Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g instances are available in AWS Europe (Paris), Asia Pacific (Osaka), AWS Canada (Central), and AWS Middle East (Bahrain) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.

AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based Amazon M7g instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. M8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS).

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

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g instances are available in AWS Europe (Paris), Asia Pacific (Osaka), AWS Canada (Central), and AWS Middle East (Bahrain) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based Amazon M7g instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. M8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 M8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.   

• Categoría: Noticias de Microsoft

octubre 14, 2025

Microsoft Ignite: Dar forma a lo que sigue con nuestro ecosistema de socios

Por: Julie Sanford Vicepresidenta, GTM global, programas y operaciones, ventas de socios de canal globales.

En solo unas semanas, nos reuniremos en Microsoft Ignite 2025 para centrarnos en cuatro pilares que definen la transformación exitosa de la IA: mejorar las experiencias de los empleados, reinventar los procesos comerciales, profundizar las conexiones con los clientes y doblar la curva de la innovación de la industria. En todos los sectores, las organizaciones se preguntan cómo lograr estos resultados con rapidez y confianza, y los socios de Microsoft son los que pueden hacerlo posible.

Únanse a nosotros en San Francisco o en línea del 18 al 21 de noviembre para ver las últimas innovaciones, conectarse con líderes y compañeros de Microsoft y aprender cómo ofrecer un impacto aún mayor para sus clientes. La inscripción está abierta y todavía hay tiempo para reservar su lugar hoy.

Qué esperar en Microsoft Ignite

Aprendan a aprovechar al máximo su asociación con Microsoft a través del programa de socios de Microsoft AI Cloud. Exploren los últimos beneficios para socios, recursos de capacitación, oportunidades de venta conjunta y soluciones diseñadas para acelerar el crecimiento y la innovación. Desde la creación de soluciones impulsadas por IA hasta el impulso de la transformación de los clientes en todos los sectores, descubran cómo reforzar su diferenciación, ampliar su alcance en el mercado y ofrecer más valor a través de Microsoft Cloud.

La agenda está diseñada para brindar a los socios una experiencia curada.

• Conferencias magistrales de Microsoft y líderes de la industria que muestran innovaciones de productos e historias de impacto de socios:
  • Discurso de apertura de Ignite
    El discurso de apertura contará con Judson Althoff, CEO de negocios comerciales de Microsoft, con nuestros líderes senior de ingeniería de Microsoft mientras revelan las últimas innovaciones que impulsan la próxima ola de transformación de la IA, lo que permite a cada ser humano y a cada organización en todas las industrias redefinir lo que significa convertirse en frontera.
  • Transformar juntos: Asociarse en el auge de las empresas fronterizas
    Únanse a Nicole Dezen, directora de socios y vicepresidenta corporativa de Global Partner Solutions, Nick Parker, presidente de Enterprise, Industry and Partnerships, y Ralph Haupter, presidente y director de CRO, Small Medium Enterprises and Channel (SME&C) para un discurso de apertura dinámico que explora el papel cambiante de los socios en la configuración de la próxima generación de empresas fronterizas. Esta sesión destacará las historias de éxito de los socios que lideran a los clientes a través de la transformación de la IA, cómo logramos el éxito juntos y las últimas inversiones y anuncios del Programa de socios de Microsoft AI Cloud.

• Sesiones de trabajo sobre incentivos, oportunidades de venta conjunta, áreas de soluciones y crecimiento impulsado por la IA.
• Sesiones de teatro con ejemplos reales de aplicaciones de IA, agentes inteligentes y soluciones de datos.
• El área de exposición del Hub con oportunidades para demostraciones de soluciones, conexión con expertos en la materia y participación en debates interactivos.
• El stand de Microsoft AI Cloud Partner Program en el Hub, donde pueden obtener más información y comprar paquetes de beneficios para socios.
• Laboratorios prácticos, oportunidades de certificación in situ y reuniones comunitarias que facilitan el aprendizaje y la creación de conexiones.
• Oportunidades de encontrar y conectarse con asistentes en persona a través de nuestro directorio de asistentes, así como oradores de eventos a través de nuestro directorio de oradores.
• Eventos nocturnos de networking que ofrecen una forma relajada de conectarse, incluida la Noche de neón el martes 18 de noviembre y la Block Party el miércoles 19 de noviembre.

Ignite también es donde celebramos a los socios que lideran la transformación digital, incluidos los ganadores del premio Microsoft Partner of the Year 2025 que se anunciarán más adelante.

Visiten nuestra página de socios de Ignite para obtener más información sobre cómo aprovechar al máximo su experiencia con Ignite.

Aspectos destacados de la sesión

• Programa de socios de Microsoft AI Cloud: descubran cómo aprovechar al máximo el programa para obtener habilidades, crecimiento de la canalización y éxito en la comercialización con experiencias de IA inmersivas y alineación estratégica.
• Modernizar con la nube y la IA: modernicen las plataformas de datos con Azure AI para impulsar la innovación, unificar estrategias y escalar las cargas de trabajo empresariales.
• Liderar la transformación de la IA con Copilot: Escalen su práctica de IA y aceleren el crecimiento del negocio con Copilot, agentes inteligentes y automatización de bajo código.
• Hacer crecer su práctica de seguridad con IA: simplifiquen la protección, impulsen la adopción y desbloqueen nuevas fuentes de ingresos con las soluciones de seguridad de Microsoft.
• Impulsar los ingresos y el crecimiento de la industria: exploren innovaciones, aprendan de las historias de éxito de los socios y posicionen su negocio como líder de Frontier Firm (Empresa Frontera).

Sus próximas acciones

1. Regístrense ahora para asegurar su lugar en San Francisco o únanse a nosotros en línea. Asegúrense de seleccionar la pista de socios adecuada  para que puedan aprovechar las sesiones adaptadas a su crecimiento.
2. Exploren el catálogo de sesiones para encontrar sesiones que les interesen y agréguenlas a su lista de favoritos para facilitar la reserva.
3. Asegúrense de revisar y actualizar su perfil antes de llegar al evento.
4. Consulten nuestra lista de patrocinadores para solicitar reuniones y comenzar a hacer conexiones.

Ignite es donde damos forma a lo que sigue, juntos. Espero conectarme con ustedes en San Francisco o en línea y ver que nuestro ecosistema de socios continúa a la cabeza el camino en la era de la IA.

Etiquetas:

• Eventos
• Socios de Negocio

The post Microsoft Ignite: Dar forma a lo que sigue con nuestro ecosistema de socios appeared first on Source LATAM.

 

​The post Microsoft Ignite: Dar forma a lo que sigue con nuestro ecosistema de socios appeared first on Source LATAM.  

AWS now provides immediate access to resource search capabilities in all accounts through AWS Resource Explorer. With this launch, you no longer need to activate Resource Explorer to discover your resources in a Region.

To start searching, you need, at minimum, permissions in the AWS Resource Explorer Read Only Access or AWS Read Only Access managed policies. You can discover resources in the AWS Resource Explorer console, Unified Search, and AWS CLI and SDKs. To search the full inventory of supported resources, including historical backfill and automatic updates, complete Resource Explorer setup. This requires additional permissions to create a Service-Linked Role, so that Resource Explorer can automatically complete setup in each Region where you search. You can also enable cross-Region search to discover resources across all Regions in your AWS account with one-click in the Console, or with a single API call using the new CreateResourceExplorerSetup API.

This feature is available at no additional cost in all AWS Regions where Resource Explorer is supported. To start searching for your resources, visit the AWS Resource Explorer console. Read about getting started in the AWS Resource Explorer documentation, or explore the AWS Resource Explorer product page.

 

​AWS now provides immediate access to resource search capabilities in all accounts through AWS Resource Explorer. With this launch, you no longer need to activate Resource Explorer to discover your resources in a Region. To start searching, you need, at minimum, permissions in the AWS Resource Explorer Read Only Access or AWS Read Only Access managed policies. You can discover resources in the AWS Resource Explorer console, Unified Search, and AWS CLI and SDKs. To search the full inventory of supported resources, including historical backfill and automatic updates, complete Resource Explorer setup. This requires additional permissions to create a Service-Linked Role, so that Resource Explorer can automatically complete setup in each Region where you search. You can also enable cross-Region search to discover resources across all Regions in your AWS account with one-click in the Console, or with a single API call using the new CreateResourceExplorerSetup API. This feature is available at no additional cost in all AWS Regions where Resource Explorer is supported. To start searching for your resources, visit the AWS Resource Explorer console. Read about getting started in the AWS Resource Explorer documentation, or explore the AWS Resource Explorer product page.  

Starting today, Amazon EC2 High Memory U7i instances with 12TB of memory (u7i-12tb.224xlarge) are now available in the Asia Pacific (Mumbai) region. U7i-12tb instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7i-12tb instances offer 12TiB of DDR5 memory enabling customers to scale transaction processing throughput in a fast-growing data environment.

U7i-12tb instances offer 896 vCPUs, support up to 100Gbps Elastic Block Storage (EBS) for faster data loading and backups, deliver up to 100Gbps of network bandwidth, and support ENA Express. U7i instances are ideal for customers using mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server.

To learn more about U7i instances, visit the High Memory instances page.

 

​Starting today, Amazon EC2 High Memory U7i instances with 12TB of memory (u7i-12tb.224xlarge) are now available in the Asia Pacific (Mumbai) region. U7i-12tb instances are part of AWS 7th generation and are powered by custom fourth generation Intel Xeon Scalable Processors (Sapphire Rapids). U7i-12tb instances offer 12TiB of DDR5 memory enabling customers to scale transaction processing throughput in a fast-growing data environment. U7i-12tb instances offer 896 vCPUs, support up to 100Gbps Elastic Block Storage (EBS) for faster data loading and backups, deliver up to 100Gbps of network bandwidth, and support ENA Express. U7i instances are ideal for customers using mission-critical in-memory databases like SAP HANA, Oracle, and SQL Server. To learn more about U7i instances, visit the High Memory instances page.  

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports the latest General Distribution Release (GDR) updates for Microsoft SQL Server. This release includes support for Microsoft SQL Server 2016 SP3+GDR KB5065226 (RDS version 13.00.6470.1.v1), SQL Server 2017 CU31+GDR KB5065225 (RDS version 14.00.3505.1.v1), SQL Server 2019 CU32+GDR KB5065222 (RDS version 15.00.4445.1.v1) and SQL Server 2022 CU21 KB5065865 (RDS version 16.00.4215.2.v1).

The GDR updates address vulnerabilities described in CVE-2025-47997, CVE-2025-55227, CVE-2024-21907. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5065226, KB5065225, KB5065222 and KB5065865. We recommend that you upgrade your Amazon RDS for SQL Server instances to apply these updates using Amazon RDS Management Console, or by using the AWS SDK or CLI. You can learn more about upgrading your database instance in the Amazon RDS SQL Server User Guide for upgrading your RDS Microsoft SQL Server DB engine.

 

​Amazon Relational Database Service (Amazon RDS) for SQL Server now supports the latest General Distribution Release (GDR) updates for Microsoft SQL Server. This release includes support for Microsoft SQL Server 2016 SP3+GDR KB5065226 (RDS version 13.00.6470.1.v1), SQL Server 2017 CU31+GDR KB5065225 (RDS version 14.00.3505.1.v1), SQL Server 2019 CU32+GDR KB5065222 (RDS version 15.00.4445.1.v1) and SQL Server 2022 CU21 KB5065865 (RDS version 16.00.4215.2.v1). The GDR updates address vulnerabilities described in CVE-2025-47997, CVE-2025-55227, CVE-2024-21907. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5065226, KB5065225, KB5065222 and KB5065865. We recommend that you upgrade your Amazon RDS for SQL Server instances to apply these updates using Amazon RDS Management Console, or by using the AWS SDK or CLI. You can learn more about upgrading your database instance in the Amazon RDS SQL Server User Guide for upgrading your RDS Microsoft SQL Server DB engine.  

Amazon SageMaker AI Projects now supports provisioning custom machine learning (ML) project templates from Amazon S3. Administrators can now manage ML templates in SageMaker AI studio so data scientists can create standardized ML projects to meet their organizational needs.

Data scientists can use Amazon SageMaker AI Projects to create standardized ML projects that meet organizational requirements and automate ML development workflows. Administrators define standardized ML project templates that include end-to-end development patterns. By provisioning custom templates from Amazon S3, administrators can define standardized project templates and provide access to these templates directly in the SageMaker AI studio for data scientists, ensuring all ML projects follow organizational standards.

SageMaker AI Projects custom template S3 provisioning is available in all AWS Regions where SageMaker AI Projects is available.

To learn more, visit SageMaker AI Projects documentation, and SageMaker AI Studio. 

 

​Amazon SageMaker AI Projects now supports provisioning custom machine learning (ML) project templates from Amazon S3. Administrators can now manage ML templates in SageMaker AI studio so data scientists can create standardized ML projects to meet their organizational needs. Data scientists can use Amazon SageMaker AI Projects to create standardized ML projects that meet organizational requirements and automate ML development workflows. Administrators define standardized ML project templates that include end-to-end development patterns. By provisioning custom templates from Amazon S3, administrators can define standardized project templates and provide access to these templates directly in the SageMaker AI studio for data scientists, ensuring all ML projects follow organizational standards. SageMaker AI Projects custom template S3 provisioning is available in all AWS Regions where SageMaker AI Projects is available. To learn more, visit SageMaker AI Projects documentation, and SageMaker AI Studio.   

Amazon CloudWatch announces the general availability of generative AI observability, helping you monitor all components of AI applications and workloads, including agents deployed and operated with Amazon Bedrock AgentCore. This release expands beyond runtime monitoring to include complete observability across AgentCore’s Built-in Tools, Gateways, Memory, and Identity capabilities. DevOps teams and developers can now get an out-of-the-box view into latency, token usage, errors, and performance across all components of their AI workloads, from model invocations to agent operations. This feature is compatible with popular generative AI orchestration frameworks such as Strands Agents, LangChain, and LangGraph, offering flexibility with your choice of framework.

With this new feature, CloudWatch enalbes developers to analyzes telemetry data across components of a generative AI application. Customers can monitor code execution patterns in Built-in Tools, track API transformation success rates through Gateways, analyze memory storage and retrieval patterns, and ensure secure agent behavior through Identity observability. The connected view helps developers quickly identify issues – from gaps in VectorDB to authentication failures – using end-to-end prompt tracing, curated metrics, and logs. Developers can monitor their entire agent fleet through the «AgentCore» section in the CloudWatch console, which integrates seamlessly with other CloudWatch capabilities including Application Signals, Alarms, Sensitive Data Protection, and Logs Insights.

This feature is now available in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Asia Pacific (Mumbai), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney).

To learn more, visit documentation. There is no additional pricing for Gen AI Observability, existing CloudWatch pricing for underlying telemetry data applies.

 

​Amazon CloudWatch announces the general availability of generative AI observability, helping you monitor all components of AI applications and workloads, including agents deployed and operated with Amazon Bedrock AgentCore. This release expands beyond runtime monitoring to include complete observability across AgentCore’s Built-in Tools, Gateways, Memory, and Identity capabilities. DevOps teams and developers can now get an out-of-the-box view into latency, token usage, errors, and performance across all components of their AI workloads, from model invocations to agent operations. This feature is compatible with popular generative AI orchestration frameworks such as Strands Agents, LangChain, and LangGraph, offering flexibility with your choice of framework. With this new feature, CloudWatch enalbes developers to analyzes telemetry data across components of a generative AI application. Customers can monitor code execution patterns in Built-in Tools, track API transformation success rates through Gateways, analyze memory storage and retrieval patterns, and ensure secure agent behavior through Identity observability. The connected view helps developers quickly identify issues – from gaps in VectorDB to authentication failures – using end-to-end prompt tracing, curated metrics, and logs. Developers can monitor their entire agent fleet through the «AgentCore» section in the CloudWatch console, which integrates seamlessly with other CloudWatch capabilities including Application Signals, Alarms, Sensitive Data Protection, and Logs Insights. This feature is now available in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Asia Pacific (Mumbai), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney). To learn more, visit documentation. There is no additional pricing for Gen AI Observability, existing CloudWatch pricing for underlying telemetry data applies.  

Vector search for Amazon ElastiCache is now generally available. Customers can now use ElastiCache to index, search, and update billions of high-dimensional vector embeddings from popular providers like Amazon Bedrock, Amazon SageMaker, Anthropic, and OpenAI with latency as low as microseconds and up to 99% recall.

Key use cases include semantic caching for large language models (LLMs) and multi-turn conversational agents, which significantly reduce latency and cost by caching semantically similar queries. Vector search for ElastiCache also powers agentic AI systems with Retrieval Augmented Generation (RAG) to ensure highly relevant results and consistently low latency across multiple retrieval steps. Additional use cases include recommendation engines, anomaly detection, and other applications that require efficient search across multiple data modalities.

Vector search for ElastiCache is available with Valkey version 8.2 on node-based clusters in all AWS Regions at no additional cost. To get started, create a Valkey 8.2 cluster using the AWS Management Console, AWS Software Development Kit (SDK), or AWS Command Line Interface (CLI). You can also use vector search on your existing clusters by upgrading from any version of Valkey or Redis OSS to Valkey 8.2 in a few clicks with no downtime. To learn more about vector search for ElastiCache for Valkey read this blog and for a list of supported commands see the ElastiCache documentation. 

 

​Vector search for Amazon ElastiCache is now generally available. Customers can now use ElastiCache to index, search, and update billions of high-dimensional vector embeddings from popular providers like Amazon Bedrock, Amazon SageMaker, Anthropic, and OpenAI with latency as low as microseconds and up to 99% recall. Key use cases include semantic caching for large language models (LLMs) and multi-turn conversational agents, which significantly reduce latency and cost by caching semantically similar queries. Vector search for ElastiCache also powers agentic AI systems with Retrieval Augmented Generation (RAG) to ensure highly relevant results and consistently low latency across multiple retrieval steps. Additional use cases include recommendation engines, anomaly detection, and other applications that require efficient search across multiple data modalities. Vector search for ElastiCache is available with Valkey version 8.2 on node-based clusters in all AWS Regions at no additional cost. To get started, create a Valkey 8.2 cluster using the AWS Management Console, AWS Software Development Kit (SDK), or AWS Command Line Interface (CLI). You can also use vector search on your existing clusters by upgrading from any version of Valkey or Redis OSS to Valkey 8.2 in a few clicks with no downtime. To learn more about vector search for ElastiCache for Valkey read this blog and for a list of supported commands see the ElastiCache documentation.   

Amazon Quick Sight now supports font customization for data labels and axes. Authors can now customize fonts for data labels and axes in supported charts, in addition to the previously supported font customization for visual titles, subtitles, and legend, as well as tables and pivot tables headers.

Authors can set the font size (in pixels), font family, color, and styling options like bold, italics, and underline across analysis, including dashboards, reports and embedded scenarios. With this update, you can further align your dashboard’s fonts with your organization’s branding guidelines, creating a more cohesive and visually appealing experience. Additionally, the expanded font customization options help improve readability, especially when viewing visualizations on large screens.

This is now available in all supported Amazon Quick Suite regions.

To learn more about this, visit Amazon Quick Suite Visual formatting guide.

 

​Amazon Quick Sight now supports font customization for data labels and axes. Authors can now customize fonts for data labels and axes in supported charts, in addition to the previously supported font customization for visual titles, subtitles, and legend, as well as tables and pivot tables headers. Authors can set the font size (in pixels), font family, color, and styling options like bold, italics, and underline across analysis, including dashboards, reports and embedded scenarios. With this update, you can further align your dashboard’s fonts with your organization’s branding guidelines, creating a more cohesive and visually appealing experience. Additionally, the expanded font customization options help improve readability, especially when viewing visualizations on large screens. This is now available in all supported Amazon Quick Suite regions. To learn more about this, visit Amazon Quick Suite Visual formatting guide.  

After careful consideration, we’re announcing availability changes for a select group of AWS services and features. These changes fall into three lifecycle categories:

Services and Capabilities moving to Maintenance

Services moving to maintenance will no longer be accessible to new customers starting Nov 7, 2025. Current customers can continue using the service or feature while exploring alternative solutions.

• Amazon Cloud Directory
• Amazon CodeCatalyst
• Amazon CodeGuru Reviewer
• Amazon Fraud Detector
• Amazon Glacier
• Amazon S3 Object Lambda
• Amazon Workspaces Web Access Client for PCoIP (STXHD)
• AWS Application Discovery Service
• AWS HealthOmics – Variant and Annotation Store
• AWS IoT SiteWise Edge Data Processing Pack
• AWS IoT SiteWise Monitor
• AWS Mainframe Modernization Service
• AWS Migration Hub
• AWS Snowball Edge Compute Optimized
• AWS Snowball Edge Storage Optimized
• AWS Systems Manager – Change Manager
• AWS Systems Manager – Incident Manager
• AWS Thinkbox Deadline 10
• .NET Modernization Tools

Services Entering Sunset

The following services are entering sunset, and we are announcing the date upon which we will end operations and support of the service. Customers using these services should click on the links below to understand the sunset timeline (typically 12 months), and begin planning migration to alternatives as recommended in the updated service web pages and documentation.

• Amazon FinSpace
• Amazon Lookout for Equipment
• AWS IoT Greengrass v1
• AWS Proton

Services Reaching End of Support

The following services have reached end of support and are no longer available as of October 7, 2025.

• AWS Mainframe Modernization App Testing

For customers affected by these changes, we’ve prepared comprehensive migration guides and our support teams are ready to assist with your transition. Visit AWS Product Lifecycle Page to learn more. or contact AWS Support.

 

​After careful consideration, we’re announcing availability changes for a select group of AWS services and features. These changes fall into three lifecycle categories: Services and Capabilities moving to Maintenance Services moving to maintenance will no longer be accessible to new customers starting Nov 7, 2025. Current customers can continue using the service or feature while exploring alternative solutions.

Amazon Cloud Directory
Amazon CodeCatalyst
Amazon CodeGuru Reviewer
Amazon Fraud Detector
Amazon Glacier
Amazon S3 Object Lambda
Amazon Workspaces Web Access Client for PCoIP (STXHD)
AWS Application Discovery Service
AWS HealthOmics – Variant and Annotation Store
AWS IoT SiteWise Edge Data Processing Pack
AWS IoT SiteWise Monitor
AWS Mainframe Modernization Service
AWS Migration Hub
AWS Snowball Edge Compute Optimized
AWS Snowball Edge Storage Optimized
AWS Systems Manager – Change Manager
AWS Systems Manager – Incident Manager
AWS Thinkbox Deadline 10
.NET Modernization Tools

Services Entering Sunset The following services are entering sunset, and we are announcing the date upon which we will end operations and support of the service. Customers using these services should click on the links below to understand the sunset timeline (typically 12 months), and begin planning migration to alternatives as recommended in the updated service web pages and documentation.

Amazon FinSpace
Amazon Lookout for Equipment
AWS IoT Greengrass v1
AWS Proton

Services Reaching End of Support The following services have reached end of support and are no longer available as of October 7, 2025.

AWS Mainframe Modernization App Testing

For customers affected by these changes, we’ve prepared comprehensive migration guides and our support teams are ready to assist with your transition. Visit AWS Product Lifecycle Page to learn more. or contact AWS Support.