Amazon SageMaker Unified Studio Notebooks now support Amazon EMR Serverless with Apache Spark Connect, giving data engineers and analysts more flexibility in choosing their Spark runtime for interactive analytics and data engineering workloads. In addition to Amazon Athena Spark, users can now leverage Amazon EMR Serverless as their Spark runtime, selecting the optimal engine based on their requirements.
With this launch, you can run PySpark and Spark SQL on an EMR Serverless Spark Application in Notebook cells. Users can select their Spark runtime from the Notebook side panel, and the selected runtime applies to both Python and SQL cells. Additionally, users can leverage SageMaker Data Agent, the built-in AI assistant, to generate code and execution plans from natural language prompts, accelerating Spark development workflows with EMR Serverless. Organizations can leverage pre-initialized capacity to improve session start times, while benefiting from unified Spark UI monitoring across all supported engines for consistent visibility into job execution and performance. Additionally, EMR Serverless provides VPC connectivity support for workloads requiring network isolation.
Amazon SageMaker Unified Studio Notebooks now support Amazon EMR Serverless with Apache Spark Connect, giving data engineers and analysts more flexibility in choosing their Spark runtime for interactive analytics and data engineering workloads. In addition to Amazon Athena Spark, users can now leverage Amazon EMR Serverless as their Spark runtime, selecting the optimal engine based on their requirements.
With this launch, you can run PySpark and Spark SQL on an EMR Serverless Spark Application in Notebook cells. Users can select their Spark runtime from the Notebook side panel, and the selected runtime applies to both Python and SQL cells. Additionally, users can leverage SageMaker Data Agent, the built-in AI assistant, to generate code and execution plans from natural language prompts, accelerating Spark development workflows with EMR Serverless. Organizations can leverage pre-initialized capacity to improve session start times, while benefiting from unified Spark UI monitoring across all supported engines for consistent visibility into job execution and performance. Additionally, EMR Serverless provides VPC connectivity support for workloads requiring network isolation.
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available, supporting both SageMaker Unified Studio notebooks and JupyterLab IDE environments. To get started, see Amazon SageMaker Unified Studio User Guide.
You can now create Amazon S3 Access Grants in the AWS European Sovereign Cloud (Germany) Region.
Amazon S3 Access Grants map identities in directories such as Microsoft Entra ID, or AWS Identity and Access Management (IAM) principals, to datasets in S3. This helps you manage data permissions at scale by automatically granting S3 access to end users based on their corporate identity.
Visit the AWS Region Table for complete regional availability information. To learn more about Amazon S3 Access Grants, visit our product page.
You can now create Amazon S3 Access Grants in the AWS European Sovereign Cloud (Germany) Region.
Amazon S3 Access Grants map identities in directories such as Microsoft Entra ID, or AWS Identity and Access Management (IAM) principals, to datasets in S3. This helps you manage data permissions at scale by automatically granting S3 access to end users based on their corporate identity.
Visit the AWS Region Table for complete regional availability information. To learn more about Amazon S3 Access Grants, visit our product page.
Claude Fable 5 is generally available on AWS and makes Mythos-level capabilities available to all customers, with strong safeguards designed to make it safe for broader use. Fable 5 is state-of-the-art on nearly all tested benchmarks and delivers a step-change in autonomous knowledge work and coding for developers and enterprises building production AI applications. Claude Mythos 5, the same model without those safety classifiers, is available to a small group of customers who currently have access to Claude Mythos Preview.
Claude Fable 5 can run for extended periods on complex knowledge work and coding tasks without intervention, representing a fundamental shift in the types of problems customers can solve with AI. It is built for professional tasks in finance, legal, marketing, sales, data, and engineering — proactively self-updating skills based on learnings, developing its own evaluation harnesses, and verifying its work before delivery.
Customers have two ways to access Claude Fable 5: Amazon Bedrock and Claude Platform on AWS. Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Fable 5 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see Amazon Bedrock documentation and regional availability.
Claude Platform on AWS, operated by Anthropic, gives you direct access to Anthropic’s native Claude platform experience with unified AWS billing and authentication. To get started, see the Claude Platform on AWS documentation.
Claude Fable 5 is generally available on AWS and makes Mythos-level capabilities available to all customers, with strong safeguards designed to make it safe for broader use. Fable 5 is state-of-the-art on nearly all tested benchmarks and delivers a step-change in autonomous knowledge work and coding for developers and enterprises building production AI applications. Claude Mythos 5, the same model without those safety classifiers, is available to a small group of customers who currently have access to Claude Mythos Preview.
Claude Fable 5 can run for extended periods on complex knowledge work and coding tasks without intervention, representing a fundamental shift in the types of problems customers can solve with AI. It is built for professional tasks in finance, legal, marketing, sales, data, and engineering — proactively self-updating skills based on learnings, developing its own evaluation harnesses, and verifying its work before delivery.
Customers have two ways to access Claude Fable 5: Amazon Bedrock and Claude Platform on AWS. Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Fable 5 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see Amazon Bedrock documentation and regional availability.
Claude Platform on AWS, operated by Anthropic, gives you direct access to Anthropic’s native Claude platform experience with unified AWS billing and authentication. To get started, see the Claude Platform on AWS documentation.
KPMG y Microsoft escalan agentes de IA empresariales de confianza a nivel global mediante el despliegue de Agent 365 y Copilot
Aspectos destacados:
El acuerdo permite a KPMG aprovechar Microsoft Agent 365 para gestionar y controlar agentes de IA para sus clientes y a lo largo de su red global
Este movimiento incluye el despliegue de Microsoft 365 Copilot en toda la plantilla global de KPMG, que cuenta con más de 276.000 profesionales
Estas capacidades ayudarán a KPMG y a sus clientes a pasar de pilotos de IA a despliegue a nivel organizacional con seguridad y gobernanza integradas
LONDRES y REDMOND, Washington — KPMG y Microsoft Corp. anunciaron el martes una ampliación de su relación global para ayudar a sus clientes a desplegar IA a gran escala. Según el acuerdo, KPMG aprovechará Microsoft Agent 365 para mejorar el marco de IA Confiable de KPMG y ayudar a los clientes a gestionar, monitorizar y proteger agentes de IA en sus organizaciones. Al mismo tiempo, las empresas miembros de KPMG desplegarán Microsoft 365 Copilot en toda la fuerza laboral global.
Este es el último movimiento de KPMG para integrar aún más la tecnología de Microsoft en sus plataformas globales de prestación de servicios al cliente, para permitir una IA más consistente y escalable en las soluciones tecnológicas de la organización global.
Novedades:
KPMG adoptará Microsoft Agent 365 para gestionar cómo se despliegan, gestionan, monitorizan y actualizan los agentes de IA en toda su organización global.
Las empresas de KPMG colaboran con Microsoft para ayudar a los clientes a poner agentes de IA en producción con gobernanza, seguridad y controles establecidos.
Dos años después del despliegue inicial de Microsoft 365 Copilot por parte de KPMG, las empresas miembros ampliarán el acceso a la tecnología a través de su plantilla global de más de 276.000 profesionales, para brindar una plataforma segura de IA empresarial que soporta múltiples modelos y ayuda a proteger los datos y la propiedad intelectual de KPMG.
«Microsoft y KPMG trabajan juntos para escalar la IA en toda nuestra red global y así ofrecer resultados significativos para los clientes, a través de poner Copilot y Agent 365 en manos de nuestra gente. Al mismo tiempo, los profesionales de KPMG trabajan de manera directa con los clientes para aplicar estas capacidades y ayudarles a escalar su propia transformación en IA de manera fiable y responsable. Esto requiere bases sólidas en gobernanza, visibilidad y rendición de cuentas — es un paso clave para integrar la IA responsable en el corazón de nuestra cultura y ayudar a los clientes a hacer lo mismo.» – Lisa Heneghan, directora digital global, KPMG
Habilitar la IA empresarial para los clientes
Las firmas de KPMG aprovecharán estas capacidades para mejorar la prestación de servicios en auditoría, fiscalidad y asesoría, mientras ayudan a los clientes a construir modelos operativos impulsados por agentes y escalar la IA en sus propias organizaciones.
Con Microsoft 365 Copilot, los profesionales de KPMG de todo el mundo utilizan IA en el trabajo cotidiano, lo que ayuda a mejorar la velocidad, la calidad y la coherencia en la entrega de los servicios a los clientes. Al mismo tiempo, Microsoft Agent 365 mejora aún más el ecosistema Workbench de KPMG, para brindar una gobernanza centralizada y control de los agentes de IA que operan en sistemas, datos y procesos empresariales. En conjunto, estas capacidades pueden ayudar a los clientes a pasar de pilotos aislados a un despliegue de IA de confianza a escala empresarial mediante:
Integrar la IA entre sistemas y flujos de trabajo para impulsar resultados empresariales medibles
Desplegar y gestionar agentes de IA de manera segura, con visibilidad, supervisión y control centralizados
Establecer marcos de gobernanza, riesgos y cumplimiento, incluida una propiedad clara y la gestión del ciclo de vida
«En Integra LifeSciences, operacionalizamos la IA para ofrecer resultados empresariales medibles. A través de una hoja de ruta por fases, integramos capacidades de IA, como Microsoft Copilot, en funciones principales, incluida la Cadena de Suministro Global, Asuntos Regulatorios y Asuntos Médicos. Hemos establecido un modelo operativo de IA empresarial y un equipo dedicado para garantizar que cada despliegue sea responsable, seguro y conforme a la normativa. Al escalar casos de uso de alto impacto y hacer un seguimiento de la adopción y el ROI, habilitamos decisiones más rápidas y basadas en datos y mejoramos el rendimiento operativo. Este enfoque acelera nuestra transformación hacia una organización más adaptativa, para impulsar la atención transformadora en neurocirugía y reconstrucción de tejidos y, en última instancia, para ayudar a restaurar vidas.» – Dimitri Kvares, vicepresidente corporativo y director de información global, Integra LifeSciences
«KPMG nos ayuda a ir más allá de la modernización de plataformas con la pila tecnológica de Microsoft y la nueva capacidad de IA habilitada por agentes. Con Microsoft como base de nuestra transformación digital global, estamos en camino de convertirnos en una organización inteligente y adaptativa donde la tecnología anticipa necesidades, apoya a nuestra gente y nos ayuda a mejorar de manera continua la forma en que apoyamos a nuestros miembros en todo el mundo.» – Julie Hotchkiss, directora ejecutiva, Asociación de Contables Públicos Certificados (ACCA)
«Junto con KPMG, desbloqueamos todo el potencial de la próxima fase de la IA en la empresa. Al combinar Microsoft 365 Copilot y Agent 365 con el profundo conocimiento del sector y las capacidades de entrega y gobernanza de KPMG, ayudamos a los clientes a integrar aún más la IA en la manera en que se realiza el trabajo y a permitir la transición de la experimentación al impacto a escala empresarial.» – Deb Cupp, vicepresidenta ejecutiva y directora de ingresos de Microsoft Global Enterprise
Cómo KPMG y Microsoft mejoran los resultados para los clientes con IA
Las firmas de KPMG integran la tecnología de Microsoft como base de sus plataformas globales de prestación de servicios al cliente en asesoría, fiscalidad e auditoría. Estas herramientas pueden ayudar a los profesionales de KPMG a ofrecer resultados más consistentes, basados en datos y de confianza, al tiempo que trabajan de manera directa con los clientes para ayudarles a adoptar y escalar la IA dentro de sus propias organizaciones.
En el centro de esta transformación está KPMG Workbench, una plataforma fundamental construida sobre Microsoft Azure AI Foundry que coordina múltiples agentes de IA en todas las plataformas de prestación de servicios al cliente.
En auditoría, las capacidades de IA seguirán integrándose en la plataforma global de auditoría inteligente de KPMG, KPMG Clara.
«Este anuncio representa un hito crucial en nuestra transformación de auditoría asegurada por IA y humana. Integrar Microsoft 365 Copilot y Agent 365 mejora el análisis en tiempo real, la identificación temprana de riesgos y ofrece información más profunda, al tiempo que fortalece la calidad, transparencia y confianza de la auditoría para los clientes.» – Scott Flynn, director global de auditoría en KPMG International
Acerca de la relación KPMG–Microsoft
KPMG y Microsoft han construido una relación estratégica de más de una década que les permite innovar y llevar soluciones tecnológicas al mercado.
La alianza global abarca modelos operativos en la nube, los datos, la IA y ahora los agentes operativos. Juntos, ayudan a las organizaciones a modernizarse con confianza, escalar la innovación de manera responsable y definir el futuro del trabajo en la era de la IA. Microsoft ha clasificado a KPMG como una Empresa Frontier — reconocida como una organización de próxima generación que reconstruye su modelo operativo en torno a la IA.
KPMG y Microsoft sienten pasión por la formación en IA y la alfabetización digital y, en colaboración con la UNESCO, han creado el programa AI EmpowerED con el objetivo de garantizar que los beneficios de la IA sean accesibles de manera amplia y contribuyan a un crecimiento económico inclusivo. La ambición del programa para finales de 2026 será formar y acreditar a más de 500.000 profesores y estudiantes.
Acerca de KPMG International
KPMG es una organización global de firmas independientes de servicios profesionales que ofrecen servicios de auditoría, fiscalidad y asesoría. KPMG es la marca bajo la cual operan y prestan servicios profesionales las firmas miembros de KPMG International Limited («KPMG International»). «KPMG» se utiliza para referirse a las firmas miembros individuales dentro de la organización KPMG o a una o más firmas miembros en conjunto.
Algunos o todos los servicios descritos aquí pueden no ser permitidos para clientes de auditoría de KPMG y sus afiliados o entidades relacionadas.
Las firmas KPMG operan en 138 países y territorios con más de 276.000 socios y empleados que trabajan en firmas miembros de todo el mundo. Cada firma de KPMG es una entidad distinta y separada a nivel legal y se describe como tal. Cada firma miembro de KPMG es responsable de sus propias obligaciones y responsabilidades.
KPMG International Limited es una empresa privada inglesa limitada por garantía. KPMG International Limited y sus entidades relacionadas no ofrecen servicios a sus clientes. Para más detalles sobre nuestra estructura, por favor visite kpmg.com/governance.
Acerca de Microsoft
Microsoft (Nasdaq «MSFT» @microsoft) crea plataformas y herramientas impulsadas por IA para ofrecer soluciones innovadoras que respondan a las necesidades cambiantes de nuestros clientes. La empresa tecnológica está comprometida a hacer que la IA esté disponible de manera amplia y responsable, con la misión de empoderar a cada persona y organización del planeta para lograr más.
Ed O’Brien, Jefe de Relaciones Globales con los Medios y Gestión de Problemas, Comunicaciones Globales, KPMG International, +44 (0)7947 006267, Ed.OBrien@kpmg.co.uk
Nota para los editores: Para más información, noticias y perspectivas de Microsoft, por favor visite Microsoft Source en https://news.microsoft.com/source/latam. Los enlaces web, números de teléfono y títulos eran correctos en el momento de la publicación, pero pueden haber cambiado. Para recibir ayuda adicional, periodistas y analistas pueden contactar con el Equipo de Respuesta Rápida de Microsoft u otros contactos apropiados listados en https://news.microsoft.com/microsoft-public-relations-contacts
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Today, AWS announces the preview of AWS FinOps Agent, a frontier agent for FinOps practitioners and engineering teams that answers cost questions, surfaces optimization opportunities, automatically investigates cost anomalies, and runs recurring FinOps workflows on a schedule you define.
With the AWS FinOps Agent, you can ask questions about your AWS costs and generate cloud cost reports for finance and engineering teams. The agent surfaces rightsizing, idle resource, and Savings Plans recommendations from AWS Cost Optimization Hub and AWS Compute Optimizer, and can open Jira tickets on your behalf. When a cost anomaly is detected, FinOps Agent can automatically investigate the root cause and can post the findings to a Slack channel, so engineering teams are notified without manual triage.
AWS FinOps Agent (preview) is available in the US East (N. Virginia) Region and includes cost and usage data covering all AWS Regions, except AWS GovCloud (US) Regions and AWS China (Beijing and Ningxia) Regions. AWS FinOps Agent is offered at no additional charge during the preview.
Learn more about AWS FinOps Agent in the User Guide, product details page, and the blog. Get started by visiting the AWS FinOps Agent page in the AWS Management Console.
Today, AWS announces the preview of AWS FinOps Agent, a frontier agent for FinOps practitioners and engineering teams that answers cost questions, surfaces optimization opportunities, automatically investigates cost anomalies, and runs recurring FinOps workflows on a schedule you define.
With the AWS FinOps Agent, you can ask questions about your AWS costs and generate cloud cost reports for finance and engineering teams. The agent surfaces rightsizing, idle resource, and Savings Plans recommendations from AWS Cost Optimization Hub and AWS Compute Optimizer, and can open Jira tickets on your behalf. When a cost anomaly is detected, FinOps Agent can automatically investigate the root cause and can post the findings to a Slack channel, so engineering teams are notified without manual triage.
AWS FinOps Agent (preview) is available in the US East (N. Virginia) Region and includes cost and usage data covering all AWS Regions, except AWS GovCloud (US) Regions and AWS China (Beijing and Ningxia) Regions. AWS FinOps Agent is offered at no additional charge during the preview.
Learn more about AWS FinOps Agent in the User Guide, product details page, and the blog. Get started by visiting the AWS FinOps Agent page in the AWS Management Console.
Amazon EMR Serverless now supports interactive sessions with Spark Connect, enabling you to develop and run Apache Spark applications from managed notebooks in Amazon SageMaker Unified Studio, as well as your favorite notebook environments and IDEs such as Jupyter and Visual Studio Code. You can also monitor and debug active and completed sessions in the EMR console, and get granular cost and usage visibility for individual sessions.
An interactive session provides a persistent Spark context that seamlessly spans across cells and scripts, enabling you to blend local Python code execution with remote Spark operations within a unified environment. This is enabled by Spark Connect’s client-server architecture, which decouples your application client from the Spark driver and allows you to maintain your preferred development environment and tooling while Spark infrastructure runs independently on EMR Serverless. This architecture unlocks workflows including ad hoc data exploration, iterative step-by-step debugging, and incremental PySpark job development before deploying to production. For observability, you get real-time session monitoring via the Spark UI, history tracking through the Spark History Server, and session management from the EMR console or API/CLI/SDK.
Amazon EMR Serverless now supports interactive sessions with Spark Connect, enabling you to develop and run Apache Spark applications from managed notebooks in Amazon SageMaker Unified Studio, as well as your favorite notebook environments and IDEs such as Jupyter and Visual Studio Code. You can also monitor and debug active and completed sessions in the EMR console, and get granular cost and usage visibility for individual sessions.
An interactive session provides a persistent Spark context that seamlessly spans across cells and scripts, enabling you to blend local Python code execution with remote Spark operations within a unified environment. This is enabled by Spark Connect’s client-server architecture, which decouples your application client from the Spark driver and allows you to maintain your preferred development environment and tooling while Spark infrastructure runs independently on EMR Serverless. This architecture unlocks workflows including ad hoc data exploration, iterative step-by-step debugging, and incremental PySpark job development before deploying to production. For observability, you get real-time session monitoring via the Spark UI, history tracking through the Spark History Server, and session management from the EMR console or API/CLI/SDK.
Spark Connect on Amazon EMR Serverless is available with EMR release 7.13 in all AWS Regions where Amazon EMR Serverless is available. The SageMaker Unified Studio experience is available in supported regions. To get started, visit the EMR Serverless Interactive Sessions User Guide or the Amazon SageMaker Unified Studio Getting Started guide.
AWS Cost Explorer now supports ‘Analyze with Amazon Q’, a new capability that delivers comprehensive cost explanations for any report you configure in Cost Explorer. With a single button click you now can receive detailed analysis from Amazon Q Developer covering your cost trends, top cost drivers, and anomalies. All analysis uses your exact filters and time-period and provides guidance to discover optimization opportunities through follow-up questions.
Previously, cost analysis required manual investigation across multiple filters and data points. With ‘Analyze with Amazon Q’, you simply configure your Cost Explorer view and click a single button. Amazon Q analyzes your current context and delivers explanations directly in its chat panel, adapting to what you’re viewing: historical explanations for past dates, forecast explanations for future dates, or both for mixed periods. You can then ask follow-up questions to explore any insights related to your cost data in greater detail as Amazon Q maintains full conversation context throughout.
‘Analyze with Amazon Q’ is available in all commercial AWS Regions at no additional charge. To get started, visit the AWS Cost Explorer console, or view the user guide.
AWS Cost Explorer now supports ‘Analyze with Amazon Q’, a new capability that delivers comprehensive cost explanations for any report you configure in Cost Explorer. With a single button click you now can receive detailed analysis from Amazon Q Developer covering your cost trends, top cost drivers, and anomalies. All analysis uses your exact filters and time-period and provides guidance to discover optimization opportunities through follow-up questions.
Previously, cost analysis required manual investigation across multiple filters and data points. With ‘Analyze with Amazon Q’, you simply configure your Cost Explorer view and click a single button. Amazon Q analyzes your current context and delivers explanations directly in its chat panel, adapting to what you’re viewing: historical explanations for past dates, forecast explanations for future dates, or both for mixed periods. You can then ask follow-up questions to explore any insights related to your cost data in greater detail as Amazon Q maintains full conversation context throughout.
‘Analyze with Amazon Q’ is available in all commercial AWS Regions at no additional charge. To get started, visit the AWS Cost Explorer console, or view the user guide.
AWS Compute Optimizer now identifies idle resources for Amazon DynamoDB provisioned tables, Amazon ElastiCache (Redis and Valkey), Amazon MemoryDB, Amazon DocumentDB (provisioned and serverless), Amazon WorkSpaces, and Amazon SageMaker endpoints. This expansion enables you to detect unused resources across more of your AWS environment and identify potential cost savings.
Compute Optimizer analyzes utilization metrics to determine whether a resource is idle. Customers can set this lookback period based on the nature of their workloads. For each resource type, Compute Optimizer evaluates service-specific signals such as consumed capacity, cache hits, active connections, and CPU utilization. When Compute Optimizer identifies potential idle resources, it surfaces these recommendations, along with detailed utilization metrics and estimated savings in the console, enabling you to evaluate recommendations before acting. You can also view idle resource recommendations across all AWS accounts in your organization through the Cost Optimization Hub, with de-duplicated estimated savings with other recommendations on the same resources.
For more information about the AWS Regions where Compute Optimizer is available, see the AWS Region table. For more information about AWS Compute Optimizer, visit our product page and documentation. You can start using AWS Compute Optimizer through the AWS Management Console, AWS CLI, and AWS SDK.
AWS Compute Optimizer now identifies idle resources for Amazon DynamoDB provisioned tables, Amazon ElastiCache (Redis and Valkey), Amazon MemoryDB, Amazon DocumentDB (provisioned and serverless), Amazon WorkSpaces, and Amazon SageMaker endpoints. This expansion enables you to detect unused resources across more of your AWS environment and identify potential cost savings.
Compute Optimizer analyzes utilization metrics to determine whether a resource is idle. Customers can set this lookback period based on the nature of their workloads. For each resource type, Compute Optimizer evaluates service-specific signals such as consumed capacity, cache hits, active connections, and CPU utilization. When Compute Optimizer identifies potential idle resources, it surfaces these recommendations, along with detailed utilization metrics and estimated savings in the console, enabling you to evaluate recommendations before acting. You can also view idle resource recommendations across all AWS accounts in your organization through the Cost Optimization Hub, with de-duplicated estimated savings with other recommendations on the same resources.
For more information about the AWS Regions where Compute Optimizer is available, see the AWS Region table. For more information about AWS Compute Optimizer, visit our product page and documentation. You can start using AWS Compute Optimizer through the AWS Management Console, AWS CLI, and AWS SDK.
Effective today, Amazon MSK Express Brokers support automatic topic creation with Kafka Streams. Customers can now deploy their Kafka Streams applications on Express Brokers without needing to manually pre-createor manage topics for stateful operations.
MSK Express Brokers are designed to deliver up to three times more throughput per broker, scale up to 20 times faster, and reduce recovery time by 90 percent. Kafka Streams uses topics to store state and repartition data for stateful operations. Previously, customers running Kafka Streams with Express Brokers had to manually name and pre-create these topics before deploying their application. With this launch, these topics are created automatically when the application starts, simplifying deployment and reducing operational setup for Kafka Streams applications on Express Brokers.
This capability is available today in all AWS regions where MSK Express Brokers are available. No additional configuration or setup is required to get started. To learn more, see Amazon MSK Developer Guide.
Effective today, Amazon MSK Express Brokers support automatic topic creation with Kafka Streams. Customers can now deploy their Kafka Streams applications on Express Brokers without needing to manually pre-create or manage topics for stateful operations. MSK Express Brokers are designed to deliver up to three times more throughput per broker, scale up to 20 times faster, and reduce recovery time by 90 percent. Kafka Streams uses topics to store state and repartition data for stateful operations. Previously, customers running Kafka Streams with Express Brokers had to manually name and pre-create these topics before deploying their application. With this launch, these topics are created automatically when the application starts, simplifying deployment and reducing operational setup for Kafka Streams applications on Express Brokers. This capability is available today in all AWS regions where MSK Express Brokers are available. No additional configuration or setup is required to get started. To learn more, see Amazon MSK Developer Guide.
Amazon DocumentDB (with MongoDB compatibility) now supports engine minor versions, starting with 5.0.1. This release delivers enhanced aggregation capabilities with new operators ($rand, $pow, $dateToParts, $dateFromParts), the active connections metric to monitor instances, and granular command-level performance metrics in CloudWatch (find, insert, findAndModify, update, etc.). For a full list of what’s included, see release notes. Minor versions provide new features and bug fixes within the same major version, giving you more control over when and how you upgrade your clusters. We recommend upgrading to the latest minor version to benefit from these performance enhancements, bug fixes, and new capabilities.
You can specify minor version 5.0.1 when creating a new cluster, or manually upgrade an existing 5.0.0 cluster to 5.0.1 using the AWS Management Console or AWS CLI (via the modify-db-cluster command with –engine-version 5.0.1). Once you upgrade to a newer minor version, you cannot downgrade back to a previous minor version. Upgrading from 5.0.0 (LTS) to 5.0.1 gives you access to the latest features and fixes, but you will no longer be on the LTS track. If minimizing upgrades is your priority, you should remain on LTS. For more information, see Using a long-term support (LTS) release.
Amazon DocumentDB engine minor version 5.0.1 is available in all AWS Regions where Amazon DocumentDB 5.0 is available. Learn more about minor version upgrades and version support dates in the Amazon DocumentDB Developer Guide. Create or update a fully managed Amazon DocumentDB cluster in the Amazon DocumentDB Management Console.
Amazon DocumentDB (with MongoDB compatibility) now supports engine minor versions, starting with 5.0.1. This release delivers enhanced aggregation capabilities with new operators ($rand, $pow, $dateToParts, $dateFromParts), the active connections metric to monitor instances, and granular command-level performance metrics in CloudWatch (find, insert, findAndModify, update, etc.). For a full list of what’s included, see release notes. Minor versions provide new features and bug fixes within the same major version, giving you more control over when and how you upgrade your clusters. We recommend upgrading to the latest minor version to benefit from these performance enhancements, bug fixes, and new capabilities. You can specify minor version 5.0.1 when creating a new cluster, or manually upgrade an existing 5.0.0 cluster to 5.0.1 using the AWS Management Console or AWS CLI (via the modify-db-cluster command with –engine-version 5.0.1). Once you upgrade to a newer minor version, you cannot downgrade back to a previous minor version. Upgrading from 5.0.0 (LTS) to 5.0.1 gives you access to the latest features and fixes, but you will no longer be on the LTS track. If minimizing upgrades is your priority, you should remain on LTS. For more information, see Using a long-term support (LTS) release. Amazon DocumentDB engine minor version 5.0.1 is available in all AWS Regions where Amazon DocumentDB 5.0 is available. Learn more about minor version upgrades and version support dates in the Amazon DocumentDB Developer Guide. Create or update a fully managed Amazon DocumentDB cluster in the Amazon DocumentDB Management Console.
