Today, AWS Backup announces additional options to assign resources to a backup policy on AWS Organizations in the AWS GovCloud (US) Regions. Customers can now select specific resources by resource type and exclude them based on resource type or tag. They can also use the combination of multiple tags within the same resource selection.

With additional options to select resources, customers can implement flexible backup strategies across their organizations by combining multiple resource types and/or tags. They can also exclude resources they do not want to back up using resource type or tag, optimizing cost on non-critical resources.

To get started, use your AWS Organizations’ management account to create or edit an AWS Backup policy in the AWS GovCloud (US) Regions. Then, create or modify a resource selection using the AWS Organizations’ API, CLI, or JSON editor in either the AWS Organizations or AWS Backup console. For more information, visit our documentation and launch blog.

 

​Today, AWS Backup announces additional options to assign resources to a backup policy on AWS Organizations in the AWS GovCloud (US) Regions. Customers can now select specific resources by resource type and exclude them based on resource type or tag. They can also use the combination of multiple tags within the same resource selection. With additional options to select resources, customers can implement flexible backup strategies across their organizations by combining multiple resource types and/or tags. They can also exclude resources they do not want to back up using resource type or tag, optimizing cost on non-critical resources. To get started, use your AWS Organizations’ management account to create or edit an AWS Backup policy in the AWS GovCloud (US) Regions. Then, create or modify a resource selection using the AWS Organizations’ API, CLI, or JSON editor in either the AWS Organizations or AWS Backup console. For more information, visit our documentation and launch blog.  

Amazon Q in Connect now supports 64 languages for agent assistance capabilities. Customer service agents can now chat with Q for assistance in their native language and Q will provide answers, knowledge article links, and recommended step-by-step guides in said language. New languages supported include: Chinese, French, French (Canadian), Italian, Japanese, Korean, Malay, Portuguese, Spanish, Swedish, and Tagalog.

For the full list of supported languages, please see the Languages supported by Amazon Connect features. For region availability, please see the availability of Amazon Connect features by Region. To learn more about Amazon Q in Connect, please visit the website or see the help documentation.

 

​Amazon Q in Connect now supports 64 languages for agent assistance capabilities. Customer service agents can now chat with Q for assistance in their native language and Q will provide answers, knowledge article links, and recommended step-by-step guides in said language. New languages supported include: Chinese, French, French (Canadian), Italian, Japanese, Korean, Malay, Portuguese, Spanish, Swedish, and Tagalog. For the full list of supported languages, please see the Languages supported by Amazon Connect features. For region availability, please see the availability of Amazon Connect features by Region. To learn more about Amazon Q in Connect, please visit the website or see the help documentation.  

AWS Glue Data Catalog now offers advanced automatic optimization for Apache Iceberg tables. This update includes supporting compaction of delete files, nested data types, partial progress commits, and partition evolution support, making it easier to maintain consistently performant transactional data lakes. These features address challenges faced by customers with streaming data continuously ingested into Apache Iceberg tables, resulting in a large number of delete files that track changes in data files.

With this new capability, Glue Data Catalog constantly monitors table partitions for positional and equality delete files, initiates the compaction process, and regularly commits partial progress to reduce conflicts. Glue Catalog optimizers now support schema evolution as you reorder or rename columns as well as partition spec evolution. In addition, Glue Catalog has expanded support for heavily nested complex data and support for parquet compression codecs – zstd, brotli, lz4, gzip, snappy. Enabling automatic compaction reduces delete files and metadata overhead on your Iceberg tables and improves query performance. These new features are automatically applied to existing and new Glue Catalog optimizers.

In addition to the AWS console, customers can also use the AWS CLI or AWS SDKs to automate optimization for Apache Iceberg tables. The feature is available in 14 AWS regions US East (N. Virginia, Ohio), US West (Oregon), Europe (Ireland, London, Frankfurt, Stockholm), Canada (central), Asia Pacific (Tokyo, Seoul, Mumbai, Singapore, Sydney), South America (São Paulo). To learn more, read the blog, and visit the AWS Glue Data Catalog documentation.
 

 

​AWS Glue Data Catalog now offers advanced automatic optimization for Apache Iceberg tables. This update includes supporting compaction of delete files, nested data types, partial progress commits, and partition evolution support, making it easier to maintain consistently performant transactional data lakes. These features address challenges faced by customers with streaming data continuously ingested into Apache Iceberg tables, resulting in a large number of delete files that track changes in data files. With this new capability, Glue Data Catalog constantly monitors table partitions for positional and equality delete files, initiates the compaction process, and regularly commits partial progress to reduce conflicts. Glue Catalog optimizers now support schema evolution as you reorder or rename columns as well as partition spec evolution. In addition, Glue Catalog has expanded support for heavily nested complex data and support for parquet compression codecs – zstd, brotli, lz4, gzip, snappy. Enabling automatic compaction reduces delete files and metadata overhead on your Iceberg tables and improves query performance. These new features are automatically applied to existing and new Glue Catalog optimizers. In addition to the AWS console, customers can also use the AWS CLI or AWS SDKs to automate optimization for Apache Iceberg tables. The feature is available in 14 AWS regions US East (N. Virginia, Ohio), US West (Oregon), Europe (Ireland, London, Frankfurt, Stockholm), Canada (central), Asia Pacific (Tokyo, Seoul, Mumbai, Singapore, Sydney), South America (São Paulo). To learn more, read the blog, and visit the AWS Glue Data Catalog documentation.    

Today, AWS announces Internet Protocol version 6 (IPv6) support for Recycle Bin, a data recovery feature that enables restoration of accidental deleted Amazon EBS Snapshots and EBS-backed AMIs. You now have the option of using IPv6 addresses for new and existing endpoints. By moving to IPv6, you can simplify your network stack by running dual-stack Recycle Bin endpoints on a network that supports both IPv4 and IPv6.

Customers can create rules in Recycle Bin to retain deleted EBS Snapshots or deregistered EBS-backed AMI for a specific retention time. This capability allows you to immediately recover your deleted snapshots or EBS-backed AMIs when you create volumes or launch instance without a need to roll back to a snapshot or AMI from an earlier point in time. Recovered snapshots or AMIs retain attributes such as prior to deletion and can be used immediately for creating volumes or launching instances. Snapshots and AMIs that are not recovered from the Recycle Bin are permanently deleted upon expiration of the retention time.

Recycle Bin with IPv6 and AWS PrivateLink is now available in all AWS Regions including the AWS GovCloud (US) Regions.

To learn more about configuring Recycle Bin endpoints for IPv6, please refer to our documentation.
 

 

​Today, AWS announces Internet Protocol version 6 (IPv6) support for Recycle Bin, a data recovery feature that enables restoration of accidental deleted Amazon EBS Snapshots and EBS-backed AMIs. You now have the option of using IPv6 addresses for new and existing endpoints. By moving to IPv6, you can simplify your network stack by running dual-stack Recycle Bin endpoints on a network that supports both IPv4 and IPv6. Customers can create rules in Recycle Bin to retain deleted EBS Snapshots or deregistered EBS-backed AMI for a specific retention time. This capability allows you to immediately recover your deleted snapshots or EBS-backed AMIs when you create volumes or launch instance without a need to roll back to a snapshot or AMI from an earlier point in time. Recovered snapshots or AMIs retain attributes such as prior to deletion and can be used immediately for creating volumes or launching instances. Snapshots and AMIs that are not recovered from the Recycle Bin are permanently deleted upon expiration of the retention time. Recycle Bin with IPv6 and AWS PrivateLink is now available in all AWS Regions including the AWS GovCloud (US) Regions. To learn more about configuring Recycle Bin endpoints for IPv6, please refer to our documentation.    

Amazon AppStream 2.0 extends native client support to macOS. Users can now access AppStream 2.0 streamed applications through a web browser, the AppStream 2.0 client for Windows, or AppStream 2.0 client for macOS. This additional macOS support provides more flexibility and platform options for users needing access to streamed applications and desktops.

The AppStream 2.0 client for macOS is an application you install on your Mac to access AppStream streaming sessions. The client provides enhanced capabilities and user experience. It supports two monitors with 4K resolution, and the ability to connect up to four monitors, leveraging multi-monitor layouts. Users can use keyboard shortcuts and relative mouse mode for a more natural feel.

Using macOS client you can also stream over UDP which offers a more responsive streaming quality in sub-optimal network conditions, with higher round trip latency. Additionally, to assist with troubleshooting macOS client issues, you can enable client automatic logging.

The macOS client works with Windows, Red Hat Enterprise Linux, Rocky Linux 8 based AppStream 2.0 applications and fleets. To run the AppStream 2.0 macOS client, ensure that your Mac is running macOS 13 (Ventura), macOS 14 (Sonoma), or macOS 15 (Sequoia).

To download and install the AppStream 2.0 macOS client application, visit Amazon AppStream 2.0 Downloads, choose the macOS link, download and install the application. Verify that the Amazon AppStream 2.0 client application icon appears on your Mac Launchpad and start streaming.
 

 

​Amazon AppStream 2.0 extends native client support to macOS. Users can now access AppStream 2.0 streamed applications through a web browser, the AppStream 2.0 client for Windows, or AppStream 2.0 client for macOS. This additional macOS support provides more flexibility and platform options for users needing access to streamed applications and desktops. The AppStream 2.0 client for macOS is an application you install on your Mac to access AppStream streaming sessions. The client provides enhanced capabilities and user experience. It supports two monitors with 4K resolution, and the ability to connect up to four monitors, leveraging multi-monitor layouts. Users can use keyboard shortcuts and relative mouse mode for a more natural feel. Using macOS client you can also stream over UDP which offers a more responsive streaming quality in sub-optimal network conditions, with higher round trip latency. Additionally, to assist with troubleshooting macOS client issues, you can enable client automatic logging. The macOS client works with Windows, Red Hat Enterprise Linux, Rocky Linux 8 based AppStream 2.0 applications and fleets. To run the AppStream 2.0 macOS client, ensure that your Mac is running macOS 13 (Ventura), macOS 14 (Sonoma), or macOS 15 (Sequoia). To download and install the AppStream 2.0 macOS client application, visit Amazon AppStream 2.0 Downloads, choose the macOS link, download and install the application. Verify that the Amazon AppStream 2.0 client application icon appears on your Mac Launchpad and start streaming.    

AWS Config now supports 3 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources.

With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available across the AWS Config feature set, including Config rules, Config aggregators, and Config advanced queries.

You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported services are available:

• AWS::Cognito::IdentityPool
• AWS::MediaConnect::Gateway
• AWS::OpenSearchServerless::VpcEndpoint

To view the complete list of AWS Config supported resource types, see supported resource types page.

 

​AWS Config now supports 3 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources. With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available across the AWS Config feature set, including Config rules, Config aggregators, and Config advanced queries. You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported services are available:

AWS::Cognito::IdentityPool
AWS::MediaConnect::Gateway
AWS::OpenSearchServerless::VpcEndpoint

To view the complete list of AWS Config supported resource types, see supported resource types page.  

Amazon Elastic Container Services (Amazon ECS) now allows you to perform network fault injection experiments on your applications deployed on AWS Fargate. Fault injection experiments create disruptions to test how your applications behave, helping you improve application performance, observability, and resilience. AWS Fault Injection Service (AWS FIS) now supports 6 actions for ECS on both EC2 and Fargate: network latency, network blackhole, network packet loss, CPU stress, I/O stress, and kill process.

Developers and operators can now verify the response of their application to potential network errors, some of which may also be required for regulatory compliance. By reproducing network behaviors that may cause applications to fail, you can identify gaps in application configurations, monitoring, alarms, and operational response. Amazon ECS is introducing the ability to opt-in to allow tasks to use a fault injector such as AWS FIS to perform network experiments for increasing network latency, increasing packet loss, and blackhole port testing (dropping inbound or outbound traffic) to test how your applications perform, in addition to existing resource stress experiments.

The new experience is now automatically enabled in all AWS Regions and integration with the AWS Fault Injection Service in those regions where AWS FIS is available.

For more details, go to Amazon ECS fault Injection documentation and the AWS FIS user guide.
 

 

​Amazon Elastic Container Services (Amazon ECS) now allows you to perform network fault injection experiments on your applications deployed on AWS Fargate. Fault injection experiments create disruptions to test how your applications behave, helping you improve application performance, observability, and resilience. AWS Fault Injection Service (AWS FIS) now supports 6 actions for ECS on both EC2 and Fargate: network latency, network blackhole, network packet loss, CPU stress, I/O stress, and kill process. Developers and operators can now verify the response of their application to potential network errors, some of which may also be required for regulatory compliance. By reproducing network behaviors that may cause applications to fail, you can identify gaps in application configurations, monitoring, alarms, and operational response. Amazon ECS is introducing the ability to opt-in to allow tasks to use a fault injector such as AWS FIS to perform network experiments for increasing network latency, increasing packet loss, and blackhole port testing (dropping inbound or outbound traffic) to test how your applications perform, in addition to existing resource stress experiments. The new experience is now automatically enabled in all AWS Regions and integration with the AWS Fault Injection Service in those regions where AWS FIS is available. For more details, go to Amazon ECS fault Injection documentation and the AWS FIS user guide.    

Amazon AppStream 2.0 now offers support for Rocky Linux from CIQ, enabling ISVs and central IT organizations to stream from an RPM Package Manager (RPM) compatible environment optimized for running compute-intensive applications while leveraging the flexibility, scalability, and cost-effectiveness of the AWS Cloud. With this launch, customers have the flexibility to choose from a broader set of operating systems including Rocky Linux, Red Hat Enterprise Linux (RHEL), and Microsoft Windows.

This launch enables organizations to stream Rocky Linux apps from AppStream 2.0, helping to accelerate time to market, scaling resources up or down with demand, and managing the entire fleet centrally through the AWS Management Console. Rocky Linux on AppStream 2.0 also enables traditional desktop apps to be converted to SaaS delivery without the cost of refactoring, while pay-as-you-go billing and license-included images ensure you only pay for the resources you use.

Rocky Linux-based AppStream 2.0 instances are supported in all AWS Regions where AppStream 2.0 is available and use per second billing (with a minimum of 15 minutes). For more information, see Amazon AppStream 2.0 pricing.

To get started with Rocky Linux on AppStream 2.0, sign in to the AWS Management Console and open the AppStream 2.0 Console. For more information, see the Amazon AppStream 2.0 Administrator Guide.
 

 

​Amazon AppStream 2.0 now offers support for Rocky Linux from CIQ, enabling ISVs and central IT organizations to stream from an RPM Package Manager (RPM) compatible environment optimized for running compute-intensive applications while leveraging the flexibility, scalability, and cost-effectiveness of the AWS Cloud. With this launch, customers have the flexibility to choose from a broader set of operating systems including Rocky Linux, Red Hat Enterprise Linux (RHEL), and Microsoft Windows. This launch enables organizations to stream Rocky Linux apps from AppStream 2.0, helping to accelerate time to market, scaling resources up or down with demand, and managing the entire fleet centrally through the AWS Management Console. Rocky Linux on AppStream 2.0 also enables traditional desktop apps to be converted to SaaS delivery without the cost of refactoring, while pay-as-you-go billing and license-included images ensure you only pay for the resources you use. Rocky Linux-based AppStream 2.0 instances are supported in all AWS Regions where AppStream 2.0 is available and use per second billing (with a minimum of 15 minutes). For more information, see Amazon AppStream 2.0 pricing. To get started with Rocky Linux on AppStream 2.0, sign in to the AWS Management Console and open the AppStream 2.0 Console. For more information, see the Amazon AppStream 2.0 Administrator Guide.    

Amazon RDS for MySQL now supports MySQL Innovation Release 9.1 in the Amazon RDS Database Preview Environment, allowing you to evaluate the latest Innovation Release on Amazon RDS for MySQL. You can deploy MySQL 9.1 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database, making it simpler to set up, operate, and monitor databases.

MySQL 9.1 is the latest Innovation Release from the MySQL community. MySQL Innovation releases include bug fixes, security patches, as well as new features. MySQL Innovation releases are supported by the community until the next major & minor release, whereas MySQL Long Term Support (LTS) Releases, such as MySQL 8.0 and MySQL 8.4, are supported by the community for up to eight years. Please refer to the MySQL 9.1 release notes for more details about this release.

The Amazon RDS Database Preview Environment supports both Single-AZ and Multi-AZ deployments on the latest generation of instance classes. Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment.

Amazon RDS Database Preview Environment database instances are priced the same as production RDS instances created in the US East (Ohio) Region.

 

​Amazon RDS for MySQL now supports MySQL Innovation Release 9.1 in the Amazon RDS Database Preview Environment, allowing you to evaluate the latest Innovation Release on Amazon RDS for MySQL. You can deploy MySQL 9.1 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database, making it simpler to set up, operate, and monitor databases. MySQL 9.1 is the latest Innovation Release from the MySQL community. MySQL Innovation releases include bug fixes, security patches, as well as new features. MySQL Innovation releases are supported by the community until the next major & minor release, whereas MySQL Long Term Support (LTS) Releases, such as MySQL 8.0 and MySQL 8.4, are supported by the community for up to eight years. Please refer to the MySQL 9.1 release notes for more details about this release. The Amazon RDS Database Preview Environment supports both Single-AZ and Multi-AZ deployments on the latest generation of instance classes. Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. Amazon RDS Database Preview Environment database instances are priced the same as production RDS instances created in the US East (Ohio) Region.  

Stability AI’s Stable Diffusion 3.5 Large (SD3.5 Large) is now available in Amazon Bedrock. SD3.5 Large is an advanced text-to-image model featuring 8.1 billion parameters. Trained on Amazon SageMaker HyperPod, this powerful model will enable AWS customers to generate high-quality, 1-megapixel images from text descriptions with superior accuracy and creative control.

The model excels at creating diverse, high-quality images across multiple styles, making it valuable for media, gaming, advertising, ecommerce, corporate training, retail, and education industries. Its enhanced capabilities include exceptional photorealism with detailed 3D imagery, superior handling of multiple subjects in complex scenes, and improved human anatomy rendering. The model also generates representative images with diverse skin tones and features without requiring extensive prompting. Today, Stable Image Ultra in Amazon Bedrock has been updated to include Stable Diffusion 3.5 Large in the model’s underlying architecture.

Stable Diffusion 3.5 Large is now available in Amazon Bedrock in the US West (Oregon) AWS region. To learn more read the AWS News Blog or visit the Stability AI in Amazon Bedrock product page, and documentation. To get started with SD3.5 Large, visit the Amazon Bedrock console.

 

​Stability AI’s Stable Diffusion 3.5 Large (SD3.5 Large) is now available in Amazon Bedrock. SD3.5 Large is an advanced text-to-image model featuring 8.1 billion parameters. Trained on Amazon SageMaker HyperPod, this powerful model will enable AWS customers to generate high-quality, 1-megapixel images from text descriptions with superior accuracy and creative control.
The model excels at creating diverse, high-quality images across multiple styles, making it valuable for media, gaming, advertising, ecommerce, corporate training, retail, and education industries. Its enhanced capabilities include exceptional photorealism with detailed 3D imagery, superior handling of multiple subjects in complex scenes, and improved human anatomy rendering. The model also generates representative images with diverse skin tones and features without requiring extensive prompting. Today, Stable Image Ultra in Amazon Bedrock has been updated to include Stable Diffusion 3.5 Large in the model’s underlying architecture.
Stable Diffusion 3.5 Large is now available in Amazon Bedrock in the US West (Oregon) AWS region. To learn more read the AWS News Blog or visit the Stability AI in Amazon Bedrock product page, and documentation. To get started with SD3.5 Large, visit the Amazon Bedrock console.