Amazon Connect forecasting, capacity planning, and scheduling is now available in AWS GovCloud (US-West). This feature helps you predict contact volumes, allocate agents efficiently, and ensure optimal agent scheduling to meet operational goals while minimizing overstaffing. Using machine learning, it anticipates contact volume and arrival rates, converts forecasts into staffing projections, and assigns daily shifts accordingly. By optimizing operations and helping meet service level goals, Amazon Connect forecasting, capacity planning, and scheduling helps businesses improve both agent productivity and customer satisfaction.

To learn more, please visit our documentation, our webpage, and pricing page. You can purchase Amazon Connect forecasting, capacity planning, and scheduling along with other Amazon Connect AI capabilities through simplified channel-based pricing (e.g. by voice, by chat, by messaging).

 

​Amazon Connect forecasting, capacity planning, and scheduling is now available in AWS GovCloud (US-West). This feature helps you predict contact volumes, allocate agents efficiently, and ensure optimal agent scheduling to meet operational goals while minimizing overstaffing. Using machine learning, it anticipates contact volume and arrival rates, converts forecasts into staffing projections, and assigns daily shifts accordingly. By optimizing operations and helping meet service level goals, Amazon Connect forecasting, capacity planning, and scheduling helps businesses improve both agent productivity and customer satisfaction. To learn more, please visit our documentation, our webpage, and pricing page. You can purchase Amazon Connect forecasting, capacity planning, and scheduling along with other Amazon Connect AI capabilities through simplified channel-based pricing (e.g. by voice, by chat, by messaging).  

Today, we’re announcing general availability of Amazon SageMaker HyperPod training operator, a purpose-built Kubernetes extension for resilient foundation model training on HyperPod.

Amazon SageMaker HyperPod empowers customers to accelerate AI model development across hundreds or thousands of GPUs with built-in resiliency, decreasing model training time by up to 40%. As training clusters expand, recovery from training interruptions becomes increasingly disruptive. Failure recovery traditionally requires a complete job restart across all nodes when even a single training process fails, resulting in additional downtime and increased costs. Moreover, identifying and resolving critical training issues such as stalled GPUs, low training throughput, and numerical instabilities, typically requires complex custom monitoring code, further extending development timelines and delaying time to market.

With the HyperPod training operator, customers can further enhance training resilience for Kubernetes workloads. Instead of a full job restart when failures occur, the HyperPod training operator performs surgical recovery, selectively restarting only the affected training resources for faster recovery from faults. It also introduces a customizable hanging job monitoring capability to help overcome problematic training scenarios including stalled training batches, non-numeric loss values, and performance degradation through simple YAML configurations. Getting started is simple: create a HyperPod cluster, install the training operator add-on, optionally define custom recovery policies for hanging jobs, and launch training.

This release is generally available in all AWS Regions where SageMaker HyperPod is currently supported.

See the documentation to learn more.

 

​Today, we’re announcing general availability of Amazon SageMaker HyperPod training operator, a purpose-built Kubernetes extension for resilient foundation model training on HyperPod.
Amazon SageMaker HyperPod empowers customers to accelerate AI model development across hundreds or thousands of GPUs with built-in resiliency, decreasing model training time by up to 40%. As training clusters expand, recovery from training interruptions becomes increasingly disruptive. Failure recovery traditionally requires a complete job restart across all nodes when even a single training process fails, resulting in additional downtime and increased costs. Moreover, identifying and resolving critical training issues such as stalled GPUs, low training throughput, and numerical instabilities, typically requires complex custom monitoring code, further extending development timelines and delaying time to market. With the HyperPod training operator, customers can further enhance training resilience for Kubernetes workloads. Instead of a full job restart when failures occur, the HyperPod training operator performs surgical recovery, selectively restarting only the affected training resources for faster recovery from faults. It also introduces a customizable hanging job monitoring capability to help overcome problematic training scenarios including stalled training batches, non-numeric loss values, and performance degradation through simple YAML configurations. Getting started is simple: create a HyperPod cluster, install the training operator add-on, optionally define custom recovery policies for hanging jobs, and launch training. This release is generally available in all AWS Regions where SageMaker HyperPod is currently supported.
See the documentation to learn more.  

Amazon Connect now lets you maintain a synchronized instance in Asia Pacific (Osaka) that mirrors the channel configurations and service quotas of your Asia Pacific (Tokyo) environment. With a resiliency instance in Asia Pacific (Osaka), you can replicate your Amazon Connect configurations, such as users, routing profiles, and flows, and configure traffic distribution settings to pre-define groups of users and phone numbers to shift between Asia Pacific (Tokyo) and Asia Pacific (Osaka), enabling your resiliency instance to handle new incoming traffic after switching regions.

To get started, you first need to set up an Amazon Connect instance in Asia Pacific (Tokyo) as your primary region. You can then create a replica instance for Amazon Connect in the Asia Pacific (Osaka) region. To learn more about Amazon Connect Global Resiliency, see the Amazon Connect Administrator Guide and Amazon Connect API Reference. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website.
 

 

​Amazon Connect now lets you maintain a synchronized instance in Asia Pacific (Osaka) that mirrors the channel configurations and service quotas of your Asia Pacific (Tokyo) environment. With a resiliency instance in Asia Pacific (Osaka), you can replicate your Amazon Connect configurations, such as users, routing profiles, and flows, and configure traffic distribution settings to pre-define groups of users and phone numbers to shift between Asia Pacific (Tokyo) and Asia Pacific (Osaka), enabling your resiliency instance to handle new incoming traffic after switching regions. To get started, you first need to set up an Amazon Connect instance in Asia Pacific (Tokyo) as your primary region. You can then create a replica instance for Amazon Connect in the Asia Pacific (Osaka) region. To learn more about Amazon Connect Global Resiliency, see the Amazon Connect Administrator Guide and Amazon Connect API Reference. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website.    

AWS Transfer Family announces Internet Protocol version 6 (IPv6) support for server endpoints and service APIs. This enhancement enables both IPv6 and IPv4 clients to communicate with Transfer Family SFTP, FTPS, FTP, and AS2 server endpoints. You can also use IPv6 while accessing the Transfer Family service APIs.

AWS Transfer Family offers fully managed support for file transfers over SFTP, AS2, FTPS, FTP, and web browser-based transfers. The addition of IPv6 support provides you with a vastly expanded address space, eliminating concerns about address exhaustion and simplifying network architecture for IPv6-native applications. With dual-stack support for both IPv4 and IPv6 clients on AWS Transfer Family endpoints, you can transition from IPv4 to IPv6, without needing to switch all systems at once.

AWS Transfer Family support for IPv6 is available in all AWS Regions where the service is available. To learn more, visit the Transfer Family User Guide.

 

​AWS Transfer Family announces Internet Protocol version 6 (IPv6) support for server endpoints and service APIs. This enhancement enables both IPv6 and IPv4 clients to communicate with Transfer Family SFTP, FTPS, FTP, and AS2 server endpoints. You can also use IPv6 while accessing the Transfer Family service APIs. AWS Transfer Family offers fully managed support for file transfers over SFTP, AS2, FTPS, FTP, and web browser-based transfers. The addition of IPv6 support provides you with a vastly expanded address space, eliminating concerns about address exhaustion and simplifying network architecture for IPv6-native applications. With dual-stack support for both IPv4 and IPv6 clients on AWS Transfer Family endpoints, you can transition from IPv4 to IPv6, without needing to switch all systems at once. AWS Transfer Family support for IPv6 is available in all AWS Regions where the service is available. To learn more, visit the Transfer Family User Guide.  

Amazon Bedrock introduces Citations API and PDF support for Anthropic’s Claude Models that empower developers to build more trustworthy AI applications and expand document processing capabilities. The Citations API allows Claude to ground its answers in source documents, providing detailed references to the exact sentences and passages used to generate responses. This leads to more verifiable and trustworthy outputs, crucial for applications requiring high accuracy and transparency.

With the new Citations API, developers can enhance the reliability of their AI-powered applications. This feature is particularly valuable in fields such as legal research, academic writing, and fact-checking, where the ability to trace information back to its source is critical. PDF support for Claude further extends Amazon Bedrock’s capabilities, allowing users to extract text, analyze charts, and understand visual content from PDF documents. This comprehensive document analysis enables more efficient processing of complex documents, making it easier for businesses to derive insights from their existing PDF libraries.

The Citations API and PDF support for Claude are available for Claude Opus 4, Claude Sonnet 4, Claude Sonnet 3.7, Claude Sonnet 3.5v2. The functionality will be available in all regions where these models are supported. These features can be accessed through Amazon Bedrock’s Invoke Model and Converse APIs, allowing for seamless integration into existing workflows and applications.

To learn more about these new features and how they can benefit your AI applications, visit the API Documentation for detailed information on implementation.

 

​Amazon Bedrock introduces Citations API and PDF support for Anthropic’s Claude Models that empower developers to build more trustworthy AI applications and expand document processing capabilities. The Citations API allows Claude to ground its answers in source documents, providing detailed references to the exact sentences and passages used to generate responses. This leads to more verifiable and trustworthy outputs, crucial for applications requiring high accuracy and transparency. With the new Citations API, developers can enhance the reliability of their AI-powered applications. This feature is particularly valuable in fields such as legal research, academic writing, and fact-checking, where the ability to trace information back to its source is critical. PDF support for Claude further extends Amazon Bedrock’s capabilities, allowing users to extract text, analyze charts, and understand visual content from PDF documents. This comprehensive document analysis enables more efficient processing of complex documents, making it easier for businesses to derive insights from their existing PDF libraries. The Citations API and PDF support for Claude are available for Claude Opus 4, Claude Sonnet 4, Claude Sonnet 3.7, Claude Sonnet 3.5v2. The functionality will be available in all regions where these models are supported. These features can be accessed through Amazon Bedrock’s Invoke Model and Converse APIs, allowing for seamless integration into existing workflows and applications.
To learn more about these new features and how they can benefit your AI applications, visit the API Documentation for detailed information on implementation.  

AWS Control Tower and Control Catalog APIs now come with AWS PrivateLink support, allowing you to invoke AWS Control Tower and Control Catalog APIs from within your Amazon Virtual Private Cloud (VPC) without traversing the public internet. AWS PrivateLink provides private connectivity between virtual private clouds (VPCs), supported services and resources, and your on-premises networks, without exposing your traffic to the public internet.

AWS Control Tower simplifies managing a secure, compliant multi-account environment within an AWS Organization. Customers enable AWS services like Config, CloudTrail, and Identity Center with AWS-recommended configurations through Control Tower, ensuring that all accounts in each Organization Unit (OU) adhere to the same baseline defined by the IT administrator. Applications running inside these accounts are governed via managed controls deployed through the Control Catalog in Control Tower, ensuring compliance with business requirements and regulatory policies on an ongoing basis.

AWS PrivateLink support for AWS Control Tower is available in all AWS Regions where AWS Control Tower is available. For a full list of AWS regions where AWS Control Tower is available, see AWS Region Table. You can start deploying AWS Control Tower from the console or using AWS Control Tower APIs.
 

 

​AWS Control Tower and Control Catalog APIs now come with AWS PrivateLink support, allowing you to invoke AWS Control Tower and Control Catalog APIs from within your Amazon Virtual Private Cloud (VPC) without traversing the public internet. AWS PrivateLink provides private connectivity between virtual private clouds (VPCs), supported services and resources, and your on-premises networks, without exposing your traffic to the public internet. AWS Control Tower simplifies managing a secure, compliant multi-account environment within an AWS Organization. Customers enable AWS services like Config, CloudTrail, and Identity Center with AWS-recommended configurations through Control Tower, ensuring that all accounts in each Organization Unit (OU) adhere to the same baseline defined by the IT administrator. Applications running inside these accounts are governed via managed controls deployed through the Control Catalog in Control Tower, ensuring compliance with business requirements and regulatory policies on an ongoing basis. AWS PrivateLink support for AWS Control Tower is available in all AWS Regions where AWS Control Tower is available. For a full list of AWS regions where AWS Control Tower is available, see AWS Region Table. You can start deploying AWS Control Tower from the console or using AWS Control Tower APIs.    

Starting today, Amazon DynamoDB global tables now supports multi-Region strong consistency. DynamoDB global tables is a fully managed, serverless, multi-Region, and multi-active database used by tens of thousands of customers. With this new capability, you can now build highly available multi-Region applications with a recovery point objective (RPO) of zero, achieving the highest level of resilience.

DynamoDB global tables with multi-Region strong consistency provides the highest level of application resilience enabling applications to be always available and always read the latest data from any Region. It also removes the undifferentiated heavy lifting of managing strongly consistent replication. Multi-Region strong consistency is ideal for building global applications with strict consistency requirements like user profile management, inventory tracking, and financial transaction processing.

DynamoDB global tables with multi-Region strong consistency is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Europe (London), Europe (Paris), Europe (Frankfurt), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Asia Pacific (Osaka). Global tables with multi-Region strong consistency is billed according to current global tables pricing.

To get started with multi-Region strong consistency, see the DynamoDB Developer Guide, and visit the DynamoDB global tables page to learn more about building resilient multi-Region applications.

 

​Starting today, Amazon DynamoDB global tables now supports multi-Region strong consistency. DynamoDB global tables is a fully managed, serverless, multi-Region, and multi-active database used by tens of thousands of customers. With this new capability, you can now build highly available multi-Region applications with a recovery point objective (RPO) of zero, achieving the highest level of resilience. DynamoDB global tables with multi-Region strong consistency provides the highest level of application resilience enabling applications to be always available and always read the latest data from any Region. It also removes the undifferentiated heavy lifting of managing strongly consistent replication. Multi-Region strong consistency is ideal for building global applications with strict consistency requirements like user profile management, inventory tracking, and financial transaction processing. DynamoDB global tables with multi-Region strong consistency is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Europe (London), Europe (Paris), Europe (Frankfurt), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Asia Pacific (Osaka). Global tables with multi-Region strong consistency is billed according to current global tables pricing. To get started with multi-Region strong consistency, see the DynamoDB Developer Guide, and visit the DynamoDB global tables page to learn more about building resilient multi-Region applications.  

Starting today, AWS Global Accelerator supports application endpoints in two additional AWS Regions, AWS Mexico (Central) Region and Asia Pacific (Malaysia) Region, expanding the number of supported AWS Regions to thirty one.

AWS Global Accelerator is a service that is designed to help you improve the availability, security, and performance of your internet-facing applications. By using the congestion-free AWS network, end-user traffic to your applications benefits from increased availability, DDoS protection at the edge, and higher performance relative to the public internet. Global Accelerator provides static IP addresses that act as fixed entry endpoints for your application resources in one or more AWS Regions, such as your Application Load Balancers, Network Load Balancers, Amazon EC2 instances, or Elastic IPs. Global Accelerator continually monitors the health of your application endpoints and offers deterministic fail-over for multi-region workloads without any DNS dependencies.

To get started, visit the AWS Global Accelerator website and review its documentation.
 

 

​Starting today, AWS Global Accelerator supports application endpoints in two additional AWS Regions, AWS Mexico (Central) Region and Asia Pacific (Malaysia) Region, expanding the number of supported AWS Regions to thirty one. AWS Global Accelerator is a service that is designed to help you improve the availability, security, and performance of your internet-facing applications. By using the congestion-free AWS network, end-user traffic to your applications benefits from increased availability, DDoS protection at the edge, and higher performance relative to the public internet. Global Accelerator provides static IP addresses that act as fixed entry endpoints for your application resources in one or more AWS Regions, such as your Application Load Balancers, Network Load Balancers, Amazon EC2 instances, or Elastic IPs. Global Accelerator continually monitors the health of your application endpoints and offers deterministic fail-over for multi-region workloads without any DNS dependencies. To get started, visit the AWS Global Accelerator website and review its documentation.    

You can now use AWS PrivateLink to privately access Amazon ElastiCache from your Amazon Virtual Private Cloud (Amazon VPC) in Asia Pacific (Thailand), Asia Pacific (Melbourne), Asia Pacific (Malaysia), Middle East (UAE), Mexico (Central), Israel (Tel Aviv), Canada West (Calgary) and Europe (Zurich) Regions. AWS PrivateLink provides private connectivity between VPCs, AWS services, and on-premises networks, without exposing traffic to the public internet and securing your network traffic.

To use AWS PrivateLink with Amazon ElastiCache, you create an interface VPC endpoint for Amazon ElastiCache in your VPC using the Amazon VPC console, AWS SDK, or AWS CLI. With an interface VPC endpoint, you can privately access the Amazon ElastiCache APIs from applications inside your Amazon VPC. You can also access the VPC endpoint from other VPCs using VPC Peering or your on-premises environments using AWS VPN or AWS Direct Connect. To learn more, and see a complete list of supported Regions, read the documentation or get started in the Amazon VPC Console.

 

​You can now use AWS PrivateLink to privately access Amazon ElastiCache from your Amazon Virtual Private Cloud (Amazon VPC) in Asia Pacific (Thailand), Asia Pacific (Melbourne), Asia Pacific (Malaysia), Middle East (UAE), Mexico (Central), Israel (Tel Aviv), Canada West (Calgary) and Europe (Zurich) Regions. AWS PrivateLink provides private connectivity between VPCs, AWS services, and on-premises networks, without exposing traffic to the public internet and securing your network traffic. To use AWS PrivateLink with Amazon ElastiCache, you create an interface VPC endpoint for Amazon ElastiCache in your VPC using the Amazon VPC console, AWS SDK, or AWS CLI. With an interface VPC endpoint, you can privately access the Amazon ElastiCache APIs from applications inside your Amazon VPC. You can also access the VPC endpoint from other VPCs using VPC Peering or your on-premises environments using AWS VPN or AWS Direct Connect. To learn more, and see a complete list of supported Regions, read the documentation or get started in the Amazon VPC Console.  

Today, AWS announces the general availability of the new Amazon Elastic Compute Cloud (Amazon EC2) C8gn instances, powered by the latest-generation AWS Graviton4 processors. The new instances provide up to 30% better compute performance than Graviton3-based Amazon EC2 C7gn instances. Amazon EC2 C8gn instances feature the latest 6th generation AWS Nitro Cards, and offer up to 600 Gbps network bandwidth, the highest network bandwidth among network optimized EC2 instances.

Take advantage of the enhanced networking capabilities of C8gn to scale performance and throughput, while optimizing the cost of running network-intensive workloads such as network virtual appliances, data analytics, CPU-based artificial intelligence and machine learning (AI/ML) inference.

For increased scalability, C8gn instances offer instance sizes up to 48xlarge, up to 384 GiB of memory, and up to 60 Gbps of bandwidth to Amazon Elastic Block Store (EBS). C8gn instances support Elastic Fabric Adapter (EFA) networking on the 16xlarge, 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes, which enables lower latency and improved cluster performance for workloads deployed on tightly coupled clusters.

C8gn instances are available in the following AWS Regions: US East (N. Virginia), and US West (Oregon). The metal instances are only available in US East (N. Virginia).

To learn more, see Amazon C8gn Instances. To begin your Graviton journey, visit the Level up your compute with AWS Graviton page. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.

 

​Today, AWS announces the general availability of the new Amazon Elastic Compute Cloud (Amazon EC2) C8gn instances, powered by the latest-generation AWS Graviton4 processors. The new instances provide up to 30% better compute performance than Graviton3-based Amazon EC2 C7gn instances. Amazon EC2 C8gn instances feature the latest 6th generation AWS Nitro Cards, and offer up to 600 Gbps network bandwidth, the highest network bandwidth among network optimized EC2 instances. Take advantage of the enhanced networking capabilities of C8gn to scale performance and throughput, while optimizing the cost of running network-intensive workloads such as network virtual appliances, data analytics, CPU-based artificial intelligence and machine learning (AI/ML) inference. For increased scalability, C8gn instances offer instance sizes up to 48xlarge, up to 384 GiB of memory, and up to 60 Gbps of bandwidth to Amazon Elastic Block Store (EBS). C8gn instances support Elastic Fabric Adapter (EFA) networking on the 16xlarge, 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes, which enables lower latency and improved cluster performance for workloads deployed on tightly coupled clusters. C8gn instances are available in the following AWS Regions: US East (N. Virginia), and US West (Oregon). The metal instances are only available in US East (N. Virginia). To learn more, see Amazon C8gn Instances. To begin your Graviton journey, visit the Level up your compute with AWS Graviton page. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.