You can now run OpenSearch version 2.19 in Amazon OpenSearch Service which introduces several improvements in the areas of Vector Search, Observability and OpenSearch Dashboards.

We have introduced four key capabilities for vector search applications. The Faiss engine now supports AVX512 SIMD instructions, to accelerate vector similarity computations. The ML inference search response processor can now rank search hits and update scores based on model predictions, enabling sophisticated and context-aware document ranking and result augmentation. Lucene binary vectors, now complement existing Faiss engine binary vector support offering greater flexibility for vector search applications. Hybrid search now includes pagination support , reciprocal rank fusion to improve result ranking along with a debugging tool for score and rank normalization process.

The launch also introduces query insights dashboards that lets users monitor and analyze the top queries collected by the query Insights plugin. Anomaly detection now offers two key improvements. First, enhanced anomaly definition capabilities allow users to specify multiple criteria to identify both spikes and dips in data patterns. Second, a new dedicated index for flattened results improves query performance and dashboard visualization experience. Finally, you can now use template query to create search queries that contain placeholder variables allowing for more flexible, efficient, and secure search operations.

For information on upgrading to OpenSearch 2.19, please see the documentation. OpenSearch 2.19 is now available in all AWS Regions where Amazon OpenSearch Service is available.
 

 

​You can now run OpenSearch version 2.19 in Amazon OpenSearch Service which introduces several improvements in the areas of Vector Search, Observability and OpenSearch Dashboards. We have introduced four key capabilities for vector search applications. The Faiss engine now supports AVX512 SIMD instructions, to accelerate vector similarity computations. The ML inference search response processor can now rank search hits and update scores based on model predictions, enabling sophisticated and context-aware document ranking and result augmentation. Lucene binary vectors, now complement existing Faiss engine binary vector support offering greater flexibility for vector search applications. Hybrid search now includes pagination support , reciprocal rank fusion to improve result ranking along with a debugging tool for score and rank normalization process. The launch also introduces query insights dashboards that lets users monitor and analyze the top queries collected by the query Insights plugin. Anomaly detection now offers two key improvements. First, enhanced anomaly definition capabilities allow users to specify multiple criteria to identify both spikes and dips in data patterns. Second, a new dedicated index for flattened results improves query performance and dashboard visualization experience. Finally, you can now use template query to create search queries that contain placeholder variables allowing for more flexible, efficient, and secure search operations. For information on upgrading to OpenSearch 2.19, please see the documentation. OpenSearch 2.19 is now available in all AWS Regions where Amazon OpenSearch Service is available.    

Amazon Simple Email Service (SES) announces that its Mail Manager email modernization and infrastructure features now have a rule action which enables messages to be published using an Amazon Simple Notification Service (SNS) notification. The notification includes the complete email content, and has options for SNS Topic and Encoding.

Amazon SNS is a fully managed service that provides message delivery from publishers (producers) to subscribers (consumers). Publishers communicate asynchornously with subscribers by sending messages to a topic, which is a logical access point and communication channel. Subscribers can choose to receive these notifications through a variety of endpoints, including email, SMS, and Lambda. By centralizing notification preferences within SNS, customers enhance messaging between applications and users while gaining advantages of high availability, durability, and flexibility. Using the Publish to SNS rule action within Mail Manager increases the number and type of delivery destinations available to customers as part of their larger ruleset configuration.

Mail Manager’s Publish to SNS rule action is available in all 17 AWS Regions where Mail Manager is launched. There is no additional fee from SES to make use of this feature, though charges from AWS for SNS and destination channel activity may apply. Customers can learn more about SES Mail Manager by clicking here.

 

​Amazon Simple Email Service (SES) announces that its Mail Manager email modernization and infrastructure features now have a rule action which enables messages to be published using an Amazon Simple Notification Service (SNS) notification. The notification includes the complete email content, and has options for SNS Topic and Encoding. Amazon SNS is a fully managed service that provides message delivery from publishers (producers) to subscribers (consumers). Publishers communicate asynchornously with subscribers by sending messages to a topic, which is a logical access point and communication channel. Subscribers can choose to receive these notifications through a variety of endpoints, including email, SMS, and Lambda. By centralizing notification preferences within SNS, customers enhance messaging between applications and users while gaining advantages of high availability, durability, and flexibility. Using the Publish to SNS rule action within Mail Manager increases the number and type of delivery destinations available to customers as part of their larger ruleset configuration. Mail Manager’s Publish to SNS rule action is available in all 17 AWS Regions where Mail Manager is launched. There is no additional fee from SES to make use of this feature, though charges from AWS for SNS and destination channel activity may apply. Customers can learn more about SES Mail Manager by clicking here.  

AWS Config now supports 13 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 in Config rules and Config aggregators.

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

Resource Types:

AWS::AppIntegrations::Application

AWS::EC2::EIPAssociation

AWS::EC2::InstanceConnectEndpoint

AWS::EC2::SnapshotBlockPublicAccess

AWS::EC2::VPCEndpointConnectionNotification

AWS::ElastiCache::UserGroup

AWS::InspectorV2:Activation

AWS::Macie::Session

AWS::Route53Profiles::Profile

AWS::OpenSearchServerless::Collection

AWS::S3::StorageLensGroup

AWS::SecurityHub::Standard

AWS::SageMaker::InferenceExperiment

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

 

​AWS Config now supports 13 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 in Config rules and Config aggregators.
You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported resources are available:

Resource Types:

AWS::AppIntegrations::Application

AWS::EC2::EIPAssociation

AWS::EC2::InstanceConnectEndpoint

AWS::EC2::SnapshotBlockPublicAccess

AWS::EC2::VPCEndpointConnectionNotification

AWS::ElastiCache::UserGroup

AWS::InspectorV2:Activation

AWS::Macie::Session

AWS::Route53Profiles::Profile

AWS::OpenSearchServerless::Collection

AWS::S3::StorageLensGroup

AWS::SecurityHub::Standard

AWS::SageMaker::InferenceExperiment

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

Today AWS Elemental MediaTailor launched recurring prefetch schedules, enhancing server-side ad prefetch capabilities for live streaming content. This feature helps content providers and broadcasters efficiently manage ad insertion for live events where exact ad break timing is unpredictable, while maintaining high-quality viewer experiences. Content providers can benefit from this during major sporting events, live concerts, or news broadcasts where ad break timing may vary.

The new mode enables you to create a single schedule for an entire live event or linear channel. After every ad break, MediaTailor will automatically create the prefetch schedule for the next ad break while ensuring that any new playback sessions that join the stream are provisioned with ads. This automation reduces operational overhead while ensuring optimal ad delivery performance and pre-transcoding of ads to improve ad monetization. The feature also includes ad request traffic shaping settings to prevent ad server overload for viewing events with large audiences and to maintain low latency for manifest delivery.

To learn more about AWS Elemental MediaTailor, visit the AWS Elemental MediaTailor page. For detailed implementation guidance on the new Recurring Prefetch Schedule feature, see the MediaTailor documentation.

 

​Today AWS Elemental MediaTailor launched recurring prefetch schedules, enhancing server-side ad prefetch capabilities for live streaming content. This feature helps content providers and broadcasters efficiently manage ad insertion for live events where exact ad break timing is unpredictable, while maintaining high-quality viewer experiences. Content providers can benefit from this during major sporting events, live concerts, or news broadcasts where ad break timing may vary. The new mode enables you to create a single schedule for an entire live event or linear channel. After every ad break, MediaTailor will automatically create the prefetch schedule for the next ad break while ensuring that any new playback sessions that join the stream are provisioned with ads. This automation reduces operational overhead while ensuring optimal ad delivery performance and pre-transcoding of ads to improve ad monetization. The feature also includes ad request traffic shaping settings to prevent ad server overload for viewing events with large audiences and to maintain low latency for manifest delivery. To learn more about AWS Elemental MediaTailor, visit the AWS Elemental MediaTailor page. For detailed implementation guidance on the new Recurring Prefetch Schedule feature, see the MediaTailor documentation.  

Today, we are excited to announce the general availability of anonymous user access for Amazon Q Business. This feature allows customers to create Q Business applications for anonymous users using publicly accessible content. Q Business applications created in this anonymous mode are billed on a API consumption basis.

Customers can now create anonymous Q Business applications to power use cases such as public web site Q&A, documentation portals, and customer self-service experiences, where user authentication is not required and content is publicly available. For example, AnyCompany wants to improve their website’s visitor support experience by providing a genAI assistant over their publicly available help/product pages. The customer would create an anonymous Q Business application and index all the public product help/documentation to power their Q Business genAI assistant. To deploy the anonymous application, customers can implement the anonymous Chat/ChatSync APIs for higher UX control or embed the built-in anonymous web experience via an iFrame. Anonymous applications are billed on API consumption basis, offering a scalable way to deploy Q Business generative AI experiences to large anonymous audiences.

The anonymous chat APIs and web experience are available in the US East (N. Virginia), US West (Oregon), Europe (Ireland), and Asia Pacific (Sydney) AWS Regions. For more information, please consult our documentation.
 

 

​Today, we are excited to announce the general availability of anonymous user access for Amazon Q Business. This feature allows customers to create Q Business applications for anonymous users using publicly accessible content. Q Business applications created in this anonymous mode are billed on a API consumption basis. Customers can now create anonymous Q Business applications to power use cases such as public web site Q&A, documentation portals, and customer self-service experiences, where user authentication is not required and content is publicly available. For example, AnyCompany wants to improve their website’s visitor support experience by providing a genAI assistant over their publicly available help/product pages. The customer would create an anonymous Q Business application and index all the public product help/documentation to power their Q Business genAI assistant. To deploy the anonymous application, customers can implement the anonymous Chat/ChatSync APIs for higher UX control or embed the built-in anonymous web experience via an iFrame. Anonymous applications are billed on API consumption basis, offering a scalable way to deploy Q Business generative AI experiences to large anonymous audiences. The anonymous chat APIs and web experience are available in the US East (N. Virginia), US West (Oregon), Europe (Ireland), and Asia Pacific (Sydney) AWS Regions. For more information, please consult our documentation.    

Amazon VPC Lattice introduces dual stack support for management API, enabling you to connect using Internet Protocol Version 6 (IPv6), Internet Protocol Version 4 (IPv4), or dual stack clients. Dual stack support is also available when the Amazon VPC Lattice management API endpoint is privately accessed from your Amazon Virtual Private Cloud (VPC) using AWS PrivateLink. Dual stack endpoints are made available on a new AWS DNS domain name. The existing Amazon VPC Lattice management API endpoints are maintained for backwards compatibility reasons.

Amazon VPC Lattice, an application networking service that simplifies connecting, securing, and monitoring service-to-service communication. You can use Amazon VPC Lattice to facilitate cross-account and cross-VPC connectivity, as well as application layer load balancing for your workloads. Whether the underlying compute types are instances, containers, or serverless, with Amazon VPC Lattice developers can work with native integration on the compute platform of their choice. With simultaneous support for both IPv4 and IPv6 clients on VPC Lattice endpoints, you are able to gradually transition from IPv4 to IPv6 based systems and applications, without needing to switch all over at once. This enables you to meet IPv6 compliance requirements and removes the need for expensive networking equipment to handle the address translation between IPv4 and IPv6.

To learn more, see the VPC Lattice user guide and IPv6 on AWS.

 

​Amazon VPC Lattice introduces dual stack support for management API, enabling you to connect using Internet Protocol Version 6 (IPv6), Internet Protocol Version 4 (IPv4), or dual stack clients. Dual stack support is also available when the Amazon VPC Lattice management API endpoint is privately accessed from your Amazon Virtual Private Cloud (VPC) using AWS PrivateLink. Dual stack endpoints are made available on a new AWS DNS domain name. The existing Amazon VPC Lattice management API endpoints are maintained for backwards compatibility reasons. Amazon VPC Lattice, an application networking service that simplifies connecting, securing, and monitoring service-to-service communication. You can use Amazon VPC Lattice to facilitate cross-account and cross-VPC connectivity, as well as application layer load balancing for your workloads. Whether the underlying compute types are instances, containers, or serverless, with Amazon VPC Lattice developers can work with native integration on the compute platform of their choice. With simultaneous support for both IPv4 and IPv6 clients on VPC Lattice endpoints, you are able to gradually transition from IPv4 to IPv6 based systems and applications, without needing to switch all over at once. This enables you to meet IPv6 compliance requirements and removes the need for expensive networking equipment to handle the address translation between IPv4 and IPv6.
To learn more, see the VPC Lattice user guide and IPv6 on AWS.  

Today, AWS Clean Rooms announces support for multiple collaboration members to receive analysis results from queries using Spark SQL. This streamlined capability enhances usability and transparency by eliminating the need for additional audit mechanisms outside of the collaboration. With this feature, multiple members can receive and validate analysis results from queries across collective datasets directly from the collaboration.

You can designate multiple collaborators as result receivers when executing a Spark SQL query. Results are automatically delivered to all selected collaborators who are configured in both the collaboration settings and table controls. For example, in a collaboration between a media publisher and an advertiser, the publisher can run a query across their collective datasets; the query results are sent to both parties’ chosen Amazon S3 location for validation.

AWS Clean Rooms helps companies and their partners to easily analyze and collaborate on their collective datasets without revealing or copying one another’s underlying data. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.

 

​Today, AWS Clean Rooms announces support for multiple collaboration members to receive analysis results from queries using Spark SQL. This streamlined capability enhances usability and transparency by eliminating the need for additional audit mechanisms outside of the collaboration. With this feature, multiple members can receive and validate analysis results from queries across collective datasets directly from the collaboration. You can designate multiple collaborators as result receivers when executing a Spark SQL query. Results are automatically delivered to all selected collaborators who are configured in both the collaboration settings and table controls. For example, in a collaboration between a media publisher and an advertiser, the publisher can run a query across their collective datasets; the query results are sent to both parties’ chosen Amazon S3 location for validation. AWS Clean Rooms helps companies and their partners to easily analyze and collaborate on their collective datasets without revealing or copying one another’s underlying data. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.  

Amazon Connect now provides bulk removal of agent schedules, making day-to-day management of agent schedules more efficient. With this launch, you can now remove schedules for up to 400 agents for a single day, or up to 30 days for a single agent. For example, remove all schedules for next Monday as the contact center is going to be closed, or remove future shifts for an agent who is no longer with the organization. With bulk remove, managers no longer have to remove agent shifts one agent and one day at a time, thus improving manager productivity by reducing time spent on managing agent schedules.

This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.

 

​Amazon Connect now provides bulk removal of agent schedules, making day-to-day management of agent schedules more efficient. With this launch, you can now remove schedules for up to 400 agents for a single day, or up to 30 days for a single agent. For example, remove all schedules for next Monday as the contact center is going to be closed, or remove future shifts for an agent who is no longer with the organization. With bulk remove, managers no longer have to remove agent shifts one agent and one day at a time, thus improving manager productivity by reducing time spent on managing agent schedules. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.  

Starting today, we’re enhancing the AWS Migration Acceleration Program (MAP) with two key capabilities to help you accelerate your modernization efforts and drive customers’ adoption of AI:

• New “Move to AI” Modernization Pathway, featuring Amazon Bedrock and Amazon SageMaker. This pathway enables you to help customers transform their existing applications and business processes with proven AI patterns that deliver measurable business value.
• Amazon Connect is now a qualifying service in the MAP Modernization Strategic Partner Incentive (SPI). This enables you to help customers transform their contact centers with AI-powered features that increase agent productivity and enhance customer experiences.

These enhancements strengthen your ability to lead customers’ AI transformation and drive contact center modernization.

Learn more:

• AWS Partner Funding Benefits Program Guide
• MAP Modernization SPI Eligible Services

 

​Starting today, we’re enhancing the AWS Migration Acceleration Program (MAP) with two key capabilities to help you accelerate your modernization efforts and drive customers’ adoption of AI:

New “Move to AI” Modernization Pathway, featuring Amazon Bedrock and Amazon SageMaker. This pathway enables you to help customers transform their existing applications and business processes with proven AI patterns that deliver measurable business value.
Amazon Connect is now a qualifying service in the MAP Modernization Strategic Partner Incentive (SPI). This enables you to help customers transform their contact centers with AI-powered features that increase agent productivity and enhance customer experiences.

These enhancements strengthen your ability to lead customers’ AI transformation and drive contact center modernization. Learn more:

AWS Partner Funding Benefits Program Guide
MAP Modernization SPI Eligible Services  

EC2 Image Builder now integrates with Systems Manager Parameter Store, offering customers a streamlined approach for referencing SSM parameters in their image recipes, components, and distribution configurations. This capability allows customers to dynamically select base images within their image recipes, easily use configuration data and sensitive information for components, and update their SSM parameters with output latest images.

Prior to today, customers had to specify AMI IDs in their image recipes to use custom base images, leading to a constant maintenance cycle when these base images had to be updated. Furthermore, customers were required to create custom scripts to update SSM parameters with output images and to utilize SSM parameter values in components, resulting in substantial operational overhead. Now, customers can leverage SSM Parameters as inputs for their image recipes, enabling them to dynamically retrieve the latest base image. This integration extends to components, where SSM Parameters can be easily referenced to save, retrieve and use sensitive information in components, and to the distribution process, where SSM parameters can be updated with latest output images. These enhancements streamline the image building workflow, reduce manual intervention and improve overall efficiency.

This capability is available to all customers at no additional costs, and is enabled in all AWS commercial regions including AWS GovCloud (US), AWS China (Beijing) Region, operated by Sinnet, and in the AWS China (Ningxia) Region, operated by NWCD.

Customers can get started from the EC2 Image Builder Console, CLI, API, CloudFormation, or CDK, and learn more in the EC2 Image Builder documentation.
 

 

​EC2 Image Builder now integrates with Systems Manager Parameter Store, offering customers a streamlined approach for referencing SSM parameters in their image recipes, components, and distribution configurations. This capability allows customers to dynamically select base images within their image recipes, easily use configuration data and sensitive information for components, and update their SSM parameters with output latest images. Prior to today, customers had to specify AMI IDs in their image recipes to use custom base images, leading to a constant maintenance cycle when these base images had to be updated. Furthermore, customers were required to create custom scripts to update SSM parameters with output images and to utilize SSM parameter values in components, resulting in substantial operational overhead. Now, customers can leverage SSM Parameters as inputs for their image recipes, enabling them to dynamically retrieve the latest base image. This integration extends to components, where SSM Parameters can be easily referenced to save, retrieve and use sensitive information in components, and to the distribution process, where SSM parameters can be updated with latest output images. These enhancements streamline the image building workflow, reduce manual intervention and improve overall efficiency. This capability is available to all customers at no additional costs, and is enabled in all AWS commercial regions including AWS GovCloud (US), AWS China (Beijing) Region, operated by Sinnet, and in the AWS China (Ningxia) Region, operated by NWCD. Customers can get started from the EC2 Image Builder Console, CLI, API, CloudFormation, or CDK, and learn more in the EC2 Image Builder documentation.