Amazon Web Services, Inc. now supports China UnionPay credit cards for creating new AWS accounts, eliminating the need for international credit cards for customers in China.

To use China UnionPay for creating your AWS account, enter your address and billing country in China, then provide your local China UnionPay credit card details and verify your personal identity or business license. All subsequent AWS charges will be billed in Chinese Yuan currency, providing convenient payment experience for customers in China.

To get started, select China UnionPay as your payment method when creating a new AWS account. For more information on using China UnionPay credit cards with AWS, visit Set up a Chinese yuan credit card.
 

​Amazon Web Services, Inc. now supports China UnionPay credit cards for creating new AWS accounts, eliminating the need for international credit cards for customers in China. To use China UnionPay for creating your AWS account, enter your address and billing country in China, then provide your local China UnionPay credit card details and verify your personal identity or business license. All subsequent AWS charges will be billed in Chinese Yuan currency, providing convenient payment experience for customers in China. To get started, select China UnionPay as your payment method when creating a new AWS account. For more information on using China UnionPay credit cards with AWS, visit Set up a Chinese yuan credit card.    

Amazon AppStream 2.0 improves the end-user experience by adding support for certificate-based authentication (CBA) on multi-session fleets running the Microsoft Windows operating system and joined to an Active Directory. This functionality helps administrators to leverage the cost benefits of the multi-session model while providing an enhanced end-user experience. By combining these enhancements with the existing advantages of multi-session fleets, AppStream 2.0 offers a solution that helps balance cost-efficiency and user satisfaction.

By using certificate-based authentication, you can rely on the security and logon experience features of your SAML 2.0 identity provider, such as passwordless authentication, to access AppStream 2.0 resources. Certificate-based authentication with AppStream 2.0 enables a single sign-on logon experience to access domain-joined desktop and application streaming sessions without separate password prompts for Active Directory.

This feature is available at no additional cost in all the AWS Regions where Amazon AppStream 2.0 is available. AppStream 2.0 offers pay-as-you go pricing. To get started with AppStream 2.0, see Getting Started with Amazon AppStream 2.0.

To enable this feature for your users, you must use an AppStream 2.0 image that uses AppStream 2.0 agent released on or after February 7, 2025 or your image is using Managed AppStream 2.0 image updates released on or after February 11, 2025.
 

​Amazon AppStream 2.0 improves the end-user experience by adding support for certificate-based authentication (CBA) on multi-session fleets running the Microsoft Windows operating system and joined to an Active Directory. This functionality helps administrators to leverage the cost benefits of the multi-session model while providing an enhanced end-user experience. By combining these enhancements with the existing advantages of multi-session fleets, AppStream 2.0 offers a solution that helps balance cost-efficiency and user satisfaction. By using certificate-based authentication, you can rely on the security and logon experience features of your SAML 2.0 identity provider, such as passwordless authentication, to access AppStream 2.0 resources. Certificate-based authentication with AppStream 2.0 enables a single sign-on logon experience to access domain-joined desktop and application streaming sessions without separate password prompts for Active Directory. This feature is available at no additional cost in all the AWS Regions where Amazon AppStream 2.0 is available. AppStream 2.0 offers pay-as-you go pricing. To get started with AppStream 2.0, see Getting Started with Amazon AppStream 2.0. To enable this feature for your users, you must use an AppStream 2.0 image that uses AppStream 2.0 agent released on or after February 7, 2025 or your image is using Managed AppStream 2.0 image updates released on or after February 11, 2025.    

We are excited to announce the general availability of fine-grained data access control (FGAC) via AWS Lake Formation for Apache Spark with Amazon EMR on EKS. This enables you to enforce full FGAC policies (database, table, column, row, and cell-level) defined in Lake Formation for your data lake tables from EMR on EKS Spark jobs. We are also sharing the general availability of Glue Data Catalog views with EMR on EKS for Spark workflows.

Lake Formation simplifies building, securing, and managing data lakes by allowing you to define fine-grained access controls through grant and revoke statements, similar to RDBMS. The same Lake Formation rules now apply to Spark jobs on EMR on EKS for Hudi, Delta Lake, and Iceberg table formats, further simplifying data lake security and governance.

AWS Glue Data Catalog views with EMR on EKS allows customers to create views from Spark jobs that can be queried from multiple engines without requiring access to referenced tables. Administrators can control underlying data access using the rich SQL dialect provided by EMR on EKS Spark jobs. Access is managed with AWS Lake Formation permissions, including named resource grants, data filters, and lake formation tags. All requests are logged in AWS CloudTrail.

Fine-grained access control for Apache Spark batch jobs on EMR on EKS is available with the EMR 7.7 release in all regions where EMR on EKS is available. To get started, see Using AWS Lake Formation with Amazon EMR on EKS.
 

​We are excited to announce the general availability of fine-grained data access control (FGAC) via AWS Lake Formation for Apache Spark with Amazon EMR on EKS. This enables you to enforce full FGAC policies (database, table, column, row, and cell-level) defined in Lake Formation for your data lake tables from EMR on EKS Spark jobs. We are also sharing the general availability of Glue Data Catalog views with EMR on EKS for Spark workflows.
Lake Formation simplifies building, securing, and managing data lakes by allowing you to define fine-grained access controls through grant and revoke statements, similar to RDBMS. The same Lake Formation rules now apply to Spark jobs on EMR on EKS for Hudi, Delta Lake, and Iceberg table formats, further simplifying data lake security and governance. AWS Glue Data Catalog views with EMR on EKS allows customers to create views from Spark jobs that can be queried from multiple engines without requiring access to referenced tables. Administrators can control underlying data access using the rich SQL dialect provided by EMR on EKS Spark jobs. Access is managed with AWS Lake Formation permissions, including named resource grants, data filters, and lake formation tags. All requests are logged in AWS CloudTrail. Fine-grained access control for Apache Spark batch jobs on EMR on EKS is available with the EMR 7.7 release in all regions where EMR on EKS is available. To get started, see Using AWS Lake Formation with Amazon EMR on EKS.    

Amazon Managed Streaming for Apache Kafka (Amazon MSK) now supports Apache Kafka version 3.8. You can now create new clusters using version 3.8 with either KRAFT or ZooKeeper mode for metadata management or upgrade your existing ZooKeeper based clusters to use version 3.8. Apache Kafka version 3.8 includes several bug fixes and new features that improve performance. Key new features include support for compression level configuration. This allows you to further optimize your performance when using compression types such as lz4, zstd and gzip, by allowing you to change the default compression level. For more details and a complete list of improvements and bug fixes, see the Apache Kafka release notes for version 3.8.

Amazon MSK is a fully managed service for Apache Kafka and Kafka Connect that makes it easier for you to build and run applications that use Apache Kafka as a data store. Amazon MSK is compatible with Apache Kafka, which enables you to quickly migrate your existing Apache Kafka workloads to Amazon MSK with confidence or build new ones from scratch. With Amazon MSK, you can spend more time innovating on streaming applications and less time managing Apache Kafka clusters. To learn how to get started, see the Amazon MSK Developer Guide.

Support for Apache Kafka version 3.8 is offered in all AWS regions where Amazon MSK is available.

​Amazon Managed Streaming for Apache Kafka (Amazon MSK) now supports Apache Kafka version 3.8. You can now create new clusters using version 3.8 with either KRAFT or ZooKeeper mode for metadata management or upgrade your existing ZooKeeper based clusters to use version 3.8. Apache Kafka version 3.8 includes several bug fixes and new features that improve performance. Key new features include support for compression level configuration. This allows you to further optimize your performance when using compression types such as lz4, zstd and gzip, by allowing you to change the default compression level. For more details and a complete list of improvements and bug fixes, see the Apache Kafka release notes for version 3.8. Amazon MSK is a fully managed service for Apache Kafka and Kafka Connect that makes it easier for you to build and run applications that use Apache Kafka as a data store. Amazon MSK is compatible with Apache Kafka, which enables you to quickly migrate your existing Apache Kafka workloads to Amazon MSK with confidence or build new ones from scratch. With Amazon MSK, you can spend more time innovating on streaming applications and less time managing Apache Kafka clusters. To learn how to get started, see the Amazon MSK Developer Guide. Support for Apache Kafka version 3.8 is offered in all AWS regions where Amazon MSK is available.  

AWS CodePipeline introduces a new action to deploy to Amazon Elastic Compute Cloud (EC2). This action enables you to easily deploy your application to a group of EC2 instances behind load balancers.

Previously, if you wanted to deploy to EC2 instances, you had to use CodeDeploy with an AppSpec file to configure the deployment. Now, you can simply use this new EC2 deploy action in your pipeline to deploy to EC2 instances, without the necessity of managing CodeDeploy resources. This streamlined approach reduces your operational overhead and simplifies your deployment process.

To learn more about using the EC2 deploy action in your pipeline, visit our tutorial and documentation. For more information about AWS CodePipeline, visit our product page. This new action is available in all regions where AWS CodePipeline is supported, except the AWS GovCloud (US) Regions and the China Regions.
 

​AWS CodePipeline introduces a new action to deploy to Amazon Elastic Compute Cloud (EC2). This action enables you to easily deploy your application to a group of EC2 instances behind load balancers. Previously, if you wanted to deploy to EC2 instances, you had to use CodeDeploy with an AppSpec file to configure the deployment. Now, you can simply use this new EC2 deploy action in your pipeline to deploy to EC2 instances, without the necessity of managing CodeDeploy resources. This streamlined approach reduces your operational overhead and simplifies your deployment process. To learn more about using the EC2 deploy action in your pipeline, visit our tutorial and documentation. For more information about AWS CodePipeline, visit our product page. This new action is available in all regions where AWS CodePipeline is supported, except the AWS GovCloud (US) Regions and the China Regions.    

Amazon Relational Database Service (RDS) for PostgreSQL now supports the latest minor versions 17.4, 16.8, 15.12, 14.17, and 13.20. Please note, this release supports the versions released by the PostgreSQL community on February, 20,2025 to address the regression that was part of the February 13, 2025 release. We recommend that you upgrade to the latest minor versions to fix known security vulnerabilities in prior versions of PostgreSQL, and to benefit from the bug fixes added by the PostgreSQL community.

You can use automatic minor version upgrades to automatically upgrade your databases to more recent minor versions during scheduled maintenance windows. You can also use Amazon RDS Blue/Green deployments for RDS for PostgreSQL using physical replication for your minor version upgrades. Learn more about upgrading your database instances, including automatic minor version upgrades and Blue/Green Deployments in the Amazon RDS User Guide.

Amazon RDS for PostgreSQL makes it simple to set up, operate, and scale PostgreSQL deployments in the cloud. See Amazon RDS for PostgreSQL Pricing for pricing details and regional availability. Create or update a fully managed Amazon RDS database in the Amazon RDS Management Console.
 

​Amazon Relational Database Service (RDS) for PostgreSQL now supports the latest minor versions 17.4, 16.8, 15.12, 14.17, and 13.20. Please note, this release supports the versions released by the PostgreSQL community on February, 20,2025 to address the regression that was part of the February 13, 2025 release. We recommend that you upgrade to the latest minor versions to fix known security vulnerabilities in prior versions of PostgreSQL, and to benefit from the bug fixes added by the PostgreSQL community. You can use automatic minor version upgrades to automatically upgrade your databases to more recent minor versions during scheduled maintenance windows. You can also use Amazon RDS Blue/Green deployments for RDS for PostgreSQL using physical replication for your minor version upgrades. Learn more about upgrading your database instances, including automatic minor version upgrades and Blue/Green Deployments in the Amazon RDS User Guide. Amazon RDS for PostgreSQL makes it simple to set up, operate, and scale PostgreSQL deployments in the cloud. See Amazon RDS for PostgreSQL Pricing for pricing details and regional availability. Create or update a fully managed Amazon RDS database in the Amazon RDS Management Console.    

Amazon Database Migration Service (DMS) now supports the Multi-ENI networking model and Credentials Vending System for DMS Homogenous Migrations.

Customers can now choose the Multi-ENI connection type and use the Credentials Vending System, providing a simplified networking configuration experience for secure connectivity to their on-premises database instances.

For information see documentation for AWS DMS Homogeneous Migrations. For AWS DMS regional availability, please refer to the AWS Region Table.
 

​Amazon Database Migration Service (DMS) now supports the Multi-ENI networking model and Credentials Vending System for DMS Homogenous Migrations. Customers can now choose the Multi-ENI connection type and use the Credentials Vending System, providing a simplified networking configuration experience for secure connectivity to their on-premises database instances.
For information see documentation for AWS DMS Homogeneous Migrations. For AWS DMS regional availability, please refer to the AWS Region Table.    

The post Desglose de datos de IA: manejar negocios riesgosos en la mitad del tiempo appeared first on Source LATAM.

​The post Desglose de datos de IA: manejar negocios riesgosos en la mitad del tiempo appeared first on Source LATAM.  

Starting today, the Amazon EC2 G6e instances powered by NVIDIA L40S Tensor Core GPUs is now available in Europe (Stockholm) region. G6e instances can be used for a wide range of machine learning and spatial computing use cases.

Customers can use G6e instances to deploy large language models (LLMs) with up to 13B parameters and diffusion models for generating images, video, and audio. Additionally, the G6e instances will unlock customers’ ability to create larger, more immersive 3D simulations and digital twins for spatial computing workloads. G6e instances feature up to 8 NVIDIA L40S Tensor Core GPUs with 48 GB of memory per GPU and third generation AMD EPYC processors. They also support up to 192 vCPUs, up to 400 Gbps of network bandwidth, up to 1.536 TB of system memory, and up to 7.6 TB of local NVMe SSD storage. Developers can run AI inference workloads on G6e instances using AWS Deep Learning AMIs, AWS Deep Learning Containers, or managed services such as Amazon Elastic Kubernetes Service (Amazon EKS), AWS Batch, and Amazon SageMaker.

Amazon EC2 G6e instances are available today in the AWS US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Tokyo), and Europe (Frankfurt, Spain, Stockholm) regions. Customers can purchase G6e instances as On-Demand Instances, Reserved Instances, Spot Instances, or as part of Savings Plans.

To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit the G6e instance page.

​Starting today, the Amazon EC2 G6e instances powered by NVIDIA L40S Tensor Core GPUs is now available in Europe (Stockholm) region. G6e instances can be used for a wide range of machine learning and spatial computing use cases. Customers can use G6e instances to deploy large language models (LLMs) with up to 13B parameters and diffusion models for generating images, video, and audio. Additionally, the G6e instances will unlock customers’ ability to create larger, more immersive 3D simulations and digital twins for spatial computing workloads. G6e instances feature up to 8 NVIDIA L40S Tensor Core GPUs with 48 GB of memory per GPU and third generation AMD EPYC processors. They also support up to 192 vCPUs, up to 400 Gbps of network bandwidth, up to 1.536 TB of system memory, and up to 7.6 TB of local NVMe SSD storage. Developers can run AI inference workloads on G6e instances using AWS Deep Learning AMIs, AWS Deep Learning Containers, or managed services such as Amazon Elastic Kubernetes Service (Amazon EKS), AWS Batch, and Amazon SageMaker. Amazon EC2 G6e instances are available today in the AWS US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Tokyo), and Europe (Frankfurt, Spain, Stockholm) regions. Customers can purchase G6e instances as On-Demand Instances, Reserved Instances, Spot Instances, or as part of Savings Plans. To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit the G6e instance page.  

Today, AWS announces the introduction of Backup Payment Methods for AWS invoices in all commercial AWS Regions. This feature enables customers to set up alternate payment methods that will be automatically charged for their invoices if the primary payment method fails. This will help customers make timely invoice payments without the need for manual intervention or last-minute payment updates.

There are several benefits this feature brings to AWS customers. Firstly, it reduces the risk of missed or late payments due to issues with the primary payment method. Backup payment method provides peace of mind, knowing that there’s a fallback payment method in place for invoice payments, reducing the risk of failed invoice payments. This can help maintain uninterrupted access to AWS services and avoid potential service disruptions. Secondly, it saves time and effort for customers by eliminating the need to manually update payment details or coordinate with their finance and accounting teams to settle invoices when the primary method fails.

To get started with Backup Payment Methods, customers can access their AWS Console and navigate to the billing section. From there, they can set their preferences for backup payment methods at any time. For more information on how to set up and manage Backup Payment Methods, please visit the AWS Billing and Cost Management documentation page or contact your AWS account representative.

​Today, AWS announces the introduction of Backup Payment Methods for AWS invoices in all commercial AWS Regions. This feature enables customers to set up alternate payment methods that will be automatically charged for their invoices if the primary payment method fails. This will help customers make timely invoice payments without the need for manual intervention or last-minute payment updates. There are several benefits this feature brings to AWS customers. Firstly, it reduces the risk of missed or late payments due to issues with the primary payment method. Backup payment method provides peace of mind, knowing that there’s a fallback payment method in place for invoice payments, reducing the risk of failed invoice payments. This can help maintain uninterrupted access to AWS services and avoid potential service disruptions. Secondly, it saves time and effort for customers by eliminating the need to manually update payment details or coordinate with their finance and accounting teams to settle invoices when the primary method fails. To get started with Backup Payment Methods, customers can access their AWS Console and navigate to the billing section. From there, they can set their preferences for backup payment methods at any time. For more information on how to set up and manage Backup Payment Methods, please visit the AWS Billing and Cost Management documentation page or contact your AWS account representative.