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Descubran el potencial de la IA agéntica en la educación superior

agosto 12, 2025

Descubran el potencial de la IA agéntica en la educación superior

Una persona sentada en un escritorio observa la pantalla de una computadora

Por: Equipo de Microsoft Educación.

En Microsoft Build 2025, presentamos una nueva ola de innovaciones agénticas que han comenzado a remodelar la forma en que las instituciones de educación superior usan la IA. Desde agentes inteligentes hasta plataformas de datos unificadas, estos avances permiten a los líderes de la educación superior acelerar con confianza la transformación digital. Una parte clave de esta evolución es el papel de Azure AI Foundry en la educación, que ayuda a las instituciones a crear soluciones de IA seguras y escalables adaptadas a sus objetivos académicos.

Con estos avances en IA, las instituciones ahora tienen una nueva y poderosa oportunidad: utilizar agentes que puedan automatizar tareas rutinarias, ayudar a la facultad y al personal, y proporcionar información contextual en tiempo real para respaldar la enseñanza y el aprendizaje. A medida que más instituciones comiencen su recorrido hacia esta próxima frontera, los agentes de IA apoyarán a las personas y los equipos en la automatización de las tareas y en brindar información contextual instantánea.

Esto significa que con las herramientas de IA centradas en datos de Microsoft, su institución puede:

  • Desarrollar agentes escalables e inteligentes con Azure AI Foundry, en los que confían las empresas y personalizados para el cumplimiento y la innovación de la educación superior.
  • Convertir la información de los datos en acción con análisis impulsados por IA, para abordar los desafíos en el éxito de los estudiantes, la productividad de la investigación y la agilidad operativa.

Acelerar la inteligencia artificial agentica con Azure AI Foundry

Azure AI Foundry Agent Service permite a las instituciones diseñar, implementar y escalar agentes de forma segura con facilidad. Mejoren la eficiencia de su equipo con agentes que simplifican los flujos de trabajo académicos y operativos con sólidas funciones de seguridad y confianza integradas. Esto proporciona herramientas y recursos clave para ayudarlos a:

  • Crear agentes específicos de dominio para automatizar tareas complejas.
  • Utilizar la identidad de nivel empresarial para los agentes y la IA confiable integrada.
  • Implementar y escalar agentes de manera rápida, con infraestructura administrada.

Introducción al servicio de agente de Azure AI Foundry

Crear y escalar agentes específicos del dominio

Una persona de pie frente a una estación de trabajo

Con Azure AI Foundry Agent Service, el equipo puede crear agentes específicos de dominio adaptados a sus necesidades únicas. Les ayuda a diseñar, implementar y escalar agentes que están listos para su uso en el mundo real. Este servicio administrado por completo, maneja la infraestructura y la orquestación. Incluye plantillas, acciones y conectores listos para usar para más de 1.400 orígenes de datos empresariales, incluidos SharePoint, Microsoft Fabric y sistemas de terceros. Por ejemplo, puede diseñar e implementar agentes para ayudar a incorporar nuevos estudiantes con orientación personalizada y apoyar a los equipos administrativos con respuestas instantáneas a preguntas comunes.

Instituciones como Stanford Medicine ya han comenzado a usar el orquestador de agentes de atención médica en Azure AI Foundry junto con Microsoft Copilot Studio. Esta integración mejora la eficiencia de las reuniones de la junta de tumores a través de flujos de trabajo clínicos personalizados.

Protejan y administren a sus agentes

La creación de agentes es solo el comienzo: administrarlos de manera responsable juega un papel fundamental en su uso efectivo. Con el identificador de agente de Microsoft Entra, ustedes pueden:

  • Obtener visibilidad y control completos sobre las acciones de los agentes.
  • Asignar identidades únicas para cada agente.
  • Compartir la administración de identidades con los miembros de su equipo.
  • Definir controles de acceso y permisos para cada agente.

Más información sobre el identificador de agente de Microsoft Entra

La IA confiable es un compromiso fundamental para Microsoft y para nuestros clientes. Hemos introducido nuevas capacidades para ayudar a las instituciones a descubrir, proteger y gobernar los sistemas de IA desde el principio.

En el lado de la seguridad, Azure AI Foundry se integra con Microsoft Defender for Cloud para proporcionar alertas e información en tiempo real cuando surgen amenazas. Para el cumplimiento, la integración lista para usar con herramientas de gobernanza como Credo AI, Saidot y Microsoft Purview, ayuda a las instituciones a monitorear el rendimiento del modelo, evaluar la equidad y realizar un seguimiento de los requisitos normativos.

Mediante el uso de las herramientas integradas de Azure AI Foundry para la seguridad, la protección y la gobernanza, las instituciones pueden diseñar e implementar sistemas de IA con mayor confiabilidad desde el principio.

Impulsar la próxima frontera de la IA con Microsoft Fabric

Dos personas colaboran en una estación de trabajo con una laptop y un monitor externo|

Los datos sólidos son fundamentales para una IA eficaz. Microsoft Fabric ayuda a unificar los datos para potenciar el análisis y los agentes, sin la carga de administrar una infraestructura compleja. Como solución SaaS, Fabric ofrece una integración perfecta de herramientas de datos y puede reducir la necesidad de conexiones de servicio manuales.

Prueben Microsoft Fabric gratis

En su núcleo se encuentra Microsoft OneLake, un lago de datos abierto y unificado que admite cualquier formato, desde cualquier nube. Esta flexibilidad permite a los desarrolladores acceder y analizar todo tipo de datos de manera eficiente.

Fabric también transforma la forma en que ustedes administran e interactúan con los datos. Con las capacidades de lenguaje natural, pueden explorar información que impulse el éxito de los estudiantes, mejore la investigación y aumente la agilidad operativa, lo que permite a todos tomar decisiones informadas y basadas en datos.

Encuentren los datos correctos cuando los necesiten

Los líderes educativos necesitan herramientas que conviertan los conocimientos en acción. Es por eso que nos enfocamos en hacer que los datos sean más accesibles a través de experiencias conversacionales. Con Copilot en Power BI, los usuarios ahora pueden hacer preguntas en lenguaje natural y recibir información instantánea, sin necesidad de formación técnica para empezar. Ya sea que se trate de tendencias de inscripción, riesgos de retención o donaciones de ex alumnos, los profesores y el personal pueden explorar datos de manera directa dentro de Microsoft Teams, para optimizar su flujo de trabajo.

Capaciten a todos para que interactúen con sus datos

Cuatro personas alrededor de una mesa mientras escriben ideas en notas adhesivas

Con las capacidades de interacción mejoradas de Power BI y Copilot Studio, la transformación de los datos en información procesable ahora puede ser más rápida e intuitiva. Ustedes pueden explorar datos a través de experiencias conversacionales naturales, para eliminar la complejidad y hacer que el análisis sea más accesible. Este cambio les permite a ustedes y a sus equipos romper los silos de datos y descubrir información valiosa con facilidad. El chat de Power BI simplifica la exploración de conjuntos de datos complejos, para ofrecer una toma de decisiones más rápida y segura.

Descubran información más detallada con agentes de datos

Por último, conectar los agentes de datos de Fabric a Copilot Studio puede ayudar a descubrir información más profunda. Estos agentes analizan de manera experta conjuntos de datos complejos, para descubrir información valiosa de OneLake e impulsar acciones informadas. Al automatizar tareas como el envío de correos electrónicos y la activación del flujo de trabajo, agilizan sus interacciones con los datos empresariales, lo que permite una toma de decisiones segura.

Adopten el futuro de la educación superior basada en datos con Microsoft Azure y Azure AI Foundry. Descubran cómo los agentes de datos innovadores y los conocimientos impulsados por IA pueden mejorar su enfoque del aprendizaje y las operaciones. Comiencen su recorrido hoy y descubran las posibilidades ilimitadas que les esperan.

Introducción a Azure AI Foundry

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Amazon QuickSight expands limits on calculated fields

Amazon QuickSight has increased the limits on number of calculated fields allowed in an analysis from 500 to 2000, and from 200 to 500 per dataset. This update enables authors and data curators to create more transformations on their data and draw additional complex insights. This is especially useful for authors and data curators who work with really large datasets and cater to multiple end user personas.

In QuickSight, users can also use natural language to build calculations using Q.

The new calculated fields limits are now available in all supported Amazon QuickSight regions.

To learn more about calculated fields and other QuickSight limits, visit item limits for analysis.

 

​Amazon QuickSight has increased the limits on number of calculated fields allowed in an analysis from 500 to 2000, and from 200 to 500 per dataset. This update enables authors and data curators to create more transformations on their data and draw additional complex insights. This is especially useful for authors and data curators who work with really large datasets and cater to multiple end user personas. In QuickSight, users can also use natural language to build calculations using Q. The new calculated fields limits are now available in all supported Amazon QuickSight regions. To learn more about calculated fields and other QuickSight limits, visit item limits for analysis.  

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Amazon Connect now supports recurring activities in agent schedules

Amazon Connect now supports recurring activities in agent schedules, making it easier for you to add repeating events in a few clicks. With this launch, you can now schedule activities such as daily stand-up at 8am or team meeting every Monday at 9am as a series that automatically gets added to agent schedules. You can schedule these activities as individual so that a different recurring series is created for each selected agent, or, you can schedule these activities as shared so that all selected agents are part of the same series. This launch eliminates the need for manually creating each occurrence as a separate activity, thus reducing time spent on managing agent schedules and improving manager productivity.

This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.

 

​Amazon Connect now supports recurring activities in agent schedules, making it easier for you to add repeating events in a few clicks. With this launch, you can now schedule activities such as daily stand-up at 8am or team meeting every Monday at 9am as a series that automatically gets added to agent schedules. You can schedule these activities as individual so that a different recurring series is created for each selected agent, or, you can schedule these activities as shared so that all selected agents are part of the same series. This launch eliminates the need for manually creating each occurrence as a separate activity, thus reducing time spent on managing agent schedules and improving manager productivity. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.  

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Amazon RDS for Oracle now supports the July 2025 Release Update (RU)

Amazon Relational Database Service (Amazon RDS) for Oracle now supports the July 2025 Release Update (RU) for Oracle Database versions 19c and 21c. These RUs include bug and security fixes and are available for RDS for Oracle Standard Edition 2 and Enterprise Edition. Review the Oracle release notes for July RU for details.

We recommend upgrading to this RU as it includes security fixes. You can upgrade with just a few clicks in the Amazon RDS Management Console or by using the AWS SDK or CLI. You can also enable auto minor version upgrade (AmVU) to automatically upgrade your database instances. Learn more about upgrading your database instances from the Amazon RDS User Guide.

This new minor version is available in all AWS regions where Amazon RDS for Oracle is available. See Amazon RDS for Oracle Pricing for pricing details and regional availability.

 

​Amazon Relational Database Service (Amazon RDS) for Oracle now supports the July 2025 Release Update (RU) for Oracle Database versions 19c and 21c. These RUs include bug and security fixes and are available for RDS for Oracle Standard Edition 2 and Enterprise Edition. Review the Oracle release notes for July RU for details. We recommend upgrading to this RU as it includes security fixes. You can upgrade with just a few clicks in the Amazon RDS Management Console or by using the AWS SDK or CLI. You can also enable auto minor version upgrade (AmVU) to automatically upgrade your database instances. Learn more about upgrading your database instances from the Amazon RDS User Guide. This new minor version is available in all AWS regions where Amazon RDS for Oracle is available. See Amazon RDS for Oracle Pricing for pricing details and regional availability.  

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CloudFormation Hooks Adds Managed Controls and Hook Activity Summary

WS CloudFormation Hooks now support managed proactive controls, allowing customers to validate resource configurations against AWS best practices without writing custom hook logic. Customers can select controls from the AWS Control Tower Controls Catalog and apply them during CloudFormation operations. This helps reduce setup time, avoid manual errors, and improve the completeness and consistency of governance coverage. With this launch, customers can also configure these controls to run in warn mode. This allows teams to test controls without blocking deployments and is currently only available through CloudFormation. It gives customers greater flexibility to evaluate control behavior before fully enforcing policies.

AWS also introduced a new Hooks Invocation Summary page in the CloudFormation console. This view provides a historical record of hook activity, showing which controls were invoked, when and where they ran, and their outcomes such as pass, warn, or fail. This helps customers troubleshoot issues faster and demonstrate control posture for audits and compliance reviews.

With this launch, customers can now use AWS managed controls as part of their provisioning workflows, without the overhead of writing and maintaining custom logic. These controls are curated by AWS and aligned with industry best practices, helping teams enforce policies consistently across environments. The new summary page offers visibility into hook execution history, enabling faster issue resolution and better reporting.

These capabilities are available in all AWS Regions where CloudFormation is supported. To learn more, visit the AWS CloudFormation Hooks documentation

 

 

​WS CloudFormation Hooks now support managed proactive controls, allowing customers to validate resource configurations against AWS best practices without writing custom hook logic. Customers can select controls from the AWS Control Tower Controls Catalog and apply them during CloudFormation operations. This helps reduce setup time, avoid manual errors, and improve the completeness and consistency of governance coverage. With this launch, customers can also configure these controls to run in warn mode. This allows teams to test controls without blocking deployments and is currently only available through CloudFormation. It gives customers greater flexibility to evaluate control behavior before fully enforcing policies. AWS also introduced a new Hooks Invocation Summary page in the CloudFormation console. This view provides a historical record of hook activity, showing which controls were invoked, when and where they ran, and their outcomes such as pass, warn, or fail. This helps customers troubleshoot issues faster and demonstrate control posture for audits and compliance reviews. With this launch, customers can now use AWS managed controls as part of their provisioning workflows, without the overhead of writing and maintaining custom logic. These controls are curated by AWS and aligned with industry best practices, helping teams enforce policies consistently across environments. The new summary page offers visibility into hook execution history, enabling faster issue resolution and better reporting. These capabilities are available in all AWS Regions where CloudFormation is supported. To learn more, visit the AWS CloudFormation Hooks documentation
   

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Amazon SageMaker HyperPod now provides a new cluster setup experience

SageMaker HyperPod now provides a new cluster creation experience that sets up all the resources needed for large-scale AI/ML workloads—including networking, storage, compute, and IAM permissions in just a few clicks. SageMaker HyperPod clusters are purpose-built for scalability and resilience, designed to accelerate large-scale distributed training and deployment of complex machine learning models like LLMs and diffusion models, as well as customization of Amazon Nova foundation models.

The new cluster creation experience for SageMaker HyperPod introduces both quick and custom setup paths that make it easier for both beginners and advanced AWS customers to get started. Previously, customers needed to manually configure networking, IAM roles, storage, and compute. With the new quick setup, model builders, who may not have AWS infrastructure expertise, can now launch a fully-operational cluster optimized for large-scale AI workloads in just a few clicks using a streamlined single-page interface that provisions all dependencies including VPCs, subnets, FSx storage, EKS/Slurm orchestrator, and essential (k8s) operators. For platform engineering teams who may want to modify the default settings, the custom setup path provides full control over every configuration—from specific subnet configurations to selective operator installations—from within the same console experience. Teams can also export an auto-generated CloudFormation template for repeatable production deployments.

You can create clusters using either the AWS Console or CloudFormation in all AWS Regions where SageMaker HyperPod is supported. To learn more, see the user guide.

 

​SageMaker HyperPod now provides a new cluster creation experience that sets up all the resources needed for large-scale AI/ML workloads—including networking, storage, compute, and IAM permissions in just a few clicks. SageMaker HyperPod clusters are purpose-built for scalability and resilience, designed to accelerate large-scale distributed training and deployment of complex machine learning models like LLMs and diffusion models, as well as customization of Amazon Nova foundation models. The new cluster creation experience for SageMaker HyperPod introduces both quick and custom setup paths that make it easier for both beginners and advanced AWS customers to get started. Previously, customers needed to manually configure networking, IAM roles, storage, and compute. With the new quick setup, model builders, who may not have AWS infrastructure expertise, can now launch a fully-operational cluster optimized for large-scale AI workloads in just a few clicks using a streamlined single-page interface that provisions all dependencies including VPCs, subnets, FSx storage, EKS/Slurm orchestrator, and essential (k8s) operators. For platform engineering teams who may want to modify the default settings, the custom setup path provides full control over every configuration—from specific subnet configurations to selective operator installations—from within the same console experience. Teams can also export an auto-generated CloudFormation template for repeatable production deployments. You can create clusters using either the AWS Console or CloudFormation in all AWS Regions where SageMaker HyperPod is supported. To learn more, see the user guide.  

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Amazon RDS for Oracle now supports July 2025 Spatial Patch Bundle

Amazon Relational Database Service (Amazon RDS) for Oracle now supports the Spatial Patch Bundle (SPB) for the July 2025 Release Update (RU) for Oracle Database version 19c. This update delivers important fixes for Oracle Spatial and Graph functionality, helping ensure reliable and optimal performance for your spatial operations.

You can now create new DB instances or upgrade existing ones to engine version ‘19.0.0.0.ru-2025-07.spb-1.r1’. The SPB engine version will be visible in the AWS Console by selecting the «Spatial Patch Bundle Engine Versions» checkbox in the engine version selector, making it simple to identify and implement the latest spatial patches for your database environment.

To learn more about Oracle SPBs supported on Amazon RDS for each engine version, see the Amazon RDS for Oracle Release notes. For more information about the AWS Regions where Amazon RDS for Oracle is available, see the AWS Region table.

 

​Amazon Relational Database Service (Amazon RDS) for Oracle now supports the Spatial Patch Bundle (SPB) for the July 2025 Release Update (RU) for Oracle Database version 19c. This update delivers important fixes for Oracle Spatial and Graph functionality, helping ensure reliable and optimal performance for your spatial operations. You can now create new DB instances or upgrade existing ones to engine version ‘19.0.0.0.ru-2025-07.spb-1.r1’. The SPB engine version will be visible in the AWS Console by selecting the «Spatial Patch Bundle Engine Versions» checkbox in the engine version selector, making it simple to identify and implement the latest spatial patches for your database environment. To learn more about Oracle SPBs supported on Amazon RDS for each engine version, see the Amazon RDS for Oracle Release notes. For more information about the AWS Regions where Amazon RDS for Oracle is available, see the AWS Region table.  

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Amazon Connect Outbound Campaigns now supports multi-profile campaigns and enhanced phone number retry sequencing

Amazon Connect Outbound Campaigns now supports account-based campaigns, allowing you to reach multiple people associated with the same account. For example, when calling about a joint bank account, if the first person is unavailable, the system automatically tries to reach other authorized members of the account. You can also define a prioritized contact sequence across multiple phone numbers, for example, mobile first, then home, then work. If the first number is unreachable, Connect will automatically try the next number in the sequence.

Previously, campaigns targeted one profile and retried a single phone number. With these updates, you can target multiple profiles within the same campaign, enabling outreach to all associated contacts in an account. You can also configure fallback phone numbers within each profile, automatically moving to the next preferred phone number if the first attempt is unsuccessful. Together, these capabilities help you create more flexible and effective engagement workflows that improve right-party contact rates and simplify campaign management.

This feature is available in all AWS Regions where Amazon Connect Outbound Campaigns is supported. To get started, refer to the Amazon Connect Customer Profiles documentation to learn how to ingest customer data, and the Outbound Campaigns documentation for guidance on creating campaigns.. 

 

​Amazon Connect Outbound Campaigns now supports account-based campaigns, allowing you to reach multiple people associated with the same account. For example, when calling about a joint bank account, if the first person is unavailable, the system automatically tries to reach other authorized members of the account. You can also define a prioritized contact sequence across multiple phone numbers, for example, mobile first, then home, then work. If the first number is unreachable, Connect will automatically try the next number in the sequence. Previously, campaigns targeted one profile and retried a single phone number. With these updates, you can target multiple profiles within the same campaign, enabling outreach to all associated contacts in an account. You can also configure fallback phone numbers within each profile, automatically moving to the next preferred phone number if the first attempt is unsuccessful. Together, these capabilities help you create more flexible and effective engagement workflows that improve right-party contact rates and simplify campaign management. This feature is available in all AWS Regions where Amazon Connect Outbound Campaigns is supported. To get started, refer to the Amazon Connect Customer Profiles documentation to learn how to ingest customer data, and the Outbound Campaigns documentation for guidance on creating campaigns..   

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Amazon Connect launches an API for real-time position in queue

Amazon Connect now provides a new API that returns real-time position in queue, enabling businesses to better estimate wait time. This new API helps contact centers manage customer expectations and offer timely alternatives like callbacks during long wait periods. Using this data, contact centers can make informed routing decisions between primary and alternative queues while optimizing resource allocation through improved queue visibility. This metric is also generated for contacts using a routing criteria and agent proficiencies. For example, customers in slow-moving queues can be proactively offered callbacks, improving their experience while reducing queue abandonment.

 

​Amazon Connect now provides a new API that returns real-time position in queue, enabling businesses to better estimate wait time. This new API helps contact centers manage customer expectations and offer timely alternatives like callbacks during long wait periods. Using this data, contact centers can make informed routing decisions between primary and alternative queues while optimizing resource allocation through improved queue visibility. This metric is also generated for contacts using a routing criteria and agent proficiencies. For example, customers in slow-moving queues can be proactively offered callbacks, improving their experience while reducing queue abandonment.  

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FSx for ONTAP now allows decreasing SSD capacity, broadening support for workloads with varying high-performance storage needs

Amazon FSx for NetApp ONTAP, a fully managed shared storage service built on NetApp’s popular ONTAP file system, now allows you to decrease your file system’s solid-state drive (SSD) storage capacity, enabling you to run project-based workloads with varying active working set sizes more efficiently. You can provision SSD capacity upfront to meet peak usage needs—for periodic reporting, analytics, or large-scale data ingestion and processing—and then easily decrease SSD capacity to optimize resource utilization and reduce storage costs.

An FSx for ONTAP file system offers two storage tiers: a provisioned high-performance SSD tier for your active working set, and a fully elastic capacity pool cost-optimized for infrequently accessed data. Previously, you could increase a file system’s SSD capacity to meet your workload’s growing active working set but decreasing SSD capacity required migrating to a file system with smaller SSD capacity incurring administrative overhead and tolerating application downtime. Starting today, you can decrease your file system’s provisioned SSD capacity in-place with just a few clicks in the Amazon FSx console. You can deliver optimal performance to serve peak usage for workloads with varying high-performance storage requirements, including Electronic Design Automation jobs like chip fabrication and circuit
simulation, and Media & Entertainment tasks like video editing and transcoding. Once data processing in SSD storage is complete, and results have been archived, you can decrease SSD capacity to optimize resource utilization. You can even accelerate large-scale data migrations by provisioning SSD capacity to temporarily accommodate more data in SSD, ensuring faster data ingestion, subsequently decreasing SSD capacity after data has been tiered to the capacity pool to optimize storage costs.

You can decrease SSD storage capacity on all FSx for ONTAP second-generation file systems in all AWS Regions where FSx for ONTAP second-generation file systems are available. For more information, see the FSx for ONTAP user guide.

 

​Amazon FSx for NetApp ONTAP, a fully managed shared storage service built on NetApp’s popular ONTAP file system, now allows you to decrease your file system’s solid-state drive (SSD) storage capacity, enabling you to run project-based workloads with varying active working set sizes more efficiently. You can provision SSD capacity upfront to meet peak usage needs—for periodic reporting, analytics, or large-scale data ingestion and processing—and then easily decrease SSD capacity to optimize resource utilization and reduce storage costs.
An FSx for ONTAP file system offers two storage tiers: a provisioned high-performance SSD tier for your active working set, and a fully elastic capacity pool cost-optimized for infrequently accessed data. Previously, you could increase a file system’s SSD capacity to meet your workload’s growing active working set but decreasing SSD capacity required migrating to a file system with smaller SSD capacity incurring administrative overhead and tolerating application downtime. Starting today, you can decrease your file system’s provisioned SSD capacity in-place with just a few clicks in the Amazon FSx console. You can deliver optimal performance to serve peak usage for workloads with varying high-performance storage requirements, including Electronic Design Automation jobs like chip fabrication and circuit simulation, and Media & Entertainment tasks like video editing and transcoding. Once data processing in SSD storage is complete, and results have been archived, you can decrease SSD capacity to optimize resource utilization. You can even accelerate large-scale data migrations by provisioning SSD capacity to temporarily accommodate more data in SSD, ensuring faster data ingestion, subsequently decreasing SSD capacity after data has been tiered to the capacity pool to optimize storage costs. You can decrease SSD storage capacity on all FSx for ONTAP second-generation file systems in all AWS Regions where FSx for ONTAP second-generation file systems are available. For more information, see the FSx for ONTAP user guide.