AWS Serverless Application Model (AWS SAM) now supports custom domain names for private REST APIs feature of Amazon API Gateway. Developers building serverless applications using SAM can now seamlessly incorporate custom domain names for private APIs directly in their SAM templates, eliminating the need to configure custom domain names separately using other tools.

API Gateway allows you to create a custom domain name, like private.example.com, for your private REST APIs, enabling you to provide API callers with a simpler and intuitive URL. With a private custom domain name, you can reduce complexity, configure security measures with TLS encryption, and manage the lifecycle of the TLS certificate associated with your domain name. AWS SAM is a collection of open-source tools (e.g. SAM, SAM CLI) that make it easy for you to build and manage serverless applications through the authoring, building, deploying, testing, and monitoring phases of your development lifecycle. This launch enables you to easily configure custom domain names for your private REST APIs using SAM and SAM CLI.

To get started, update SAM CLI to the latest version and modify your SAM template to set the EndpointConfiguration to PRIVATE and specify a policy document in the Policy field in the Domain property of the AWS::Serverless::Api resource. SAM will then automatically generate DomainNameV2 and BasePathMappingV2 resources under AWS::Serverless::Api. To learn more, visit the AWS SAM documentation. You can learn more about custom domain name for private REST APIs in API Gateway blog post.
 

 

​AWS Serverless Application Model (AWS SAM) now supports custom domain names for private REST APIs feature of Amazon API Gateway. Developers building serverless applications using SAM can now seamlessly incorporate custom domain names for private APIs directly in their SAM templates, eliminating the need to configure custom domain names separately using other tools. API Gateway allows you to create a custom domain name, like private.example.com, for your private REST APIs, enabling you to provide API callers with a simpler and intuitive URL. With a private custom domain name, you can reduce complexity, configure security measures with TLS encryption, and manage the lifecycle of the TLS certificate associated with your domain name. AWS SAM is a collection of open-source tools (e.g. SAM, SAM CLI) that make it easy for you to build and manage serverless applications through the authoring, building, deploying, testing, and monitoring phases of your development lifecycle. This launch enables you to easily configure custom domain names for your private REST APIs using SAM and SAM CLI. To get started, update SAM CLI to the latest version and modify your SAM template to set the EndpointConfiguration to PRIVATE and specify a policy document in the Policy field in the Domain property of the AWS::Serverless::Api resource. SAM will then automatically generate DomainNameV2 and BasePathMappingV2 resources under AWS::Serverless::Api. To learn more, visit the AWS SAM documentation. You can learn more about custom domain name for private REST APIs in API Gateway blog post.    

Amazon Bedrock Guardrails announces new capabilities to safely build generative AI applications at scale. These new capabilities offer grater flexibility, finer-grained control, and ease of use while using the configurable safeguards provided by Bedrock Guardrails aligning with use cases and responsible AI policies.

Bedrock Guardrails now offers a detect mode that provides a preview of the expected results from your configured policies allowing you to evaluate the effectiveness of the safeguards before deploying them. This enables faster iteration and accelerating time-to-product with different combinations and strengths of policies, allowing you to fine-tune your guardrails before deployment.

Guardrails now offers more configurability with options to enable policies on input prompts, model responses, or both prompts and responses – a significant improvement over the previous default setting where policies were automatically applied to both inputs and outputs. Providing finer-grained control enables you to selectively apply the safeguards to make them work for you.

Bedrock Guardrails offers sensitive information filters that detect personally identifiable information (PIIs) with two modes: Block where requests containing sensitive information are completely blocked, and Mask where sensitive information is redacted and replaced with identifier tags. You can now use either of these two modes for both input prompts and model responses giving you flexibility and ease of use to safely build generative AI applications at scale.

These new capabilities are available in all AWS regions where Amazon Bedrock Guardrails is supported.

To learn more, see the blog post, technical documentation and the Bedrock Guardrails product page.

 

​Amazon Bedrock Guardrails announces new capabilities to safely build generative AI applications at scale. These new capabilities offer grater flexibility, finer-grained control, and ease of use while using the configurable safeguards provided by Bedrock Guardrails aligning with use cases and responsible AI policies. Bedrock Guardrails now offers a detect mode that provides a preview of the expected results from your configured policies allowing you to evaluate the effectiveness of the safeguards before deploying them. This enables faster iteration and accelerating time-to-product with different combinations and strengths of policies, allowing you to fine-tune your guardrails before deployment. Guardrails now offers more configurability with options to enable policies on input prompts, model responses, or both prompts and responses – a significant improvement over the previous default setting where policies were automatically applied to both inputs and outputs. Providing finer-grained control enables you to selectively apply the safeguards to make them work for you. Bedrock Guardrails offers sensitive information filters that detect personally identifiable information (PIIs) with two modes: Block where requests containing sensitive information are completely blocked, and Mask where sensitive information is redacted and replaced with identifier tags. You can now use either of these two modes for both input prompts and model responses giving you flexibility and ease of use to safely build generative AI applications at scale. These new capabilities are available in all AWS regions where Amazon Bedrock Guardrails is supported. To learn more, see the blog post, technical documentation and the Bedrock Guardrails product page.  

At re:Invent 2024, AWS announced the preview of prompt caching, a new capability that can reduce costs by up to 90% and latency by up to 85% by caching frequently used prompts across multiple API calls. Today, AWS is launching prompt caching in generally availability on Amazon Bedrock.

Prompt caching allows you to cache repetitive inputs and avoid reprocessing context such as long system prompts and common examples that help guide the model’s response. When you use prompt caching, fewer computing resources are needed to process your inputs. As a result, not only can we process your request faster, but we can also pass along the cost savings.

Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading AI companies via a single API. Amazon Bedrock also provides a broad set of capabilities customers need to build generative AI applications with security, privacy, and responsible AI capabilities built in. These capabilities help you build tailored applications for multiple use cases across different industries, helping organizations unlock sustained growth from generative AI while providing tools to build customer trust and data governance.

Prompt caching is now generally available for Anthropic’s Claude 3.5 Haiku and Claude 3.7 Sonnet, Nova Micro, Nova Lite, and Nova Pro models. Customers who were given access to Claude 3.5 Sonnet v2 during the prompt caching preview will retain their access, however no additional customers will be granted access to prompt caching on the Claude 3.5 Sonnet v2 model. For regional availability or to learn more about prompt caching, please see our documentation and blog.

 

​At re:Invent 2024, AWS announced the preview of prompt caching, a new capability that can reduce costs by up to 90% and latency by up to 85% by caching frequently used prompts across multiple API calls. Today, AWS is launching prompt caching in generally availability on Amazon Bedrock. Prompt caching allows you to cache repetitive inputs and avoid reprocessing context such as long system prompts and common examples that help guide the model’s response. When you use prompt caching, fewer computing resources are needed to process your inputs. As a result, not only can we process your request faster, but we can also pass along the cost savings. Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading AI companies via a single API. Amazon Bedrock also provides a broad set of capabilities customers need to build generative AI applications with security, privacy, and responsible AI capabilities built in. These capabilities help you build tailored applications for multiple use cases across different industries, helping organizations unlock sustained growth from generative AI while providing tools to build customer trust and data governance. Prompt caching is now generally available for Anthropic’s Claude 3.5 Haiku and Claude 3.7 Sonnet, Nova Micro, Nova Lite, and Nova Pro models. Customers who were given access to Claude 3.5 Sonnet v2 during the prompt caching preview will retain their access, however no additional customers will be granted access to prompt caching on the Claude 3.5 Sonnet v2 model. For regional availability or to learn more about prompt caching, please see our documentation and blog.  

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7i and R7i instances powered by custom 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in Asia Pacific (Melbourne) region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers.

M7i and R7i deliver up to 15% better price-performance compared to M6i and R6i instances respectively. They offer larger instance sizes up to 48xlarge, can attach up to 128 EBS volumes and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads.

In addition, all two instance types support the new Intel Advanced Matrix Extensions (AMX) that accelerate matrix multiplication operations for applications such as CPU-based ML.

To learn more, visit Amazon EC2 M7i, R7i instance pages.

 

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7i and R7i instances powered by custom 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in Asia Pacific (Melbourne) region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers. M7i and R7i deliver up to 15% better price-performance compared to M6i and R6i instances respectively. They offer larger instance sizes up to 48xlarge, can attach up to 128 EBS volumes and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads. In addition, all two instance types support the new Intel Advanced Matrix Extensions (AMX) that accelerate matrix multiplication operations for applications such as CPU-based ML. To learn more, visit Amazon EC2 M7i, R7i instance pages.  

AWS Transfer Family now enables you to delete, rename, or move files on remote SFTP servers using SFTP connectors. This enhancement allows you to easily manage files and directories stored on remote SFTP file systems and keep them up to date.

SFTP connectors provide fully managed and low-code capability to copy files between remote SFTP servers and Amazon S3. You can now organize your remote directories by deleting, renaming or moving source files to archive locations after they have been copied from the remote server. This helps you ensure that your remote directories remain current and prevent duplicate file transfers during subsequent job runs. These new features add to the existing SFTP connector functionalities, including capabilities to list remote directory contents and execute bidirectional file transfers.

SFTP connectors support for deleting, renaming and moving files on remote SFTP servers is available in all AWS Regions where AWS Transfer Family is available. To learn more about SFTP connectors, take the self paced workshop or visit the documentation. For information on pricing, see AWS Transfer Family pricing.
 

 

​AWS Transfer Family now enables you to delete, rename, or move files on remote SFTP servers using SFTP connectors. This enhancement allows you to easily manage files and directories stored on remote SFTP file systems and keep them up to date. SFTP connectors provide fully managed and low-code capability to copy files between remote SFTP servers and Amazon S3. You can now organize your remote directories by deleting, renaming or moving source files to archive locations after they have been copied from the remote server. This helps you ensure that your remote directories remain current and prevent duplicate file transfers during subsequent job runs. These new features add to the existing SFTP connector functionalities, including capabilities to list remote directory contents and execute bidirectional file transfers. SFTP connectors support for deleting, renaming and moving files on remote SFTP servers is available in all AWS Regions where AWS Transfer Family is available. To learn more about SFTP connectors, take the self paced workshop or visit the documentation. For information on pricing, see AWS Transfer Family pricing.    

AWS CodeBuild now supports enhanced debugging experience through secure and isolated sandbox environments. You can connect to the sandbox environment via SSH clients or from an IDE to interactively troubleshoot your build or test runs. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment.

With the enhanced debugging capability, you can investigate issues and validate the fixes in real-time, before committing changes to your buildspec configurations. The sandbox environment maintains a persistent file system during the debugging session, and offers the same native integration with source providers and AWS services as your build environment.

The enhanced debugging experience through sandbox environments is available in all AWS Regions where CodeBuild is offered. To learn more, please visit our documentation and pricing information. To get started with CodeBuild, visit the AWS CodeBuild product page.
 

 

​AWS CodeBuild now supports enhanced debugging experience through secure and isolated sandbox environments. You can connect to the sandbox environment via SSH clients or from an IDE to interactively troubleshoot your build or test runs. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment. With the enhanced debugging capability, you can investigate issues and validate the fixes in real-time, before committing changes to your buildspec configurations. The sandbox environment maintains a persistent file system during the debugging session, and offers the same native integration with source providers and AWS services as your build environment. The enhanced debugging experience through sandbox environments is available in all AWS Regions where CodeBuild is offered. To learn more, please visit our documentation and pricing information. To get started with CodeBuild, visit the AWS CodeBuild product page.    

We are excited to announce Amazon Nova Reel 1.1, which enables the generation of multi-shot videos up to 2-minutes in length and style consistency across shots. In addition, Amazon Nova Reel 1.1 provides quality and latency improvements in 6-second single-shot video generation over Amazon Nova Reel 1.0.

Multi-shot videos in Amazon Nova Reel 1.1 offers two modes: automated mode and manual mode. In automated mode, users can generate multiple 6-second videos by providing a single prompt and specifying the total video duration, up to 2 minutes. In manual mode, the model provides granular control, allowing users to input a text prompt and an optional image for each 6-second shot. Users can choose to receive either individual 6-second shots stored separately or a single stitched video in their S3 location.

Amazon Nova Reel 1.1 is available in US East (N. Virginia).

To learn more about Amazon Nova Reel 1.1, visit the Amazon Nova creative models page. And to get started with Amazon Nova on Amazon Bedrock, visit the Amazon Bedrock console.
 

 

​We are excited to announce Amazon Nova Reel 1.1, which enables the generation of multi-shot videos up to 2-minutes in length and style consistency across shots. In addition, Amazon Nova Reel 1.1 provides quality and latency improvements in 6-second single-shot video generation over Amazon Nova Reel 1.0. Multi-shot videos in Amazon Nova Reel 1.1 offers two modes: automated mode and manual mode. In automated mode, users can generate multiple 6-second videos by providing a single prompt and specifying the total video duration, up to 2 minutes. In manual mode, the model provides granular control, allowing users to input a text prompt and an optional image for each 6-second shot. Users can choose to receive either individual 6-second shots stored separately or a single stitched video in their S3 location. Amazon Nova Reel 1.1 is available in US East (N. Virginia). To learn more about Amazon Nova Reel 1.1, visit the Amazon Nova creative models page. And to get started with Amazon Nova on Amazon Bedrock, visit the Amazon Bedrock console.    

AWS End User Messaging now allows customers to use Internet Protocol version 6 (IPv6) addresses for their new and existing service endpoints. Customers moving to IPv6 can simplify their network stack by running their AWS End User Messaging endpoints on a network that supports both IPv4 and IPv6.

The continued growth of the Internet, particularly in the areas of mobile applications, connected devices, and IoT, has spurred an industry-wide move to IPv6. IPv6 increases the number of available addresses by several orders of magnitude so customers will no longer need to manage overlapping address spaces in their VPCs. Customers can standardize their applications on the new version of Internet Protocol by moving their AWS End User Messaging endpoints to IPv6 with AWS CLI.

Support for IPv6 on AWS End User Messaging is available in all Regions where AWS End User Messaging is available.

 

​AWS End User Messaging now allows customers to use Internet Protocol version 6 (IPv6) addresses for their new and existing service endpoints. Customers moving to IPv6 can simplify their network stack by running their AWS End User Messaging endpoints on a network that supports both IPv4 and IPv6. The continued growth of the Internet, particularly in the areas of mobile applications, connected devices, and IoT, has spurred an industry-wide move to IPv6. IPv6 increases the number of available addresses by several orders of magnitude so customers will no longer need to manage overlapping address spaces in their VPCs. Customers can standardize their applications on the new version of Internet Protocol by moving their AWS End User Messaging endpoints to IPv6 with AWS CLI. Support for IPv6 on AWS End User Messaging is available in all Regions where AWS End User Messaging is available.  

Amazon Nova Canvas now supports fine-tuning through Amazon Bedrock, enabling customers to adapt the model to their unique datasets and brand characteristics. With custom model fine-tuning, customers can train the model on their proprietary data to generate fully customized images that align with their specific requirements and style guidelines. Fine-tuned models can be tested and deployed with provisioned throughput for consistent performance.

Text-to-image models are transforming how businesses across industries create and edit visual content. From architects visualizing floor plans to fashion designers iterating on new concepts, these models accelerate innovation by enabling rapid visualization of ideas through simple text descriptions. The technology streamlines creative workflows in manufacturing, retail, gaming, and advertising while enabling personalized customer experiences through interactive visual AI.

Fine-tuning for Amazon Nova Canvas is available in US East (N. Virginia).

To learn more about Amazon Nova Canvas, see the Amazon Nova creative models page 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.

 

​Amazon Nova Canvas now supports fine-tuning through Amazon Bedrock, enabling customers to adapt the model to their unique datasets and brand characteristics. With custom model fine-tuning, customers can train the model on their proprietary data to generate fully customized images that align with their specific requirements and style guidelines. Fine-tuned models can be tested and deployed with provisioned throughput for consistent performance. Text-to-image models are transforming how businesses across industries create and edit visual content. From architects visualizing floor plans to fashion designers iterating on new concepts, these models accelerate innovation by enabling rapid visualization of ideas through simple text descriptions. The technology streamlines creative workflows in manufacturing, retail, gaming, and advertising while enabling personalized customer experiences through interactive visual AI. Fine-tuning for Amazon Nova Canvas is available in US East (N. Virginia). To learn more about Amazon Nova Canvas, see the Amazon Nova creative models page 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.  

Amazon FSx for NetApp ONTAP, a service that provides fully managed shared storage built on NetApp’s popular ONTAP file system, now supports ONTAP Autonomous Ransomware Protection (ARP). ARP is a NetApp ONTAP feature that proactively monitors your file system for unusual activity and automatically generates ONTAP snapshots when a potential attack is detected, helping you protect your business-critical data against a broader set of ransomware and malware attacks.

When enabled on your FSx for ONTAP storage volumes, ARP analyzes your workload access patterns to proactively detect suspicious activity – including changes in the randomness of data in files, the usage of unusual file extensions, and surges in abnormal volume activity with encrypted data – that might indicate a potential ransomware or malware attack. If activity is detected, ARP will automatically create a snapshot of the affected storage volume and generate alerts that you can monitor via EMS messages or the ONTAP CLI and REST API. By helping protect your file system against ransomware and malware attacks, ARP helps you maintain business continuity and improve data protection for your business-critical data stored on FSx for ONTAP.

NetApp Autonomous Ransomware Protection is now available at no additional cost for all FSx for ONTAP file systems in all AWS Regions where the service is available. For more information on how to enable ARP on your file system, see Amazon FSx for NetApp ONTAP documentation. For detailed information on ARP, see NetApp ONTAP ARP documentation.
 

 

​Amazon FSx for NetApp ONTAP, a service that provides fully managed shared storage built on NetApp’s popular ONTAP file system, now supports ONTAP Autonomous Ransomware Protection (ARP). ARP is a NetApp ONTAP feature that proactively monitors your file system for unusual activity and automatically generates ONTAP snapshots when a potential attack is detected, helping you protect your business-critical data against a broader set of ransomware and malware attacks. When enabled on your FSx for ONTAP storage volumes, ARP analyzes your workload access patterns to proactively detect suspicious activity – including changes in the randomness of data in files, the usage of unusual file extensions, and surges in abnormal volume activity with encrypted data – that might indicate a potential ransomware or malware attack. If activity is detected, ARP will automatically create a snapshot of the affected storage volume and generate alerts that you can monitor via EMS messages or the ONTAP CLI and REST API. By helping protect your file system against ransomware and malware attacks, ARP helps you maintain business continuity and improve data protection for your business-critical data stored on FSx for ONTAP. NetApp Autonomous Ransomware Protection is now available at no additional cost for all FSx for ONTAP file systems in all AWS Regions where the service is available. For more information on how to enable ARP on your file system, see Amazon FSx for NetApp ONTAP documentation. For detailed information on ARP, see NetApp ONTAP ARP documentation.