Today, AWS announces new capabilities in AWS Security Hub that allow security teams to centrally enable and configure Security Hub standards and controls across accounts and Regions in just a few steps. This enhancement is designed to streamline and simplify how you set up and administer Security Hub in your multi-account, multi-Region organizations. You can now use Security Hub central configuration to address gaps in your security coverage by creating security policies with your desired standards and controls and applying them in selected Regions across accounts and Organizational Units (OUs). 

Today, Amazon Simple Queue Service (SQS) announces support for dead-letter queue redrive for FIFO queues. Dead-letter queue redrive is an enhanced capability to improve the dead-letter queue management experience for Amazon SQS customers. Amazon SQS already supports redriving messages from a standard dead-letter queue to a standard source queues or a standard custom destination queue. Now SQS customers can also redrive messages from a FIFO dead-letter queue to FIFO source queues or FIFO custom destination queues. 

Today, AWS announces the support of multi-account experiments for AWS Fault Injection Service (FIS). This feature allows you to set up and run real-world failure scenarios on an application which spans multiple AWS accounts using a single FIS experiment. You can centrally configure, monitor, and review an experiment that targets resources in multiple accounts. 

Today, AWS Elastic Disaster Recovery (AWS DRS) announces general availability in the AWS GovCloud (US) Regions. This launch gives customers in both the public and commercial sectors, as well as their partners, access to AWS DRS capabilities in the AWS GovCloud (US) Regions.

AWS Graviton3-based M7g instances are now generally available for use with new provisioned Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters. MSK provisioned clusters running on M7g instances deliver up to 24% price/ performance improvement, up to 29% higher write and read throughput, and up to 27% reduction in CPU usage over comparable MSK clusters running on M5 instances. 

Today, AWS announces the general availability of AWS B2B Data Interchange, a fully managed service for automating the transformation of Electronic Data Interchange (EDI) documents into common data representations such as JSON and XML at scale and with pay-as-you-go pricing. Customers across verticals such as manufacturing, retail, healthcare, and more can now reduce the time, complexity, and cost associated with preparing and integrating EDI data into their business applications and purpose-built data lakes.

Today, AWS announces the general availability of Amazon Relational Database Service (Amazon RDS) for Db2, which makes it easy to set up, operate, and scale Db2 databases in the cloud. Amazon RDS manages time-consuming database administration tasks, such as provisioning, patching, backups, recovery, failure detection, and repair, so you can focus on applications and business.

Today, AWS Backup announces the general availability of restore testing, a new capability within AWS Backup that helps perform automated and periodic restore tests of supported AWS resources that have been backed up. AWS Backup is a fully managed service that centralizes and automates data protection across AWS services and hybrid workloads. With this launch, AWS Backup customers can test recovery readiness to prepare for possible data loss events and to measure duration times for restore jobs to satisfy compliance or regulatory requirements.

Amazon EFS Replication now supports failback, making it easier and more cost-effective to synchronize changes between EFS file systems after Disaster Recovery (DR) and other failover events.

Starting today, the AWS Command Line Interface (AWS CLI) and Python SDK automatically use the AWS Common Runtime (CRT) to accelerate data transfer between Amazon S3 and Amazon EC2 Trn1, P4d, and P5 instances. The AWS CRT implements Amazon S3’s performance best practices for request parallelization, automatic retry, DNS load balancing, and more to deliver high data transfer rates between Amazon EC2 and Amazon S3. As a result, machine learning training jobs now download training data from Amazon S3 up to 3x faster and upload model checkpoints to Amazon S3 up to 5x faster, which accelerates total training times.