Amazon Elastic Compute Cloud (Amazon EC2) R8gd instances with up to 11.4 TB of local NVMe-based SSD block-level storage are now available in US West (N. California), Asia Pacific (Seoul, Hong Kong, Jakarta), Africa (Cape Town), and Canada West (Calgary) AWS Regions. These instances are powered by AWS Graviton4 processors, delivering up to 30% better performance over Graviton3-based instances. They have up to 40% higher performance for I/O intensive database workloads, and up to 20% faster query results for I/O intensive real-time data analytics than comparable AWS Graviton3-based instances. These instances are built on the AWS Nitro System and are a great fit for applications that need access to high-speed, low latency local storage.
Each instance is available in 12 different sizes. They provide up to 50 Gbps of network bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Additionally, customers can now adjust the network and Amazon EBS bandwidth on these instances by 25% using EC2 instance bandwidth weighting configuration, providing greater flexibility with the allocation of bandwidth resources to better optimize workloads. These instances offer Elastic Fabric Adapter (EFA) networking on 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes.
Amazon Elastic Compute Cloud (Amazon EC2) R8gd instances with up to 11.4 TB of local NVMe-based SSD block-level storage are now available in US West (N. California), Asia Pacific (Seoul, Hong Kong, Jakarta), Africa (Cape Town), and Canada West (Calgary) AWS Regions. These instances are powered by AWS Graviton4 processors, delivering up to 30% better performance over Graviton3-based instances. They have up to 40% higher performance for I/O intensive database workloads, and up to 20% faster query results for I/O intensive real-time data analytics than comparable AWS Graviton3-based instances. These instances are built on the AWS Nitro System and are a great fit for applications that need access to high-speed, low latency local storage. Each instance is available in 12 different sizes. They provide up to 50 Gbps of network bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Additionally, customers can now adjust the network and Amazon EBS bandwidth on these instances by 25% using EC2 instance bandwidth weighting configuration, providing greater flexibility with the allocation of bandwidth resources to better optimize workloads. These instances offer Elastic Fabric Adapter (EFA) networking on 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes. To learn more, see Amazon R8gd 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.
Muchos agentes, un solo equipo: Escalar la modernización en Azure
Por: Jeremy Winter, vicepresidente corporativo y director de producto de Azure Platform.
Anunciamos nuevos agentes para modernización diseñados para escalar y para el control.
Cuando ven una transmisión en directo—como los Juegos Olímpicos o un gran evento deportivo—no piensan en la coordinación que hay detrás. Solo experimentan el evento. Fuera de la vista, equipos especializados sincronizan cámaras, repeticiones, datos y comentarios en tiempo real. Cuando esa coordinación funciona, la complejidad desaparece.
Así es como pienso sobre los agentes de IA. Cada uno observa una señal diferente y aporta una parte de la imagen. La telemetría pone a la luz lo que ocurre, las dependencias revelan cómo están conectados los sistemas y los riesgos surgen a medida que avanza el trabajo. El humano mantiene el control durante todo el proceso—al decidir sobre qué actuar y cómo validar los resultados.
Este modelo es importante porque la modernización se ha convertido en una de las mayores oportunidades en la era de la IA. De hecho, según la Encuesta de Modernización de Aplicaciones de Nube e IA de Forrester en el primer trimestre de 2026, el 91% de los líderes de TI considera la modernización de aplicaciones necesaria para facilitar avances en IA en su negocio.1 Sin embargo, muchas organizaciones aun gestionan complejos conjuntos heredados con herramientas desconectadas y meses de planificación manual solo para decidir qué modernizar. TI y los desarrolladores a menudo trabajan en paralelo pero sin una visión compartida del sistema. La IA cambia la dinámica, al ayudar a los equipos a analizar los entornos, priorizar las cargas de trabajo y acelerar la modernización.
Fuente: Encuesta de Modernización de Aplicaciones en la Nube y IA de Forrester Q1 2026.
Hoy, damos otro paso para ayudar a las organizaciones a adoptar nuevas capacidades de IA con un impacto real en el negocio. Anunciamos la primera solución de modernización agéntica de extremo a extremo que reúne a TI y desarrolladores en un único flujo de trabajo conectado. Con capacidades ampliadas en Azure Copilot y GitHub Copilot, incorporamos la IA a través de estas herramientas para acelerar decisiones basadas en información de valor y llevar la modernización del análisis a la acción, más rápido y a gran escala.
Los agentes de IA hacen esto posible al operar en paralelo a través del descubrimiento, la evaluación, la planificación, la migración y la transformación del código. Automatizan el mapeo de dependencias, generan planes listos para tomar decisiones y guían la ejecución dentro de las herramientas que ya utilizan los equipos. El trabajo que antes era lento, manual y fragmentado se vuelve coordinado y continuo a medida que los equipos se modernizan entre aplicaciones, infraestructura, datos y código.
Un sistema. Un equipo.
El nuevo compañero de equipo agéntico, el agente de migración de Azure Copilot, está ahora en vista previa pública. El agente de migración ayuda a las organizaciones a eliminar la deuda técnica a través de la integración de la IA en el descubrimiento, evaluación, planificación y despliegue, para reducir de manera importante los plazos de modernización. Funciona para sus servidores, máquinas virtuales, aplicaciones y bases de datos más críticos, para convertir la migración de un proyecto puntual en un movimiento de modernización continua.
El agente utiliza lo que los clientes ya saben sobre sus entornos para crear este sistema de modernización continua que proporciona claridad temprana sobre su inventario de servidores, bases de datos, aplicaciones y sus dependencias, cómo funciona todo, cuánto cuesta y qué merece la pena modernizar. Lo que antes requería meses de planificación manual ahora puede requerir minutos de conversación con el agente y un plan basado en datos.
Al reducir el trabajo, cerrar brechas de habilidades y alinear los equipos de TI y desarrollo mediante flujos de trabajo conectados, el agente de migración de Azure Copilot puede ayudar a las empresas a migrar a Azure más rápido y con mayor confianza.
Las capacidades de modernización de GitHub Copilot también enriquecen su equipo de modernización con agentes para transformar aplicaciones heredadas y hacerlas listas para la nube y la IA. Integrados directo donde trabajan los desarrolladores, estos agentes pueden extraer evaluaciones, crear planes de modernización personalizados para cada aplicación, ejecutar actualizaciones y desplegar de manera directa en Azure, todo ello con los desarrolladores al volante.
Y hoy, su capacidad más reciente, el agente de modernización, está en vista previa pública. El agente de modernización les permite ir más allá de las aplicaciones individuales y abordar la modernización a gran escala, actúa como orquestador para ejecutar de manera simultánea múltiples evaluaciones de código, crear planes de modernización únicos para cada aplicación y ejecutar los planes con estructuras automatizadas y actualizaciones en tiempo de ejecución. Esto supone un gran avance en la forma en que los propietarios de aplicaciones, arquitectos y desarrolladores pueden transformar un amplio conjunto de aplicaciones a gran escala, lo que mantiene la personalización necesaria para cada una.
En una experiencia multiagente verdadera, el agente de modernización dirige la difusión: los propietarios de la aplicación y arquitectos establecen la dirección, los agentes especializados ejecutan y los desarrolladores se mantienen informados para guiar y validar.
Las organizaciones ya han tenido éxito con las capacidades de GitHub Copilot que se hicieron disponibles de manera general este pasado otoño, modernizándose en horas en lugar de meses con actualizaciones automatizadas de .NET y Java. Para un cliente reciente, el esfuerzo total de modernización se redujo en un 70%.2 Hoy en día, gracias a su conexión al agente de migración Azure Copilot y su integración nativa en entornos de desarrollo, la modernización de GitHub Copilot puede transformar aplicaciones de extremo a extremo, con mayores resultados y control en cada paso.
A nivel histórico, las decisiones de infraestructura—zonas de aterrizaje, redes, gobernanza—se tomaban aguas arriba, sin visibilidad sobre las realidades de las aplicaciones. Los desarrolladores modernizaban el código sin saber cómo se ejecutaría, escalaría o estaría gobernado en el entorno objetivo. Esto hizo que los desajustes surgieran tarde, cuando las reparaciones eran más caras.
Con el trabajo en conjunto de Azure Copilot y GitHub Copilot, esa desconexión desaparece. Los agentes ayudan a conectar los conocimientos de código a nivel de desarrollador con la migración a la nube y la planificación de modernización. Las capacidades de modernización de GitHub Copilot escanean el código de la aplicación para producir informes detallados de evaluación de código, mientras que el agente de migración de Azure Copilot absorbe esos informes para mostrar problemas, advertencias e información de valor a nivel de código. Esta integración permite a Azure Copilot incorporar análisis real de código al evaluar la preparación y recomendar el objetivo adecuado de Azure, para conectar el trabajo de modernización impulsado por desarrolladores con la planificación de la nube y la infraestructura que utilizan los equipos de migración. Ustedes disponen de una planificación guiada por IA de migración y modernización con priorización inteligente de cargas de trabajo, visibilidad de costes y recomendaciones automáticas de oleadas.
Por qué su base de datos es fundamental para la modernización
Modernizar las aplicaciones es solo una parte del camino. Su base de datos es fundamental, porque su estrategia de IA solo es tan fuerte como lo es su estrategia de datos. Cuando los datos se fragmentan o se bloquean en infraestructuras envejecidas, incluso los flujos de trabajo agénticos más sofisticados alcanzan un techo.
Pasar a Azure gestiona los servicios de base de datos para la IA y transfiere la carga operativa de la gestión de infraestructura a una plataforma diseñada para gestionarla. Los servicios gestionados por completo reducen la sobrecarga, mejoran la resiliencia y permiten a los equipos centrarse en construir aplicaciones inteligentes. El resultado es una base de datos que puede escalar con la demanda, cumplir con las expectativas de seguridad y estar preparada para lo que requieren las cargas de trabajo de IA.
Una vez que su patrimonio de datos se moderniza en Azure, el destino es una plataforma de datos unificada—donde bases de datos, análisis e IA funcionan como un solo patrimonio coherente. Con capacidades de IA integradas de manera nativa en las bases de datos de Azure, las organizaciones pueden crear aplicaciones de IA nativas en la nube que aprovechen la búsqueda semántica, la integración de memoria y la invocación avanzada de modelos. Esas capacidades están fundamentadas en la capa de datos de Azure, por lo que los modelos siempre trabajan con las señales más actuales y fiables que produce el negocio.
Cómo la modernización en Azure empodera a los clientes
Nuestros agentes hacen que esto sea posible. Nos alejamos del uso puntual de herramientas agénticas hacia una ejecución agente consistente y repetible. Esta es la importancia de combinar herramientas agénticas con modelos de entrega estructurados, para que las organizaciones puedan escalar la modernización con confianza en equipos y entornos.
Ahold Delhaize, uno de los mayores grupos minoristas de alimentos del mundo, compartió cómo modernizaron su patrimonio de aplicaciones y datos en Azure para apoyar resultados empresariales impulsados por IA. A través de herramientas de agentes a lo largo de los flujos de trabajo de migración y modernización, redujeron la complejidad, mejoraron la colaboración en modernización entre equipos y aceleraron la entrega.
Al aplicar agentes en la fase de descubrimiento, evaluación y ejecución, Ahold Delhaize se alejó de los esfuerzos de modernización fragmentados y se acercó a un proceso más continuo e inteligente, uno que proporcionara confianza tanto en el plan como en la ejecución.
Resultados como estos para los clientes apuntan a la misma conclusión: el futuro de la modernización es agéntico, conectado y liderado por el ser humano.
Cloud Accelerate Factory da vida a la modernización de los agentes a gran escala
Las herramientas agentes redefinen lo que es posible, pero los resultados escalan cuando la innovación se combina con la ejecución. Cloud Accelerate Factory, un beneficio de Azure Accelerate, ayuda a las organizaciones a operacionalizar la modernización con una entrega gratuita y práctica por expertos especializados de Microsoft.
Como motor de entrega de modernización de primera mano de Microsoft, Cloud Accelerate Factory trabaja junto a clientes y socios desde el descubrimiento hasta la producción, a través de la aplicación de un enfoque estructurado a la modernización a gran escala en aplicaciones, infraestructura y datos—a menudo en días, no en meses.
Combinado con capacidades de agente como Azure Copilot y GitHub Copilot, Cloud Accelerate Factory ayuda a las organizaciones a modernizarse con confianza y rapidez, para que los planes se conviertan en un progreso medible en cargas de trabajo clave como .NET, Java y SQL.
Únanse a los visionarios en Microsoft Azure Summit
Prepárense para una agenda rica en Microsoft Azure Summit de este año: migra y moderniza con IA agéntica. Este evento en directo del 23 de abril de 2026 (Américas) incluye sesiones interactivas dirigidas por ingeniería de Microsoft, con historias de clientes atractivas y demostraciones en directo de las últimas innovaciones que se discuten en este blog. Escuchen de manera directa a organizaciones que han aprovechado con éxito las últimas herramientas y capacidades agénticas para migrar y modernizarse a Azure, y vean de primera mano cómo las nuevas ofertas pueden tener un impacto tangible en su negocio.
La cumbre de este año presenta una impresionante lista de temas que les ayudarán a construir el futuro de la nube y la IA.
Conferencia principal: Migra y moderniza con IA agéntica
Sesión regional (personalizada): Modernización para una figura soberana y lista para IA
Breakout: Acelerar y simplificar la planificación, migración y operaciones con agentes de IA
Breakout: Reimaginar la modernización de aplicaciones y bases de datos con herramientas agenticas
1Encuesta de Modernización de Aplicaciones de Nube e IA del primer trimestre de 2026 de Forrester [E-66670] Base: 223 líderes globales responsables de la estrategia de nube e IA de su organización.
Amazon Quick is now available in the AWS Asia Pacific (Tokyo) region (ap-northeast-1). This launch allows customers in Japan to access the full power of Amazon Quick while meeting local and regional requirements for data sovereignty.
Amazon Quick provides business users an agentic teammate that quickly answers questions at work and turns those answers into actions. With Amazon Quick, every user is empowered to make better decisions, faster and take actions without switching applications using AI they can trust. Today’s launch allows customers to take advantage of Amazon Quick’s capabilities including AI-powered chat, Research, Spaces, Flows, and QuickSight dashboards — with their data stored and processed locally within the AWS Tokyo region. This expansion also supports in-region inference through JP-CRIS (Japan Cross-Region Inference), ensuring that inference requests from Tokyo instances are routed exclusively within the AWS Tokyo region. Customers in regulated industries such as financial services, healthcare, and the public sector can meet strict data sovereignty requirements of Japan’s data protection frameworks, including the Act on the Protection of Personal Information (APPI).
Amazon Quick is now available in the AWS Asia Pacific (Tokyo) region (ap-northeast-1). This launch allows customers in Japan to access the full power of Amazon Quick while meeting local and regional requirements for data sovereignty.
Amazon Quick provides business users an agentic teammate that quickly answers questions at work and turns those answers into actions. With Amazon Quick, every user is empowered to make better decisions, faster and take actions without switching applications using AI they can trust. Today’s launch allows customers to take advantage of Amazon Quick’s capabilities including AI-powered chat, Research, Spaces, Flows, and QuickSight dashboards — with their data stored and processed locally within the AWS Tokyo region. This expansion also supports in-region inference through JP-CRIS (Japan Cross-Region Inference), ensuring that inference requests from Tokyo instances are routed exclusively within the AWS Tokyo region. Customers in regulated industries such as financial services, healthcare, and the public sector can meet strict data sovereignty requirements of Japan’s data protection frameworks, including the Act on the Protection of Personal Information (APPI).
For a full list of AWS regions where Amazon Quick is available, visit the Quick regional availability page. To learn more, visit the Amazon Quick documentation or product detail page.
AWS announces the Agent Plugin for AWS Serverless, enabling developers to easily build, deploy, troubleshoot, and manage serverless applications using AI coding assistants like Kiro, Claude Code, and Cursor.
Agent plugins extend AI coding assistants with structured, reusable capabilities by packaging skills, sub-agents, hooks, and Model Context Protocol (MCP) servers into a single modular unit. The Agent Plugin for AWS Serverless dynamically loads relevant guidance and expertise required throughout the development lifecycle for building production-ready serverless applications on AWS. You can create AWS Lambda functions that integrate with popular event sources like Amazon EventBridge, Amazon Kinesis, and AWS Step Functions, while following built-in best practices for observability, performance optimization, and troubleshooting. As you adopt Infrastructure as Code (IaC), you can streamline project setup with AWS Serverless Application Model (SAM) and AWS Cloud Development Kit (CDK), with reusable constructs, proven architectural patterns, automated CI/CD pipelines, and local testing workflows. For long-running, stateful workflows, you can build with confidence using Lambda durable functions, which provides checkpoint-replay model, advanced orchestration patterns, and error handling capabilities. Lastly, you can design and manage APIs as part of your application using Amazon API Gateway, with guidance across REST APIs, HTTP APIs, and WebSocket APIs. These capabilities are packaged as agent skills in the open Agent Skills format, making them usable across compatible AI tools such as Kiro, Claude Code, and Cursor.
The Agent Plugin for AWS Serverless is available in any AI coding assistant tools that support agent plugins such as Claude Code and Cursor. In Claude Code, you can install it from the official Claude Marketplace using a simple command ‘/plugin install aws-serverless@claude-plugins-official’. You can also install agent skills from the plugin individually in any AI coding assistant tools that support agent skills. To learn more about the plugin and its capabilities, visit GitHub.
AWS announces the Agent Plugin for AWS Serverless, enabling developers to easily build, deploy, troubleshoot, and manage serverless applications using AI coding assistants like Kiro, Claude Code, and Cursor.
Agent plugins extend AI coding assistants with structured, reusable capabilities by packaging skills, sub-agents, hooks, and Model Context Protocol (MCP) servers into a single modular unit. The Agent Plugin for AWS Serverless dynamically loads relevant guidance and expertise required throughout the development lifecycle for building production-ready serverless applications on AWS. You can create AWS Lambda functions that integrate with popular event sources like Amazon EventBridge, Amazon Kinesis, and AWS Step Functions, while following built-in best practices for observability, performance optimization, and troubleshooting. As you adopt Infrastructure as Code (IaC), you can streamline project setup with AWS Serverless Application Model (SAM) and AWS Cloud Development Kit (CDK), with reusable constructs, proven architectural patterns, automated CI/CD pipelines, and local testing workflows. For long-running, stateful workflows, you can build with confidence using Lambda durable functions, which provides checkpoint-replay model, advanced orchestration patterns, and error handling capabilities. Lastly, you can design and manage APIs as part of your application using Amazon API Gateway, with guidance across REST APIs, HTTP APIs, and WebSocket APIs. These capabilities are packaged as agent skills in the open Agent Skills format, making them usable across compatible AI tools such as Kiro, Claude Code, and Cursor.
The Agent Plugin for AWS Serverless is available in any AI coding assistant tools that support agent plugins such as Claude Code and Cursor. In Claude Code, you can install it from the official Claude Marketplace using a simple command ‘/plugin install aws-serverless@claude-plugins-official’. You can also install agent skills from the plugin individually in any AI coding assistant tools that support agent skills. To learn more about the plugin and its capabilities, visit GitHub.
Today, AWS announces remote connection from Cursor IDE to Amazon SageMaker Unified Studio via the AWS Toolkit extension. This new capability allows data scientists, ML engineers, and developers to leverage their Cursor setup – including its AI-powered code completion, natural language editing, and multi-file editing capabilities – while accessing the scalable compute resources of Amazon SageMaker. By connecting Cursor to SageMaker Unified Studio using the AWS Toolkit extension, you can eliminate context switching between your local IDE and cloud infrastructure, maintaining your existing AI-assisted development workflows within a single environment for all your AWS analytics and AI/ML services.
SageMaker Unified Studio, part of the next generation of Amazon SageMaker, offers a broad set of fully managed cloud interactive development environments (IDE), including JupyterLab and Code Editor based on Code-OSS (Open-Source Software). Starting today, you can also use your customized local Cursor setup – complete with custom rules, extensions, and AI model preferences – while accessing your compute resources and data on Amazon SageMaker. Since Cursor is built on Code-OSS, authentication is secure via IAM through the AWS Toolkit extension, giving you access to all your SageMaker Unified Studio domains and projects. This integration provides a convenient path from your local AI-powered development environment to scalable infrastructure for running workloads across data processing, SQL analytics services like Amazon EMR, AWS Glue, and Amazon Athena, and ML workflows – all with enterprise-grade security including customer-managed encryption keys and AWS IAM integration.
Today, AWS announces remote connection from Cursor IDE to Amazon SageMaker Unified Studio via the AWS Toolkit extension. This new capability allows data scientists, ML engineers, and developers to leverage their Cursor setup – including its AI-powered code completion, natural language editing, and multi-file editing capabilities – while accessing the scalable compute resources of Amazon SageMaker. By connecting Cursor to SageMaker Unified Studio using the AWS Toolkit extension, you can eliminate context switching between your local IDE and cloud infrastructure, maintaining your existing AI-assisted development workflows within a single environment for all your AWS analytics and AI/ML services.
SageMaker Unified Studio, part of the next generation of Amazon SageMaker, offers a broad set of fully managed cloud interactive development environments (IDE), including JupyterLab and Code Editor based on Code-OSS (Open-Source Software). Starting today, you can also use your customized local Cursor setup – complete with custom rules, extensions, and AI model preferences – while accessing your compute resources and data on Amazon SageMaker. Since Cursor is built on Code-OSS, authentication is secure via IAM through the AWS Toolkit extension, giving you access to all your SageMaker Unified Studio domains and projects. This integration provides a convenient path from your local AI-powered development environment to scalable infrastructure for running workloads across data processing, SQL analytics services like Amazon EMR, AWS Glue, and Amazon Athena, and ML workflows – all with enterprise-grade security including customer-managed encryption keys and AWS IAM integration.
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the local IDE support documentation..
Amazon Aurora PostgreSQL now offers a new experience to create a cluster with express configuration, enabling you to create and query an Aurora serverless database in seconds. With pre-configured settings, the new experience accelerates initial setup and reduces time to first query. You have the flexibility to modify certain settings during creation and most other settings afterward.
Aurora clusters created using express configuration reside outside a virtual private cloud (VPC) network and include an internet access gateway for secure connections from your favorite development tools – no VPN, or AWS Direct Connect required. The internet access gateway supports the full PostgreSQL wire protocol, enabling connectivity from a broad range of development tools and clients. It is distributed across multiple Availability Zones, providing the same level of high availability as your Aurora cluster. It also sets up AWS Identity and Access Management (IAM) authentication for your administrator user by default, enabling passwordless database authentication from the beginning without additional configuration.
Amazon Aurora PostgreSQL now offers a new experience to create a cluster with express configuration, enabling you to create and query an Aurora serverless database in seconds. With pre-configured settings, the new experience accelerates initial setup and reduces time to first query. You have the flexibility to modify certain settings during creation and most other settings afterward.
Aurora clusters created using express configuration reside outside a virtual private cloud (VPC) network and include an internet access gateway for secure connections from your favorite development tools – no VPN, or AWS Direct Connect required. The internet access gateway supports the full PostgreSQL wire protocol, enabling connectivity from a broad range of development tools and clients. It is distributed across multiple Availability Zones, providing the same level of high availability as your Aurora cluster. It also sets up AWS Identity and Access Management (IAM) authentication for your administrator user by default, enabling passwordless database authentication from the beginning without additional configuration.
Aurora PostgreSQL serverless is now available with the AWS Free Tier on both the Free and Paid plans. For regional availability and more details, see the Amazon Aurora documentation or read the launch blog. To get started, use the Amazon RDS Console, AWS CLI, or AWS SDKs.
Amazon Aurora PostgreSQL is now available on the AWS Free Tier, which offers new customers $100 in AWS credits upon sign-up and the ability to earn an additional $100 in credits by using services including Amazon RDS.
With a Free Plan account, you can create an Aurora PostgreSQL serverless cluster from the Amazon RDS Console, AWS CLI, or AWS SDKs using express configuration, which enables you to create and query an Aurora PostgreSQL database in seconds. To get started, select the Free Plan during new AWS account sign-up.
Amazon Aurora PostgreSQL is now available on the AWS Free Tier, which offers new customers $100 in AWS credits upon sign-up and the ability to earn an additional $100 in credits by using services including Amazon RDS. With a Free Plan account, you can create an Aurora PostgreSQL serverless cluster from the Amazon RDS Console, AWS CLI, or AWS SDKs using express configuration, which enables you to create and query an Aurora PostgreSQL database in seconds. To get started, select the Free Plan during new AWS account sign-up.
AWS Free Tier is available in all AWS Regions where Aurora PostgreSQL serverless is supported. For more details, see the Aurora & RDS Free Tier and AWS Free Tier pages.
AWS Batch now provides enhanced visibility into your compute environments with two new capabilities that help you maintain operational best practices. When you describe a compute environment, you can now see the status of your Batch-provided default Amazon Machine Images (AMIs), indicating when updates are available. Additionally, AWS Batch now publishes AWS Health Planned Lifecycle Events to help you prepare for and track changes affecting your batch computing resources.
The AMI status indicator shows whether you’re using the latest AMI (LATEST) or if an update is available (UPDATE_AVAILABLE), helping you identify compute environments that may be running outdated AMIs. AWS Health Planned Lifecycle Events provide advance notification of upcoming changes, such as AMI deprecations, help you monitor migration status of your affected compute environments, and automate responses using Amazon EventBridge.
AWS Batch now provides enhanced visibility into your compute environments with two new capabilities that help you maintain operational best practices. When you describe a compute environment, you can now see the status of your Batch-provided default Amazon Machine Images (AMIs), indicating when updates are available. Additionally, AWS Batch now publishes AWS Health Planned Lifecycle Events to help you prepare for and track changes affecting your batch computing resources. The AMI status indicator shows whether you’re using the latest AMI (LATEST) or if an update is available (UPDATE_AVAILABLE), helping you identify compute environments that may be running outdated AMIs. AWS Health Planned Lifecycle Events provide advance notification of upcoming changes, such as AMI deprecations, help you monitor migration status of your affected compute environments, and automate responses using Amazon EventBridge. AMI status indicator and AWS Health Planned Lifecycle Events are available today in all AWS Regions where AWS Batch is available. For more information, see Managing AMI versions and AWS Health Planned Lifecycle Events pages in the AWS Batch User Guide.
Amazon Bedrock AgentCore now enables customers to configure Chrome Enterprise policies for AgentCore Browser and specify custom root Certificate Authority (CA) certificates for both AgentCore Browser and Code Interpreter. These enhancements help ensure enterprise requirements are met when allowing AI agents to operate within organizations that have strict security policies and internal infrastructure using custom certificates.
With Chrome policies, you can leverage over 100+ configurable policies for managing browser behavior across security, URL filtering, content settings, and more to enforce organizational compliance requirements. For example, restrict agents to specific URLs for kiosk-mode operations, disable password managers and downloads for data-entry tasks, or implement URL blocklists for regulatory compliance. Custom root CA support enables agents to seamlessly connect to internal services like Artifactory, Jira, and finance portals that use SSL certificates signed by your organization’s internal Certificate Authority, and work with corporate proxies performing TLS interception.
These features are available in all 14 AWS Regions where Amazon Bedrock AgentCore Browser and Code Interpreter are available: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Canada (Central).
Amazon Bedrock AgentCore now enables customers to configure Chrome Enterprise policies for AgentCore Browser and specify custom root Certificate Authority (CA) certificates for both AgentCore Browser and Code Interpreter. These enhancements help ensure enterprise requirements are met when allowing AI agents to operate within organizations that have strict security policies and internal infrastructure using custom certificates. With Chrome policies, you can leverage over 100+ configurable policies for managing browser behavior across security, URL filtering, content settings, and more to enforce organizational compliance requirements. For example, restrict agents to specific URLs for kiosk-mode operations, disable password managers and downloads for data-entry tasks, or implement URL blocklists for regulatory compliance. Custom root CA support enables agents to seamlessly connect to internal services like Artifactory, Jira, and finance portals that use SSL certificates signed by your organization’s internal Certificate Authority, and work with corporate proxies performing TLS interception. These features are available in all 14 AWS Regions where Amazon Bedrock AgentCore Browser and Code Interpreter are available: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Canada (Central). To learn more, visit the AgentCore Browser documentation.
Amazon Route 53 Profiles now supports granular AWS Identity and Access Management (IAM) permissions, allowing you to control which users can manage specific resource types and VPC associations within your Profiles. With this launch, you can create IAM policies that restrict users to specific operations (associate, disassociate, or update) on individual resource types such as private hosted zones, Resolver rules, or DNS Firewall rule groups. You can also define permissions based on resource ARNs, hosted zone names, Resolver rule domain names, DNS Firewall rule group priority ranges, or specific VPC associations.
Route 53 Profiles enable you to define a standard DNS configuration that includes private hosted zone associations, Resolver rules, and DNS Firewall rule groups, and apply this configuration to multiple VPCs in your account or share with AWS accounts using AWS Resource Access Manager (RAM). This new capability provides administrators with fine-grained control over Profile management, enabling you to delegate specific responsibilities while maintaining security and governance standards across your organization.
This feature is available at no additional charge in all AWS Regions where Route 53 Profiles is available, except in Middle East (Bahrain) and Middle East (UAE). To learn more, see the Amazon Route 53 Profiles documentation and pricing page.
Amazon Route 53 Profiles now supports granular AWS Identity and Access Management (IAM) permissions, allowing you to control which users can manage specific resource types and VPC associations within your Profiles. With this launch, you can create IAM policies that restrict users to specific operations (associate, disassociate, or update) on individual resource types such as private hosted zones, Resolver rules, or DNS Firewall rule groups. You can also define permissions based on resource ARNs, hosted zone names, Resolver rule domain names, DNS Firewall rule group priority ranges, or specific VPC associations. Route 53 Profiles enable you to define a standard DNS configuration that includes private hosted zone associations, Resolver rules, and DNS Firewall rule groups, and apply this configuration to multiple VPCs in your account or share with AWS accounts using AWS Resource Access Manager (RAM). This new capability provides administrators with fine-grained control over Profile management, enabling you to delegate specific responsibilities while maintaining security and governance standards across your organization. This feature is available at no additional charge in all AWS Regions where Route 53 Profiles is available, except in Middle East (Bahrain) and Middle East (UAE). To learn more, see the Amazon Route 53 Profiles documentation and pricing page.
