Today, AWS launches AWS Parallel Computing Service (PCS) in the AWS Europe (London) region, enabling you to easily build and manage High Performance Computing (HPC) clusters using the Slurm workload manager.

AWS PCS is a managed service that makes it easier for you to run and scale your high performance computing (HPC) workloads and build scientific and engineering models on AWS using Slurm. You can use AWS PCS to build complete, elastic environments that integrate compute, storage, networking, and visualization tools. AWS PCS simplifies cluster operations with managed updates and built-in observability features, helping to remove the burden of maintenance. You can work in a familiar environment, focusing on your research and innovation instead of worrying about infrastructure.

To get started, visit the AWS PCS page and the AWS PCS documentation.

​Today, AWS launches AWS Parallel Computing Service (PCS) in the AWS Europe (London) region, enabling you to easily build and manage High Performance Computing (HPC) clusters using the Slurm workload manager. AWS PCS is a managed service that makes it easier for you to run and scale your high performance computing (HPC) workloads and build scientific and engineering models on AWS using Slurm. You can use AWS PCS to build complete, elastic environments that integrate compute, storage, networking, and visualization tools. AWS PCS simplifies cluster operations with managed updates and built-in observability features, helping to remove the burden of maintenance. You can work in a familiar environment, focusing on your research and innovation instead of worrying about infrastructure. To get started, visit the AWS PCS page and the AWS PCS documentation.  

Today, AWS announces two new Model Context Protocol (MCP) servers in the AWS Labs MCP open-source repository: CloudWatch MCP server and Application Signals MCP server. These servers enable AI agents to leverage comprehensive observability capabilities for automated troubleshooting and monitoring. The MCP servers allow AI assistants to analyze metrics, alarms, logs, traces, and service health data across your AWS environment to quickly identify and diagnose issues through simple conversational interfaces.

The MCP servers provide curated sets of tools designed specifically for operational troubleshooting scenarios. The CloudWatch MCP server supports alarm-based incident response, metric analysis, and log pattern detection, while the Application Signals MCP server enables service health monitoring through Service Level Objectives (SLOs), and automated root cause analysis using OpenTelemetry data. By leveraging the MCP standard, AI agents can perform complex troubleshooting workflows through natural language interactions, from analyzing alarm patterns, and metric anomalies to investigating service health issues and querying logs and traces. Rather than requiring developers to manually navigate multiple AWS consoles and APIs, these MCP servers enable AI agents to orchestrate these interactions intelligently while reducing the development times typically required for API integrations.

The CloudWatch MCP server can be used with CloudWatch in all AWS regions, and the Application Signals MCP server can be used in all regions where Application Signals is available.

To download and try out these open-source MCP servers locally with your AI-enabled IDE of choice, visit the AWS Labs MCP open-source repository.

​Today, AWS announces two new Model Context Protocol (MCP) servers in the AWS Labs MCP open-source repository: CloudWatch MCP server and Application Signals MCP server. These servers enable AI agents to leverage comprehensive observability capabilities for automated troubleshooting and monitoring. The MCP servers allow AI assistants to analyze metrics, alarms, logs, traces, and service health data across your AWS environment to quickly identify and diagnose issues through simple conversational interfaces. The MCP servers provide curated sets of tools designed specifically for operational troubleshooting scenarios. The CloudWatch MCP server supports alarm-based incident response, metric analysis, and log pattern detection, while the Application Signals MCP server enables service health monitoring through Service Level Objectives (SLOs), and automated root cause analysis using OpenTelemetry data. By leveraging the MCP standard, AI agents can perform complex troubleshooting workflows through natural language interactions, from analyzing alarm patterns, and metric anomalies to investigating service health issues and querying logs and traces. Rather than requiring developers to manually navigate multiple AWS consoles and APIs, these MCP servers enable AI agents to orchestrate these interactions intelligently while reducing the development times typically required for API integrations. The CloudWatch MCP server can be used with CloudWatch in all AWS regions, and the Application Signals MCP server can be used in all regions where Application Signals is available. To download and try out these open-source MCP servers locally with your AI-enabled IDE of choice, visit the AWS Labs MCP open-source repository.  

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports Cumulative Update (CU) 19 for Microsoft SQL Server 2022. This update is available for SQL Server Developer, Web, Standard, and Enterprise editions, and includes performance improvements, security fixes, and bug fixes. For more details about the improvements in this update, please review Microsoft KB5054531 release notes.

We recommend upgrading to this CU 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. Learn more about upgrading your database instances from the Amazon RDS Custom User Guide.

This CU is available in all AWS Regions where Amazon RDS Custom for SQL Server is available.

RDS Custom is a managed database service that allows customization of the underlying operating system and database environment. RDS Custom for SQL Server supports two licensing models: License Included (LI) and Bring Your Own Media (BYOM). By using Bring Your Own Media (BYOM), customers can use their existing SQL Server licenses with Amazon RDS Custom for SQL Server. See Amazon RDS Custom Pricing for pricing details and regional availability.

​Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports Cumulative Update (CU) 19 for Microsoft SQL Server 2022. This update is available for SQL Server Developer, Web, Standard, and Enterprise editions, and includes performance improvements, security fixes, and bug fixes. For more details about the improvements in this update, please review Microsoft KB5054531 release notes. We recommend upgrading to this CU 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. Learn more about upgrading your database instances from the Amazon RDS Custom User Guide. This CU is available in all AWS Regions where Amazon RDS Custom for SQL Server is available. RDS Custom is a managed database service that allows customization of the underlying operating system and database environment. RDS Custom for SQL Server supports two licensing models: License Included (LI) and Bring Your Own Media (BYOM). By using Bring Your Own Media (BYOM), customers can use their existing SQL Server licenses with Amazon RDS Custom for SQL Server. See Amazon RDS Custom Pricing for pricing details and regional availability.  

Oracle Database@AWS is now generally available in the US East (N. Virginia) and US West (Oregon) Regions. It is a joint offering from AWS and Oracle that gives you access to Oracle Exadata Database Service and Oracle Autonomous Database on Dedicated Exadata Infrastructure within AWS data centers. You can benefit from a unified experience between AWS and Oracle with collaborative support, purchasing, management, and operations. Use of Oracle Database@AWS qualifies for AWS commitments as well as Oracle Support Rewards.

With Oracle Database@AWS, you can easily and quickly migrate your Oracle Exadata Database workloads, including Oracle Real Application Clusters (RAC), with minimal to no modifications to databases and associated applications. You can establish low-latency connections between AWS applications and Oracle Database@AWS. Zero-ETL integration with Amazon Redshift enables near real-time analytics and machine learning (ML) on transactional data stored in Oracle Database@AWS. You can store both Oracle-managed backups and backups you manually take to Amazon Simple Storage Service (Amazon S3), which is designed to provide 11 nines of durability. Oracle Database@AWS also integrates with AWS services such as AWS IAM for authentication and authorization, Amazon CloudWatch for monitoring, AWS CloudFormation for infrastructure as code, AWS CloudTrail for governance and compliance, Amazon EventBridge for event management, and Amazon VPC Lattice for simplified connectivity to AWS services.

Oracle Database@AWS will expand to 20 more regions across the Americas, Europe, and Asia Pacific including: US East (Ohio), US West (N. California), Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Milan), Europe (Paris), Europe (Spain), Europe (Stockholm), Europe (Zurich), and South America (São Paulo).  

To learn more, visit Oracle Database@AWS and its documentation. You can request a private offer from Oracle through AWS Marketplace and use the AWS Management Console to provision and manage your resources.

​Oracle Database@AWS is now generally available in the US East (N. Virginia) and US West (Oregon) Regions. It is a joint offering from AWS and Oracle that gives you access to Oracle Exadata Database Service and Oracle Autonomous Database on Dedicated Exadata Infrastructure within AWS data centers. You can benefit from a unified experience between AWS and Oracle with collaborative support, purchasing, management, and operations. Use of Oracle Database@AWS qualifies for AWS commitments as well as Oracle Support Rewards.
With Oracle Database@AWS, you can easily and quickly migrate your Oracle Exadata Database workloads, including Oracle Real Application Clusters (RAC), with minimal to no modifications to databases and associated applications. You can establish low-latency connections between AWS applications and Oracle Database@AWS. Zero-ETL integration with Amazon Redshift enables near real-time analytics and machine learning (ML) on transactional data stored in Oracle Database@AWS. You can store both Oracle-managed backups and backups you manually take to Amazon Simple Storage Service (Amazon S3), which is designed to provide 11 nines of durability. Oracle Database@AWS also integrates with AWS services such as AWS IAM for authentication and authorization, Amazon CloudWatch for monitoring, AWS CloudFormation for infrastructure as code, AWS CloudTrail for governance and compliance, Amazon EventBridge for event management, and Amazon VPC Lattice for simplified connectivity to AWS services.
Oracle Database@AWS will expand to 20 more regions across the Americas, Europe, and Asia Pacific including: US East (Ohio), US West (N. California), Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Milan), Europe (Paris), Europe (Spain), Europe (Stockholm), Europe (Zurich), and South America (São Paulo).  
To learn more, visit Oracle Database@AWS and its documentation. You can request a private offer from Oracle through AWS Marketplace and use the AWS Management Console to provision and manage your resources.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8g, M8g, and R8g instances are available in AWS Asia Pacific (Singapore) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 C8g instances are built for compute-intensive workloads, such as high performance computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based machine learning (ML) inference, and ad serving. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System.

AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors.

To learn more, see Amazon EC2 C8g Instances, Amazon EC2 M8g Instances, and Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console. 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8g, M8g, and R8g instances are available in AWS Asia Pacific (Singapore) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 C8g instances are built for compute-intensive workloads, such as high performance computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based machine learning (ML) inference, and ad serving. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. To learn more, see Amazon EC2 C8g Instances, Amazon EC2 M8g Instances, and Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.   

• Categoría: Noticias de Microsoft

julio 8, 2025

Interacción proactiva y recorridos conversacionales impulsados por IA con Microsoft Dynamics 365 en versión preliminar pública

Por: Sundar Raghavan, vicepresidente de productos de Dynamics 365 Customer Engagement Applications.

Los clientes no solo quieren un servicio rápido, sino que esperan que las empresas vayan un paso por delante. Los clientes de hoy en día quieren que las empresas se anticipen a sus necesidades incluso antes de pedirlas, por ejemplo: enviar un recordatorio antes de que un pago se retrase; dar un aviso cuando una entrega se retrasa o hacer un seguimiento después de una llamada interrumpida. No se trata solo de productos agradables de tener, sino que creemos que son el nuevo estándar para la experiencia del cliente.

Es por eso que anunciamos  la interacción proactiva y los recorridos conversacionales con Microsoft Dynamics 365 Contact Center y Microsoft Dynamics 365 Customer Insights – Journeys, ahora disponibles en versión preliminar pública. Con esta solución, las organizaciones pueden utilizar agentes y representantes de servicio de IA personalizados para comunicarse de forma proactiva a través de los canales, como informar a un cliente sobre un vuelo cancelado y guiarlo hacia una resolución en la misma conversación. Las empresas pueden beneficiarse de menores volúmenes de llamadas y costos de soporte, mientras que los clientes pueden obtener experiencias más rápidas y personalizadas que impulsan la satisfacción y la lealtad a la marca. Se espera que esté disponible para el público general a finales de este verano.

Por supuesto, ofrecer un servicio proactivo a escala no es fácil. Las organizaciones pueden estar bajo presión para hacer más con menos: menos recursos, presupuestos más ajustados y mayores expectativas de los clientes. Llegar en el momento adecuado, con el mensaje correcto, en el canal correcto requiere orquestación, conocimiento y automatización inteligente. Eso es justo para lo que están diseñadas estas nuevas capacidades: un compromiso más inteligente y con una alta personalización.

El impacto de la IA en el servicio al cliente

De cara al futuro, la influencia de la IA en la experiencia del cliente no hará más que profundizarse. Según el Índice de Tendencias Laborales de Microsoft, el 82% de los líderes esperan ampliar su uso de la mano de obra digital para aumentar la capacidad de la fuerza laboral en los próximos 12 a 18 meses.

Nuestros clientes ya han comenzado a cosechar los beneficios de los compañeros de equipo digitales impulsados por IA. Los segmentos de turismo y viajes, por ejemplo, utilizan la participación proactiva y los recorridos conversacionales para ayudar a los clientes con la planificación de viajes, desde las reservas hasta la orientación del itinerario, con representantes humanos disponibles para ayudar más según sea necesario.

Apollo Travel, una agencia de viajes que atiende más de 350 mil reservas al año en Escandinavia, utiliza la participación proactiva para reducir las llamadas entrantes de reservas.

«Siempre estamos en la búsqueda de formas de atender mejor a nuestros clientes, y estas nuevas capacidades abren oportunidades emocionantes para interactuar con ellos de manera más proactiva. Vemos un claro potencial de beneficios en ambos lados, al mejorar la experiencia de nuestros clientes e impulsar la eficiencia de nuestro negocio».

—Johnny Nilsson, jefe del centro de excelencia de plataformas de energía del Grupo Apollo Travel (parte del Grupo DERTOUR)

Otros casos de uso demuestran el valor más amplio de este enfoque: los retrasos en los envíos y las entregas, los recordatorios de citas, las interrupciones del sistema, las reposiciones de recetas, las notificaciones de recompensas por fidelidad y las actualizaciones de servicios son posibles gracias a la divulgación basada en agentes de IA. Las interacciones se sienten naturales y útiles y, si es necesario, se transfieren sin problemas a un representante de servicio para obtener soporte personalizado, para convertir un problema potencial en un momento de lealtad a la marca. Los clientes pueden comunicarse de forma natural con el agente de IA, que, basándose en ese diálogo, ofrecerá soluciones como transferirse a un vuelo diferente o emitir un reembolso. En función de sus requisitos, la interacción proactiva puede seguir con acciones adicionales, como un correo electrónico de confirmación o un mensaje de texto.

Debido a que estas tareas repetitivas y que consumen mucho tiempo ahora están automatizadas, los representantes pueden concentrarse en problemas más críticos y brindar compromisos significativos a cada cliente. Esto ayuda a generar confianza y garantizar que los clientes se sientan valorados, al tiempo que permite que los equipos de servicio se centren en interacciones más complejas y de alto valor, lo que ayuda a reducir los costos operativos y mejorar la eficiencia general.

Un escenario típico tiene tres partes. La primera parte es un recorrido del cliente que le dice al agente de IA a quién llamar, cuándo llamar y cómo procesar las elecciones que el cliente hace durante la llamada. La segunda parte es el agente de IA, que puede comunicarse con los clientes mediante lenguaje natural. La parte final lo reúne todo, con los autores que gestionan las colas de clientes del agente, los números de teléfono y similares. Si un cliente pregunta, aquí es también donde un agente transferiría la llamada a un representante de servicio y luego administraría esa llamada hasta que se resuelva. La solución completa se puede crear sin código (incluida la capacidad de diseñar el agente de IA utilizando lenguaje natural), lo que la hace accesible para que los usuarios empresariales no técnicos definan sus experiencias de cliente con facilidad. Con la gestión de consentimiento integrada y los horarios/días de silencio designados, el cumplimiento de las preferencias del cliente y los requisitos reglamentarios se puede mantener sin esfuerzo. Además, ofrece la flexibilidad de responder a eventos en tiempo real o programar un alcance con anticipación.

Permitir la participación proactiva

Para habilitar la solución, se requieren Microsoft Dynamics 365 Contact Center, Dynamics 365 Customer Insights-Journeys y Microsoft Copilot Studio. A medida que utilicen la solución, envíen sus comentarios a pefeedback@microsoft.com y no olviden consultar este blog para obtener actualizaciones sobre esta y otras versiones próximas.

Etiquetas:

• IA
• Tecnología

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​The post Interacción proactiva y recorridos conversacionales impulsados por IA con Microsoft Dynamics 365 en versión preliminar pública appeared first on Source LATAM.  

The post Microsoft for Startups presenta Catalysts: avances impulsados por IA con Microsoft Azure y NVIDIA appeared first on Source LATAM.

​The post Microsoft for Startups presenta Catalysts: avances impulsados por IA con Microsoft Azure y NVIDIA appeared first on Source LATAM.  

The post Afinar es el secreto para ampliar el conocimiento experto en toda la empresa appeared first on Source LATAM.

​The post Afinar es el secreto para ampliar el conocimiento experto en toda la empresa appeared first on Source LATAM.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in Asia Pacific (Seoul), and AWS Asia Pacific (Malaysia) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.

AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS).

To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in Asia Pacific (Seoul), and AWS Asia Pacific (Malaysia) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.  

Amazon Simple Notification Services (Amazon SNS) now supports notification delivery to Amazon Data Firehose endpoints in three additional AWS Regions, Asia Pacific (Taipei), Asia Pacific (Thailand) and Mexico (Central) Regions.

You can now use Amazon SNS to deliver notifications to Amazon Data Firehose (Firehose) endpoints for storage and analysis. Through Firehose delivery streams, customers can deliver events to AWS destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Redshift, and Amazon OpenSearch Service, or to third-party destinations such as Datadog, New Relic, MongoDB, and Splunk.

To get started, see the following resources:

• Fanout to Firehose delivery streams in the Amazon SNS Developer Guide.
• Create Firehose Stream in the Amazon Data Firehose Developer Guide.
• SNS pricing for deliveries to Amazon Data Firehose in the Amazon SNS Pricing Page.

​Amazon Simple Notification Services (Amazon SNS) now supports notification delivery to Amazon Data Firehose endpoints in three additional AWS Regions, Asia Pacific (Taipei), Asia Pacific (Thailand) and Mexico (Central) Regions. You can now use Amazon SNS to deliver notifications to Amazon Data Firehose (Firehose) endpoints for storage and analysis. Through Firehose delivery streams, customers can deliver events to AWS destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Redshift, and Amazon OpenSearch Service, or to third-party destinations such as Datadog, New Relic, MongoDB, and Splunk. To get started, see the following resources:

Fanout to Firehose delivery streams in the Amazon SNS Developer Guide.
Create Firehose Stream in the Amazon Data Firehose Developer Guide.
SNS pricing for deliveries to Amazon Data Firehose in the Amazon SNS Pricing Page.