AWS Site-to-Site VPN is extending three new capabilities, including AWS Secrets Manager integration, for enhanced security and ease of configuration in AWS GovCloud (US) Regions and AWS Europe (Milan) Region.

• AWS Secrets Manager Integration: With the AWS Secrets Manager integration, when customers store their pre-shared keys (PSKs) in Secrets Manager, VPN connection API responses will redact the PSK and instead display the Secrets Manager ARN (Amazon Resource Name), providing enhanced security.
• New API to track VPN algorithms: You can now easily track the currently negotiated internet key exchange (IKE) version, Diffie-Hellman (DH) groups, encryption algorithms, and integrity algorithms using the “GetActiveVpnTunnelStatus” API. This new API eliminates the need for you to enable Site-to-Site VPN logs to get this information, saving time and reducing operational overhead.
• Recommended Configuration: “GetVpnConnectionDeviceSampleConfiguration” API now includes “recommended” parameter to help you use the best-practices security configuration – IKE version 2, DH group 20, SHA-384 integrity algorithm, and AES-GCM-256 encryption algorithm – on your customer gateway devices, reducing configuration time and potential errors.

There is no additional charge for using these capabilities. To learn more and get started, visit the AWS Site-to-Site VPN documentation.

​AWS Site-to-Site VPN is extending three new capabilities, including AWS Secrets Manager integration, for enhanced security and ease of configuration in AWS GovCloud (US) Regions and AWS Europe (Milan) Region.

AWS Secrets Manager Integration: With the AWS Secrets Manager integration, when customers store their pre-shared keys (PSKs) in Secrets Manager, VPN connection API responses will redact the PSK and instead display the Secrets Manager ARN (Amazon Resource Name), providing enhanced security.
New API to track VPN algorithms: You can now easily track the currently negotiated internet key exchange (IKE) version, Diffie-Hellman (DH) groups, encryption algorithms, and integrity algorithms using the “GetActiveVpnTunnelStatus” API. This new API eliminates the need for you to enable Site-to-Site VPN logs to get this information, saving time and reducing operational overhead.
Recommended Configuration: “GetVpnConnectionDeviceSampleConfiguration” API now includes “recommended” parameter to help you use the best-practices security configuration – IKE version 2, DH group 20, SHA-384 integrity algorithm, and AES-GCM-256 encryption algorithm – on your customer gateway devices, reducing configuration time and potential errors.

There is no additional charge for using these capabilities. To learn more and get started, visit the AWS Site-to-Site VPN documentation.  

Today, AWS announces the general availability of Neuron 2.24, delivering new features and performance improvements for customers building and deploying deep learning models on AWS Inferentia and Trainium-based instances. Neuron 2.24 introduces support for PyTorch 2.7, enhanced inference capabilities, and expanded compatibility with popular machine learning frameworks. These updates help developers and data scientists accelerate model training and inference, improve efficiency, and simplify the deployment of large language models and other AI workloads.

With Neuron 2.24, customers can take advantage of advanced inference features such as prefix caching for faster Time-To-First-Token (TTFT), disaggregated inference to reduce prefill-decode interference, and context parallelism for improved performance on long sequences. The release also brings support for Qwen 2.5 text models and improved integration with Hugging Face Optimum Neuron and PyTorch-based NxD Core backend.

Neuron 2.24 is available in all AWS Regions where Inferentia and Trainium instances are offered.

To learn more and for a full list of new features and enhancements, see:

• AWS Neuron 2.24 release notes
• Trn2 Instances
• Trn1 Instances
• Inf2 Instances

​Today, AWS announces the general availability of Neuron 2.24, delivering new features and performance improvements for customers building and deploying deep learning models on AWS Inferentia and Trainium-based instances. Neuron 2.24 introduces support for PyTorch 2.7, enhanced inference capabilities, and expanded compatibility with popular machine learning frameworks. These updates help developers and data scientists accelerate model training and inference, improve efficiency, and simplify the deployment of large language models and other AI workloads. With Neuron 2.24, customers can take advantage of advanced inference features such as prefix caching for faster Time-To-First-Token (TTFT), disaggregated inference to reduce prefill-decode interference, and context parallelism for improved performance on long sequences. The release also brings support for Qwen 2.5 text models and improved integration with Hugging Face Optimum Neuron and PyTorch-based NxD Core backend. Neuron 2.24 is available in all AWS Regions where Inferentia and Trainium instances are offered. To learn more and for a full list of new features and enhancements, see:

AWS Neuron 2.24 release notes
Trn2 Instances
Trn1 Instances
Inf2 Instances  

Amazon Q Business, the generative AI-powered assistant for finding information, gaining insight, and taking action at work, today introduced response customization for Q Business applications. This new capability enables organizations to tailor how their Q Business applications generate and format responses to user queries, ensuring consistent communication for all users.

With response customization, customers can provide instructions for identity, tone, and output style when configuring Q Business applications. This customizes the chat persona and its communication formality, along with response length and detail to match their specific needs. This feature includes built-in guardrails to ensure that response settings align with existing admin controls.

Response customization is available in all AWS Regions where Amazon Q Business is offered. To learn more about this feature, visit the Amazon Q Business User Guide and Amazon Q Business API Reference documentation.
 

​Amazon Q Business, the generative AI-powered assistant for finding information, gaining insight, and taking action at work, today introduced response customization for Q Business applications. This new capability enables organizations to tailor how their Q Business applications generate and format responses to user queries, ensuring consistent communication for all users. With response customization, customers can provide instructions for identity, tone, and output style when configuring Q Business applications. This customizes the chat persona and its communication formality, along with response length and detail to match their specific needs. This feature includes built-in guardrails to ensure that response settings align with existing admin controls. Response customization is available in all AWS Regions where Amazon Q Business is offered. To learn more about this feature, visit the Amazon Q Business User Guide and Amazon Q Business API Reference documentation.    

Amazon Keyspaces (for Apache Cassandra) now supports Change Data Capture (CDC) streams, enabling you to capture row-level changes in your tables in near-real time. CDC streams in Amazon Keyspaces automatically capture insert, update, and delete operations as change events, delivering them in order with automatic deduplication. With CDC streams, you can build event-driven applications and implement use cases such as data analytics, text search, ML training/inference, and continuous data backups for archival.

Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage.

CDC streams retain data for up to 24 hours and can scale automatically to match your workload, without requiring any infrastructure management. Additionally, enabling CDC streams will have no impact on your table capacity for compute or storage operations. To consume the CDC stream records, you can use either the Keyspaces Data Streams API or leverage the Kinesis Client Library, a java library that makes it easy to consume and process stream records.

CDC streams are available today in all AWS Commercial and AWS GovCloud (US) Regions where Amazon Keyspaces is available, and you pay only for the change events captured and delivered through your streams. To learn more, visit the Amazon Keyspaces CDC documentation.

​Amazon Keyspaces (for Apache Cassandra) now supports Change Data Capture (CDC) streams, enabling you to capture row-level changes in your tables in near-real time. CDC streams in Amazon Keyspaces automatically capture insert, update, and delete operations as change events, delivering them in order with automatic deduplication. With CDC streams, you can build event-driven applications and implement use cases such as data analytics, text search, ML training/inference, and continuous data backups for archival. Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. CDC streams retain data for up to 24 hours and can scale automatically to match your workload, without requiring any infrastructure management. Additionally, enabling CDC streams will have no impact on your table capacity for compute or storage operations. To consume the CDC stream records, you can use either the Keyspaces Data Streams API or leverage the Kinesis Client Library, a java library that makes it easy to consume and process stream records. CDC streams are available today in all AWS Commercial and AWS GovCloud (US) Regions where Amazon Keyspaces is available, and you pay only for the change events captured and delivered through your streams. To learn more, visit the Amazon Keyspaces CDC documentation.  

Amazon Connect now supports custom work labels for agent schedules, making it easier for you to identify the type of work an agent is scheduled for. With this launch, you can create work activities with custom labels and assign them to agent schedules by day of the week. For example, you can assign “Order processing” as the work activity for Monday, “Returns management” for Tuesday, and “Work” (existing default activity) for rest of the week. Thus simplifying the experience for managers as they can now easily identify who is scheduled for which type of work. This launch also improves the experience for agents as they now have visibility into how their time is allocated.

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

​Amazon Connect now supports custom work labels for agent schedules, making it easier for you to identify the type of work an agent is scheduled for. With this launch, you can create work activities with custom labels and assign them to agent schedules by day of the week. For example, you can assign “Order processing” as the work activity for Monday, “Returns management” for Tuesday, and “Work” (existing default activity) for rest of the week. Thus simplifying the experience for managers as they can now easily identify who is scheduled for which type of work. This launch also improves the experience for agents as they now have visibility into how their time is allocated. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.    

Today, we are releasing two capabilities in Amazon Nova Canvas: virtual try-on and style options. These features enhance AI-powered image generation, enabling more engaging and customized visual content.

With virtual try-on integrated into Amazon Nova Canvas, you can now create immersive shopping experiences by visualizing products in context. Whether it’s seeing clothing naturally draped on a shopper or furniture intelligently placed in a living space, the process is simple – you just need to upload two images: one showing the person or space, and another showing the product. Amazon Nova Canvas then creates realistic visualizations while preserving important details, making it easier for customers to make confident purchasing decisions.

With style options integrated into Amazon Nova Canvas, users can specify different artistic styles that will consistently produce an image using that style, without having to specifying it in each text prompt. There are 8 supported styles including 3D animated family film, design sketch, flat vector illustration, graphic novel illustration, maximalism, midcentury retro, photorealism, and soft digital painting.

Virtual try-on and style options are available in Amazon Nova Canvas in the US East (N. Virginia), Asia Pacific (Tokyo), and Europe (Ireland). Current users of Amazon Nova Canvas can immediately use these capabilities without migrating to a new model.

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

​Today, we are releasing two capabilities in Amazon Nova Canvas: virtual try-on and style options. These features enhance AI-powered image generation, enabling more engaging and customized visual content. With virtual try-on integrated into Amazon Nova Canvas, you can now create immersive shopping experiences by visualizing products in context. Whether it’s seeing clothing naturally draped on a shopper or furniture intelligently placed in a living space, the process is simple – you just need to upload two images: one showing the person or space, and another showing the product. Amazon Nova Canvas then creates realistic visualizations while preserving important details, making it easier for customers to make confident purchasing decisions. With style options integrated into Amazon Nova Canvas, users can specify different artistic styles that will consistently produce an image using that style, without having to specifying it in each text prompt. There are 8 supported styles including 3D animated family film, design sketch, flat vector illustration, graphic novel illustration, maximalism, midcentury retro, photorealism, and soft digital painting. Virtual try-on and style options are available in Amazon Nova Canvas in the US East (N. Virginia), Asia Pacific (Tokyo), and Europe (Ireland). Current users of Amazon Nova Canvas can immediately use these capabilities without migrating to a new model. To learn more about Amazon Nova creative models, see the Amazon Nova creative models page and learn about Amazon Nova Canvas responsible use of AI. To get started with Amazon Nova on Amazon Bedrock, visit the Amazon Bedrock console.  

Amazon Keyspaces (for Apache Cassandra) now supports Change Data Capture (CDC) streams, enabling you to capture row-level changes in your tables in near-real time. CDC streams in Amazon Keyspaces automatically capture insert, update, and delete operations as change events, delivering them in order with automatic deduplication. With CDC streams, you can build event-driven applications and implement use cases such as data analytics, text search, ML training/inference, and continuous data backups for archival.

Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage.

CDC streams retain data for up to 24 hours and can scale automatically to match your workload, without requiring any infrastructure management. Additionally, enabling CDC streams will have no impact on your table capacity for compute or storage operations. To consume the CDC stream records, you can use either the Keyspaces Data Streams API or leverage the Kinesis Client Library, a java library that makes it easy to consume and process stream records.

CDC streams are available today in all AWS Commercial and AWS GovCloud (US) Regions where Amazon Keyspaces is available, and you pay only for the change events captured and delivered through your streams. To learn more, visit the Amazon Keyspaces CDC documentation.
 

​Amazon Keyspaces (for Apache Cassandra) now supports Change Data Capture (CDC) streams, enabling you to capture row-level changes in your tables in near-real time. CDC streams in Amazon Keyspaces automatically capture insert, update, and delete operations as change events, delivering them in order with automatic deduplication. With CDC streams, you can build event-driven applications and implement use cases such as data analytics, text search, ML training/inference, and continuous data backups for archival. Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. CDC streams retain data for up to 24 hours and can scale automatically to match your workload, without requiring any infrastructure management. Additionally, enabling CDC streams will have no impact on your table capacity for compute or storage operations. To consume the CDC stream records, you can use either the Keyspaces Data Streams API or leverage the Kinesis Client Library, a java library that makes it easy to consume and process stream records. CDC streams are available today in all AWS Commercial and AWS GovCloud (US) Regions where Amazon Keyspaces is available, and you pay only for the change events captured and delivered through your streams. To learn more, visit the Amazon Keyspaces CDC documentation.    

Amazon QuickSight Enterprise Edition customers can now load up to 2 billion rows of data into Super-fast Parallel In-memory Calculation Engine (SPICE) datasets. This improvement doubles previous capacity of 1 billion rows without slowing ingestion speed or query performance, enabling customers to explore business data over longer time periods or more categories to discover new business insights. Learn more.

The new SPICE dataset size limitation is now available in Amazon QuickSight Enterprise Editions in all QuickSight regions – US East (N. Virginia and Ohio), US West (Oregon), Canada, Sau Paulo, Europe (Frankfurt, Ireland and London), Asia Pacific (Mumbai, Seoul, Singapore, Sydney and Tokyo), and AWS GovCloud (US-West).
 

​Amazon QuickSight Enterprise Edition customers can now load up to 2 billion rows of data into Super-fast Parallel In-memory Calculation Engine (SPICE) datasets. This improvement doubles previous capacity of 1 billion rows without slowing ingestion speed or query performance, enabling customers to explore business data over longer time periods or more categories to discover new business insights. Learn more. The new SPICE dataset size limitation is now available in Amazon QuickSight Enterprise Editions in all QuickSight regions – US East (N. Virginia and Ohio), US West (Oregon), Canada, Sau Paulo, Europe (Frankfurt, Ireland and London), Asia Pacific (Mumbai, Seoul, Singapore, Sydney and Tokyo), and AWS GovCloud (US-West).    

The post Adopción de la IA y la nube adaptativa para impulsar la transformación digital en la minería appeared first on Source LATAM.

​The post Adopción de la IA y la nube adaptativa para impulsar la transformación digital en la minería appeared first on Source LATAM.  

AWS HealthImaging announces support for DICOM BulkData to ensure consistent, low latency metadata retrievals. With this launch, DICOM metadata retrieved via DICOMweb WADO-RS actions will have large data elements substituted with BulkDataURIs.

Medical imaging workflows demand low latency, and retrieving DICOM metadata is often a first step. Large DICOM data elements, such as private attributes and ICC profiles, can increase the size of metadata payloads, potentially slowing down retrieval and processing. With this launch, HealthImaging automatically replaces DICOM data elements over 1 MB in size with in-line BulkDataURIs, in accordance with the DICOMweb standard. Now users can retrieve compact DICOM metadata payloads with low latency, with flexibility to download large data elements through a standards-conformant API.

AWS HealthImaging is generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland).

AWS HealthImaging is a HIPAA-eligible service that empowers healthcare providers, life sciences researchers, and their software partners to store, analyze, and share medical images at petabyte scale. To learn more, see the AWS HealthImaging Developer Guide.
 

​AWS HealthImaging announces support for DICOM BulkData to ensure consistent, low latency metadata retrievals. With this launch, DICOM metadata retrieved via DICOMweb WADO-RS actions will have large data elements substituted with BulkDataURIs. Medical imaging workflows demand low latency, and retrieving DICOM metadata is often a first step. Large DICOM data elements, such as private attributes and ICC profiles, can increase the size of metadata payloads, potentially slowing down retrieval and processing. With this launch, HealthImaging automatically replaces DICOM data elements over 1 MB in size with in-line BulkDataURIs, in accordance with the DICOMweb standard. Now users can retrieve compact DICOM metadata payloads with low latency, with flexibility to download large data elements through a standards-conformant API. AWS HealthImaging is generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). AWS HealthImaging is a HIPAA-eligible service that empowers healthcare providers, life sciences researchers, and their software partners to store, analyze, and share medical images at petabyte scale. To learn more, see the AWS HealthImaging Developer Guide.