AWS Updates Feed

← トップに戻る

AWS Updates - 2026-02-23

AWS What's New

Amazon Redshift Serverless introduces 3-year Serverless Reservations

Amazon Redshift now offers 3-year Serverless Reservations for Amazon Redshift Serverless, a new discounted pricing option that provides up to 45% savings and improved cost predictability for your analytics workloads. With Serverless Reservations, you commit to a specific number of Redshift Processing Units (RPUs) for a 3-year term with a no-upfront payment option.

Amazon Redshift Serverless allows you to run and scale analytics without having to provision and manage clusters with a pay-as-you-go pricing model. Serverless Reservations help you further optimize compute costs and improve cost predictability of existing and new workloads on Amazon Redshift Serverless. Managed at the AWS payer account level, Serverless Reservations can be shared between multiple AWS accounts, reducing your compute costs by up to 45% on all Amazon Redshift Serverless workloads in your AWS account. Serverless Reservations are billed hourly and metered per second, offering a consistent billing model (24 hours a day, seven days a week) while maintaining the flexibility offered by Amazon Redshift Serverless. Any usage exceeding the specified RPU level is charged at standard on-demand rates. You can purchase Serverless Reservations via the Amazon Redshift console or by invoking the Serverless Reservations API “create-reservation”.

Serverless Reservations are available in all regions where Amazon Redshift Serverless is currently available. To learn more about Amazon Redshift Serverless pricing options, see the Redshift Serverless feature page, Redshift Pricing Page, or the Amazon Redshift Management Guide. 

AWS IAM Policy Autopilot is now available as a Kiro Power

AWS IAM Policy Autopilot, the open source static code analysis tool launched at re:Invent 2025, is now available as a Kiro power to bring policy expertise to agentic AI development. This tool helps developers quickly create baseline AWS IAM policies that can be refined as applications evolve, eliminating the need for manual IAM policy creation.

The Kiro power delivers significant benefits through one-click installation directly from the Kiro IDE and web interface, removing the need for manual MCP server configuration. This streamlined workflow enables faster policy creation and integrates seamlessly into AI-assisted development environments. Key use cases include rapid prototyping of AWS applications requiring IAM policies, baseline policy creation for new AWS projects, and enhanced productivity within IDE environments where developers can generate policies without leaving their coding workflow.

To learn more about AWS IAM Policy Autopilot and access the integration, visit the AWS IAM Policy Autopilot GitHub repository. To learn more about Kiro powers, visit the Kiro powers page. 

AWS Trusted Advisor now delivers more accurate unused NAT Gateway checks powered by AWS Compute Optimizer

AWS Trusted Advisor has enhanced its detection of unused NAT Gateway checks powered by AWS Compute Optimizer detection capabilities. The enhanced detection analyzes additional CloudWatch metrics over a 32-day lookback period and verifies whether NAT Gateways are associated with route tables, reducing false positives by avoiding flagging critical backup resources. This helps cost optimization teams and DevOps engineers confidently identify and remove unused NAT Gateways that incur unnecessary charges.

Each recommendation includes estimated monthly cost savings, enabling you to prioritize cleanup based on monetary impact. With these recommendations, you can run regular cost audits to catch idle NAT Gateways before charges accumulate. This simplifies cleaning up resources left behind after workload migrations or decommissions. You can view and act on these recommendations in the Trusted Advisor console alongside your other cost optimization checks, or through Trusted Advisor APIs.

This feature is available in all AWS Regions where AWS Trusted Advisor is supported. Organizations must be opted-in to Cost Optimization Hub and Compute Optimizer to access these enhanced recommendations. To learn more, visit the AWS Trusted Advisor documentation.

Amazon announces generative AI-based artifacts in Amazon Q Developer for visualizing resource and cost data

Today, AWS announces the general availability of Amazon Q Developer artifacts in the AWS Management Console. Amazon Q artifacts is a generative AI-based user experience that enables customers to visualize resource data in tables and cost data in charts. The launch also moves the Q icon to the navigation bar and the chat panel to the left, making Amazon Q easier to use and find.

Customers can access Amazon Q artifacts by selecting the Amazon Q icon from the navigation bar in the AWS Management Console. They can ask questions about their AWS resources to understand the state of their resources and costs using Amazon Q artifacts. For example, on asking “List S3 buckets with tag value production", Amazon Q displays the S3 buckets that has a tag value of production in a tabular format. Customers can then select the hyperlinks on the bucket name to view the bucket details in the S3 console. Customers can also visualize cost and billing information with charts. For example, on entering "Show me RDS costs by instance type over the last 6 months", Q will render the response in a Q artifacts using a chart (e.g., bar graph, line chart, pie chart, or area chart). Customers can also use sample prompts in the Prompt Library in the Amazon Q chat panel to get started quickly. The artifacts are displayed in an artifact panel next to the Amazon Q chat panel, which is now on the left. Users can expand Amazon Q to full-screen for a dedicated focus mode experience.

The Amazon Q Developer artifacts are available in all AWS Regions where Amazon Q Developer is available. To get started visit Amazon Q Developer documentation.

AWS Elemental Media Services Now Available in Asia Pacific (Malaysia) Region

AWS Elemental Media Services are now available in the Asia Pacific (Malaysia) Region, expanding your ability to build cloud-based video workflows closer to your audiences in Southeast Asia. AWS Elemental MediaConnect, MediaLive, MediaPackage, MediaConvert, and MediaTailor form a comprehensive suite of services that enable you to ingest, transport, transcode, package, and deliver high-quality video content with lower latency and improved performance for viewers across Malaysia and the broader Southeast Asia region.

With this regional expansion, broadcasters, content providers, and streaming platforms in the region can now process video workloads closer to the edge reducing latency and improving video quality for regional audiences. For example, you can use MediaLive or MediaConvert to encode live sports events or VOD assets, respectively, in Kuala Lumpur, package the streams with MediaPackage for multi-device delivery, and monetize content using MediaTailor's server-side ad insertion, all while keeping your video processing infrastructure within the Asia Pacific (Malaysia) Region.

AWS Elemental Media Services are a family of services that form the foundation of cloud-based workflows to transport, transcode, package, and deliver video.

Visit the AWS region table for a full list of AWS Regions where Elemental Media Services are available. 

Amazon S3 Tables are now available in AWS GovCloud (US) Regions

Amazon S3 Tables are now available in AWS GovCloud (US-East) and AWS GovCloud (US-West).

Amazon S3 Tables deliver the first cloud object store with built-in Apache Iceberg support, offering optimized tabular data storage at scale. S3 Tables are designed to perform continual table maintenance to automatically optimize query efficiency and storage cost over time, even as your data lake scales and evolves. With S3 Tables support for the Apache Iceberg standard, your tabular data can be easily queried by popular AWS and third-party query engines. Additionally, with the Intelligent-Tiering storage class, S3 Tables automatically manage costs based on access patterns, without performance impact or operational overhead.

For a full list of AWS Regions where S3 Tables are available, see S3 Tables AWS Regions and endpoints. To learn more, visit the product page, documentation, and the Amazon S3 pricing page.

Automated Reasoning policies now include references to the source document

AWS announces the launch of source document references for Automated Reasoning policies, simplifying the task of reviewing and refining an Automated Reasoning policy. Automated Reasoning checks uses formal verification techniques to validate that content generated by foundation models is compliant with an Automated Reasoning policy. Automated Reasoning checks deliver up to 99% accuracy at detecting correct responses from LLMs, giving you provable assurance in detecting AI hallucinations while also assisting with ambiguity detection in model responses.

To create Automated Reasoning policies, users upload documents that describe the rules in a knowledge domain like HR policies or financial transaction approval guidelines. These documents are translated into a collection of formal logic rules and variables called an Automated Reasoning policy. With source document references, users can now review the generated policy rules and variables using references to content they are familiar with from the original document,

Test generation for Automated Reasoning checks is now available in the US (N. Virginia), US (Ohio), US (Oregon), Europe (Frankfurt), Europe (Ireland), and Europe (Paris) Regions. Customers can access the service through the Amazon Bedrock console, as well as the Amazon Bedrock Python SDK.

To learn more about Automated Reasoning checks and how you can integrate it into your generative AI workflows, please read the Amazon Bedrock documentation, review the tutorials on the AWS AI blog, and visit the Bedrock Guardrails webpage.

Amazon S3 now provides AWS source region information in server access logs

Amazon S3 server access logs now include source region information, specifying which AWS Region requests to your data originate from. This identifies applications that are making cross-region requests, helping you to optimize cost and performance.

Source region information automatically appears at the end of each server access log entry with no additional configuration. For example, if your application requests data from your us-east-1 bucket from us-west-2, the log entry shows "us-west-2" as the source region.

This feature will be available in all AWS Regions in the coming weeks at no additional cost. To learn more about S3 server access log format and best practices, visit the S3 User Guide.

AWS News Blog

AWS Weekly Roundup: Claude Sonnet 4.6 in Amazon Bedrock, Kiro in GovCloud Regions, new Agent Plugins, and more (February 23, 2026)

Last week, my team met many developers at Developer Week in San Jose. My colleague, Vinicius Senger delivered a great keynote about renascent software—a new way of building and evolving applications where humans and AI collaborate as co-developers using Kiro. Other colleagues spoke about building and deploying production-ready AI agents. Everyone stayed to ask and […]