Amazon Data Lifecycle Manager now supports AWS PrivateLink to connect directly to the Amazon Data Lifecycle Manager APIs in your virtual private cloud (VPC) instead of connecting over the internet.

Customers create Amazon Data Lifecycle Manager policies to automate the creation, retention, and management of EBS Snapshots and EBS-backed Amazon Machine Images (AMIs). When you use AWS PrivateLink to access Amazon Data Lifecycle Manager APIs, communication between your VPC and Amazon Data Lifecycle Manager API is conducted privately within the AWS network, providing a secure pathway for your data. An AWS PrivateLink endpoint connects your VPC directly to the Amazon Data Lifecycle Manager API.

This feature is available in all AWS Regions where Amazon Data Lifecycle Manager is available. You can create an AWS PrivateLink to connect to Amazon Data Lifecycle Manager using the AWS Management Console or AWS Command Line Interface (AWS CLI) commands. To learn more about using AWS PrivateLink, please refer to our documentation.

 

​Amazon Data Lifecycle Manager now supports AWS PrivateLink to connect directly to the Amazon Data Lifecycle Manager APIs in your virtual private cloud (VPC) instead of connecting over the internet. Customers create Amazon Data Lifecycle Manager policies to automate the creation, retention, and management of EBS Snapshots and EBS-backed Amazon Machine Images (AMIs). When you use AWS PrivateLink to access Amazon Data Lifecycle Manager APIs, communication between your VPC and Amazon Data Lifecycle Manager API is conducted privately within the AWS network, providing a secure pathway for your data. An AWS PrivateLink endpoint connects your VPC directly to the Amazon Data Lifecycle Manager API. This feature is available in all AWS Regions where Amazon Data Lifecycle Manager is available. You can create an AWS PrivateLink to connect to Amazon Data Lifecycle Manager using the AWS Management Console or AWS Command Line Interface (AWS CLI) commands. To learn more about using AWS PrivateLink, please refer to our documentation.  

Amazon Connect Contact Lens now provides generative AI-powered contact categorization in five additional regions, making it easy to identify top drivers, customer experience, and agent behavior for your contacts. With this launch, you can use natural language instructions to define a criteria to automatically categorize customer contacts (e.g., “show me calls where customers attempted payment”). Contact Lens automatically labels interactions matching your criteria and extracts relevant conversation points. In addition, you can receive alerts and generate tasks on categorized contacts, and search for contacts using the automated labels. This feature helps managers easily categorize contacts for scenarios such as identifying customer interest in specific products, assessing customer satisfaction, monitoring whether agents exhibited professional behavior on calls, and more.

This feature is supported in English language and is available in five additional AWS regions including Europe (London), Asia Pacific (Tokyo), Asia Pacific (Singapore), Asia Pacific (Sydney) and Canada (Central). To learn more, please visit our documentation and our webpage. This feature is included within Contact Lens conversational analytics price at no additional cost. For information about Contact Lens pricing, please visit our pricing page.

 

​Amazon Connect Contact Lens now provides generative AI-powered contact categorization in five additional regions, making it easy to identify top drivers, customer experience, and agent behavior for your contacts. With this launch, you can use natural language instructions to define a criteria to automatically categorize customer contacts (e.g., “show me calls where customers attempted payment”). Contact Lens automatically labels interactions matching your criteria and extracts relevant conversation points. In addition, you can receive alerts and generate tasks on categorized contacts, and search for contacts using the automated labels. This feature helps managers easily categorize contacts for scenarios such as identifying customer interest in specific products, assessing customer satisfaction, monitoring whether agents exhibited professional behavior on calls, and more. This feature is supported in English language and is available in five additional AWS regions including Europe (London), Asia Pacific (Tokyo), Asia Pacific (Singapore), Asia Pacific (Sydney) and Canada (Central). To learn more, please visit our documentation and our webpage. This feature is included within Contact Lens conversational analytics price at no additional cost. For information about Contact Lens pricing, please visit our pricing page.  

Starting today, EC2 Fleet customers can override the Block Device Mapping specified in the Launch Template when launching a new fleet. With this release, customers save the effort of creating and associating new Launch Templates with their fleet requests, when they need to customize the Block Device Mapping but keep rest of the instance configurations the same.

Customers use EC2 Fleet to access wider EC2 capacity across instance types and availability zones within a single launch request. To provide their EC2 instance configurations such as Amazon Machine Images, Key pair etc, customers associate a Launch Template with their Fleet requests. They can override the values specified for select parameters in the Launch Template for each instance type. With this release, customers can also override Block Device Mapping parameters specified in the Launch Template. With Block Device Mapping, customers can launch additional EBS volumes or instance store volumes to attach to an instance, or update the Block Device Mapping specified in the Amazon Machine Image that you use to launch the instances.

The feature is available in all commercial AWS regions and the AWS GovCloud (US) Regions. To learn more, refer the API references and EC2 user guide.

 

​Starting today, EC2 Fleet customers can override the Block Device Mapping specified in the Launch Template when launching a new fleet. With this release, customers save the effort of creating and associating new Launch Templates with their fleet requests, when they need to customize the Block Device Mapping but keep rest of the instance configurations the same. Customers use EC2 Fleet to access wider EC2 capacity across instance types and availability zones within a single launch request. To provide their EC2 instance configurations such as Amazon Machine Images, Key pair etc, customers associate a Launch Template with their Fleet requests. They can override the values specified for select parameters in the Launch Template for each instance type. With this release, customers can also override Block Device Mapping parameters specified in the Launch Template. With Block Device Mapping, customers can launch additional EBS volumes or instance store volumes to attach to an instance, or update the Block Device Mapping specified in the Amazon Machine Image that you use to launch the instances. The feature is available in all commercial AWS regions and the AWS GovCloud (US) Regions. To learn more, refer the API references and EC2 user guide.  

AWS Elastic Beanstalk now enables customers to build and deploy Tomcat 11 applications on Amazon Linux 2023 (AL2023) platform. This latest platform support allows developers to leverage the newest Tomcat features while benefiting from AL2023’s enhanced security and performance features.

AWS Elastic Beanstalk is a service that provides the ability to deploy and manage applications in AWS without worrying about the infrastructure that runs those applications. Tomcat 11 on AL2023 allows developers to take advantage of the latest Jakarta EE specifications. Developers can create Elastic Beanstalk environments running Corretto 17 and 21 with Tomcat 11 on AL2023 through the Elastic Beanstalk Console, CLI, or API.

This platform is generally available in commercial regions where Elastic Beanstalk is available including the AWS GovCloud (US) Regions. For a complete list of regions and service offerings, see AWS Regions.

For more information about Corretto 17 and 21 with Tomcat 11 and Linux Platforms, see the Elastic Beanstalk developer guide. To learn more about Elastic Beanstalk, visit the Elastic Beanstalk product page.

 

​AWS Elastic Beanstalk now enables customers to build and deploy Tomcat 11 applications on Amazon Linux 2023 (AL2023) platform. This latest platform support allows developers to leverage the newest Tomcat features while benefiting from AL2023’s enhanced security and performance features.
AWS Elastic Beanstalk is a service that provides the ability to deploy and manage applications in AWS without worrying about the infrastructure that runs those applications. Tomcat 11 on AL2023 allows developers to take advantage of the latest Jakarta EE specifications. Developers can create Elastic Beanstalk environments running Corretto 17 and 21 with Tomcat 11 on AL2023 through the Elastic Beanstalk Console, CLI, or API.
This platform is generally available in commercial regions where Elastic Beanstalk is available including the AWS GovCloud (US) Regions. For a complete list of regions and service offerings, see AWS Regions.
For more information about Corretto 17 and 21 with Tomcat 11 and Linux Platforms, see the Elastic Beanstalk developer guide. To learn more about Elastic Beanstalk, visit the Elastic Beanstalk product page.  

AWS Elastic Beanstalk now enables customers to build and deploy Ruby 3.4 applications on the Amazon Linux 2023 (AL2023) platform. This latest platform support allows developers to leverage the newest Ruby features while benefiting from AL2023’s enhanced security and performance features.

AWS Elastic Beanstalk is a service that provides the ability to deploy and manage applications in AWS without worrying about the infrastructure that runs those applications. Ruby 3.4 on AL2023 delivers performance improvements and reduced memory usage. Developers can create Elastic Beanstalk environments running Ruby 3.4 on AL2023 through the Elastic Beanstalk Console, CLI, or API.

This platform is generally available in commercial regions where Elastic Beanstalk is available including the AWS GovCloud (US) Regions. For a complete list of regions and service offerings, see AWS Regions.

For more information about Ruby 3.4 and Linux Platforms, see the Elastic Beanstalk developer guide. To learn more about Elastic Beanstalk, visit the Elastic Beanstalk product page.

 

​AWS Elastic Beanstalk now enables customers to build and deploy Ruby 3.4 applications on the Amazon Linux 2023 (AL2023) platform. This latest platform support allows developers to leverage the newest Ruby features while benefiting from AL2023’s enhanced security and performance features.
AWS Elastic Beanstalk is a service that provides the ability to deploy and manage applications in AWS without worrying about the infrastructure that runs those applications. Ruby 3.4 on AL2023 delivers performance improvements and reduced memory usage. Developers can create Elastic Beanstalk environments running Ruby 3.4 on AL2023 through the Elastic Beanstalk Console, CLI, or API.
This platform is generally available in commercial regions where Elastic Beanstalk is available including the AWS GovCloud (US) Regions. For a complete list of regions and service offerings, see AWS Regions.
For more information about Ruby 3.4 and Linux Platforms, see the Elastic Beanstalk developer guide. To learn more about Elastic Beanstalk, visit the Elastic Beanstalk product page.  

Today, AWS announces the general availability of the Amazon Q Business integrations for Microsoft 365 for Word and Outlook. These new integrations improve the usability and usefulness of Amazon Q Business by making its generative AI features available where business users do their work. Users can now get Amazon Q Business’ help in creating content, reviewing documents, and reading or drafting their emails without switching context.

The Word integration helps users boost their document creation and review efficiency. Users can leverage generative AI capabilities to draft content, enhance writing quality, and analyze lengthy documents with ease. Through the Amazon Q Business interface, users can perform various AI-powered text transformations on selected text – such as improving its readability or modifying its writing style – and seamlessly incorporate these improvements directly into their Word documents.

The Outlook integration helps users streamline their communication workflows and improve the effectiveness of their emails. Users can summarize lengthy email threads, identify and extract action items for follow up, get assistance with draft composition, adjust message tone, and seamlessly incorporate enhanced content directly into their emails from the Amazon Q Business window.

These integrations are designed to be easy for customers to set up and distribute to their users within hours and are available to Q Business customers using AWS IAM Identity Center in all AWS Regions where Q Business is available.

To learn more, visit the Amazon Q Business product page or review the documentation for detailed setup instructions and feature descriptions.
 

 

​Today, AWS announces the general availability of the Amazon Q Business integrations for Microsoft 365 for Word and Outlook. These new integrations improve the usability and usefulness of Amazon Q Business by making its generative AI features available where business users do their work. Users can now get Amazon Q Business’ help in creating content, reviewing documents, and reading or drafting their emails without switching context. The Word integration helps users boost their document creation and review efficiency. Users can leverage generative AI capabilities to draft content, enhance writing quality, and analyze lengthy documents with ease. Through the Amazon Q Business interface, users can perform various AI-powered text transformations on selected text – such as improving its readability or modifying its writing style – and seamlessly incorporate these improvements directly into their Word documents. The Outlook integration helps users streamline their communication workflows and improve the effectiveness of their emails. Users can summarize lengthy email threads, identify and extract action items for follow up, get assistance with draft composition, adjust message tone, and seamlessly incorporate enhanced content directly into their emails from the Amazon Q Business window. These integrations are designed to be easy for customers to set up and distribute to their users within hours and are available to Q Business customers using AWS IAM Identity Center in all AWS Regions where Q Business is available. To learn more, visit the Amazon Q Business product page or review the documentation for detailed setup instructions and feature descriptions.    

Amazon Bedrock announces the preview launch of the Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI (GenAI) applications built with popular open-source frameworks such as LangGraph and LlamaIndex. Session Management APIs provide an out-of-the-box solution that enables developers to securely manage state and conversation context across multi-step GenAI workflows, eliminating the need to build, maintain, or scale custom backend solutions.

By preserving session state between interactions, Session Management APIs enhance workflow continuity, enabling GenAI applications, such as virtual assistants and multi-agent research workflows, that require persistent context across extended interactions. Developers can use this capability to checkpoint workflow stages, save intermediate states, and resume tasks from points of failure or interruption. Additionally, they can pause and replay sessions and leverage detailed traces to debug and enhance their GenAI applications. By treating session as a first-class resource, this capability enables developers to enforce granular access control through AWS Identity and Access Management (IAM) and encrypt data using AWS Key Management Service (KMS), ensuring that data from different user sessions is securely isolated and supporting multi-tenant applications with strong privacy protections.

Session Management APIs are now available in preview in US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Zurich), and South America (São Paulo). To learn more, visit the technical documentation.

 

​Amazon Bedrock announces the preview launch of the Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI (GenAI) applications built with popular open-source frameworks such as LangGraph and LlamaIndex. Session Management APIs provide an out-of-the-box solution that enables developers to securely manage state and conversation context across multi-step GenAI workflows, eliminating the need to build, maintain, or scale custom backend solutions. By preserving session state between interactions, Session Management APIs enhance workflow continuity, enabling GenAI applications, such as virtual assistants and multi-agent research workflows, that require persistent context across extended interactions. Developers can use this capability to checkpoint workflow stages, save intermediate states, and resume tasks from points of failure or interruption. Additionally, they can pause and replay sessions and leverage detailed traces to debug and enhance their GenAI applications. By treating session as a first-class resource, this capability enables developers to enforce granular access control through AWS Identity and Access Management (IAM) and encrypt data using AWS Key Management Service (KMS), ensuring that data from different user sessions is securely isolated and supporting multi-tenant applications with strong privacy protections. Session Management APIs are now available in preview in US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Zurich), and South America (São Paulo). To learn more, visit the technical documentation.  

Today, we are excited to announce Amazon Nova creative models, including Amazon Nova Canvas and Amazon Nova Reel, in Asia Pacific (Tokyo). These models are designed to generate high-quality images and videos from text and image inputs, providing customizable visual content for various applications. This expansion addresses the growing demand for automated, high-quality visual content generation, benefiting marketers, content creators, and developers who need efficient solutions for producing engaging media.

Amazon Nova creative models offer built-in controls to enable the safe and responsible use of AI, including watermarking for traceability, content moderation, and indemnification. Customers can now leverage these advanced capabilities to create compelling visuals that enhance their digital presence and user engagement.

To learn more about Amazon Nova creative models, see the Amazon Nova creative models and learn about Amazon Nova creative models responsible use of AI. To get started with Amazon Nova on Amazon Bedrock, visit the Amazon Bedrock console.

 

​Today, we are excited to announce Amazon Nova creative models, including Amazon Nova Canvas and Amazon Nova Reel, in Asia Pacific (Tokyo). These models are designed to generate high-quality images and videos from text and image inputs, providing customizable visual content for various applications. This expansion addresses the growing demand for automated, high-quality visual content generation, benefiting marketers, content creators, and developers who need efficient solutions for producing engaging media. Amazon Nova creative models offer built-in controls to enable the safe and responsible use of AI, including watermarking for traceability, content moderation, and indemnification. Customers can now leverage these advanced capabilities to create compelling visuals that enhance their digital presence and user engagement. To learn more about Amazon Nova creative models, see the Amazon Nova creative models and learn about Amazon Nova creative models responsible use of AI. To get started with Amazon Nova on Amazon Bedrock, visit the Amazon Bedrock console.  

With the Mountpoint for Amazon S3 Container Storage Interface (CSI) driver, your Kubernetes applications can access S3 objects through a file system interface, achieving high aggregate throughput without any changes to your application. Built on Mountpoint for Amazon S3, the CSI driver presents an S3 bucket as a volume accessible by containers in Amazon Elastic Kubernetes Service (Amazon EKS) and self-managed Kubernetes clusters. As a result, distributed machine learning training jobs in Amazon EKS and self-managed Kubernetes clusters can read data from Amazon S3 at high throughput to accelerate training times.

The Mountpoint for Amazon S3 CSI driver supports sequential and random read operations on existing files and sequential write operations for creating new files. For details on supported file system operations, visit the documentation. Amazon EKS supports the Mountpoint for Amazon S3 CSI driver as an EKS add-on. You can install, configure, and update the CSI driver with just a few clicks in Amazon EKS console, AWS Command Line Interface (AWS CLI), EKS Application Programming Interface (API), and AWS CloudFormation.

With this launch, the Mountpoint for Amazon S3 CSI driver is now available in all commercial and AWS GovCloud (US) Regions. To get started, follow the user guide.
 

 

​With the Mountpoint for Amazon S3 Container Storage Interface (CSI) driver, your Kubernetes applications can access S3 objects through a file system interface, achieving high aggregate throughput without any changes to your application. Built on Mountpoint for Amazon S3, the CSI driver presents an S3 bucket as a volume accessible by containers in Amazon Elastic Kubernetes Service (Amazon EKS) and self-managed Kubernetes clusters. As a result, distributed machine learning training jobs in Amazon EKS and self-managed Kubernetes clusters can read data from Amazon S3 at high throughput to accelerate training times. The Mountpoint for Amazon S3 CSI driver supports sequential and random read operations on existing files and sequential write operations for creating new files. For details on supported file system operations, visit the documentation. Amazon EKS supports the Mountpoint for Amazon S3 CSI driver as an EKS add-on. You can install, configure, and update the CSI driver with just a few clicks in Amazon EKS console, AWS Command Line Interface (AWS CLI), EKS Application Programming Interface (API), and AWS CloudFormation. With this launch, the Mountpoint for Amazon S3 CSI driver is now available in all commercial and AWS GovCloud (US) Regions. To get started, follow the user guide.    

AWS CodeBuild now supports macOS 15.2 as a new major version for macOS builds. This allows developers to build and test their applications in the latest macOS environment. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment.

The new major version includes the latest Xcode 16.2, Fastlane for iOS automation and Finch for container management in macOS environment. We have also updated our existing macOS AMI to version 14.7, ensuring customers have access to the latest security updates and improvements.

The new macOS 15.2 is available in US East (Ohio), US East (N. Virginia), US West (Oregon), Europe (Frankfurt), and Asia Pacific (Sydney). For more information about the AWS Regions where CodeBuild is available, see the AWS Regions page.

To learn more about the runtimes supported by macOS, please visit our documentation. To learn more about how to get started with CodeBuild, visit the AWS CodeBuild product page.

 

​AWS CodeBuild now supports macOS 15.2 as a new major version for macOS builds. This allows developers to build and test their applications in the latest macOS environment. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment. The new major version includes the latest Xcode 16.2, Fastlane for iOS automation and Finch for container management in macOS environment. We have also updated our existing macOS AMI to version 14.7, ensuring customers have access to the latest security updates and improvements. The new macOS 15.2 is available in US East (Ohio), US East (N. Virginia), US West (Oregon), Europe (Frankfurt), and Asia Pacific (Sydney). For more information about the AWS Regions where CodeBuild is available, see the AWS Regions page. To learn more about the runtimes supported by macOS, please visit our documentation. To learn more about how to get started with CodeBuild, visit the AWS CodeBuild product page.