Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R7i instances are available in Asia Pacific (Hyderabad) Region.

Amazon EC2 R7i instances are powered by custom 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids), available only on AWS, and offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers.

R7i instances deliver up to 15% better price-performance versus R6i instances. These instances are SAP certified and are a great choice for memory-intensive workloads, such as SAP, SQL and NoSQL databases, distributed web scale in-memory caches, in-memory databases like SAP HANA, and real time big data analytics like Hadoop and Spark. They offer larger instance sizes, up to 48xlarge, and two bare metal sizes (metal-24xl, metal-48xl) for high-transaction and latency-sensitive workloads. These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology, allowing customers to facilitate efficient offload and acceleration of data operations, and optimize performance for workloads.

R7i instances support the new Intel Advanced Matrix Extensions (AMX) that accelerate matrix multiplication operations for applications such as CPU-based ML. In addition, customers can now attach up to 128 EBS volumes to an R7i instance (vs 28 EBS volume attachments on R6i). This allows processing of larger amounts of data, scale workloads, and improve performance over R6i instances.

To learn more, visit Amazon EC2 R7i Instances.

​Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R7i instances are available in Asia Pacific (Hyderabad) Region. Amazon EC2 R7i instances are powered by custom 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids), available only on AWS, and offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers. R7i instances deliver up to 15% better price-performance versus R6i instances. These instances are SAP certified and are a great choice for memory-intensive workloads, such as SAP, SQL and NoSQL databases, distributed web scale in-memory caches, in-memory databases like SAP HANA, and real time big data analytics like Hadoop and Spark. They offer larger instance sizes, up to 48xlarge, and two bare metal sizes (metal-24xl, metal-48xl) for high-transaction and latency-sensitive workloads. These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology, allowing customers to facilitate efficient offload and acceleration of data operations, and optimize performance for workloads. R7i instances support the new Intel Advanced Matrix Extensions (AMX) that accelerate matrix multiplication operations for applications such as CPU-based ML. In addition, customers can now attach up to 128 EBS volumes to an R7i instance (vs 28 EBS volume attachments on R6i). This allows processing of larger amounts of data, scale workloads, and improve performance over R6i instances. To learn more, visit Amazon EC2 R7i Instances.  

Amazon ECS customers using AWS Fargate launch mode now benefit from improved deployment consistency with SOCI Index Manifest v2 support. Seekable OCI (SOCI) accelerates Amazon ECS task launches by enabling containers to start running before the full container image is downloaded. SOCI Index Manifest v2 uses a cryptographic method to establish an explicit link between the image and its manifest, ensuring integrity and consistency during and across all deployment stages.

To get started, create a SOCI index using the new convert subcommand in the soci CLI, available from the SOCI Snapshotter GitHub repository. Once generated, push the container image along with the SOCI index to your Amazon ECR repository, and use it to launch Amazon ECS tasks on AWS Fargate.

As of today, SOCI Index Manifest v2 is the default mechanism for using SOCI with ECS and Fargate. If you’re still using the legacy Manifest v1 implementation, we recommend upgrading to take advantage of the improved reliability and consistency. For more information, see the documentation on using SOCI Index Manifest v2 with Amazon ECS and AWS Fargate and the blog post.

​Amazon ECS customers using AWS Fargate launch mode now benefit from improved deployment consistency with SOCI Index Manifest v2 support. Seekable OCI (SOCI) accelerates Amazon ECS task launches by enabling containers to start running before the full container image is downloaded. SOCI Index Manifest v2 uses a cryptographic method to establish an explicit link between the image and its manifest, ensuring integrity and consistency during and across all deployment stages. To get started, create a SOCI index using the new convert subcommand in the soci CLI, available from the SOCI Snapshotter GitHub repository. Once generated, push the container image along with the SOCI index to your Amazon ECR repository, and use it to launch Amazon ECS tasks on AWS Fargate. As of today, SOCI Index Manifest v2 is the default mechanism for using SOCI with ECS and Fargate. If you’re still using the legacy Manifest v1 implementation, we recommend upgrading to take advantage of the improved reliability and consistency. For more information, see the documentation on using SOCI Index Manifest v2 with Amazon ECS and AWS Fargate and the blog post.  

Today, we are excited to announce the launch of a new feature in Graph Explorer that enables users to write and execute native Gremlin and openCypher queries directly within the interface.

This enhancement empowers data scientists, developers, and database administrators to seamlessly interact with their graph databases using their preferred query language, eliminating the need for additional tools or interfaces. With this update, users can now leverage the full expressive power of both Gremlin and openCypher to traverse complex relationships, perform advanced pattern matching, and extract valuable insights from their graph data while enjoying the intuitive visual environment of Graph Explorer.

To get started, create a new Notebook from the Amazon Neptune console, and start the Graph Explorer from the Notebook actions menu. You can also contribute to the graph-explorer GitHub project here. For more information on how graph-explorer works with Amazon Neptune, see the Amazon Neptune User Guide.
 

​Today, we are excited to announce the launch of a new feature in Graph Explorer that enables users to write and execute native Gremlin and openCypher queries directly within the interface. This enhancement empowers data scientists, developers, and database administrators to seamlessly interact with their graph databases using their preferred query language, eliminating the need for additional tools or interfaces. With this update, users can now leverage the full expressive power of both Gremlin and openCypher to traverse complex relationships, perform advanced pattern matching, and extract valuable insights from their graph data while enjoying the intuitive visual environment of Graph Explorer. To get started, create a new Notebook from the Amazon Neptune console, and start the Graph Explorer from the Notebook actions menu. You can also contribute to the graph-explorer GitHub project here. For more information on how graph-explorer works with Amazon Neptune, see the Amazon Neptune User Guide.    

Today, AWS announces accuracy improvements and new settings for Amazon Rekognition Face Liveness. Amazon Rekognition Face Liveness is a feature of Amazon Rekognition that detects in real-time whether real users, not bad actors using spoofs, can access your services.

Customers across financial, gig economy, telecommunications, healthcare, and social media use Rekognition Face Liveness detection for workflows such as onboarding, authentication, and bot detection. Until now, Rekognition Liveness only offered a single experience with the ‘FaceMovementAndLightChallenge’ setting, which delivers the highest accuracy by requiring users to move their face toward the screen and hold still for a series of flashing lights. With this launch, the new ‘FaceMovementChallenge’ setting reduces the check time by 3 seconds by eliminating the flashing lights. While ‘FaceMovementAndLightChallenge’ remains the best setting to maximize accuracy, ‘FaceMovementChallenge’ allows customers to prioritize faster liveness checks when appropriate. For additional flexibility, ‘FaceMovementChallenge’, allows users to complete checks using the front or back facing camera. Lastly, this update also delivers improved accuracy across both settings to aid with fraud mitigation.

The new Face Liveness settings are available in all AWS commercial regions where Rekognition Liveness is offered at no additional cost. Customers can enable the ‘FaceMovementChallenge’ setting in the CreateFaceLivenessSession API call.

To get started with the new settings, visit the Amazon Rekognition Face Liveness page or refer to the Amazon Rekognition Developer Guide.

​Today, AWS announces accuracy improvements and new settings for Amazon Rekognition Face Liveness. Amazon Rekognition Face Liveness is a feature of Amazon Rekognition that detects in real-time whether real users, not bad actors using spoofs, can access your services. Customers across financial, gig economy, telecommunications, healthcare, and social media use Rekognition Face Liveness detection for workflows such as onboarding, authentication, and bot detection. Until now, Rekognition Liveness only offered a single experience with the ‘FaceMovementAndLightChallenge’ setting, which delivers the highest accuracy by requiring users to move their face toward the screen and hold still for a series of flashing lights. With this launch, the new ‘FaceMovementChallenge’ setting reduces the check time by 3 seconds by eliminating the flashing lights. While ‘FaceMovementAndLightChallenge’ remains the best setting to maximize accuracy, ‘FaceMovementChallenge’ allows customers to prioritize faster liveness checks when appropriate. For additional flexibility, ‘FaceMovementChallenge’, allows users to complete checks using the front or back facing camera. Lastly, this update also delivers improved accuracy across both settings to aid with fraud mitigation. The new Face Liveness settings are available in all AWS commercial regions where Rekognition Liveness is offered at no additional cost. Customers can enable the ‘FaceMovementChallenge’ setting in the CreateFaceLivenessSession API call. To get started with the new settings, visit the Amazon Rekognition Face Liveness page or refer to the Amazon Rekognition Developer Guide.  

Amazon Connect now provides APIs that allow you to delete cases, case comments, undo contact associations, and remove service level agreements (SLAs) from cases. These new capabilities enable you to programmatically remove sensitive customer information from cases or delete cases upon a customer’s request.

Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.
 

​Amazon Connect now provides APIs that allow you to delete cases, case comments, undo contact associations, and remove service level agreements (SLAs) from cases. These new capabilities enable you to programmatically remove sensitive customer information from cases or delete cases upon a customer’s request. Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.    

Amazon Connect now provides new editing and accessibility enhancements for the drag-and-drop flow designer making it easier to build customer service experiences. These enhancements include keyboard navigation, auto arranging of blocks, screen reader support, and improved support for high zoom on browsers. Additionally, when editing a flow block in configuration side panel on the flow designer UI, you can view and edit all incoming and outgoing branch connections, create new flow blocks, and review all attached notes. Each of these capabilities can be accessed through new keyboard shortcuts which are visible on the canvas.

To learn more, see the Amazon Connect Administrator Guide. These features are available in all AWS regions where Amazon Connect is available. To learn more about Amazon Connect, the AWS contact center as a service solution on the cloud, please visit the Amazon Connect website.

​Amazon Connect now provides new editing and accessibility enhancements for the drag-and-drop flow designer making it easier to build customer service experiences. These enhancements include keyboard navigation, auto arranging of blocks, screen reader support, and improved support for high zoom on browsers. Additionally, when editing a flow block in configuration side panel on the flow designer UI, you can view and edit all incoming and outgoing branch connections, create new flow blocks, and review all attached notes. Each of these capabilities can be accessed through new keyboard shortcuts which are visible on the canvas. To learn more, see the Amazon Connect Administrator Guide. These features are available in all AWS regions where Amazon Connect is available. To learn more about Amazon Connect, the AWS contact center as a service solution on the cloud, please visit the Amazon Connect website.  

Amazon Aurora DSQL is now available in Asia Pacific (Seoul) and supports multi-Region clusters within Asia Pacific Regions – Asia Pacific (Osaka), Asia Pacific (Tokyo), Asia Pacific (Seoul) as well as European Regions – Europe (Ireland), Europe (London), Europe (Paris). Aurora DSQL is the fastest serverless, distributed SQL database with active-active high availability and multi-Region strong consistency. Aurora DSQL enables you to build always available applications with virtually unlimited scalability, the highest availability, and zero infrastructure management. It is designed to make scaling and resilience effortless for your applications and offers the fastest distributed SQL reads and writes.

Aurora DSQL is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Osaka), Asia Pacific (Tokyo), Asia Pacific (Seoul), Europe (Ireland), Europe (London), and Europe (Paris).

Get started with Aurora DSQL for free with the AWS Free Tier. To learn more, visit the Aurora DSQL webpage and documentation.

​Amazon Aurora DSQL is now available in Asia Pacific (Seoul) and supports multi-Region clusters within Asia Pacific Regions – Asia Pacific (Osaka), Asia Pacific (Tokyo), Asia Pacific (Seoul) as well as European Regions – Europe (Ireland), Europe (London), Europe (Paris). Aurora DSQL is the fastest serverless, distributed SQL database with active-active high availability and multi-Region strong consistency. Aurora DSQL enables you to build always available applications with virtually unlimited scalability, the highest availability, and zero infrastructure management. It is designed to make scaling and resilience effortless for your applications and offers the fastest distributed SQL reads and writes. Aurora DSQL is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Osaka), Asia Pacific (Tokyo), Asia Pacific (Seoul), Europe (Ireland), Europe (London), and Europe (Paris). Get started with Aurora DSQL for free with the AWS Free Tier. To learn more, visit the Aurora DSQL webpage and documentation.  

Amazon Aurora PostgreSQL-Compatible Edition now supports a maximum storage limit of 256 TiB, doubling the previous limit of 128 TiB. This enhancement allows customers to store and manage even larger datasets within a single Aurora database cluster simplifying data management for large-scale applications and supporting the growing data needs of modern applications. Customers only pay for the storage they use, with no need for upfront provisioning of the full 256 TiB.

To access the increased storage limit, upgrade your cluster to supported database versions. Once upgraded, Aurora storage will automatically scale up to 256 TiB capacity based on the amount of data in the cluster volume. Visit technical documentation to learn more about supported versions. This new storage volume capacity is available in all AWS regions where Aurora PostgreSQL is available.

Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.

​Amazon Aurora PostgreSQL-Compatible Edition now supports a maximum storage limit of 256 TiB, doubling the previous limit of 128 TiB. This enhancement allows customers to store and manage even larger datasets within a single Aurora database cluster simplifying data management for large-scale applications and supporting the growing data needs of modern applications. Customers only pay for the storage they use, with no need for upfront provisioning of the full 256 TiB. To access the increased storage limit, upgrade your cluster to supported database versions. Once upgraded, Aurora storage will automatically scale up to 256 TiB capacity based on the amount of data in the cluster volume. Visit technical documentation to learn more about supported versions. This new storage volume capacity is available in all AWS regions where Aurora PostgreSQL is available. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.  

The post Robótica para la protección y mitigación de incendios forestales appeared first on Source LATAM.

​The post Robótica para la protección y mitigación de incendios forestales appeared first on Source LATAM.  

Amazon S3 Express One Zone, a high performance S3 storage class, now supports tags for cost allocation and attribute-based access control (ABAC). You can add tags to S3 directory buckets to track and organize AWS costs using AWS Billing and Cost Management. Additionally, with ABAC support, you can extend your tag-based access control to new and existing users, roles, and directory buckets. This helps eliminate frequent AWS Identity and Access Management (IAM) or S3 bucket policy updates, simplifying how you scale access governance.

S3 Express One Zone supports tags on directory buckets in all AWS Regions where the storage class is available. You can get started with tagging using the AWS Management Console, S3 REST API, AWS CLI, or the AWS SDK. To learn more about using tags to simplify cost allocation or ABAC, visit the S3 User Guide.

​Amazon S3 Express One Zone, a high performance S3 storage class, now supports tags for cost allocation and attribute-based access control (ABAC). You can add tags to S3 directory buckets to track and organize AWS costs using AWS Billing and Cost Management. Additionally, with ABAC support, you can extend your tag-based access control to new and existing users, roles, and directory buckets. This helps eliminate frequent AWS Identity and Access Management (IAM) or S3 bucket policy updates, simplifying how you scale access governance. S3 Express One Zone supports tags on directory buckets in all AWS Regions where the storage class is available. You can get started with tagging using the AWS Management Console, S3 REST API, AWS CLI, or the AWS SDK. To learn more about using tags to simplify cost allocation or ABAC, visit the S3 User Guide.