Starting today, Amazon Elastic Compute Cloud (Amazon EC2) X8g instances are available in Europe (Stockholm) region. These instances are powered by AWS Graviton4 processors, and they offer up to 3 TiB of total memory and increased memory per vCPU compared to other Graviton4-based instances. X8g instances are ideal for memory-intensive workloads, such as electronic design automation (EDA) workloads, in-memory databases (Redis, Memcached), relational databases (MySQL, PostgreSQL), real-time big data analytics, real-time caching servers, and memory-intensive containerized applications.

X8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 3TiB) than Graviton2-based X2gd instances. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Elastic Fabric Adapter (EFA) networking support is offered on 24xlarge, 48xlarge, and bare metal sizes, and Elastic Network Adapter (ENA) Express support is available on instance sizes larger than 12xlarge.

X8g instances are currently available in the following AWS Regions: US East (N. Virginia, Ohio), US West (Oregon), and Europe (Frankfurt, Stockholm).

To learn more, see Amazon EC2 X8g Instances. To quickly migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program. To get started, see the AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) X8g instances are available in Europe (Stockholm) region. These instances are powered by AWS Graviton4 processors, and they offer up to 3 TiB of total memory and increased memory per vCPU compared to other Graviton4-based instances. X8g instances are ideal for memory-intensive workloads, such as electronic design automation (EDA) workloads, in-memory databases (Redis, Memcached), relational databases (MySQL, PostgreSQL), real-time big data analytics, real-time caching servers, and memory-intensive containerized applications.
X8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 3TiB) than Graviton2-based X2gd instances. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Elastic Fabric Adapter (EFA) networking support is offered on 24xlarge, 48xlarge, and bare metal sizes, and Elastic Network Adapter (ENA) Express support is available on instance sizes larger than 12xlarge.
X8g instances are currently available in the following AWS Regions: US East (N. Virginia, Ohio), US West (Oregon), and Europe (Frankfurt, Stockholm).
To learn more, see Amazon EC2 X8g Instances. To quickly migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program. To get started, see the AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.  

Amazon RDS and Aurora now support resource tagging for automated backups and cluster automated backups. You can now tag your automated backups separately from the parent DB instance or DB cluster, enabling Attribute-Based Access Control (ABAC) and simplifying resource management and cost tracking.

With this launch, you can tag automated backups in the same way as other RDS resources using the AWS Management Console, API, or SDK. Use these tags with IAM policies to control access and permissions to automated backups. Additionally, these tags can help you categorize your resources by application, project, department, environment, and more, as well as manage, organize, and track costs of your automated backups. For example, create application specific tags to control permissions for describing, deleting, or restoring automated backups and to organize and track backup costs of the application.

This capability is available in all AWS Regions, including the AWS GovCloud (US) Regions where Aurora and RDS are available.

To learn more about tagging Aurora and RDS automated backups, see the Amazon documentation on Tagging Amazon Aurora resources, Tagging Amazon RDS resources, and Using tags for attribute-based access control.

​Amazon RDS and Aurora now support resource tagging for automated backups and cluster automated backups. You can now tag your automated backups separately from the parent DB instance or DB cluster, enabling Attribute-Based Access Control (ABAC) and simplifying resource management and cost tracking.
With this launch, you can tag automated backups in the same way as other RDS resources using the AWS Management Console, API, or SDK. Use these tags with IAM policies to control access and permissions to automated backups. Additionally, these tags can help you categorize your resources by application, project, department, environment, and more, as well as manage, organize, and track costs of your automated backups. For example, create application specific tags to control permissions for describing, deleting, or restoring automated backups and to organize and track backup costs of the application.
This capability is available in all AWS Regions, including the AWS GovCloud (US) Regions where Aurora and RDS are available.
To learn more about tagging Aurora and RDS automated backups, see the Amazon documentation on Tagging Amazon Aurora resources, Tagging Amazon RDS resources, and Using tags for attribute-based access control.  

Today, AWS announces deal sizing capability in AWS Partner Central. This new feature, available within the APN Customer Engagements (ACE) Opportunities, uses AI to provide deal size estimates and AWS service recommendations. Deal Sizing capability allows Partners to save time on deal management by simplifying the process of estimating AWS monthly recurring revenue (MMR) when creating or updating opportunities.

Partners can optionally import AWS Pricing Calculator URLs to automatically populate AWS service selections and corresponding spend estimates into their opportunities, reducing the need for manual re-entry. When a Pricing Calculator URL is provided, deal sizing delivers enhanced insights including pricing strategy optimization recommendations, potential cost savings analysis, Migration Acceleration Program (MAP) eligibility indicators, and modernization pathway analysis. These enhanced insights help Partners refine their technical approach and strengthen funding applications, accelerating the funding approval process.

Deal sizing is now available in AWS Partner Central worldwide. The feature is accessible through both AWS Partner Central and the AWS Partner Central API for Selling, which is available in the US East (N. Virginia) Region.

To get started, log in to AWS Partner Central in the console to create or update opportunities and view deal sizing insights. For API integration with your CRM system, see the AWS Partner Central API Documentation. To learn more about deal sizing, visit the Partner Central Sales Guide.

​Today, AWS announces deal sizing capability in AWS Partner Central. This new feature, available within the APN Customer Engagements (ACE) Opportunities, uses AI to provide deal size estimates and AWS service recommendations. Deal Sizing capability allows Partners to save time on deal management by simplifying the process of estimating AWS monthly recurring revenue (MMR) when creating or updating opportunities. Partners can optionally import AWS Pricing Calculator URLs to automatically populate AWS service selections and corresponding spend estimates into their opportunities, reducing the need for manual re-entry. When a Pricing Calculator URL is provided, deal sizing delivers enhanced insights including pricing strategy optimization recommendations, potential cost savings analysis, Migration Acceleration Program (MAP) eligibility indicators, and modernization pathway analysis. These enhanced insights help Partners refine their technical approach and strengthen funding applications, accelerating the funding approval process. Deal sizing is now available in AWS Partner Central worldwide. The feature is accessible through both AWS Partner Central and the AWS Partner Central API for Selling, which is available in the US East (N. Virginia) Region. To get started, log in to AWS Partner Central in the console to create or update opportunities and view deal sizing insights. For API integration with your CRM system, see the AWS Partner Central API Documentation. To learn more about deal sizing, visit the Partner Central Sales Guide.  

​The post Cinco de cada diez empresas argentinas ya utilizan agentes de IA para fortalecer su ciberseguridad appeared first on Source LATAM.  

Amazon Quick Suite now includes Quick Research as a step within Quick Flows. This integration enables teams to generate comprehensive research reports as part of automated, multi-step workflows, transforming research projects into reusable workflows that can be shared across their organization.

Quick Suite is Amazon’s new AI-powered workspace that helps organizations get answers from their business data and move quickly from insights to action. With this integration, teams can trigger research automatically within their flows rather than conducting separate analysis. This addresses a critical productivity challenge by enabling teams to capture and scale proven research methods across hundreds of automated use cases. The integration also allows users to automate research workflows through scheduled triggers so users can set up flows that automatically generate research at specific times. Common use cases include automated account plan creation, standardizing product compliance analysis, and scheduled industry reports.

Users benefit from pre-configured flows that generate research based on flow creator instructions and optional user inputs. The generated research report can be used further to automatically trigger downstream actions like updating a Salesforce opportunity for an account team to follow up on, posting on a Jira ticket for a compliance team to review, or creating an Asana task for a patent lawyer to approve. This unlocks «set and forget» workflows that deliver consistent analysis without manual heavy lifting. Now operating within these automated workflows, Quick Research maintains its core strength of streamlining analysis across diverse enterprise data sources while delivering verified, source-traced insights. For existing Flow users, this provides access to more comprehensive analysis.

Quick Research with Flows integration is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). To learn more about automating your research needs, read the Quick Suite user guide.  

​Amazon Quick Suite now includes Quick Research as a step within Quick Flows. This integration enables teams to generate comprehensive research reports as part of automated, multi-step workflows, transforming research projects into reusable workflows that can be shared across their organization. Quick Suite is Amazon’s new AI-powered workspace that helps organizations get answers from their business data and move quickly from insights to action. With this integration, teams can trigger research automatically within their flows rather than conducting separate analysis. This addresses a critical productivity challenge by enabling teams to capture and scale proven research methods across hundreds of automated use cases. The integration also allows users to automate research workflows through scheduled triggers so users can set up flows that automatically generate research at specific times. Common use cases include automated account plan creation, standardizing product compliance analysis, and scheduled industry reports. Users benefit from pre-configured flows that generate research based on flow creator instructions and optional user inputs. The generated research report can be used further to automatically trigger downstream actions like updating a Salesforce opportunity for an account team to follow up on, posting on a Jira ticket for a compliance team to review, or creating an Asana task for a patent lawyer to approve. This unlocks «set and forget» workflows that deliver consistent analysis without manual heavy lifting. Now operating within these automated workflows, Quick Research maintains its core strength of streamlining analysis across diverse enterprise data sources while delivering verified, source-traced insights. For existing Flow users, this provides access to more comprehensive analysis. Quick Research with Flows integration is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). To learn more about automating your research needs, read the Quick Suite user guide.    

Today, AWS is announcing Spatial Data Management on AWS (SDMA), a solution that enables customers to store, enrich, and connect spatial data at scale. SDMA enables customers to store their multimodal spatial data representing their physical assets (3D, geospatial, behavioral, temporal data) in a secure, centralized cloud environment. SDMA serves as a collaborative hub enabling connectivity between customer’s spatial data, their ISV SaaS applications, and AWS Services. In addition, customers can use SDMA’s collection rules to define how their spatial data is organized and enriched, helping maintain consistency and governance. Customers can use SDMA’s APIs, desktop application, and web interface to efficiently manage spatial data to accelerate insights and informed decision making around physical operations.

SDMA centralizes customer’s spatial data in a secure and highly available cloud repository to enhance data transparency and accessibility across workflows. Leveraging SDMA’s automated metadata extraction for spatial data file formats, starting with: .LAZ, .E57, .GLB, and .GLTF, customers can improve data discoverability and relationships. SDMA’s REST APIs and customizable connectors simplify integrations with external applications — eliminating manual file handling and enhancing cloud and on-premises interoperability. SDMA’s intuitive web and desktop interfaces enable users across technical skill levels to manage spatial data efficiently. Auto-generated file previews are designed to improve workflow speed and data accuracy, they allow users to view and validate data without downloading large files.

SDMA is available in the following AWS regions: Asia Pacific (Tokyo, Singapore, Sydney), Europe (Frankfurt, Ireland, London), US East (N. Virginia, Ohio), US West (Oregon).

To learn more, visit the SDMA Product page.

​Today, AWS is announcing Spatial Data Management on AWS (SDMA), a solution that enables customers to store, enrich, and connect spatial data at scale. SDMA enables customers to store their multimodal spatial data representing their physical assets (3D, geospatial, behavioral, temporal data) in a secure, centralized cloud environment. SDMA serves as a collaborative hub enabling connectivity between customer’s spatial data, their ISV SaaS applications, and AWS Services. In addition, customers can use SDMA’s collection rules to define how their spatial data is organized and enriched, helping maintain consistency and governance. Customers can use SDMA’s APIs, desktop application, and web interface to efficiently manage spatial data to accelerate insights and informed decision making around physical operations.
SDMA centralizes customer’s spatial data in a secure and highly available cloud repository to enhance data transparency and accessibility across workflows. Leveraging SDMA’s automated metadata extraction for spatial data file formats, starting with: .LAZ, .E57, .GLB, and .GLTF, customers can improve data discoverability and relationships. SDMA’s REST APIs and customizable connectors simplify integrations with external applications — eliminating manual file handling and enhancing cloud and on-premises interoperability. SDMA’s intuitive web and desktop interfaces enable users across technical skill levels to manage spatial data efficiently. Auto-generated file previews are designed to improve workflow speed and data accuracy, they allow users to view and validate data without downloading large files.
SDMA is available in the following AWS regions: Asia Pacific (Tokyo, Singapore, Sydney), Europe (Frankfurt, Ireland, London), US East (N. Virginia, Ohio), US West (Oregon).
To learn more, visit the SDMA Product page.  

diciembre 8, 2025

• Categoría: Noticias de Microsoft

78% de las organizaciones en Chile priorizará la ciberseguridad en los próximos años y 53% anticipa un alto impacto de la IA

• Según una encuesta de Microsoft, el 63% de las empresas chilenas aplican la inteligencia artificial de forma alta o moderada para enfrentar amenazas, lo que evidencia progresos en su preparación digital.
• En el ámbito de ciberseguridad, el 61% ya emplea agentes de IA y otro 35% evalúa incorporarlos; además, la mitad de las compañías tiene políticas formales acerca del uso de esta tecnología.

• Source LATAM

Santiago de Chile – Como parte de su compromiso con un futuro digital más seguro, Microsoft presenta los resultados de la encuesta “Ciberseguridad 2025: Desafíos y estrategias en la era de la IA para grandes empresas”, comisionada a Edelman. La encuesta, aplicada a 100 profesionales de seguridad y TI en Chile, ofrece una visión actualizada sobre cómo las organizaciones están ajustando sus enfoques frente a los cambios del entorno digital.

El informe revela que 53% de las organizaciones percibe un nivel alto o muy alto de riesgo, confirmando que la exposición a amenazas digitales se ha convertido en un estado permanente. Además, 70% afirma que las amenazas han aumentado en los últimos tres años, y 78% proyecta que la ciberseguridad será una prioridad mayor en el futuro cercano. De cara a los próximos años, 53% anticipa un alto impacto de la IA en sus prácticas de ciberseguridad, lo que sugiere una transformación acelerada del panorama de riesgo.

Los especialistas también destacan un avance progresivo en materia de gobernanza para enfrentar este panorama. El 65% de las empresas cuenta con una estrategia formal de ciberseguridad y, de ellas, el 91% afirma que este plan está integrado a la estrategia general de negocio de la empresa. Sin embargo, solo el 54% reporta una alta participación de la junta directiva en decisiones de ciberseguridad y la inversión del presupuesto de TI en esta área sigue siendo ligera o moderada en el 66% de las organizaciones. Esto evidencia la necesidad de un mayor patrocinio y compromiso ejecutivo, dado que el riesgo cibernético impacta directamente en la reputación del negocio.

Por el momento, las prioridades de inversión para los próximos años están concentradas en seguridad en la nube (61%), soluciones impulsadas por IA (56%) e inteligencia y monitoreo de amenazas (54%). En contraste, áreas críticas para la resiliencia organizacional, como la respuesta y recuperación ante incidentes (19%) y la arquitectura Zero Trust (11%), reciben menor prioridad, lo que evidencia brechas en la preparación operativa y la capacidad de contención frente a ataques.

Según el estudio, el 45% de las empresas considera estar bien preparada para afrontar amenazas actuales; destacan sus fortalezas en privacidad de datos (64%), políticas eficaces de ciberseguridad (53%), cumplimiento de regulaciones (50%) y protección de identidad (50%). Sin embargo, la formación y sensibilización del personal se mantiene baja, con solo un 36%.  

Agentes de IA: un nuevo capítulo en la estrategia de ciberseguridad 

La evolución tecnológica continúa ampliando las herramientas disponibles para reforzar la seguridad digital y, en este escenario, los agentes de IA han adquirido un papel destacado gracias a su capacidad para optimizar procesos críticos y mejorar la eficiencia operativa en distintos ámbitos. 

El 52% de las empresas cuentan con políticas formales para el uso de agentes de IA y 8 de cada 10 consideran que estos lineamientos son efectivos. Aunque la percepción de efectividad varía según el tipo de organización, en las empresas nativas digitales el 40% califica estas políticas como altamente efectivas, mientras que en las no nativas digitales este nivel alcanza solo el 27%.

En la actualidad, el 61% de las organizaciones ya emplea agentes de inteligencia artificial en sus procesos de ciberseguridad, mientras que un 35% adicional está considerando su incorporación, lo que demuestra una tendencia sostenida hacia su adopción. El uso de estas tecnologías se extiende transversalmente a múltiples áreas funcionales, destacando experimentos en servicios críticos como atención al cliente (57%), infraestructura tecnológica (57%), finanzas (50%) y ventas/marketing (50%).

En este sentido, Andrés Roepke, Country Manager de Microsoft Chile, destacó: “Hoy la inteligencia artificial está transformando por completo la forma en que las organizaciones operan, crean y se protegen. En Microsoft estamos convencidos de que no hay transformación digital sin confianza, por eso ponemos la seguridad, la privacidad y el uso responsable de la tecnología en el centro de todo lo que hacemos. La IA ya no es solo una palanca de productividad, se ha convertido en un aliado clave para reforzar la ciberseguridad, ayudando a enfrentar un panorama de amenazas cada vez más sofisticado y desafiante”.

De acuerdo con la encuesta, el aporte de estas soluciones en seguridad se observa en el fortalecimiento de tareas clave. Los agentes, diseñados para automatizar actividades, orquestar flujos y operar bajo salvaguardas, facilitan la reducción de tiempos de investigación, la priorización de alertas, la contención de incidentes y la aplicación consistente de políticas de identidad y datos. La combinación de modelos de IA con telemetría a gran escala y controles basados en Zero Trust contribuye a robustecer la postura de seguridad frente a amenazas cada vez más complejas.

 “La IA no solo aumenta la velocidad y el alcance de las defensas: a través de agentes especializados, ayuda a cerrar brechas de talento, estandarizar procesos y elevar la resiliencia del negocio. El desafío ya no es ‘si’ invertir en seguridad, sino ‘cómo’ escalarla con IA y con gobernanza responsable en cada capa de la organización”, afirmó Marcelo Felman, Director de Ciberseguridad de Microsoft para América Latina. 

Recomendaciones de ciberseguridad en la era de la IA:    

1. Hacer de la Seguridad una Prioridad, gestionando el riesgo desde el nivel directivo.   
2. Refuerza tus Buenos Hábitos Digitales: prioriza la protección de identidades, asegura el perímetro de tu empresa y monitorea continuamente los activos en la nube.   
3. Fortalecer la Resiliencia digital: identifica tus vulnerabilidades, planifica con anticipación y capacítate para responder y recuperarte rápidamente ante cualquier brecha.   
4. Invertir en las Personas, no solo en las herramientas.   
5. Prepararse para el Futuro. Anticipar cambios, entender que no sabemos lo que no sabemos, y siempre intercambiar inteligencia de amenazas.   
6. Hacer que la decisión más fácil, sea la correcta.   En lugar de bloquear y prohibir, fomentar el uso seguro.  

Acerca de Microsoft

Microsoft (Nasdaq «MSFT» @microsoft) crea plataformas y herramientas impulsadas por la IA para ofrecer soluciones innovadoras que satisfagan las necesidades cambiantes de nuestros clientes. La empresa de tecnología está comprometida con hacer que la IA esté ampliamente disponible, de manera responsable, con la misión de empoderar a cada persona y a cada organización en el planeta para lograr más.

Etiquetas:

• Chile
• IA
• Press Releases
• Seguridad

The post 78% de las organizaciones en Chile priorizará la ciberseguridad en los próximos años y 53% anticipa un alto impacto de la IA appeared first on Source LATAM.

​The post 78% de las organizaciones en Chile priorizará la ciberseguridad en los próximos años y 53% anticipa un alto impacto de la IA appeared first on Source LATAM.  

AWS Elastic Beanstalk now enables customers to build and deploy Python 3.14 applications on Amazon Linux 2023 (AL2023) platform. This latest platform support allows developers to leverage the newest features and improvements in Python while taking advantage of the enhanced security and performance of AL2023.

AWS Elastic Beanstalk is a service that provides the ability to deploy and manage applications in AWS without worrying about the infrastructure that runs those applications. Python 3.14 on AL2023 delivers enhanced interactive interpreter capabilities, improved error messages, important security and API improvements. Developers can create Elastic Beanstalk environments running Python 3.14 on AL2023 through the Elastic Beanstalk Console, CLI, or API.

This platform is available in all commercial AWS Regions where Elastic Beanstalk is available, including the AWS GovCloud (US) Regions. For a complete list of regions and service offerings, see AWS Regions.

To learn more about Python 3.14 on Amazon Linux 2023, see the AWS Elastic Beanstalk Developer guide. For additional information, visit the AWS Elastic Beanstalk product page.

​AWS Elastic Beanstalk now enables customers to build and deploy Python 3.14 applications on Amazon Linux 2023 (AL2023) platform. This latest platform support allows developers to leverage the newest features and improvements in Python while taking advantage of the enhanced security and performance of AL2023.
AWS Elastic Beanstalk is a service that provides the ability to deploy and manage applications in AWS without worrying about the infrastructure that runs those applications. Python 3.14 on AL2023 delivers enhanced interactive interpreter capabilities, improved error messages, important security and API improvements. Developers can create Elastic Beanstalk environments running Python 3.14 on AL2023 through the Elastic Beanstalk Console, CLI, or API.
This platform is available in all commercial AWS Regions where Elastic Beanstalk is available, including the AWS GovCloud (US) Regions. For a complete list of regions and service offerings, see AWS Regions.
To learn more about Python 3.14 on Amazon Linux 2023, see the AWS Elastic Beanstalk Developer guide. For additional information, visit the AWS Elastic Beanstalk product page.  

Today, AWS launches simplified enablement of AWS CloudTrail events in Amazon CloudWatch, a monitoring and logging service that helps you collect, monitor, and analyze log data from your AWS resources and applications. With this launch, you can now centrally configure collection of CloudTrail events in CloudWatch alongside other popular AWS log sources such as Amazon VPC flow logs and Amazon EKS Control Plane Logs. CloudWatch’s ingestion experience provides a consolidated view that simplifies collecting telemetry from different sources for accounts in your AWS Organization thus ensuring comprehensive monitoring and data collection across your AWS environment.

This new integration leverages service-linked channels (SLCs) to receive events from CloudTrail without requiring trails, and also provides additional benefits such as safety-checks and termination protection. You incur both CloudTrail event delivery charges and CloudWatch Logs ingestion fees based on custom logs pricing.

To learn more about enablement of CloudTrail events in CloudWatch and supported AWS regions, visit the Amazon CloudWatch documentation.

​Today, AWS launches simplified enablement of AWS CloudTrail events in Amazon CloudWatch, a monitoring and logging service that helps you collect, monitor, and analyze log data from your AWS resources and applications. With this launch, you can now centrally configure collection of CloudTrail events in CloudWatch alongside other popular AWS log sources such as Amazon VPC flow logs and Amazon EKS Control Plane Logs. CloudWatch’s ingestion experience provides a consolidated view that simplifies collecting telemetry from different sources for accounts in your AWS Organization thus ensuring comprehensive monitoring and data collection across your AWS environment. This new integration leverages service-linked channels (SLCs) to receive events from CloudTrail without requiring trails, and also provides additional benefits such as safety-checks and termination protection. You incur both CloudTrail event delivery charges and CloudWatch Logs ingestion fees based on custom logs pricing. To learn more about enablement of CloudTrail events in CloudWatch and supported AWS regions, visit the Amazon CloudWatch documentation.  

Amazon SageMaker Notebook instance now supports self-service migration, allowing you to update your notebook instance platform identifier through the UpdateNotebookInstance API. This enables you to seamlessly transition from unsupported platform identifiers (notebook-al1-v1, notebook-al2-v1, notebook-al2-v2) to supported versions (notebook-al2-v3, notebook-al2023-v1).

With the new PlatformIdentifier parameter in the UpdateNotebookInstance API, you can update to newer versions of the Notebook instance platform while preserving your existing data and configurations. The platform identifier determines which Operating System and JupyterLab version combination your notebook instance runs. This self-service capability simplifies the migration process and helps you keep your notebook instances current.

This feature is supported through AWS CLI (version 2.31.27 or newer) and SDK, and is available in all AWS Regions where Amazon SageMaker Notebook instances are supported. To learn more, see Update a Notebook Instance in the Amazon SageMaker Developer Guide.

​Amazon SageMaker Notebook instance now supports self-service migration, allowing you to update your notebook instance platform identifier through the UpdateNotebookInstance API. This enables you to seamlessly transition from unsupported platform identifiers (notebook-al1-v1, notebook-al2-v1, notebook-al2-v2) to supported versions (notebook-al2-v3, notebook-al2023-v1). With the new PlatformIdentifier parameter in the UpdateNotebookInstance API, you can update to newer versions of the Notebook instance platform while preserving your existing data and configurations. The platform identifier determines which Operating System and JupyterLab version combination your notebook instance runs. This self-service capability simplifies the migration process and helps you keep your notebook instances current. This feature is supported through AWS CLI (version 2.31.27 or newer) and SDK, and is available in all AWS Regions where Amazon SageMaker Notebook instances are supported. To learn more, see Update a Notebook Instance in the Amazon SageMaker Developer Guide.