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Amazon RDS for MySQL announces Extended Support minor 5.7.44-RDS.20250508

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Amazon Relational Database Service (RDS) for MySQL now supports new Amazon RDS Extended Support minor version 5.7.44-RDS.20250508. We recommend that you upgrade to this version to fix known security vulnerabilities and bugs in prior versions of MySQL. Learn more about upgrading your database instances, including minor and major version upgrades, in the Amazon RDS User Guide .

Amazon RDS Extended Support provides you more time, up to three years, to upgrade to a new major version to help you meet your business requirements. During Extended Support, Amazon RDS will provide critical security and bug fixes for your MySQL databases on Aurora and RDS after the community ends support for a major version. You can run your MySQL databases on Amazon RDS with Extended Support for up to three years beyond a major version’s end of standard support date. Learn more about Extended Support in the Amazon RDS User Guide and the Pricing FAQs .

Amazon RDS for MySQL makes it simple to set up, operate, and scale MySQL deployments in the cloud. See Amazon RDS for MySQL Pricing for pricing details and regional availability. Create or update a fully managed Amazon RDS database in the Amazon RDS Management Console .
 

Amazon Aurora DSQL is now generally available

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Today, AWS announces the general availability of Amazon Aurora DSQL, 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 active-active distributed architecture is designed for 99.99% single-Region and 99.999% multi-Region availability with no single point of failure, and automated failure recovery. It offers multi-Region strong consistency which ensures all reads and writes to any Regional endpoint are strongly consistent and durable. Aurora DSQL independently scales reads, writes, compute, and storage, offering the flexibility and cost efficiency to both scale up and scale out to meet any workload demand without compromising performance. With today’s launch, we’ve added support for AWS Backup, AWS PrivateLink, AWS CloudFormation, AWS CloudTrail, AWS KMS customer managed keys, and PostgreSQL views. In addition, Aurora DSQL provides a Model Context Protocol (MCP) server for AI applications. 

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), Europe (Ireland), Europe (London), and Europe (Paris). 

Get started with Aurora DSQL for free with the AWS Free Tier . Set up your database in only a few steps in the Aurora DSQL console or use the Aurora DSQL API or AWS CLI. To learn more, read the Aurora DSQL overview page , blog post , pricing page , and documentation .

AWS Backup now supports Amazon Aurora DSQL

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AWS Backup now provides fully managed data protection capabilities for Amazon Aurora DSQL , a serverless distributed SQL database for always available applications. As organizations build applications with Aurora DSQL, they can do so with confidence, knowing that their critical data is protected by AWS Backup. Using AWS Backup’s integration with AWS Organizations, you can centrally create and manage immutable backups across all your accounts, standardizing data protection across your organization.

From day one, customers can leverage AWS Backup’s comprehensive data protection features for Aurora DSQL, including automated scheduling, retention management, immutable and logically air-gapped vaults, cross-Region and cross-account copies, and cost-effective cold storage. This integration streamlines backup management, allowing organizations to unify their data protection strategy across Aurora DSQL and other AWS resources. AWS Backup enables customers to confidently adopt Aurora DSQL while maintaining a consistent approach to data protection across their entire AWS environment.

AWS Backup support for Amazon Aurora DSQL is available in all AWS Regions where both AWS Backup and Amazon Aurora DSQL are supported. For the most up-to-date information on Regional availability, please refer to the AWS Backup Regional availability .

To get started with AWS Backup for Aurora DSQL, visit the AWS Backup console or refer to the AWS Backup documentation . For more information about Amazon Aurora DSQL, please visit the Amazon Aurora DSQL documentation .

AWS Backup search now supports creating backup indexes within backup policies

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Today, AWS Backup announces support for the creation of backup indexes in backup policies, allowing you to automatically create backup indexes of your Amazon S3 backups or Amazon EBS snapshots at the AWS Organization level. The creation of a backup index is the prerequisite for searching your backups. Once the backup index is created, you can perform a search and item level recovery of your S3 backups or EBS snapshots. You can now use your Organization management account to set a backup indexing policy across your AWS accounts.

To get started, create a new or edit an existing AWS Backup policy from your AWS Organization management account. You can designate your backup policies to automatically create a backup index of your S3 backups and/or EBS Snapshots. Once your backup is indexed, you can search across multiple backups to locate specific files or objects. You can specify your search criteria based on one or more filters such as file name, creation time, and size. Once you identify the specific files or objects you are looking for, you can choose to restore just these items to an Amazon S3 bucket rather than restoring the full backup, allowing for quicker recovery times.

AWS Backup support for backup indexes in backup policies is available in all AWS Commercial and AWS GovCloud (US) Regions, where AWS Backup, backup policies, and backup indexes are available . You can get started by using the AWS Organizations API, or CLI. For more information, visit our documentation and blog post .
 

AWS Neuron introduces NxD Inference GA, new features, and improved tools

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Today, AWS announces the release of Neuron 2.23 , featuring enhancements across inference, training capabilities, and developer tools. This release moves the NxD Inference library (NxDI) to general availability (GA), introduces new training capabilities including Context Parallelism and ORPO, and adds support for PyTorch 2.6 and JAX 0.5.3.

The NxD Inference library moves from beta to general availability, now recommended for all multi-chip inference use-cases. Key enhancements include Persistent Cache support to reduce compilation times and optimized model loading time.

For training workloads, the NxD Training library introduces Context Parallelism support (beta) for Llama models, enabling sequence lengths up to 32K. The release adds support for model alignment using ORPO with DPO-style datasets, upgraded support for 3rd party libraries, specifically: PyTorch Lightning 2.5, Transformers 4.48, and NeMo 2.1.

The Neuron Kernel Interface (NKI) introduces new 32-bit integer operations, improved ISA features for Trainium2, and new performance tuning APIs. The Neuron Profiler now offers 5x faster profile result viewing, timeline-based error tracking, and improved multiprocess visualization with Perfetto.

AWS Neuron SDK supports training and deploying models on Trn1, Trn2, and Inf2 instances, available in AWS Regions as On-Demand Instances, Reserved Instances, Spot Instances, or part of Savings Plan.

For a full list of new features and enhancements in Neuron 2.23 and to get started with Neuron, see:

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