Today, we are announcing improvements to the Amazon Q Developer chat experience in Amazon SageMaker Unified Studio Jupyter notebooks and adding Amazon Q Developer in the command line in Jupyter notebooks and Code Editor. By integrating with Model Context Protocol (MCP) servers, Amazon Q Developer is aware of your SageMaker Unified Studio project resources, including data, compute, and code, and provides personalized assistance for data engineering and machine learning development work.

These new capabilities provide highly relevant responses to assist with tasks like code refactoring, file modification, and troubleshooting. This helps data scientists and data engineers quickly set up their integrated development environments and work more efficiently while maintaining transparency into how the AI assistant is acting on their behalf.

These features are available at no additional cost with the Amazon Q Developer Free Tier in all AWS Regions where Amazon SageMaker Unified Studio is available. To make even more use of these features, we recommend enabling Amazon Q Developer Pro. To do so, please refer to the documentation.

 

​Today, we are announcing improvements to the Amazon Q Developer chat experience in Amazon SageMaker Unified Studio Jupyter notebooks and adding Amazon Q Developer in the command line in Jupyter notebooks and Code Editor. By integrating with Model Context Protocol (MCP) servers, Amazon Q Developer is aware of your SageMaker Unified Studio project resources, including data, compute, and code, and provides personalized assistance for data engineering and machine learning development work. These new capabilities provide highly relevant responses to assist with tasks like code refactoring, file modification, and troubleshooting. This helps data scientists and data engineers quickly set up their integrated development environments and work more efficiently while maintaining transparency into how the AI assistant is acting on their behalf. These features are available at no additional cost with the Amazon Q Developer Free Tier in all AWS Regions where Amazon SageMaker Unified Studio is available. To make even more use of these features, we recommend enabling Amazon Q Developer Pro. To do so, please refer to the documentation.  

Amazon CloudFront expands its IPv6 capabilities by introducing support for IPv6 connectivity to origin servers, allowing customers to implement end-to-end IPv6 content delivery for their web applications. Support for IPv6 origins enables customers to send IPv6 traffic all the way to their origins, allowing them to meet their architectural and regulatory requirements for IPv6 adoption. End-to-end IPv6 support improves network performance for end users connecting over IPv6 networks, and also removes concerns for IPv4 address exhaustion for origin infrastructure.

Previously, CloudFront only supported IPv4 connectivity to origins, despite accepting IPv6 connections from end users. Customers using CloudFront can configure their custom origins to use IPv4-only (default), IPv6-only, or dual-stack connectivity. When using dual-stack, CloudFront will automatically choose between IPv4 and IPv6 addresses to ensure even distribution of traffic towards origin over both.

Customers can configure IPv6 origins in all supported AWS Commercial Regions. Customers can configure IPv6-only or dual-stack origins with CloudFront, excluding Amazon S3 and VPC origins. To learn more IPv6 support with CloudFront, visit the CloudFront documentation.

 

​Amazon CloudFront expands its IPv6 capabilities by introducing support for IPv6 connectivity to origin servers, allowing customers to implement end-to-end IPv6 content delivery for their web applications. Support for IPv6 origins enables customers to send IPv6 traffic all the way to their origins, allowing them to meet their architectural and regulatory requirements for IPv6 adoption. End-to-end IPv6 support improves network performance for end users connecting over IPv6 networks, and also removes concerns for IPv4 address exhaustion for origin infrastructure. Previously, CloudFront only supported IPv4 connectivity to origins, despite accepting IPv6 connections from end users. Customers using CloudFront can configure their custom origins to use IPv4-only (default), IPv6-only, or dual-stack connectivity. When using dual-stack, CloudFront will automatically choose between IPv4 and IPv6 addresses to ensure even distribution of traffic towards origin over both. Customers can configure IPv6 origins in all supported AWS Commercial Regions. Customers can configure IPv6-only or dual-stack origins with CloudFront, excluding Amazon S3 and VPC origins. To learn more IPv6 support with CloudFront, visit the CloudFront documentation.  

Today, we are announcing a new capability that NetworkX now supports Neptune Analytics as a graph store. With this release, developers can continue to use familiar NetworkX APIs while automatically offloading graph algorithm workloads to Neptune’s scalable, high-performance analytics engine. This makes it simple to scale graph computations on demand without refactoring code, combining the ease of local development with the performance and elasticity of a fully managed AWS service.

Previously, when datasets grew beyond the limits of a local environment, users had to turn to third-party services—rebuilding their graph models to fit proprietary formats, exporting and importing data, and learning entirely new systems. With the new nx-neptune integration, developers only need an AWS account and credentials; the solution automatically handles graph data modeling, data movement (Zero-ETL), and infrastructure management. It provisions a Neptune Analytics instance, runs the requested algorithm, returns results directly to the user, and then tears down the infrastructure for a cost-effective, serverless-like experience—all without requiring the user to leave their familiar Python workflow.

NetworkX is a widely used open-source Python library for creating, analyzing, and visualizing complex graphs. It offers an extensive collection of graph algorithms and utilities, making it a popular choice among researchers, data scientists, and developers for prototyping and experimenting with graph-based applications. To learn more about the Neptune–NetworkX Integration, visit the documentation.

 

 

​Today, we are announcing a new capability that NetworkX now supports Neptune Analytics as a graph store. With this release, developers can continue to use familiar NetworkX APIs while automatically offloading graph algorithm workloads to Neptune’s scalable, high-performance analytics engine. This makes it simple to scale graph computations on demand without refactoring code, combining the ease of local development with the performance and elasticity of a fully managed AWS service. Previously, when datasets grew beyond the limits of a local environment, users had to turn to third-party services—rebuilding their graph models to fit proprietary formats, exporting and importing data, and learning entirely new systems. With the new nx-neptune integration, developers only need an AWS account and credentials; the solution automatically handles graph data modeling, data movement (Zero-ETL), and infrastructure management. It provisions a Neptune Analytics instance, runs the requested algorithm, returns results directly to the user, and then tears down the infrastructure for a cost-effective, serverless-like experience—all without requiring the user to leave their familiar Python workflow. NetworkX is a widely used open-source Python library for creating, analyzing, and visualizing complex graphs. It offers an extensive collection of graph algorithms and utilities, making it a popular choice among researchers, data scientists, and developers for prototyping and experimenting with graph-based applications. To learn more about the Neptune–NetworkX Integration, visit the documentation.
   

AWS WAF now includes 500 MB of CloudWatch Logs Vended Logs Ingestion for every 1 million WAF requests processed, at no additional cost. This helps customers better manage their WAF logging costs while maintaining comprehensive security visibility.

WAF logs in CloudWatch provide valuable insights for security analysis, compliance, and troubleshooting. Customers can leverage CloudWatch’s advanced analytics capabilities, including Log Insights queries, anomaly detection, and dashboards, to monitor and analyze their web application traffic patterns and security events. The included logs allocation is automatically applied based on WAF requests usage on your AWS bill at month end, making it easy to take advantage of the new pricing.

The free WAF logs allocation is across WAF specific Vended Logs to CloudWatch, S3, and Firehose. Usage beyond the included 500 MB per 1 million WAF requests will be charged at AWS WAF specific Vended Logs pricing in CloudWatch. For pricing details, please visit the AWS WAF pricing page.

To learn more about WAF logging capabilities and how to get started, visit the AWS WAF documentation.

 

​AWS WAF now includes 500 MB of CloudWatch Logs Vended Logs Ingestion for every 1 million WAF requests processed, at no additional cost. This helps customers better manage their WAF logging costs while maintaining comprehensive security visibility. WAF logs in CloudWatch provide valuable insights for security analysis, compliance, and troubleshooting. Customers can leverage CloudWatch’s advanced analytics capabilities, including Log Insights queries, anomaly detection, and dashboards, to monitor and analyze their web application traffic patterns and security events. The included logs allocation is automatically applied based on WAF requests usage on your AWS bill at month end, making it easy to take advantage of the new pricing. The free WAF logs allocation is across WAF specific Vended Logs to CloudWatch, S3, and Firehose. Usage beyond the included 500 MB per 1 million WAF requests will be charged at AWS WAF specific Vended Logs pricing in CloudWatch. For pricing details, please visit the AWS WAF pricing page. To learn more about WAF logging capabilities and how to get started, visit the AWS WAF documentation.  

Etiquetas:

• IA
• Salud
• Tecnología

The post El grupo Ribera utiliza tecnología de IA para ayudar a pacientes y médicos appeared first on Source LATAM.

 

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AWS Config now tracks resource tags for IAM policy resource types, enhancing the granularity of metadata you can capture to assess, audit, and evaluate configurations of your IAM policies.

With this enhancement, you can now track resource tags and their changes for IAM Policies directly in your Config recorder. This capability allows you to scope both Config-managed and custom rule evaluations based on resource tags, ensuring your IAM policies maintain desired configurations. Additionally, you can leverage Config aggregators to selectively aggregate IAM policies across multiple accounts using tags, streamlining your multi-account governance.

This feature is now available across all supported AWS Regions at no additional cost. Resource tags are automatically populated in Config when you record IAM policy resource types. For recording IAM policy resource type in your Config recorder, please refer our documentation.

 

​AWS Config now tracks resource tags for IAM policy resource types, enhancing the granularity of metadata you can capture to assess, audit, and evaluate configurations of your IAM policies. With this enhancement, you can now track resource tags and their changes for IAM Policies directly in your Config recorder. This capability allows you to scope both Config-managed and custom rule evaluations based on resource tags, ensuring your IAM policies maintain desired configurations. Additionally, you can leverage Config aggregators to selectively aggregate IAM policies across multiple accounts using tags, streamlining your multi-account governance. This feature is now available across all supported AWS Regions at no additional cost. Resource tags are automatically populated in Config when you record IAM policy resource types. For recording IAM policy resource type in your Config recorder, please refer our documentation.  

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 KB5063762 (RDS version 13.00.6465.1.v1), SQL Server 2017 CU31 KB5063759 (RDS version 14.00.3500.1.v1), SQL Server 2019 CU32 KB5063757 (RDS version 15.00.4440.1.v1) and SQL Server 2022 CU20 KB5063814 (RDS version 16.00.4210.1.v1).

The GDR updates address vulnerabilities described in CVE-2025-49758, CVE-2025-24999, CVE-2025-49759, CVE-2025-53727, and CVE-2025-47954. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5063762, KB5063759, KB5063757 and KB5063814. 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 KB5063762 (RDS version 13.00.6465.1.v1), SQL Server 2017 CU31 KB5063759 (RDS version 14.00.3500.1.v1), SQL Server 2019 CU32 KB5063757 (RDS version 15.00.4440.1.v1) and SQL Server 2022 CU20 KB5063814 (RDS version 16.00.4210.1.v1). The GDR updates address vulnerabilities described in CVE-2025-49758, CVE-2025-24999, CVE-2025-49759, CVE-2025-53727, and CVE-2025-47954. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5063762, KB5063759, KB5063757 and KB5063814. 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.  

AWS Elemental MediaConvert now integrates with Time-Addressable Media Store (TAMS), enabling customers to temporally reference and extract media asset segments. This capability allows MediaConvert customers to work more efficiently meet quick turn around deadlines. With TAMS integration, customers can extract highlights from live events for near real-time social media publishing, repurpose archived broadcast content into fresh programming or documentaries, and streamline media operations by connecting directly to existing broadcast infrastructure and content management systems.

This integration is designed for customers who operate their own TAMS servers—MediaConvert does not host or manage a TAMS instance. By leveraging your own TAMS deployment, MediaConvert can ingest time-based media segments on demand and use them as inputs in your encoding workflows. Whether you’re modernizing a legacy archive, building automation around editorial workflows, or enabling UGC teams to clip and publish with precision, the combination of MediaConvert and TAMS provides a powerful foundation for flexible, high-performance media processing at scale.

Please visit the TAMS specification and MediaConvert’s documentation for more information on this new feature.

 

​AWS Elemental MediaConvert now integrates with Time-Addressable Media Store (TAMS), enabling customers to temporally reference and extract media asset segments. This capability allows MediaConvert customers to work more efficiently meet quick turn around deadlines. With TAMS integration, customers can extract highlights from live events for near real-time social media publishing, repurpose archived broadcast content into fresh programming or documentaries, and streamline media operations by connecting directly to existing broadcast infrastructure and content management systems. This integration is designed for customers who operate their own TAMS servers—MediaConvert does not host or manage a TAMS instance. By leveraging your own TAMS deployment, MediaConvert can ingest time-based media segments on demand and use them as inputs in your encoding workflows. Whether you’re modernizing a legacy archive, building automation around editorial workflows, or enabling UGC teams to clip and publish with precision, the combination of MediaConvert and TAMS provides a powerful foundation for flexible, high-performance media processing at scale. Please visit the TAMS specification and MediaConvert’s documentation for more information on this new feature.  

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports the latest General Distribution Release (GDR) updates for Microsoft SQL Server. This includes support for Microsoft SQL Server 2019 CU32 KB5063757 (RDS version 15.00.4440.1.v1) and SQL Server 2022 CU20 KB5063814 (RDS version 16.00.4210.1.v1).

The GDR updates address vulnerabilities described in CVE-2025-49758, CVE-2025-24999, CVE-2025-49759, CVE-2025-53727, and CVE-2025-47954. For additional information on the improvements and fixes included in these updates, please see Microsoft documentation for KB5063757 and KB5063814. We recommend that you upgrade your Amazon RDS Custom 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 Custom User Guide.

 

​Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports the latest General Distribution Release (GDR) updates for Microsoft SQL Server. This includes support for Microsoft SQL Server 2019 CU32 KB5063757 (RDS version 15.00.4440.1.v1) and SQL Server 2022 CU20 KB5063814 (RDS version 16.00.4210.1.v1). The GDR updates address vulnerabilities described in CVE-2025-49758, CVE-2025-24999, CVE-2025-49759, CVE-2025-53727, and CVE-2025-47954. For additional information on the improvements and fixes included in these updates, please see Microsoft documentation for KB5063757 and KB5063814. We recommend that you upgrade your Amazon RDS Custom 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 Custom User Guide.  

Amazon CloudFront announces support for hybrid post-quantum key establishment across all existing Transport Layer Security (TLS) security policies, providing enhanced protection against future quantum computing threats for client-to-edge connections. Additionally, CloudFront launched a new TLS 1.3 only security policy that enhances TLS options between viewers and edge locations. These updates allow customers to leverage quantum-resistant encryption while having more flexibility in configuring their CloudFront distributions to meet specific security and compliance requirements.

The post-quantum cryptography (PQC) capabilities are automatically enabled for client-to-edge connections, providing future-proof encryption that ensures long-term data security and regulatory compliance readiness. PQC support is available on all existing security policies by default, requiring no customer configuration. The new TLS1.3_2025 policy, which supports TLS 1.3 only, enables customers to leverage the latest TLS protocol, which provides improved security and performance compared to earlier TLS versions. This is particularly useful for organizations that enforce using the most up-to-date security standards.

These PQC capabilities and new security policy are available in all CloudFront edge locations. There are no additional charges for using PQC or the TLS1.3_2025 policy. To learn more about Post Quantum Cryptography and this new TLS policy and how to implement them in your CloudFront distributions, visit the CloudFront documentation. CloudFront documentation.

 

​Amazon CloudFront announces support for hybrid post-quantum key establishment across all existing Transport Layer Security (TLS) security policies, providing enhanced protection against future quantum computing threats for client-to-edge connections. Additionally, CloudFront launched a new TLS 1.3 only security policy that enhances TLS options between viewers and edge locations. These updates allow customers to leverage quantum-resistant encryption while having more flexibility in configuring their CloudFront distributions to meet specific security and compliance requirements. The post-quantum cryptography (PQC) capabilities are automatically enabled for client-to-edge connections, providing future-proof encryption that ensures long-term data security and regulatory compliance readiness. PQC support is available on all existing security policies by default, requiring no customer configuration. The new TLS1.3_2025 policy, which supports TLS 1.3 only, enables customers to leverage the latest TLS protocol, which provides improved security and performance compared to earlier TLS versions. This is particularly useful for organizations that enforce using the most up-to-date security standards. These PQC capabilities and new security policy are available in all CloudFront edge locations. There are no additional charges for using PQC or the TLS1.3_2025 policy. To learn more about Post Quantum Cryptography and this new TLS policy and how to implement them in your CloudFront distributions, visit the CloudFront documentation. CloudFront documentation.