Amazon SageMaker HyperPod now integrates with Amazon EventBridge, enabling you to receive near-real time notifications about changes in your cluster’s status. With this integration, you can easily track key events such as HyperPod cluster status transitions and node health changes.

SageMaker HyperPod delivers two types of notifications via EventBridge – 1. Cluster Status Change Events, that notify you when your HyperPod cluster transitions between states, such as InService or Failed. 2) Node Health Events that notify you when nodes change health status (e.g. Healthy/Unhealthy), or are automatically replaced during recovery from failures. You can also write simple EventBridge rules to trigger automated actions when these events occur.

SageMaker HyperPod events via EventBridge are now available in all AWS regions where both SageMaker HyperPod and Amazon EventBridge are generally available.

To learn more about Amazon SageMaker HyperPod’s integration with EventBridge, visit the Amazon SageMaker AI documentation.

 

​Amazon SageMaker HyperPod now integrates with Amazon EventBridge, enabling you to receive near-real time notifications about changes in your cluster’s status. With this integration, you can easily track key events such as HyperPod cluster status transitions and node health changes. SageMaker HyperPod delivers two types of notifications via EventBridge – 1. Cluster Status Change Events, that notify you when your HyperPod cluster transitions between states, such as InService or Failed. 2) Node Health Events that notify you when nodes change health status (e.g. Healthy/Unhealthy), or are automatically replaced during recovery from failures. You can also write simple EventBridge rules to trigger automated actions when these events occur. SageMaker HyperPod events via EventBridge are now available in all AWS regions where both SageMaker HyperPod and Amazon EventBridge are generally available. To learn more about Amazon SageMaker HyperPod’s integration with EventBridge, visit the Amazon SageMaker AI documentation.  

Customers can now create Amazon FSx for Windows File Server file systems in the AWS Asia Pacific (Thailand) Region, providing fully managed shared storage built on Windows Server.

Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for Windows File Server provides fully managed, highly reliable file storage built on Windows Server and can be accessed via the industry-standard Server Message Block (SMB) protocol.

To learn more about Amazon FSx for Windows File Server, visit our product page, and see the AWS Region Table for complete regional availability information.

 

​Customers can now create Amazon FSx for Windows File Server file systems in the AWS Asia Pacific (Thailand) Region, providing fully managed shared storage built on Windows Server. Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for Windows File Server provides fully managed, highly reliable file storage built on Windows Server and can be accessed via the industry-standard Server Message Block (SMB) protocol. To learn more about Amazon FSx for Windows File Server, visit our product page, and see the AWS Region Table for complete regional availability information.  

Amazon VPC Reachability Analyzer now supports the ability to exclude network resources when analyzing reachability between a source and destination, providing you greater flexibility to run reachability analyses.

VPC Reachability Analyzer is a configuration analysis feature that enables you to check network reachability between a source resource and a destination resource in your virtual private clouds (VPCs). With this launch, you can easily identify an alternative traffic path in your network. For example, if you want to identify any path from your internet gateway to Elastic Network Interfaces (ENIs) that is not passing through the network firewall for inspection, you can specify Network Firewall under resource exclusion and run the reachability analysis. If the analysis returns a reachable path, you know there is an alternative path in your network and can take required actions.

To learn more about Amazon VPC Reachability Analyzer, please visit documentation. To view Reachability Analyzer prices, visit Amazon VPC Pricing.

 

​Amazon VPC Reachability Analyzer now supports the ability to exclude network resources when analyzing reachability between a source and destination, providing you greater flexibility to run reachability analyses. VPC Reachability Analyzer is a configuration analysis feature that enables you to check network reachability between a source resource and a destination resource in your virtual private clouds (VPCs). With this launch, you can easily identify an alternative traffic path in your network. For example, if you want to identify any path from your internet gateway to Elastic Network Interfaces (ENIs) that is not passing through the network firewall for inspection, you can specify Network Firewall under resource exclusion and run the reachability analysis. If the analysis returns a reachable path, you know there is an alternative path in your network and can take required actions. To learn more about Amazon VPC Reachability Analyzer, please visit documentation. To view Reachability Analyzer prices, visit Amazon VPC Pricing.  

Customers can now create Amazon FSx for Lustre file systems in the AWS Mexico (Central) Region, providing fully managed shared storage with the scalability and performance of the popular Lustre file system.

Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for Lustre provides fully managed shared storage built on the world’s most popular high-performance file system, designed for fast processing of workloads such as machine learning, high performance computing (HPC), video processing, financial modeling, and electronic design automation (EDA).

To learn more about Amazon FSx for Lustre, visit our product page, and see the AWS Region Table for complete regional availability information.
 

 

​Customers can now create Amazon FSx for Lustre file systems in the AWS Mexico (Central) Region, providing fully managed shared storage with the scalability and performance of the popular Lustre file system. Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for Lustre provides fully managed shared storage built on the world’s most popular high-performance file system, designed for fast processing of workloads such as machine learning, high performance computing (HPC), video processing, financial modeling, and electronic design automation (EDA). To learn more about Amazon FSx for Lustre, visit our product page, and see the AWS Region Table for complete regional availability information.    

Customers can now create Amazon FSx for Windows File Server file systems in the AWS Mexico (Central) Region, providing fully managed shared storage built on Windows Server.

Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for Windows File Server provides fully managed, highly reliable file storage built on Windows Server and can be accessed via the industry-standard Server Message Block (SMB) protocol.

To learn more about Amazon FSx for Windows File Server, visit our product page, and see the AWS Region Table for complete regional availability information.
 

 

​Customers can now create Amazon FSx for Windows File Server file systems in the AWS Mexico (Central) Region, providing fully managed shared storage built on Windows Server. Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for Windows File Server provides fully managed, highly reliable file storage built on Windows Server and can be accessed via the industry-standard Server Message Block (SMB) protocol. To learn more about Amazon FSx for Windows File Server, visit our product page, and see the AWS Region Table for complete regional availability information.    

Customers can now create Amazon FSx for NetApp ONTAP file systems in the AWS Mexico (Central) Region, providing fully managed shared storage in the cloud with the data access and management capabilities of ONTAP.

Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for NetApp ONTAP provides the first and only complete, fully managed NetApp ONTAP file systems in the cloud. It offers the familiar features, performance, capabilities, and APIs of ONTAP with the agility, scalability, and simplicity of an AWS service.

To learn more about Amazon FSx for NetApp ONTAP, visit our product page, and see the AWS Region Table for complete regional availability information.
 

 

​Customers can now create Amazon FSx for NetApp ONTAP file systems in the AWS Mexico (Central) Region, providing fully managed shared storage in the cloud with the data access and management capabilities of ONTAP. Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for NetApp ONTAP provides the first and only complete, fully managed NetApp ONTAP file systems in the cloud. It offers the familiar features, performance, capabilities, and APIs of ONTAP with the agility, scalability, and simplicity of an AWS service. To learn more about Amazon FSx for NetApp ONTAP, visit our product page, and see the AWS Region Table for complete regional availability information.    

Customers can now create Amazon FSx for OpenZFS file systems in the AWS Mexico (Central) Region, providing fully managed shared file storage built on the OpenZFS file system..

Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for OpenZFS provides fully managed, cost-effective, shared file storage powered by the popular OpenZFS file system, and is designed to deliver sub-millisecond latencies and multi-GB/s throughput along with rich ZFS-powered data management capabilities (like snapshots, data cloning, and compression).

To learn more about Amazon FSx for OpenZFS, visit our product page, and see the AWS Region Table for complete regional availability information.
 

 

​Customers can now create Amazon FSx for OpenZFS file systems in the AWS Mexico (Central) Region, providing fully managed shared file storage built on the OpenZFS file system.. Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for OpenZFS provides fully managed, cost-effective, shared file storage powered by the popular OpenZFS file system, and is designed to deliver sub-millisecond latencies and multi-GB/s throughput along with rich ZFS-powered data management capabilities (like snapshots, data cloning, and compression). To learn more about Amazon FSx for OpenZFS, visit our product page, and see the AWS Region Table for complete regional availability information.    

Amazon Connect now has new pricing models for external voice transfer and Contact Lens with external voice systems. The new pricing models have independent pricing for external voice connectors and external voice minutes and are effective for all customers from May 1, 2025.

External voice transfer directly transfers voice calls and metadata from Amazon Connect to another voice system, so you can use Amazon Connect telephony and Interactive Voice Response (IVR) to help improve customer experience. Each external transfer connector is now $3,100 per month and each external voice transfer is $0.005 per minute.

Contact Lens with external voice enables Connect Contact Lens contact records, call recording, real-time and post-call analytics, and agent evaluations with your existing voice system to help improve customer experience and agent performance. Each external voice connector is now $3,100 per month and each external voice minute is $0.012 per minute. Standard Contact Lens conversational analytics and performance evaluation charges apply when used with external voice.

Amazon Connect external voice transfer and Contact Lens with external voice are available in the US East (N. Virginia) and US West (Oregon) AWS Regions. To learn more about Amazon Connect and other voice systems, review the following resources:

• Amazon Connect website and pricing
• External voice transfer – Amazon Connect Administrator Guide
• Contact Lens with external voice – Amazon Connect Administrator Guide

 

​Amazon Connect now has new pricing models for external voice transfer and Contact Lens with external voice systems. The new pricing models have independent pricing for external voice connectors and external voice minutes and are effective for all customers from May 1, 2025. External voice transfer directly transfers voice calls and metadata from Amazon Connect to another voice system, so you can use Amazon Connect telephony and Interactive Voice Response (IVR) to help improve customer experience. Each external transfer connector is now $3,100 per month and each external voice transfer is $0.005 per minute. Contact Lens with external voice enables Connect Contact Lens contact records, call recording, real-time and post-call analytics, and agent evaluations with your existing voice system to help improve customer experience and agent performance. Each external voice connector is now $3,100 per month and each external voice minute is $0.012 per minute. Standard Contact Lens conversational analytics and performance evaluation charges apply when used with external voice. Amazon Connect external voice transfer and Contact Lens with external voice are available in the US East (N. Virginia) and US West (Oregon) AWS Regions. To learn more about Amazon Connect and other voice systems, review the following resources:

Amazon Connect website and pricing
External voice transfer – Amazon Connect Administrator Guide
Contact Lens with external voice – Amazon Connect Administrator Guide  

Amazon DocumentDB (with MongoDB compatibility), a fully managed, native JSON database that makes it simple and cost-effective to operate critical document workloads at virtually any scale without managing infrastructure, is now available in the AWS Europe (Stockholm) Region. Amazon DocumentDB provides scalability and durability for mission-critical MongoDB workloads, supporting millions of requests per second and can be scaled to 15 low latency read replicas in minutes without application downtime. Storage scales automatically up to 128 TiB without any impact to your application. In addition, Amazon DocumentDB natively integrates with AWS Database Migration Service (DMS), Amazon CloudWatch, AWS CloudTrail, AWS Lambda, AWS Backup and more.

To learn more about Amazon DocumentDB, please visit the Amazon DocumentDB product page, and see the AWS Region Table for complete regional availability.

You can create a Amazon DocumentDB cluster from the AWS Management console, AWS Command Line Interface (CLI), or SDK.

 

​Amazon DocumentDB (with MongoDB compatibility), a fully managed, native JSON database that makes it simple and cost-effective to operate critical document workloads at virtually any scale without managing infrastructure, is now available in the AWS Europe (Stockholm) Region. Amazon DocumentDB provides scalability and durability for mission-critical MongoDB workloads, supporting millions of requests per second and can be scaled to 15 low latency read replicas in minutes without application downtime. Storage scales automatically up to 128 TiB without any impact to your application. In addition, Amazon DocumentDB natively integrates with AWS Database Migration Service (DMS), Amazon CloudWatch, AWS CloudTrail, AWS Lambda, AWS Backup and more. To learn more about Amazon DocumentDB, please visit the Amazon DocumentDB product page, and see the AWS Region Table for complete regional availability. You can create a Amazon DocumentDB cluster from the AWS Management console, AWS Command Line Interface (CLI), or SDK.  

Today, AWS announces significant enhancements to Amazon Q Developer in Amazon SageMaker AI Jupyter Lab, introducing customization of code suggestions based on private code repositories and the ability to include entire workspace context for improved code assistance. These new features empower organizations to leverage their proprietary code and improve the relevance of code suggestions, ultimately enhancing developer productivity and code quality within Jupyter Lab environments.

With the new customization feature, Amazon Q Developer can now assist with software development in ways that conform to your team’s internal libraries, proprietary algorithmic techniques, and enterprise code style. An Amazon Q Developer customization is a set of elements that enables Amazon Q to provide suggestions based on your company’s code-base. This ensures that code suggestions, both inline and chat based, align perfectly with your organization’s specific coding practices and standards.

Additionally, the workspace context enables Amazon Q Developer to locate files, understand how code is used across multiple files, and generate code that leverages multiple files, including those that aren’t currently opened. This contextual awareness results in more accurate and relevant code assistance, helping developers better understand their entire project structure before they start coding. Users can access the workspace features through the chat interface, ensuring a seamless development experience that takes into account the full scope of their project.

These enhancements to Amazon Q Developer in Amazon SageMaker AI Jupyter Lab are now available in All Regions where Amazon SageMaker AI is offered.

To learn more about these new features see documentation.
 

 

​Today, AWS announces significant enhancements to Amazon Q Developer in Amazon SageMaker AI Jupyter Lab, introducing customization of code suggestions based on private code repositories and the ability to include entire workspace context for improved code assistance. These new features empower organizations to leverage their proprietary code and improve the relevance of code suggestions, ultimately enhancing developer productivity and code quality within Jupyter Lab environments. With the new customization feature, Amazon Q Developer can now assist with software development in ways that conform to your team’s internal libraries, proprietary algorithmic techniques, and enterprise code style. An Amazon Q Developer customization is a set of elements that enables Amazon Q to provide suggestions based on your company’s code-base. This ensures that code suggestions, both inline and chat based, align perfectly with your organization’s specific coding practices and standards. Additionally, the workspace context enables Amazon Q Developer to locate files, understand how code is used across multiple files, and generate code that leverages multiple files, including those that aren’t currently opened. This contextual awareness results in more accurate and relevant code assistance, helping developers better understand their entire project structure before they start coding. Users can access the workspace features through the chat interface, ensuring a seamless development experience that takes into account the full scope of their project. These enhancements to Amazon Q Developer in Amazon SageMaker AI Jupyter Lab are now available in All Regions where Amazon SageMaker AI is offered. To learn more about these new features see documentation.