posiciones, comparar fondos, analizar carteras y apoyar las decisiones de asignación de activos.
PitchBook incorpora directo a Excel inteligencia de mercados privados de capital de nivel institucional, incluidos perfiles de empresas, historiales de operaciones, datos de fondos e investigación de analistas. Los equipos lo utilizan para crear listas de objetivos, apoyar flujos de trabajo de diligencia y filtrar inversiones por medio de datos de mercado privado de confianza e investigación experta de analistas.
S&P Global – Deterministic Retrieval, desarrollado por Kensho, proporciona acceso estructurado y basado en API a datos S&P Global para LLMs y sistemas basados en agentes. Los equipos lo utilizan para investigación de la empresa, análisis financiero, inteligencia de transcripciones y comparaciones entre múltiples entidades, con resultados predecibles y citados y control total sobre la orquestación y ejecución.
Nota: Los conectores y proveedores de datos de terceros pueden requerir licencias o suscripciones separadas del proveedor respectivo. Más información aquí. FactSet está en vista previa y estará disponible en general en julio.
Desbloquear flujos de trabajo financieros
Combinadas con Work IQ para consolidarse en el contexto laboral, estas funciones desbloquean escenarios reales en los que trabajan los equipos financieros cada día. Algunos ejemplos de prompts que ahora pueden probar con Work IQ, habilidades y conectores (Nota: los datos externos mencionados en los prompts siguientes pueden requerir uno o más conectores).
Cerrar los libros: Compara los datos reales del trimestre pasado con la planificación utilizando revisiones internas de previsión y cartas de planificación. Identifica las cinco mayores variaciones en ingresos, gastos, márgenes y flujo de caja, explica los posibles factores y redacta un resumen de revisión empresarial listo para ejecutivos con análisis @variance.
Actualizar la previsión de la previsión actual: Avanza la previsión actual usando las últimas suposiciones y presupuestos aprobados por mi equipo. Incorpora datos de mercado, concilia los cambios con el plan operativo actual y resume los principales factores detrás de la actualización con @model-update.
Construir el modelo de valoración: Utiliza el análisis @comps para construir un DCF, un análisis de empresa comparable y un modelo de sensibilidad para esta empresa. Consulta los fundamentos financieros, las expectativas de los analistas, los índices de índice de mercado y los múltiplos de transacciones para explicar los principales factores de valoración.
Encontrar la siguiente adquisición: Utiliza el filtro de @deal para ayudar a identificar candidatos a adquisición que coincidan con nuestros documentos de estrategia interna y criterios de adquisición. Combina el rendimiento de la empresa y las señales de mercado con el historial de financiación y la actividad de los inversores para evaluar, clasificar y recomendar las oportunidades más sólidas.
Analizar el rendimiento de la cartera: Utiliza la monitorización @portfolio para evaluar el rendimiento de esta cartera frente a los objetivos de inversión y los materiales internos del comité de inversión. Consulta análisis y calificaciones de fondos junto con datos de rendimiento de mercado y riesgo para identificar riesgos de concentración y recomendar ajustes de cartera.
Mantenerse por delante de los resultados: Utiliza @catalyst-calendar para analizar resultados de ganancias, revisiones de estimaciones, expectativas de los analistas y comentarios de la dirección sobre las empresas de esta lista. Recopila previsiones de consenso, inteligencia de transcripciones y datos de mercado para identificar cambios de sentimiento y resumir los desarrollos que más importan a los inversores.
Controlable por diseño
En finanzas, la respuesta por sí sola no es suficiente. Tienen que saber cómo llegaron ahí. Ya sea al actualizar una previsión, actualizar un modelo de informes del consejo o revisar cambios antes del cierre del trimestre, los equipos financieros necesitan lo mismo que siempre han exigido a Excel: visibilidad sobre lo que ha cambiado, confianza en la metodología y un camino claro.
Por eso ahora pueden elegir planificar con Copilotantes de actuar, para detallar qué rangos, hojas de trabajo, fórmulas y suposiciones pretende actualizar, junto con preguntas aclaradoras. Una vez realizados los cambios, cada edición permanece rastreable, con enlaces de vuelta a las células afectadas y los cambios ahora se atribuyen a Copilot junto con el trabajo de colaboradores en el panel Mostrar Cambios.
El resultado es un Copilot que funciona más como un analista de confianza: propone un camino a seguir, explica su enfoque y hace que cada cambio sea transparente y revisable.
Disponibilidad
La personalización, las reglas del cuaderno de trabajo, las habilidades predefinidas, los conectores federados de Copilot, Plan con Copilot y la atribución de Copilot en Mostrar Cambios están disponibles a nivel general para los clientes de Microsoft 365 Copilot en Excel para Web, Windows y Mac.
Las habilidades personalizadas están disponibles hoy a través del canal Insiders para Windows y Mac, y el mes que viene se desplegarán en disponibilidad general en Excel para Web, Windows y Mac.
Las habilidades desarrolladas por socios llegarán en el tercer trimestre de 2026. Aprendan más aquí sobre cómo desarrollar y desplegar habilidades.
Las funciones descritas en esta publicación se despliegan de manera progresiva para los clientes de Microsoft 365 Copilot. La disponibilidad específica, las regiones soportadas y los requisitos de licencia pueden variar.
Amazon EC2 introduces AMI watermarks, letting you embed custom identifiers in your private AMIs. Once applied, a watermark automatically carries forward to every AMI derived from the original, whether you copy it across regions or create a new AMI from a running instance. Watermarks also remain visible when you share an AMI with other accounts. This helps you identify trusted AMIs, track provenance, and enforce governance policies across your organization.
Each watermark includes metadata such as the AMI ID, owner ID, region, and creation timestamps, providing reliable provenance that persists regardless of how many times an AMI is copied or new AMIs are created from it. AMI Watermarks improve AMI tracking by enabling you to filter and find related AMIs across your accounts. For governance, you can combine watermarks with Allowed AMIs to restrict instance launches to only AMIs carrying approved watermarks and enforce the setting at scale across your organization through Declarative Policies.
You can start adding AMI watermarks to your private AMIs by using the AWS Management Console, AWS CLI, or SDKs. To learn more, please visit the documentation. You can also attach watermarks through EC2 Image Builder, a service used to create and manage AMIs, as part of your AMI build pipeline.
AMI watermarks are available to all customers at no additional cost in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US) Regions.
Amazon EC2 introduces AMI watermarks, letting you embed custom identifiers in your private AMIs. Once applied, a watermark automatically carries forward to every AMI derived from the original, whether you copy it across regions or create a new AMI from a running instance. Watermarks also remain visible when you share an AMI with other accounts. This helps you identify trusted AMIs, track provenance, and enforce governance policies across your organization. Each watermark includes metadata such as the AMI ID, owner ID, region, and creation timestamps, providing reliable provenance that persists regardless of how many times an AMI is copied or new AMIs are created from it. AMI Watermarks improve AMI tracking by enabling you to filter and find related AMIs across your accounts. For governance, you can combine watermarks with Allowed AMIs to restrict instance launches to only AMIs carrying approved watermarks and enforce the setting at scale across your organization through Declarative Policies. You can start adding AMI watermarks to your private AMIs by using the AWS Management Console, AWS CLI, or SDKs. To learn more, please visit the documentation. You can also attach watermarks through EC2 Image Builder, a service used to create and manage AMIs, as part of your AMI build pipeline. AMI watermarks are available to all customers at no additional cost in all AWS regions including AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US) Regions.
The AWS IoT Device SDK for Swift is now generally available, enabling Swift developers to build secure, scalable IoT applications natively on Apple platforms including macOS, iOS, and tvOS, as well as Linux. This SDK addresses the previous lack of native Swift support for AWS IoT services, providing stable, production-ready APIs specifically designed for teams managing IoT device fleets and building cross-platform IoT solutions across the Apple ecosystem.
The SDK delivers comprehensive capabilities for real-time device management and secure communication. With integrated service clients for AWS IoT Device Shadow, Jobs, and Fleet Provisioning, developers can synchronize device states between applications and AWS IoT Core, manage remote operations on connected devices at scale, and automate certificate and policy creation for secure device onboarding. The SDK also provides built-in TLS 1.3 support on Apple iOS and tvOS platforms, ensuring IoT applications use the latest industry-standard security practices for protecting data in transit.
The AWS IoT Device SDK for Swift is now generally available, enabling Swift developers to build secure, scalable IoT applications natively on Apple platforms including macOS, iOS, and tvOS, as well as Linux. This SDK addresses the previous lack of native Swift support for AWS IoT services, providing stable, production-ready APIs specifically designed for teams managing IoT device fleets and building cross-platform IoT solutions across the Apple ecosystem.
The SDK delivers comprehensive capabilities for real-time device management and secure communication. With integrated service clients for AWS IoT Device Shadow, Jobs, and Fleet Provisioning, developers can synchronize device states between applications and AWS IoT Core, manage remote operations on connected devices at scale, and automate certificate and policy creation for secure device onboarding. The SDK also provides built-in TLS 1.3 support on Apple iOS and tvOS platforms, ensuring IoT applications use the latest industry-standard security practices for protecting data in transit.
To learn more, visit the AWS IoT Device SDK documentation and explore code samples on GitHub . Get started by installing the SDK via Swift Package Manager.
