AWS Serverless Application Model Command Line Interface (SAM CLI) now supports Finch as an alternative to Docker for local development and testing of serverless applications. This gives developers greater flexibility in choosing their preferred local development environment when working with SAM CLI to build and test their serverless applications.
Developers building serverless applications spend significant time in their local development environments. SAM CLI is a command-line tool for local development and testing of serverless applications. It allows you to build, test, debug, and package your serverless applications locally before deploying to AWS Cloud. To provide the local development and testing environment for your applications, SAM CLI uses a tool that can run containers on your local device. Previously, SAM CLI only supported Docker as the tool for running containers locally. Starting today, SAM CLI also supports Finch as a container development tool. Finch is an open-source tool, developed and supported by AWS, for local container development. This means you can now choose between Docker and Finch as your preferred container tool for local development when working with SAM CLI.
You can use SAM CLI to invoke Lambda functions locally, test API endpoints, and debug your serverless applications with the same experience you would have in the AWS Cloud. With Finch support, SAM CLI now automatically detects and uses Finch as the container development tool when Docker is not available. You can also set Finch as your preferred container tool for SAM CLI. This new feature supports all core SAM CLI commands including sam build, sam local invoke, sam local start-api, and sam local start-lambda.
AWS Serverless Application Model Command Line Interface (SAM CLI) now supports Finch as an alternative to Docker for local development and testing of serverless applications. This gives developers greater flexibility in choosing their preferred local development environment when working with SAM CLI to build and test their serverless applications. Developers building serverless applications spend significant time in their local development environments. SAM CLI is a command-line tool for local development and testing of serverless applications. It allows you to build, test, debug, and package your serverless applications locally before deploying to AWS Cloud. To provide the local development and testing environment for your applications, SAM CLI uses a tool that can run containers on your local device. Previously, SAM CLI only supported Docker as the tool for running containers locally. Starting today, SAM CLI also supports Finch as a container development tool. Finch is an open-source tool, developed and supported by AWS, for local container development. This means you can now choose between Docker and Finch as your preferred container tool for local development when working with SAM CLI. You can use SAM CLI to invoke Lambda functions locally, test API endpoints, and debug your serverless applications with the same experience you would have in the AWS Cloud. With Finch support, SAM CLI now automatically detects and uses Finch as the container development tool when Docker is not available. You can also set Finch as your preferred container tool for SAM CLI. This new feature supports all core SAM CLI commands including sam build, sam local invoke, sam local start-api, and sam local start-lambda. To learn more about using SAM CLI with Finch, visit the SAM CLI developer guide.
Second-generation AWS Outposts racks are now supported in the AWS Europe (Ireland) Region. Outposts racks extend AWS infrastructure, AWS services, APIs, and tools to virtually any on-premises data center or colocation space for a truly consistent hybrid experience.
Organizations from startups to enterprises and the public sector in and outside of Europe can now order their Outposts racks connected to this new supported region, optimizing for their latency and data residency needs. Outposts allows customers to run workloads that need low latency access to on-premises systems locally while connecting back to their home Region for application management. Customers can also use Outposts and AWS services to manage and process data that needs to remain on-premises to meet data residency requirements. This regional expansion provides additional flexibility in the AWS Regions that customers’ Outposts can connect to.
To learn more about second-generation Outposts racks, read this blog post and user guide. For the most updated list of countries and territories and the AWS Regions where second-generation Outposts racks are supported, check out the Outposts rack FAQs page.
Second-generation AWS Outposts racks are now supported in the AWS Europe (Ireland) Region. Outposts racks extend AWS infrastructure, AWS services, APIs, and tools to virtually any on-premises data center or colocation space for a truly consistent hybrid experience. Organizations from startups to enterprises and the public sector in and outside of Europe can now order their Outposts racks connected to this new supported region, optimizing for their latency and data residency needs. Outposts allows customers to run workloads that need low latency access to on-premises systems locally while connecting back to their home Region for application management. Customers can also use Outposts and AWS services to manage and process data that needs to remain on-premises to meet data residency requirements. This regional expansion provides additional flexibility in the AWS Regions that customers’ Outposts can connect to. To learn more about second-generation Outposts racks, read this blog post and user guide. For the most updated list of countries and territories and the AWS Regions where second-generation Outposts racks are supported, check out the Outposts rack FAQs page.
Claude Haiku 4.5 is now available in Amazon Bedrock. Claude Haiku 4.5 delivers near-frontier performance matching Claude Sonnet 4’s capabilities in coding, computer use, and agent tasks at substantially lower cost and faster speeds, making state-of-the-art AI accessible for scaled deployments and budget-conscious applications.
The model’s enhanced speed makes it ideal for latency-sensitive applications like real-time customer service agents and chatbots where response time is critical. For computer use tasks, Haiku 4.5 delivers significant performance improvements over previous models, enabling faster and more responsive applications. This model supports vision and unlocks new use cases where customers previously had to choose between performance and cost. It enables economically viable agent experiences, supports multi-agent systems for complex coding projects, and powers large-scale financial analysis and research applications. Haiku 4.5 maintains Claude’s unique character while delivering the performance and efficiency needed for production deployments.
Claude Haiku 4.5 is now available in Amazon Bedrock via global cross region inference in multiple locations. To view the full list of available regions, refer to the documentation. To get started with Haiku 4.5 in Amazon Bedrock visit the Amazon Bedrock console, Anthropic’s Claude in Amazon Bedrock product page, and the Amazon Bedrock pricing page.
Claude Haiku 4.5 is now available in Amazon Bedrock. Claude Haiku 4.5 delivers near-frontier performance matching Claude Sonnet 4’s capabilities in coding, computer use, and agent tasks at substantially lower cost and faster speeds, making state-of-the-art AI accessible for scaled deployments and budget-conscious applications. The model’s enhanced speed makes it ideal for latency-sensitive applications like real-time customer service agents and chatbots where response time is critical. For computer use tasks, Haiku 4.5 delivers significant performance improvements over previous models, enabling faster and more responsive applications. This model supports vision and unlocks new use cases where customers previously had to choose between performance and cost. It enables economically viable agent experiences, supports multi-agent systems for complex coding projects, and powers large-scale financial analysis and research applications. Haiku 4.5 maintains Claude’s unique character while delivering the performance and efficiency needed for production deployments. Claude Haiku 4.5 is now available in Amazon Bedrock via global cross region inference in multiple locations. To view the full list of available regions, refer to the documentation. To get started with Haiku 4.5 in Amazon Bedrock visit the Amazon Bedrock console, Anthropic’s Claude in Amazon Bedrock product page, and the Amazon Bedrock pricing page.
AWS Backup now provides schedule preview for backup plans, helping you validate when your backups are scheduled to run. Schedule preview shows the next ten scheduled backup runs, including when continuous backup, indexing, or copy settings take effect.
Backup plan schedule preview consolidates all backup rules into a single timeline, showing how they work together. You can see when each backup occurs across all backup rules, along with settings like lifecycle to cold storage, point-in-time recovery, and indexing. This unified view helps you quickly identify and resolve conflicts or gaps between your backup strategy and actual configuration.
Backup plan schedule preview is available in all AWS Regions where AWS Backup is available. You can start using this feature automatically from the AWS Backup console, API, or CLI without any additional settings. For more information, visit our documentation.
AWS Backup now provides schedule preview for backup plans, helping you validate when your backups are scheduled to run. Schedule preview shows the next ten scheduled backup runs, including when continuous backup, indexing, or copy settings take effect.
Backup plan schedule preview consolidates all backup rules into a single timeline, showing how they work together. You can see when each backup occurs across all backup rules, along with settings like lifecycle to cold storage, point-in-time recovery, and indexing. This unified view helps you quickly identify and resolve conflicts or gaps between your backup strategy and actual configuration.
Backup plan schedule preview is available in all AWS Regions where AWS Backup is available. You can start using this feature automatically from the AWS Backup console, API, or CLI without any additional settings. For more information, visit our documentation.
Amazon Kinesis Data Streams now supports Fault Injection Service (FIS) actions for Kinesis API errors. Customers can now test their application’s error handling capabilities, retry mechanisms (such as exponential backoff patterns), and CloudWatch alarms in a controlled environment. This allows customers to validate their monitoring systems and recovery processes before encountering real-world failures, ultimately improving application resilience and availability. This integration supports Kinesis Data Streams API errors including throttling, internal errors, service unavailable, and expired iterator exceptions for Amazon Kinesis Data Streams.
Amazon Kinesis Data Streams is a serverless data streaming service that enables customers to capture, process, and store real-time data streams at any scale. Now customers can create real-world Kinesis Data Stream API errors (including 500, 503, and 400 errors for GET and PUT operations) to test application resilience. This feature eliminates the previous need for custom implementation or to wait for actual production failures to verify error handling mechanisms. To get started, customers can create experiment templates through the FIS console to run tests directly or integrate them into their continuous integration pipeline. For additional safety, FIS experiments include automatic stop mechanisms that trigger when customer-defined thresholds are reached, ensuring controlled testing without risking application stability.
Amazon Kinesis Data Streams now supports Fault Injection Service (FIS) actions for Kinesis API errors. Customers can now test their application’s error handling capabilities, retry mechanisms (such as exponential backoff patterns), and CloudWatch alarms in a controlled environment. This allows customers to validate their monitoring systems and recovery processes before encountering real-world failures, ultimately improving application resilience and availability. This integration supports Kinesis Data Streams API errors including throttling, internal errors, service unavailable, and expired iterator exceptions for Amazon Kinesis Data Streams. Amazon Kinesis Data Streams is a serverless data streaming service that enables customers to capture, process, and store real-time data streams at any scale. Now customers can create real-world Kinesis Data Stream API errors (including 500, 503, and 400 errors for GET and PUT operations) to test application resilience. This feature eliminates the previous need for custom implementation or to wait for actual production failures to verify error handling mechanisms. To get started, customers can create experiment templates through the FIS console to run tests directly or integrate them into their continuous integration pipeline. For additional safety, FIS experiments include automatic stop mechanisms that trigger when customer-defined thresholds are reached, ensuring controlled testing without risking application stability. These actions are generally available in all AWS Regions where FIS is available, including the AWS GovCloud (US) Regions. To learn more about using these actions, please see the Kinesis Data Streams User Guide and FIS User Guide.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) now supports Apache Kafka version 4.1, introducing Queues as a preview feature, a new Streams Rebalance Protocol in early access, and Eligible Leader Replicas (ELR). Along with these features, Apache Kafka version 4.1 includes various bug fixes and improvements. For more details, please refer to the Apache Kafka release notes for version 4.1.
A key highlight of Kafka 4.1 is the introduction of Queues as a preview feature. Customers can use multiple consumers to process messages from the same topic partitions, improving parallelism and throughput for workloads that need point-to-point message delivery. The new Streams Rebalance Protocol builds upon Kafka 4.0’s consumer rebalance protocol, extending broker coordination capabilities to Kafka Streams for optimized task assignments and rebalancing. Additionally, ELR is now enabled by default to strengthen availability.
To start using Apache Kafka 4.1 on Amazon MSK, simply select version 4.1.x when creating a new cluster via the AWS Management Console, AWS CLI, or AWS SDKs. You can also upgrade existing MSK provisioned clusters with an in-place rolling update. Amazon MSK orchestrates broker restarts to maintain availability and protect your data during the upgrade. Kafka version 4.1 support is available today across all AWS regions where Amazon MSK is offered. To learn how to get started, see the Amazon MSK Developer Guide.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) now supports Apache Kafka version 4.1, introducing Queues as a preview feature, a new Streams Rebalance Protocol in early access, and Eligible Leader Replicas (ELR). Along with these features, Apache Kafka version 4.1 includes various bug fixes and improvements. For more details, please refer to the Apache Kafka release notes for version 4.1. A key highlight of Kafka 4.1 is the introduction of Queues as a preview feature. Customers can use multiple consumers to process messages from the same topic partitions, improving parallelism and throughput for workloads that need point-to-point message delivery. The new Streams Rebalance Protocol builds upon Kafka 4.0’s consumer rebalance protocol, extending broker coordination capabilities to Kafka Streams for optimized task assignments and rebalancing. Additionally, ELR is now enabled by default to strengthen availability. To start using Apache Kafka 4.1 on Amazon MSK, simply select version 4.1.x when creating a new cluster via the AWS Management Console, AWS CLI, or AWS SDKs. You can also upgrade existing MSK provisioned clusters with an in-place rolling update. Amazon MSK orchestrates broker restarts to maintain availability and protect your data during the upgrade. Kafka version 4.1 support is available today across all AWS regions where Amazon MSK is offered. To learn how to get started, see the Amazon MSK Developer Guide.
Amazon Web Services (AWS) announces URL and Host Header rewrite capabilities for Application Load Balancer (ALB). This feature enables customers to modify request URLs and Host Headers using regex-based pattern matching before routing requests to targets.
With URL and Host Header rewrites, you can transform URLs using regex patterns (e.g., rewrite «/api/v1/users» to «/users»), standardize URL patterns across different applications, modify Host Headers for internal service routing, remove or add URL path prefixes, and redirect legacy URL structures to new formats. This capability eliminates the need for additional proxy layers and simplifies application architectures. The feature is valuable for microservices deployments where maintaining a single external hostname while routing to different internal services is critical.
You can configure URL and Host Header rewrites through the AWS Management Console, AWS CLI, AWS SDKs, and AWS APIs. There are no additional charges for using URL and Host Header rewrites. You pay only for your use of Application Load Balancer based on Application Load Balancer pricing.
This feature is now available in all AWS commercial regions.
To learn more, visit the ALB Documentation, and the AWS Blog post on URL and Host Header rewrites with Application Load Balancer.
Amazon Web Services (AWS) announces URL and Host Header rewrite capabilities for Application Load Balancer (ALB). This feature enables customers to modify request URLs and Host Headers using regex-based pattern matching before routing requests to targets.
With URL and Host Header rewrites, you can transform URLs using regex patterns (e.g., rewrite «/api/v1/users» to «/users»), standardize URL patterns across different applications, modify Host Headers for internal service routing, remove or add URL path prefixes, and redirect legacy URL structures to new formats. This capability eliminates the need for additional proxy layers and simplifies application architectures. The feature is valuable for microservices deployments where maintaining a single external hostname while routing to different internal services is critical.
You can configure URL and Host Header rewrites through the AWS Management Console, AWS CLI, AWS SDKs, and AWS APIs. There are no additional charges for using URL and Host Header rewrites. You pay only for your use of Application Load Balancer based on Application Load Balancer pricing.
This feature is now available in all AWS commercial regions.
To learn more, visit the ALB Documentation, and the AWS Blog post on URL and Host Header rewrites with Application Load Balancer.
AWS Backup now provides more details in backup job API responses and Backup Audit Manager reports to give you better visibility into backup configurations and compliance settings. You can verify your backup policies with a single API call.
List and Describe APIs for backup, copy, and restore jobs now return fields that required multiple API calls before. Delegated administrators can now view backup job details across their organization. Backup jobs APIs include retention settings, vault lock status, encryption details, and backup plan information like plan names, rule names, and schedules. Copy job APIs return destination vault configurations, vault type, lock state, and encryption settings. Restore job APIs show source resource details and vault access policies. Backup Audit Manager reports include new columns with vault type, lock status, encryption details, archive settings, and retention periods. You can use this information to enhance audit trails and verify compliance with data protection policies.
These expanded information fields are available today in all AWS Regions where AWS Backup and AWS Backup Audit Manager are supported, with no additional charges.
AWS Backup now provides more details in backup job API responses and Backup Audit Manager reports to give you better visibility into backup configurations and compliance settings. You can verify your backup policies with a single API call.
List and Describe APIs for backup, copy, and restore jobs now return fields that required multiple API calls before. Delegated administrators can now view backup job details across their organization. Backup jobs APIs include retention settings, vault lock status, encryption details, and backup plan information like plan names, rule names, and schedules. Copy job APIs return destination vault configurations, vault type, lock state, and encryption settings. Restore job APIs show source resource details and vault access policies. Backup Audit Manager reports include new columns with vault type, lock status, encryption details, archive settings, and retention periods. You can use this information to enhance audit trails and verify compliance with data protection policies.
These expanded information fields are available today in all AWS Regions where AWS Backup and AWS Backup Audit Manager are supported, with no additional charges.
To learn more about AWS Backup Audit Manager, visit the product page and documentation. To get started, visit the AWS Backup console.
Diseñar Microsoft 365 Copilot para capacitar a los educadores, estudiantes y personal
Por: Deirdre Quarnstrom, vicepresidenta de Educación.
Los educadores dan forma al plan de estudios, abogan por los estudiantes, innovan en primera línea y más, todo al mismo tiempo. Los estudiantes se enfrentan a su propio acto de equilibrio cuando se les pide que absorban conocimientos, generen confianza y encuentren su voz, y se preparen para un futuro en constante evolución. Y, a menudo, entre bastidores, el personal y los líderes trabajan para alinear los sistemas, responder a las demandas cambiantes y trazar el camino a seguir para que todos prosperen.
Si bien más del 80% de los encuestados en el Informe sobre la IA en la Educación 2025 ya han utilizado la IA para la escuela, creemos que existen oportunidades significativas para diseñar IA que pueda satisfacer mejor cada una de sus necesidades y ampliar el acceso a la más reciente innovación.1
Es por eso que hoy anunciamos experiencias impulsadas por IA creadas para la enseñanza y el aprendizaje sin costo adicional, nuevas integraciones en aplicaciones de Microsoft 365 y sistemas de administración de aprendizaje, y una oferta académica para Microsoft 365 Copilot.
Presentamos la enseñanza y el aprendizaje impulsados por IA
Empoderar a los educadores con Teach
Presentamos Teach para ayudar a optimizar la preparación de clases y adaptar la IA para respaldar la experiencia docente de los educadores con funciones intuitivas y personalizables. En un solo lugar, los educadores pueden acceder con facilidad a herramientas de enseñanza impulsadas por IA para crear planes de lecciones, redactar materiales como cuestionarios y rúbricas, y realizar con rapidez modificaciones en el lenguaje, el nivel de lectura, la longitud, la dificultad, la alineación con los estándares relevantes y más.
Teach se ha comenzado a implementar en la aplicación Microsoft 365 Copilot a partir de hoy sin costo adicional para los clientes de educación con más funcionalidades, incluida la integración del sistema de administración de aprendizaje (LMS, por sus siglas en inglés), más adelante. Muchas de estas características también están disponibles en el flujo diario de educadores que usan aplicaciones como Microsoft Teams y OneNote.
Apoyar a los estudiantes con Study and Learn Agent
Al crear experiencias de IA basadas en el aprendizaje de la ciencia, podemos apoyar de manera más efectiva el proceso de aprendizaje de los estudiantes y cambiar el enfoque en el uso de la IA para la generación rápida de contenido para fomentar el crecimiento de las habilidades con el tiempo. Llevamos Study and Learn, un agente avanzado, a los estudiantes para brindar experiencias adaptativas y ayudar a fomentar el pensamiento crítico y reflexivo. Pueden optar por trabajar en su comprensión, practicar con ejercicios, estudiar un tema específico o tan solo chatear y seleccionar entre actividades integradas atractivas como tarjetas didácticas, emparejamiento, completar espacios en blanco o cuestionarios a medida que avanzan. Study and Learn llegará en versión preliminar en noviembre de 2025 y estará disponible sin costo adicional.
Nuevas integraciones en aplicaciones cotidianas para la educación
Millones de educadores, personal y estudiantes de 13 años o más utilizan Copilot Chat para personalizar el aprendizaje, mejorar la instrucción y reimaginar las tareas administrativas. En las escuelas del condado de Fulton, ayuda a aumentar la agencia y el compromiso de los estudiantes y en Babson College acelera el tiempo de comercialización para la próxima generación de empresarios. Copilot Chat se incluye sin costo adicional con Microsoft 365 y ahora está disponible en aplicaciones como Outlook y PowerPoint para proporcionar un chat de IA seguro con tecnología GPT-5 con protección de datos empresariales y controles de TI. Además, al llegar a la versión preliminar en diciembre de 2025, se podrá acceder a él en LMS como Canvas, Schoology, Brightspace, Blackboard y Moodle a través de Microsoft 365 LTI.
Nos complace presentar una oferta académica para Microsoft 365 Copilot en educación a $18 (USD) por usuario por mes para educadores, personal y estudiantes mayores de 13 años a partir de diciembre de 2025.2 Integrado a profundidad en las aplicaciones que se usan todos los días, Microsoft 365 Copilot combina el poder de la IA con sus datos (documentos, presentaciones, correos electrónicos, reuniones, chats, conocimiento institucional y más), además de la web para ofrecer respuestas relevantes con fuentes. También ofrece capacidades de vanguardia como el acceso integral de los agentes, incluidos Researcher y Analyst, el Copilot Tuning para una mayor personalización y el Copilot Control System para proteger los datos institucionales.
Microsoft 365 Copilot ha ayudado a ahorrar mucho tiempo a nuestros educadores y personal, permitiéndoles centrarse en la razón por la que llegaron a la educación: apoyar el aprendizaje de los estudiantes y personalizar la educación de formas que antes no eran posibles.
Leigh Williams, CIO, Educación Católica de Brisbane
En Brisbane Catholic Education, los educadores participantes ahorraron más de 9 horas por semana en tareas administrativas y de planificación, lo que permitió más tiempo para mejorar las experiencias y el bienestar de los estudiantes. El ochenta y cuatro por ciento de los usuarios, incluidos los estudiantes, de la Universidad de Carolina del Sur informaron que ahorraban entre una y cinco horas por semana, y 8 de cada 10 usuarios informaron estar satisfechos con Copilot. Los profesores informaron ahorros de tiempo y una mejor calidad en la producción académica, lo que permitió un mayor enfoque en la investigación y la tutoría de mayor valor. Mientras tanto, los administradores informaron de una reducción del tiempo de preparación de las reuniones y de una mejor toma de decisiones gracias a una síntesis de datos más rápida, y los equipos de comunicación aumentaron su producción creativa sin sacrificar la calidad.
Transformar las experiencias educativas con los agentes
Las instituciones profundizan el uso de la IA para avanzar en su misión y preparar a los estudiantes para el futuro, al mismo tiempo que comienzan a demostrar el potencial de los agentes para transformar las experiencias en la enseñanza, el aprendizaje, la investigación y las operaciones. Ya sea que busquen usar soluciones prediseñadas, construir con rapidez las suyas propias o desarrollar sistemas avanzados, hemos facilitado llevar el poder de la IA generativa un paso más allá con los agentes. Tan solo usen el lenguaje natural para crear instrucciones y seleccionen contenido relevante para comenzar a transformar experiencias y procesos con agentes personalizados.
La Universidad del Sur de Florida impulsa un enfoque integral en todo el espectro de agentes. El equipo de TI ha creado agentes para mejorar las experiencias del campus y el soporte para temas como la política de viajes, la mesa de ayuda de TI o eventos como la graduación de estudiantes. Han trabajado con la biblioteca, el atletismo y se han asociado con la Facultad de Medicina para crear soluciones personalizadas que incluyen un sistema de acreditación avanzado y manuales interactivos para estudiantes.
Los Estudiantes Embajadores crearon agentes para varios departamentos, lo que resultó en una disminución del tiempo de informes manuales, un análisis de inventario acelerado y mejores flujos de trabajo de creación de contenido. Sus usuarios de Microsoft 365 Copilot también han comenzado a ver ganancias de eficiencia con Researcher and Analyst para respaldar tareas como el desarrollo de informes anuales, adquisiciones, evaluación de facturación y revisiones de presupuestos. Luego, han probado el uso de agentes autónomos para impulsar la automatización de procesos de TI y un centro de contacto impulsado por agentes.
En las Escuelas Públicas del Condado de Broward, los líderes académicos han comenzado a crear agentes innovadores, como un motor de cuestionarios interactivo para mejorar la participación de los estudiantes, un analizador de currículum y descripción de trabajo para apoyar las iniciativas de preparación profesional. También han comenzado a explorar casos de uso de agentes como planificación de desarrollo profesional, asistencia de reclutamiento, redacción de boletines e informes, y más. Para agilizar las operaciones, Broward ha creado agentes para facilitar la gestión de contratos y mejorar el acceso a la información de apoyo para los usuarios de su Sistema de Información Estudiantil.
Más formas de comenzar su recorrido de IA
No importa dónde se encuentren en su recorrido de IA, ofrecemos un lugar para comenzar, incluidas muchas opciones sin costo adicional. Los educadores pueden aprovechar nuestros Aceleradores de aprendizaje como Reading Coach para recibir comentarios e información inmediatos impulsados por IA, Fundamentos de IA de Minecraft para desarrollar la alfabetización en IA de manera atractiva con los estudiantes y las familias, así como Khanmigo para maestros para un conjunto de herramientas alineadas con los estándares sin necesidad de indicaciones y Khanmigo Writing Coach para estudiantes. GitHub Copilot Pro está disponible para educadores y estudiantes de manera gratuita, además de acceso a docenas de recursos de aprendizaje en el Student Developer Pack.
Muchos estudiantes no solo han comenzado a usar herramientas de IA en el aula, sino también en casa y para fines fuera del trabajo escolar, como la planificación de viajes o comidas, compras y trabajos secundarios. Microsoft 365 Personal está disponible para el uso de aplicaciones de productividad y créditos para nuevas características de IA. Los estudiantes universitarios elegibles pueden recibir un descuento del 50% en Microsoft 365 Personal y pueden registrarse para obtener una prueba gratuita de 12 meses por tiempo limitado.
2 Todos los precios están en dólares estadounidenses y son exactos a partir de diciembre de 2025. Los precios regionales variarán según los tipos de cambio en el momento de realizar el pedido de SKU.
Amazon Elastic Container Services (Amazon ECS) now allows you to run Firelens containers as a non-root user, by specifying a User ID in your Task Definition.
Specifying a non-root user with a specific user ID reduces the potential attack footprint by users who may gain access to such software, a security best practice and a compliance requirement by some industries and security services such as the AWS Security Hub. With this release, Amazon ECS allows you to specify a user ID in the «user» field of your Firelens containerDefinition element of your Task Definition, instead of only allowing «user»: «0» (root user).
The new capability is supported in all AWS Regions. See the documentation for using Firelens for more details on how to set up your Firelens container to run as non-root.
Amazon Elastic Container Services (Amazon ECS) now allows you to run Firelens containers as a non-root user, by specifying a User ID in your Task Definition. Specifying a non-root user with a specific user ID reduces the potential attack footprint by users who may gain access to such software, a security best practice and a compliance requirement by some industries and security services such as the AWS Security Hub. With this release, Amazon ECS allows you to specify a user ID in the «user» field of your Firelens containerDefinition element of your Task Definition, instead of only allowing «user»: «0» (root user). The new capability is supported in all AWS Regions. See the documentation for using Firelens for more details on how to set up your Firelens container to run as non-root.
a través de Microsoft 365 LTI.