12/19/2024, 12:00:00 AM ~ 12/20/2024, 12:00:00 AM (UTC)

Recent Announcements

AWS Backup now supports resource type and multiple tag selections in backup policies in the AWS GovCloud (US) Regions

Today, AWS Backup announces additional options to assign resources to a backup policy on AWS Organizations in the AWS GovCloud (US) Regions. Customers can now select specific resources by resource type and exclude them based on resource type or tag. They can also use the combination of multiple tags within the same resource selection.\n With additional options to select resources, customers can implement flexible backup strategies across their organizations by combining multiple resource types and/or tags. They can also exclude resources they do not want to back up using resource type or tag, optimizing cost on non-critical resources. To get started, use your AWS Organizations’ management account to create or edit an AWS Backup policy in the AWS GovCloud (US) Regions. Then, create or modify a resource selection using the AWS Organizations’ API, CLI, or JSON editor in either the AWS Organizations or AWS Backup console. For more information, visit our documentation and launch blog.

Amazon Connect launches support for 64 languages for Amazon Q in Connect agent assistance

Amazon Q in Connect now supports 64 languages for agent assistance capabilities. Customer service agents can now chat with Q for assistance in their native language and Q will provide answers, knowledge article links, and recommended step-by-step guides in said language. New languages supported include: Chinese, French, French (Canadian), Italian, Japanese, Korean, Malay, Portuguese, Spanish, Swedish, and Tagalog.\n For the full list of supported languages, please see the Languages supported by Amazon Connect features. For region availability, please see the availability of Amazon Connect features by Region. To learn more about Amazon Q in Connect, please visit the website or see the help documentation.

Introducing Stable Diffusion 3.5 Large in Amazon Bedrock

Stability AI’s Stable Diffusion 3.5 Large (SD3.5 Large) is now available in Amazon Bedrock. SD3.5 Large is an advanced text-to-image model featuring 8.1 billion parameters. Trained on Amazon SageMaker HyperPod, this powerful model will enable AWS customers to generate high-quality, 1-megapixel images from text descriptions with superior accuracy and creative control.\n The model excels at creating diverse, high-quality images across multiple styles, making it valuable for media, gaming, advertising, ecommerce, corporate training, retail, and education industries. Its enhanced capabilities include exceptional photorealism with detailed 3D imagery, superior handling of multiple subjects in complex scenes, and improved human anatomy rendering. The model also generates representative images with diverse skin tones and features without requiring extensive prompting. Today, Stable Image Ultra in Amazon Bedrock has been updated to include Stable Diffusion 3.5 Large in the model’s underlying architecture.

Stable Diffusion 3.5 Large is now available in Amazon Bedrock in the US West (Oregon) AWS region. To learn more read the AWS News Blog or visit the Stability AI in Amazon Bedrock product page, and documentation. To get started with SD3.5 Large, visit the Amazon Bedrock console.

New insights and reporting for resell revenue available in AWS Partner Central Analytics

AWS Partner Central Analytics now provides insights for resell revenue for AWS Partners participating in the AWS Solution Provider or Distribution Programs. The new data helps Partners gain visibility into amortized revenue generated through resellers. With this new resell revenue section in Partner Central Analytics, Partners can measure revenue by month, reseller, end customer, and geography to help define sales growth strategies.\n Prior to this launch, Partners could see discounts for authorized resell services, but received limited visibility into program revenue. With this launch, the “Solution provider and distributor“ tab within Partner Central Analytics is renamed to ”Channel“, delivering four new visualizations, providing Partners with a view into amortized resell revenue by program revenue and net program revenue. Key new features include amortized Partner revenue tracking to measure customer impact, monthly refresh schedule to include previous month’s data, and comprehensive coverage of resell revenue on authorized services. This update gives Partners customer level insights, helping Partners understand spending patterns across different regions. This helps Partners decide where and how to invest to expand their market reach. Also, these new insights help Partners better track revenue generated before and after program discounts. Approved users of an AWS Partner organization at either the Validated or Differentiated stage can access the new datasets through the Analytics tab in AWS Partner Central. To learn more about resell revenue available in the analytics dashboard, log in to AWS Partner Central and explore the Analytics and Insights User Guide

AWS ParallelCluster 3.12 now available with custom image build enhancements

AWS ParallelCluster 3.12 is now generally available. This release makes it possible to include Lustre and NVIDIA software components in ParallelCluster custom images. Now, you can include ParallelCluster’s recommended Nvidia drivers and CUDA libraries in custom images. This update also makes the Lustre client optional to account for scenarios where you may opt for alternative storage solutions. To enable these optional software components when creating custom images, configure the NvidiaSoftware and the LustreClient parameters in the build image configuration file when using the build-image command.\n For more details on the release, review the AWS ParallelCluster 3.12.0 release notes. AWS ParallelCluster is a fully-supported and maintained open-source cluster management tool that enables R&D customers and their IT administrators to operate high-performance computing (HPC) clusters on AWS. AWS ParallelCluster is designed to automatically and securely provision cloud resources into elastically-scaling HPC clusters capable of running scientific, engineering, and machine-learning (ML/AI) workloads at scale on AWS. AWS ParallelCluster is available at no additional charge in the AWS Regions listed here, and you pay only for the AWS resources needed to run your applications. To learn more about launching HPC clusters on AWS, visit the AWS ParallelCluster User Guide. To start using ParallelCluster, see the installation instructions for ParallelCluster UI and CLI.

Amazon AppStream 2.0 introduces Rocky Linux Application and Desktop streaming

Amazon AppStream 2.0 now offers support for Rocky Linux from CIQ, enabling ISVs and central IT organizations to stream from an RPM Package Manager (RPM) compatible environment optimized for running compute-intensive applications while leveraging the flexibility, scalability, and cost-effectiveness of the AWS Cloud. With this launch, customers have the flexibility to choose from a broader set of operating systems including Rocky Linux, Red Hat Enterprise Linux (RHEL), and Microsoft Windows.\n This launch enables organizations to stream Rocky Linux apps from AppStream 2.0, helping to accelerate time to market, scaling resources up or down with demand, and managing the entire fleet centrally through the AWS Management Console. Rocky Linux on AppStream 2.0 also enables traditional desktop apps to be converted to SaaS delivery without the cost of refactoring, while pay-as-you-go billing and license-included images ensure you only pay for the resources you use. Rocky Linux-based AppStream 2.0 instances are supported in all AWS Regions where AppStream 2.0 is available and use per second billing (with a minimum of 15 minutes). For more information, see Amazon AppStream 2.0 pricing. To get started with Rocky Linux on AppStream 2.0, sign in to the AWS Management Console and open the AppStream 2.0 Console. For more information, see the Amazon AppStream 2.0 Administrator Guide.

Amazon AppStream 2.0 introduces client for macOS

Amazon AppStream 2.0 extends native client support to macOS. Users can now access AppStream 2.0 streamed applications through a web browser, the AppStream 2.0 client for Windows, or AppStream 2.0 client for macOS. This additional macOS support provides more flexibility and platform options for users needing access to streamed applications and desktops.\n The AppStream 2.0 client for macOS is an application you install on your Mac to access AppStream streaming sessions. The client provides enhanced capabilities and user experience. It supports two monitors with 4K resolution, and the ability to connect up to four monitors, leveraging multi-monitor layouts. Users can use keyboard shortcuts and relative mouse mode for a more natural feel. Using macOS client you can also stream over UDP which offers a more responsive streaming quality in sub-optimal network conditions, with higher round trip latency. Additionally, to assist with troubleshooting macOS client issues, you can enable client automatic logging. The macOS client works with Windows, Red Hat Enterprise Linux, Rocky Linux 8 based AppStream 2.0 applications and fleets. To run the AppStream 2.0 macOS client, ensure that your Mac is running macOS 13 (Ventura), macOS 14 (Sonoma), or macOS 15 (Sequoia). To download and install the AppStream 2.0 macOS client application, visit Amazon AppStream 2.0 Downloads, choose the macOS link, download and install the application. Verify that the Amazon AppStream 2.0 client application icon appears on your Mac Launchpad and start streaming.

AWS Config now supports 3 new resource types

AWS Config now supports 3 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources.\n With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available across the AWS Config feature set, including Config rules, Config aggregators, and Config advanced queries. You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported services are available:

AWS::Cognito::IdentityPool

AWS::MediaConnect::Gateway

AWS::OpenSearchServerless::VpcEndpoint

To view the complete list of AWS Config supported resource types, see supported resource types page.

Amazon Connect now supports multi-party chat

Amazon Connect now supports multi-party chat, allowing up to 4 additional agents to join an ongoing chat conversation, making it easier to collaborate and resolve customer issues quickly. For example, agents can add a supervisor or subject matter experts to join the chat, ensuring customers receive accurate and timely support.\n Multi-party chat can be enabled within the AWS Console. Once enabled, agents can simply use a Quick Connect to invite additional agents to an ongoing chat. This feature is available in all commercial AWS regions where Amazon Connect is available. To learn more and get started, please refer to the help documentation or visit the Amazon Connect website.

Meta’s Llama 3.3 70B model now available in Amazon Bedrock

Meta’s Llama 3.3 70B model is now available in Amazon Bedrock. Llama 3.3 70B represents a significant advancement in model efficiency and performance optimization. This instruction-tuned model delivers impressive capabilities across diverse tasks, including multilingual dialogue, text summarization, and complex reasoning. Llama 3.3 70B is a text-only instruction-tuned model that provides enhanced performance relative to Llama 3.1 70B–and to Llama 3.2 90B when used for text-only applications.\n The new model delivers similar performance to Llama 3.1 405B, while requiring only a fraction of the computational resources. Llama 3.3 demonstrates substantial improvements in reasoning, mathematical understanding, general knowledge, and instruction following. Its comprehensive training enables robust language understanding across multiple domains. You can use Llama 3.3 for enterprise applications, content creation, and advanced research initiatives. The model supports multiple languages and outperforms many existing conversational models on industry standard benchmarks. It also supports the ability to leverage model outputs to improve other models including synthetic data generation and distillation. Llama 3.3 provides an accessible and powerful generative AI solution for businesses seeking high-quality, efficient language model capabilities. Meta’s Llama 3.3 70B model is available in Amazon Bedrock in the US East (Ohio) Region, and in the US East (N. Virginia) and US West (Oregon) Regions via cross-region inference. To learn more, visit the Llama product page and documentation. To get started with Llama 3.3 70B in Amazon Bedrock, visit the Amazon Bedrock console.

Amazon ECS now supports network fault injection experiments on AWS Fargate

Amazon Elastic Container Services (Amazon ECS) now allows you to perform network fault injection experiments on your applications deployed on AWS Fargate. Fault injection experiments create disruptions to test how your applications behave, helping you improve application performance, observability, and resilience. AWS Fault Injection Service (AWS FIS) now supports 6 actions for ECS on both EC2 and Fargate: network latency, network blackhole, network packet loss, CPU stress, I/O stress, and kill process.\n Developers and operators can now verify the response of their application to potential network errors, some of which may also be required for regulatory compliance. By reproducing network behaviors that may cause applications to fail, you can identify gaps in application configurations, monitoring, alarms, and operational response. Amazon ECS is introducing the ability to opt-in to allow tasks to use a fault injector such as AWS FIS to perform network experiments for increasing network latency, increasing packet loss, and blackhole port testing (dropping inbound or outbound traffic) to test how your applications perform, in addition to existing resource stress experiments. The new experience is now automatically enabled in all AWS Regions and integration with the AWS Fault Injection Service in those regions where AWS FIS is available. For more details, go to Amazon ECS fault Injection documentation and the AWS FIS user guide.

AWS IoT Device Management introduces high-throughput device connectivity status queries

Today, AWS IoT Device Management announces the general availability of a high-throughput connectivity status query API, allowing developers to query the latest connectivity state of IoT devices, for monitoring and management purposes. AWS IoT Device Management is a fully managed cloud service that helps you register, organize, monitor, and remotely manage Internet of Things (IoT) devices at scale.\n Device connectivity status is crucial for monitoring device failures and executing remote commands. The new connectivity status API which will be available to AWS IoT Device Management Fleet Indexing customers, provides a high-throughput solution (350+ requests per second) for customers to ascertain device connectivity to the cloud. It also retrieves most recent connect or disconnect event timestamp along with disconnect reason, aiding troubleshooting activities. AWS IoT Device Management’s Fleet Indexing feature enables customers to search, group devices based on device metadata, state stored across thing registry, IoT device shadow and connectivity data sources. While existing search queries are optimized for fleet-level querying, this API is optimized for single-device connectivity queries and offers lower latency to reflect connectivity state changes. With connectivity status queries, developers can now easily support targeted device monitoring and management capabilities in their applications. For example, in automotive applications, developers can first query vehicle connectivity status using this API prior to issuing remote commands to the vehicle. Connectivity status is available to AWS IoT Device Management Fleet indexing customers and in all AWS regions where AWS IoT Device Management is available. For more information please refer to the developer guide and API documentation.

Amazon RDS Proxy announces caching_sha2_password authentication support for MySQL on Aurora and RDS

Amazon RDS Proxy announces caching_sha2_password authentication plugin support for client to proxy connections on MySQL on Aurora and RDS.\n Customers need to use plugins to perform authentication between databases and clients while using RDS Proxy. Starting with MySQL 8.4, community MySQL uses caching_sha2_password plugin as the default, which is more secure than the previous default plugins. To align with this, starting today, caching_sha2_password will also be the default authentication plugin for new connection creates with RDS Proxy, if a value is not specified. RDS Proxy is a fully managed and a highly available database proxy for Amazon Aurora and RDS databases. RDS Proxy helps improve application scalability, resiliency, and security. You can setup your RDS Proxy to use caching_sha2_password authentication on all available RDS for MySQL and Aurora MySQL versions with just a few clicks on the Amazon RDS Management Console or using the AWS SDK or CLI. Support for caching_sha2_password with RDS Proxy is available in all AWS Commercial Regions. For more information, including instructions on getting started, read the Amazon RDS Proxy documentation.

AWS Glue Data Catalog offers advanced automatic optimization for Apache Iceberg tables

AWS Glue Data Catalog now offers advanced automatic optimization for Apache Iceberg tables. This update includes supporting compaction of delete files, nested data types, partial progress commits, and partition evolution support, making it easier to maintain consistently performant transactional data lakes. These features address challenges faced by customers with streaming data continuously ingested into Apache Iceberg tables, resulting in a large number of delete files that track changes in data files.\n With this new capability, Glue Data Catalog constantly monitors table partitions for positional and equality delete files, initiates the compaction process, and regularly commits partial progress to reduce conflicts. Glue Catalog optimizers now support schema evolution as you reorder or rename columns as well as partition spec evolution. In addition, Glue Catalog has expanded support for heavily nested complex data and support for parquet compression codecs - zstd, brotli, lz4, gzip, snappy. Enabling automatic compaction reduces delete files and metadata overhead on your Iceberg tables and improves query performance. These new features are automatically applied to existing and new Glue Catalog optimizers. In addition to the AWS console, customers can also use the AWS CLI or AWS SDKs to automate optimization for Apache Iceberg tables. The feature is available in 14 AWS regions US East (N. Virginia, Ohio), US West (Oregon), Europe (Ireland, London, Frankfurt, Stockholm), Canada (central), Asia Pacific (Tokyo, Seoul, Mumbai, Singapore, Sydney), South America (São Paulo). To learn more, read the blog, and visit the AWS Glue Data Catalog documentation.

Announcing Internet Protocol Version 6 (IPv6) support for Recycle Bin

Today, AWS announces Internet Protocol version 6 (IPv6) support for Recycle Bin, a data recovery feature that enables restoration of accidental deleted Amazon EBS Snapshots and EBS-backed AMIs. You now have the option of using IPv6 addresses for new and existing endpoints. By moving to IPv6, you can simplify your network stack by running dual-stack Recycle Bin endpoints on a network that supports both IPv4 and IPv6.\n Customers can create rules in Recycle Bin to retain deleted EBS Snapshots or deregistered EBS-backed AMI for a specific retention time. This capability allows you to immediately recover your deleted snapshots or EBS-backed AMIs when you create volumes or launch instance without a need to roll back to a snapshot or AMI from an earlier point in time. Recovered snapshots or AMIs retain attributes such as prior to deletion and can be used immediately for creating volumes or launching instances. Snapshots and AMIs that are not recovered from the Recycle Bin are permanently deleted upon expiration of the retention time. Recycle Bin with IPv6 and AWS PrivateLink is now available in all AWS Regions including the AWS GovCloud (US) Regions. To learn more about configuring Recycle Bin endpoints for IPv6, please refer to our documentation.

AWS Blogs

AWS Japan Blog (Japanese)

AWS News Blog

AWS Big Data Blog

AWS Contact Center

AWS Database Blog

AWS for Industries

AWS Machine Learning Blog

AWS for M&E Blog

AWS Security Blog

AWS Storage Blog

Open Source Project

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Amplify for JavaScript

Amazon EKS Anywhere