Amazon Elastic Container Service (Amazon ECS) Service Connect now supports Envoy access logs, providing deeper observability into request-level traffic patterns and service interactions. This new capability captures detailed per-request telemetry for end-to-end tracing, debugging, and compliance monitoring.

Amazon ECS Service Connect makes it simple to build secure, resilient service-to-service communication across clusters, VPCs, and AWS accounts. It integrates service discovery and service mesh capabilities by automatically injecting AWS-managed Envoy proxies as sidecars that handle traffic routing, load balancing, and inter-service connectivity. Envoy Access logs capture detailed traffic metadata enabling request-level visibility into service communication patterns. This enables you to perform network diagnostics, troubleshoot issues efficiently, and maintain audit trails for compliance requirements.

You can now configure access logs within ECS Service Connect by updating the ServiceConnectConfiguration to enable access logging. Query strings are redacted by default to protect sensitive data. Envoy access logs will output to the standard output (STDOUT) stream alongside application logs and flow through the existing ECS log pipeline without requiring additional infrastructure. This configuration supports all existing application protocols (HTTP, HTTP2, GRPC and TCP). This feature is available in all regions where Amazon ECS Service Connect is supported. To learn more, visit the Amazon ECS Developer Guide.

​Amazon Elastic Container Service (Amazon ECS) Service Connect now supports Envoy access logs, providing deeper observability into request-level traffic patterns and service interactions. This new capability captures detailed per-request telemetry for end-to-end tracing, debugging, and compliance monitoring. Amazon ECS Service Connect makes it simple to build secure, resilient service-to-service communication across clusters, VPCs, and AWS accounts. It integrates service discovery and service mesh capabilities by automatically injecting AWS-managed Envoy proxies as sidecars that handle traffic routing, load balancing, and inter-service connectivity. Envoy Access logs capture detailed traffic metadata enabling request-level visibility into service communication patterns. This enables you to perform network diagnostics, troubleshoot issues efficiently, and maintain audit trails for compliance requirements. You can now configure access logs within ECS Service Connect by updating the ServiceConnectConfiguration to enable access logging. Query strings are redacted by default to protect sensitive data. Envoy access logs will output to the standard output (STDOUT) stream alongside application logs and flow through the existing ECS log pipeline without requiring additional infrastructure. This configuration supports all existing application protocols (HTTP, HTTP2, GRPC and TCP). This feature is available in all regions where Amazon ECS Service Connect is supported. To learn more, visit the Amazon ECS Developer Guide.  

AWS Cloud Map now supports cross-account service discovery through integration with AWS Resource Access Manager (AWS RAM) in AWS GovCloud (US) Regions. This enhancement lets you seamlessly manage and discover cloud resources—such as Amazon ECS tasks, Amazon EC2 instances, and Amazon DynamoDB tables—across AWS accounts. By sharing your AWS Cloud Map namespace via AWS RAM, workloads in other accounts can discover and manage resources registered in that namespace. This enhancement simplifies resource sharing, reduces duplication, and promotes consistent service discovery across environments for organizations with multi-account architectures.

You can now share your AWS Cloud Map namespaces using AWS RAM with individual AWS accounts, specific Organizational Units (OUs), or your entire AWS Organization. To get started, create a resource share in AWS RAM, add the namespaces you want to share, and specify the principals (accounts, OUs, or the organization) that should have access. This enables platform engineers to maintain a centralized service registry—or a small set of registries—and share them across multiple accounts, simplifying service discovery. Application developers can then build services that rely on a consistent, shared registry without worrying about availability or synchronization across accounts. AWS Cloud Map’s cross-account service discovery support improves operational efficiency and makes it easier to scale service discovery as your organization grows by reducing duplication and streamlining access to namespaces.

This feature is available now in the AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions via the AWS Management Console, API, SDK, CLI, and CloudFormation. To learn more, please refer to the AWS Cloud Map documentation.

​AWS Cloud Map now supports cross-account service discovery through integration with AWS Resource Access Manager (AWS RAM) in AWS GovCloud (US) Regions. This enhancement lets you seamlessly manage and discover cloud resources—such as Amazon ECS tasks, Amazon EC2 instances, and Amazon DynamoDB tables—across AWS accounts. By sharing your AWS Cloud Map namespace via AWS RAM, workloads in other accounts can discover and manage resources registered in that namespace. This enhancement simplifies resource sharing, reduces duplication, and promotes consistent service discovery across environments for organizations with multi-account architectures. You can now share your AWS Cloud Map namespaces using AWS RAM with individual AWS accounts, specific Organizational Units (OUs), or your entire AWS Organization. To get started, create a resource share in AWS RAM, add the namespaces you want to share, and specify the principals (accounts, OUs, or the organization) that should have access. This enables platform engineers to maintain a centralized service registry—or a small set of registries—and share them across multiple accounts, simplifying service discovery. Application developers can then build services that rely on a consistent, shared registry without worrying about availability or synchronization across accounts. AWS Cloud Map’s cross-account service discovery support improves operational efficiency and makes it easier to scale service discovery as your organization grows by reducing duplication and streamlining access to namespaces. This feature is available now in the AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions via the AWS Management Console, API, SDK, CLI, and CloudFormation. To learn more, please refer to the AWS Cloud Map documentation.  

Amazon Elastic Container Service (Amazon ECS) announces support for linear and canary deployment strategies, giving you more flexibility and control when deploying containerized applications. These new strategies complement ECS built-in blue/green deployments, enabling you to choose the traffic shifting approach that best matches your application’s risk profile and validation requirements.

With linear deployments, you can gradually shift traffic from your current service revision to the new revision in equal percentage increments over a specified time period. You configure the step percentage (for example, 10%) to control how much traffic shifts at each increment, and set a step bake time to wait between each traffic shift for monitoring and validation. This allows you to validate your new application version at multiple stages with increasing amounts of production traffic. With canary deployments, you can route a small percentage of production traffic to your new service revision while the majority of traffic remains on the current stable version. You set a canary bake time to monitor the new revision’s performance, after which Amazon ECS shifts the remaining traffic to the new revision. Both strategies support a deployment bake time that waits after all production traffic has shifted to the new revision before terminating the old revision, enabling quick rollback without downtime if issues are detected. You can configure deployment lifecycle hooks to perform custom validation steps, and use Amazon CloudWatch alarms to automatically detect failures and trigger rollbacks.

The feature is available in all commercial AWS Regions where Amazon ECS is available. You can use linear and canary deployment strategies for new and existing Amazon ECS services that use Application Load Balancer (ALB) or ECS Service Connect, using the Console, SDK, CLI, CloudFormation, CDK, and Terraform. To learn more, see our documentation on Amazon ECS linear deployments and Amazon ECS canary deployments.

​Amazon Elastic Container Service (Amazon ECS) announces support for linear and canary deployment strategies, giving you more flexibility and control when deploying containerized applications. These new strategies complement ECS built-in blue/green deployments, enabling you to choose the traffic shifting approach that best matches your application’s risk profile and validation requirements.
With linear deployments, you can gradually shift traffic from your current service revision to the new revision in equal percentage increments over a specified time period. You configure the step percentage (for example, 10%) to control how much traffic shifts at each increment, and set a step bake time to wait between each traffic shift for monitoring and validation. This allows you to validate your new application version at multiple stages with increasing amounts of production traffic. With canary deployments, you can route a small percentage of production traffic to your new service revision while the majority of traffic remains on the current stable version. You set a canary bake time to monitor the new revision’s performance, after which Amazon ECS shifts the remaining traffic to the new revision. Both strategies support a deployment bake time that waits after all production traffic has shifted to the new revision before terminating the old revision, enabling quick rollback without downtime if issues are detected. You can configure deployment lifecycle hooks to perform custom validation steps, and use Amazon CloudWatch alarms to automatically detect failures and trigger rollbacks.
The feature is available in all commercial AWS Regions where Amazon ECS is available. You can use linear and canary deployment strategies for new and existing Amazon ECS services that use Application Load Balancer (ALB) or ECS Service Connect, using the Console, SDK, CLI, CloudFormation, CDK, and Terraform. To learn more, see our documentation on Amazon ECS linear deployments and Amazon ECS canary deployments.  

Amazon Managed Service for Prometheus, a fully managed Prometheus-compatible monitoring service now supports anomaly detection. Anomaly detection applies machine-learning algorithms to continuously analyze time series and surfaces anomalies with minimal user intervention. You can use anomaly detection to isolate and troubleshoot unexpected changes in your metric behavior.

Amazon Managed Service for Prometheus Anomaly Detection currently supports Random Cut Forest (RCF), an unsupervised algorithm for detecting anomalous data points within a time series. Once you create and configure an anomaly detector in an Amazon Managed Service for Prometheus workspace, it will create four new time series to represent resulting anomalies and confidence values along with them. Based on the resulting time series, you can create dynamic alerting rules in the Amazon Managed Service for Prometheus Alert manager, to notify you when anomalies occur, and you can also visualize the resulting time series alongside the input time series either in self-managed Grafana or Amazon Managed Grafana dashboards.

This feature is now available in all AWS regions where Amazon Managed Service for Prometheus is generally available. To configure anomaly detection use the AWS CLI, SDK, or APIs. Check out the Amazon Managed Service for Prometheus user guide for detailed documentation.

​Amazon Managed Service for Prometheus, a fully managed Prometheus-compatible monitoring service now supports anomaly detection. Anomaly detection applies machine-learning algorithms to continuously analyze time series and surfaces anomalies with minimal user intervention. You can use anomaly detection to isolate and troubleshoot unexpected changes in your metric behavior.
Amazon Managed Service for Prometheus Anomaly Detection currently supports Random Cut Forest (RCF), an unsupervised algorithm for detecting anomalous data points within a time series. Once you create and configure an anomaly detector in an Amazon Managed Service for Prometheus workspace, it will create four new time series to represent resulting anomalies and confidence values along with them. Based on the resulting time series, you can create dynamic alerting rules in the Amazon Managed Service for Prometheus Alert manager, to notify you when anomalies occur, and you can also visualize the resulting time series alongside the input time series either in self-managed Grafana or Amazon Managed Grafana dashboards.
This feature is now available in all AWS regions where Amazon Managed Service for Prometheus is generally available. To configure anomaly detection use the AWS CLI, SDK, or APIs. Check out the Amazon Managed Service for Prometheus user guide for detailed documentation.  

We are excited to announce the Amazon OCSF Ready Specialization that recognizes AWS Partners who have technically validated their software solutions to integrate with OCSF-compatible Amazon services with proven customer success in production environments. The Open Cybersecurity Schema Framework (OCSF) is an open-source initiative that simplifies how security data is normalized and shared across your security tools. This validation ensures customers can confidently select solutions that will help them improve their security operations through standardized data formats, leading to efficient threat detection, vulnerability identification, and enhanced security analytics.

The AWS Service Ready Program provides customers with AWS Partner software solutions that work with AWS Services. This specialization helps you quickly find and deploy pre-validated AWS Partner solutions that work seamlessly with OCSF-compatible Amazon services, reducing the complexity of your security operations. Partners can participate in the Amazon OCSF Ready designation by either sending logs and security events in the OCSF schema, or receiving logs or security events from OCSF-compatible Amazon services. This standardization helps customers to collect, combine, and analyze security data reducing the time and effort needed for security operations.

Amazon OCSF Ready Partners receive AWS Specialization Program benefits, and have access to signature benefits, including private strategy sessions and AWS guest speaker support for virtual events. The Amazon OCSF specialization expands and replaces the Amazon Security Lake Specialization.

To learn more about how to become an Amazon OCSF Ready Partner, visit the AWS Service Ready Program webpage.

​We are excited to announce the Amazon OCSF Ready Specialization that recognizes AWS Partners who have technically validated their software solutions to integrate with OCSF-compatible Amazon services with proven customer success in production environments. The Open Cybersecurity Schema Framework (OCSF) is an open-source initiative that simplifies how security data is normalized and shared across your security tools. This validation ensures customers can confidently select solutions that will help them improve their security operations through standardized data formats, leading to efficient threat detection, vulnerability identification, and enhanced security analytics. The AWS Service Ready Program provides customers with AWS Partner software solutions that work with AWS Services. This specialization helps you quickly find and deploy pre-validated AWS Partner solutions that work seamlessly with OCSF-compatible Amazon services, reducing the complexity of your security operations. Partners can participate in the Amazon OCSF Ready designation by either sending logs and security events in the OCSF schema, or receiving logs or security events from OCSF-compatible Amazon services. This standardization helps customers to collect, combine, and analyze security data reducing the time and effort needed for security operations. Amazon OCSF Ready Partners receive AWS Specialization Program benefits, and have access to signature benefits, including private strategy sessions and AWS guest speaker support for virtual events. The Amazon OCSF specialization expands and replaces the Amazon Security Lake Specialization. To learn more about how to become an Amazon OCSF Ready Partner, visit the AWS Service Ready Program webpage.  

AWS announces the release of a new AI agent context package for accelerating edge device application development using AWS IoT Greengrass. AWS IoT Greengrass is an IoT edge runtime and cloud service that helps developers build, deploy, and manage device software at the edge. The context package includes ready-to-use instructions, examples, and templates – enabling developers to leverage generative AI tools and agents for faster software creation, testing and deployment.

Available as an open-source GitHub repository under the Creative Commons Attribution Share Alike 4.0 license, the AWS IoT Greengrass AI agent context package helps streamline development workflows. Developers can boost productivity by cloning the repository and integrating it with modern generative AI tools like Amazon Q to help accelerate cloud-connected edge application development while simplifying fleet-wide deployment and management.

This new capability is available in all AWS Regions where AWS IoT Greengrass is supported. To learn more about AWS IoT Greengrass and its new AI agent context pack, visit the AWS IoT Greengrass documentation. Follow the getting started guide for a quick introduction to AWS IoT Greengrass.

​AWS announces the release of a new AI agent context package for accelerating edge device application development using AWS IoT Greengrass. AWS IoT Greengrass is an IoT edge runtime and cloud service that helps developers build, deploy, and manage device software at the edge. The context package includes ready-to-use instructions, examples, and templates – enabling developers to leverage generative AI tools and agents for faster software creation, testing and deployment. Available as an open-source GitHub repository under the Creative Commons Attribution Share Alike 4.0 license, the AWS IoT Greengrass AI agent context package helps streamline development workflows. Developers can boost productivity by cloning the repository and integrating it with modern generative AI tools like Amazon Q to help accelerate cloud-connected edge application development while simplifying fleet-wide deployment and management. This new capability is available in all AWS Regions where AWS IoT Greengrass is supported. To learn more about AWS IoT Greengrass and its new AI agent context pack, visit the AWS IoT Greengrass documentation. Follow the getting started guide for a quick introduction to AWS IoT Greengrass.  

The AWS Serverless Model Context Protocol (MCP) Server now supports specialized tools for AWS Lambda event source mappings (ESM), helping developers configure and manage ESMs more efficiently. These new tools combine the power of AI assistance with Lambda ESM expertise to streamline how developers set up, optimize, and troubleshoot event-driven serverless applications built on Lambda.

We previously launched the open-source Serverless MCP Server to enhance how developers build modern applications with AI-powered contextual guidance for architecture decisions, infrastructure provisioning, deployment automation, and troubleshooting of serverless applications. Starting today, we’re expanding the MCP server’s capabilities with new ESM tools that empower AI assistants, like Amazon Q Developer and Kiro, with proven knowledge of ESM patterns and best practices. The new ESM tools translate high-level throughput, latency, and reliability requirements into specific ESM configurations, generate complete AWS Serverless Application Model (AWS SAM) templates with optimized settings, validate network topology for Amazon Virtual Private Cloud (VPC)-based event sources, and diagnose common ESM issues. Thus, these tools enhance the event-driven application development experience, guiding developers through the entire ESM lifecycle, from initial setup to optimization and troubleshooting.

The key new ESM tools being added to the Serverless MCP Server are: the ESM guidance tool for contextual guidance across all supported event sources, the ESM optimization tool for analyzing configuration tradeoffs, and the ESM Kafka troubleshooting tool for specialized diagnostics with Amazon Managed Streaming for Apache Kafka (Amazon MSK) and self-managed Apache Kafka clusters.

To learn more about the Serverless MCP Server and how it can transform your AI-assisted application development, visit the launch blog post and documentation. To download and try out the open-source MCP server with your AI-enabled IDE of choice, visit the GitHub repository.

​The AWS Serverless Model Context Protocol (MCP) Server now supports specialized tools for AWS Lambda event source mappings (ESM), helping developers configure and manage ESMs more efficiently. These new tools combine the power of AI assistance with Lambda ESM expertise to streamline how developers set up, optimize, and troubleshoot event-driven serverless applications built on Lambda. We previously launched the open-source Serverless MCP Server to enhance how developers build modern applications with AI-powered contextual guidance for architecture decisions, infrastructure provisioning, deployment automation, and troubleshooting of serverless applications. Starting today, we’re expanding the MCP server’s capabilities with new ESM tools that empower AI assistants, like Amazon Q Developer and Kiro, with proven knowledge of ESM patterns and best practices. The new ESM tools translate high-level throughput, latency, and reliability requirements into specific ESM configurations, generate complete AWS Serverless Application Model (AWS SAM) templates with optimized settings, validate network topology for Amazon Virtual Private Cloud (VPC)-based event sources, and diagnose common ESM issues. Thus, these tools enhance the event-driven application development experience, guiding developers through the entire ESM lifecycle, from initial setup to optimization and troubleshooting. The key new ESM tools being added to the Serverless MCP Server are: the ESM guidance tool for contextual guidance across all supported event sources, the ESM optimization tool for analyzing configuration tradeoffs, and the ESM Kafka troubleshooting tool for specialized diagnostics with Amazon Managed Streaming for Apache Kafka (Amazon MSK) and self-managed Apache Kafka clusters. To learn more about the Serverless MCP Server and how it can transform your AI-assisted application development, visit the launch blog post and documentation. To download and try out the open-source MCP server with your AI-enabled IDE of choice, visit the GitHub repository.  

AWS Backup now supports copying database snapshots across AWS Regions and accounts using a single copy action. This feature supports Amazon RDS, Amazon Aurora, Amazon Neptune, and Amazon DocumentDB snapshots. It eliminates the need for sequential copying steps.

You can use cross-Region and cross-account snapshot copies to protect against incidents like ransomware attacks and Region outages that might affect your production accounts or primary Regions. Previously, you needed to perform this as a two-step process—first copying to a different Region, and then to a different account (or vice versa). Now, by completing this in one step, you can achieve faster recovery point objectives (RPOs) while eliminating costs associated with intermediate copies. This streamlined process also simplifies the workflow by removing the need for custom scripts or Lambda functions that monitor intermediate copy status.

This feature is available for all Amazon RDS and Amazon Aurora engines, Amazon Neptune and Amazon DocumentDB, in all regions where AWS Backup supports cross-Region and cross-account copying of snapshots in separate steps. You can start using this feature today through the AWS Management Console, AWS Command Line Interface (CLI), or AWS SDKs. To get started, refer the AWS Backup documentation.

​AWS Backup now supports copying database snapshots across AWS Regions and accounts using a single copy action. This feature supports Amazon RDS, Amazon Aurora, Amazon Neptune, and Amazon DocumentDB snapshots. It eliminates the need for sequential copying steps.
You can use cross-Region and cross-account snapshot copies to protect against incidents like ransomware attacks and Region outages that might affect your production accounts or primary Regions. Previously, you needed to perform this as a two-step process—first copying to a different Region, and then to a different account (or vice versa). Now, by completing this in one step, you can achieve faster recovery point objectives (RPOs) while eliminating costs associated with intermediate copies. This streamlined process also simplifies the workflow by removing the need for custom scripts or Lambda functions that monitor intermediate copy status.
This feature is available for all Amazon RDS and Amazon Aurora engines, Amazon Neptune and Amazon DocumentDB, in all regions where AWS Backup supports cross-Region and cross-account copying of snapshots in separate steps. You can start using this feature today through the AWS Management Console, AWS Command Line Interface (CLI), or AWS SDKs. To get started, refer the AWS Backup documentation.  

AWS announces the general availability of the Amazon Elastic Compute Cloud (EC2) Capacity Reservation Topology API. It joins the Instance Topology API in enabling customers to efficiently manage capacity, schedule jobs, and rank nodes for Artificial Intelligence, Machine Learning, and High-Performance Computing distributed workloads. The Capacity Reservation Topology API gives customers a unique per-account hierarchical view of the relative location of their capacity reservations.

Customers running distributed parallel workloads are managing thousands of instances across tens to hundreds of capacity reservations. With the Capacity Reservation Topology API, customers can describe the topology of their reservations as a network node set, which will show the relative proximity of their capacity without the need to launch an instance. This enables efficient capacity planning and management as customers provision workloads on tightly coupled capacity. Customers can then use the Instance Topology API, which provides consistent network nodes from the Capacity Reservation Topology API with further granularity, enabling a consistent and seamless way to schedule jobs and rank nodes for optimal performance in distributed parallel workloads.

The Capacity Reservation Topology API is available in the following AWS regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Africa (Cape Town), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), 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 (Paris), Europe (Spain), Europe (Stockholm), Europe (Zurich), Middle East (Bahrain), Middle East (UAE), and South America (São Paulo), and it is supported on all instances available with the Instance Topology API.

To learn more, please visit the latest EC2 user guide.

​AWS announces the general availability of the Amazon Elastic Compute Cloud (EC2) Capacity Reservation Topology API. It joins the Instance Topology API in enabling customers to efficiently manage capacity, schedule jobs, and rank nodes for Artificial Intelligence, Machine Learning, and High-Performance Computing distributed workloads. The Capacity Reservation Topology API gives customers a unique per-account hierarchical view of the relative location of their capacity reservations.
Customers running distributed parallel workloads are managing thousands of instances across tens to hundreds of capacity reservations. With the Capacity Reservation Topology API, customers can describe the topology of their reservations as a network node set, which will show the relative proximity of their capacity without the need to launch an instance. This enables efficient capacity planning and management as customers provision workloads on tightly coupled capacity. Customers can then use the Instance Topology API, which provides consistent network nodes from the Capacity Reservation Topology API with further granularity, enabling a consistent and seamless way to schedule jobs and rank nodes for optimal performance in distributed parallel workloads.
The Capacity Reservation Topology API is available in the following AWS regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Africa (Cape Town), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), 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 (Paris), Europe (Spain), Europe (Stockholm), Europe (Zurich), Middle East (Bahrain), Middle East (UAE), and South America (São Paulo), and it is supported on all instances available with the Instance Topology API.
To learn more, please visit the latest EC2 user guide.  

Formas fluidas, colores vibrantes

Cómo una actualización sutil de nuestros íconos de Microsoft 365 indica un cambio más profundo.

Por: Jon Friedman, CVP de diseño e investigación de Microsoft 365.

Cuando se trata de un impacto descomunal, es difícil debatir sobre el ícono todopoderoso. No más grandes que un sello postal, estos pequeños símbolos son puertas de entrada a experiencias completas, destilan ideas complejas, habilidades de productos e identidades de marca en una sola imagen memorable. Al evocar emociones, despertar la curiosidad y brindar una guía intuitiva, hacen que la tecnología sea más accesible y cercana.

A medida que hemos implementado íconos actualizados para las aplicaciones de Microsoft 365, los cambios de diseño pequeños pero significativos son un reflejo y una señal. Como reflexión, encapsulan cómo la IA cambia la disciplina del diseño y la naturaleza del desarrollo de productos. Como símbolo, encarnan un espíritu arraigado en la conexión, la coherencia y la colaboración fluida. Si bien estos principios guiaron los rediseños anteriores, su significado ha cambiado: la conexión hoy en día no se trata tanto de la coherencia visual como del flujo continuo de la intención humana en cada lienzo de Microsoft 365.

Un recorrido de diseño de UI a UX

Las 10 aplicaciones principales de Office se actualizaron por última vez en 2018 y la forma en que describimos lo que representaban los diseños es casi idéntica al lenguaje que se usa hoy: conexión, coherencia, colaboración fluida, transiciones fluidas. En ese momento, eso hacía referencia al diseño de la interfaz. Señalábamos una apariencia conectada en todas las plataformas y dispositivos con transiciones visuales fluidas entre aplicaciones y animaciones. Fueron los primeros días de las aplicaciones que componían experiencias juntas y en verdad colaborativas.

Hoy en día, la colaboración sin esfuerzo significa tanto de persona a persona como de persona a IA, con experiencias inteligentes a nivel contextual, que comprenden y anticipan los matices de su trabajo, los datos a los que hacen referencia y los objetivos que persiguen. La conexión y la coherencia tienen que ver con la capacidad de Copilot para comprender su intención para que puedan atravesar sin problemas la totalidad del ecosistema de Microsoft 365 para lograr su objetivo. Ese es el cambio de paradigma; Microsoft 365 siempre ha potenciado la productividad, pero la fuerza impulsora de la experiencia de usuario a menudo eran las características de la aplicación o las herramientas en sí. Hoy, la fuerza impulsora es el resultado que desean.

Con ese cambio de paradigma vienen cambios significativos en la disciplina de UX en sí y en la forma en que abordamos la creación de productos. Los ciclos más largos de desarrollo con la cabeza hacia abajo solían ser seguidos por una gran revelación de grandes cambios. Hoy en día, con las capacidades de los modelos que emergen con rapidez y nuestro aprendizaje como profesionales de UX que avanzan a gran velocidad, incluida la mejora de la tecnología como disciplina, la evolución del producto ocurre en oleadas continuas. La investigación muestra que los cambios en la iconografía casi siempre se reciben como una señal de cambios en el producto y en una era de cambios continuos y más pequeños, los íconos deberían reflejar eso. Como tal, adoptamos la idea de «evolución, no revolución» a lo largo de nuestro proceso de diseño.

Nuevas formas, colores y metáforas

Los nuevos íconos emanan una sensación de fluidez y juego, al mismo tiempo que son más simples, intuitivos y con una alta accesibilidad. Su metáfora, forma, color y letra se han redefinido para crear un sistema cohesivo, detectable y navegable, elaborado con degradados y gestos entretejidos en la expresión y las experiencias de IA de Microsoft.

Simpleza encantadora: para mantener la familiaridad y optimizar la experiencia visual, simplificamos a nivel gráfico los íconos para mayor claridad y reducción del ruido visual. Mientras que antes el ícono de Word usaba cuatro barras horizontales, la nueva versión usa solo tres, lo que mejora la legibilidad en tamaños pequeños y crea una mayor concisión visual.

Formas fluidas: Nos hemos alejado de la solidez audaz y estática para adoptar formas más suaves y fluidas. Los bordes afilados y las líneas nítidas se reemplazan por pliegues y curvas suaves, lo que da a los íconos una sensación de movimiento lúdico y accesibilidad.

Ricos y coloridos: La paleta de colores se ha refinado de manera importante. Donde los degradados alguna vez fueron sutiles, ahora son más ricos y vibrantes, con transiciones análogas exageradas que mejoran el contraste y la accesibilidad. Este cambio hace que los íconos se sientan más brillantes, más impactantes y más dinámicos.

Reconocibles al instante: las placas con letras fueron muy debatidas porque son bienes raíces valiosos y los íconos que siguen a los 10 principales Office ya no las usan. Sin embargo, su valor de marca es tan fuerte que decidimos conservarlos, para  mantener nuestra herencia y al mismo tiempo modernizándolos a través de una integración visual más cohesiva con el diseño general.

El arte imita la verdad; la verdad imita al arte

La iconografía a menudo equilibra la precisión y la aspiración. Ningún producto digital está horneado por completo, por lo que sus metáforas deben encarnar la verdad actual y el futuro que se construye de manera activa. Cuando rediseñamos nuestros íconos en 2018, el arte imitó la idea de que Microsoft 365 comenzara a fusionarse. Esa verdad del producto se había vuelto cada vez más fuerte, y luego Copilot se aceleró y transformó nuestra capacidad para crear un ecosistema en verdad conectado para los clientes.

Para crear el ícono de Copilot, nos basamos en un amplio linaje de influencias de diseño: íconos tradicionales de Office, aplicaciones más nuevas como Designer y Viva, íconos comerciales e industriales como Copilot for Sales y muchos más, al tiempo que adoptamos nuevas metáforas para significar un intercambio fluido entre ustedes y la IA, donde ustedes siempre tienen el control. La paleta de colores vibrantes del ícono representa todos los productos de Microsoft, en lugar de solo el azul tradicional, y expresa a nivel visual la colaboración y la creatividad de manera simple, lúdica y accesible.

Dado que Copilot ahora es un sistema más completo e integrado dentro de Microsoft 365, es apropiado que al actualizar los 10 íconos principales de Office, la principal fuente de inspiración fuera el ícono de Copilot en sí. Reflejo y resultado del impacto transformador de Copilot, los nuevos diseños completan a nivel visual un ciclo en el que el arte y la verdad se moldean de manera continua.

¡Un proyecto de este tamaño requiere un pueblo! Hay demasiada gente para mencionarlos a todos, pero un agradecimiento especial para Aaron Martinez, Ada Hurd, Alexis Copeland, Anna Gray, Anthony Dart, Arman Keyvanskhou, Braz De Pina, Claudia Nafarrate, Cole Rise, Colin Day, Danny Pak, Heath Hinegardner, Jana Huskey, Jason Custer, Ju Hyun Lee, Kris Bennett, Laura Clark, Mathieu James, Michelle Barrueto, Mike LaJoie,  Phil Evans, Shelby Hutchison, Sven Seger y Tati Astua.

Etiquetas:

• Desarrollo de productos
• Vida y Trabajo

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