Link: https://aws.amazon.com/about-aws/whats-new/2026/02/aws-backup-extends-amazon-neptune-five-additional-regions/

AWS Backup now supports Amazon Neptune in five additional AWS Regions: Europe (Zurich), Asia Pacific (Melbourne), Canada West (Calgary), Asia Pacific (Malaysia), and Europe (Spain).

This expansion brings policy-based data protection and recovery to your Amazon Neptune clusters in these newly supported Regions.

To start protecting your Amazon Neptune clusters with AWS Backup, add your Amazon Neptune clusters to your existing backup plans or create a new backup plan, and attach your Neptune clusters to the newly created backup plan. To learn more about AWS Backup for Amazon Neptune clusters, visit the product page, pricing page, and documentation. To get started, visit the AWS Backup console, AWS Command Line Interface (CLI), or AWS SDKs.

Published: 2026-02-25 15:55:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-opensearch-service-expands-support-graviton4-based-instances

Amazon OpenSearch Service expands support for the latest generation Graviton4-based Amazon EC2 instance families. These new instance types are compute optimized (c8g), general purpose (m8g), and memory optimized (r8g, r8gd) instances.

AWS Graviton4 processors provide up to 30% better performance than AWS Graviton3 processors with c8g, m8g and r8g & r8gd offering the best price performance for compute-intensive, general purpose, and memory-intensive workloads respectively. To learn more about Graviton4 improvements, please see the blog on r8g instances and the blog on c8g & m8g instances.

Amazon OpenSearch Service Graviton4 instances are supported for all OpenSearch versions, and Elasticsearch (open source) versions 7.9 and 7.10.

Apart from the regions already supported, one or more than one Graviton4 instance types are now also available in following region: Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Jakarta), Asia Pacific (Melbourne), Asia Pacific (Osaka), Asia Pacific (Thailand), Europe (Milan), Europe (Paris), Europe (Zurich), Middle East (UAE), AWS GovCloud (US-West) and AWS GovCloud (US-East).

For region specific availability & pricing, visit our pricing page. To learn more about Amazon OpenSearch Service and its capabilities, visit our product page.

Published: 2026-02-18 05:30:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-opensearch-service-supports-i7i-instances

Amazon OpenSearch Service now supports latest generation x86 based high performance Storage Optimized i7i instances. Powered by 5th generation Intel Xeon Scalable processors, I7i instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances.

I7i instances have 3rd generation AWS Nitro SSDs with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances. Built on the AWS Nitro System, these instances offload CPU virtualization, storage, and networking functions to dedicated hardware and software enhancing the performance and security for your workloads.

Amazon OpenSearch Service supports i7i instances in following AWS Regions US East (N. Virginia, Ohio), US West (N. California, Oregon), Canada (Central), Canada West (Calgary), Europe (Frankfurt, Ireland, London, Milan, Spain, Stockholm, Zurich ), Africa (Cape Town), Asia Pacific (Hong Kong, Hyderabad, Jakarta, Malaysia, Melbourne, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Middle East (UAE), South America (São Paulo) & AWS GovCloud (US-West).

For region specific availability & pricing, visit our pricing page. To learn more about Amazon OpenSearch Service and its capabilities, visit our product page.

Published: 2026-02-18 04:30:00+00:00

Link: https://aws.amazon.com/blogs/aws/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, Du’An Lightfoot, Elizabeth Fuentes, Laura Salinas, and Sandhya Subramani spoke about building and […]

Published: 2026-02-23 16:56:24+00:00

Link: https://aws.amazon.com/blogs/aws/aws-iam-identity-center-now-supports-multi-region-replication-for-aws-account-access-and-application-use/

AWS IAM Identity Center now supports multi-Region replication of workforce identities and permission sets, enabling improved resiliency for AWS account access and allowing applications to be deployed closer to users while meeting data residency requirements.

Published: 2026-02-03 19:13:34+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/03/aws-batch-configurable-scale-down-delay/

AWS Batch now allows you to configure a scale down delay for managed compute environments, helping reduce job processing delays for intermittent and periodic workloads. With the new minScaleDownDelayMinutes parameter, you can specify how long AWS Batch keeps instances running after their jobs complete (from 20 minutes to 1 week), preventing unnecessary instance terminations and relaunches that can delay subsequent job processing.

You can configure the scale down delay when creating or updating a compute environment via the AWS Batch API (CreateComputeEnvironment or UpdateComputeEnvironment) or the AWS Batch Management Console. The delay is applied at the instance level, based on when each instance last completed a job.

Scale down delay is supported today in all AWS Regions where AWS Batch is available. For more information, see the AWS Batch API Guide.

Published: 2026-03-02 19:05:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/aws-medialive-introduces-srt-listener/

AWS Elemental MediaLive now supports Secure Reliable Transport (SRT) Listener mode for both inputs and outputs. With SRT Listener mode, MediaLive waits for connections rather than initiating them. Upstream sources push live video directly to MediaLive, and downstream systems pull encoded streams on demand. This simplifies network setup by removing the need for complex firewall configurations or static, publicly accessible IP addresses on the source or destination side. SRT Listener mode complements MediaLive's existing SRT Caller mode, giving you full control over which side of the connection initiates the SRT handshake.

SRT Listener mode enables flexible contribution and distribution workflows. On the input side, you can push streams from on-premises encoders or remote production sites, including MediaLive Anywhere deployments, directly to MediaLive in the cloud without coordinating firewall changes with your network team. On the output side, downstream distribution partners can connect to MediaLive and pull encoded streams when ready, without requiring MediaLive to initiate outbound connections. Both SRT Listener inputs and outputs support configurable latency settings and mandatory AES encryption to help ensure content security.

SRT Listener mode is available in all AWS Regions where AWS Elemental MediaLive is offered. To get started, see Setting up an SRT Listener input and Creating SRT outputs in listener mode in the AWS Elemental MediaLive User Guide.

Published: 2026-02-28 00:14:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-bedrock-batch-inference-supports-converse-api-format/

Amazon Bedrock batch inference now supports the Converse API as a model invocation type, enabling you to use a consistent, model-agnostic input format for your batch workloads.

Previously, batch inference required model-specific request formats using the InvokeModel API. Now, when creating a batch inference job, you can select Converse as the model invocation type and structure your input data using the standard Converse API request format. Output for Converse batch jobs follows the Converse API response format. With this feature, you can use the same unified request format for both real-time and batch inference, simplifying prompt management and reducing the effort needed to switch between models. You can configure the Converse model invocation type through both the Amazon Bedrock console and the API.

This capability is available in all AWS Regions that support Amazon Bedrock batch inference. To get started, see Create a batch inference job and Format and upload your batch inference data in the Amazon Bedrock User Guide.

Published: 2026-02-27 19:00:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-opensearch-service-adds-new-insights-improved-cluster-stability/

Amazon OpenSearch Service has enhanced Cluster Insights with two new insights — Cluster Overload and Suboptimal Sharding Strategy. Suboptimal Sharding Strategy provides instant visibility into shard imbalances that cause uneven workload distribution, while Cluster Overload surfaces elevated cluster resource utilization that can lead to request throttling or rejections. Both insights come with details of affected resources along with actionable mitigation recommendations.

Previously, identifying resource constraints and shard imbalances required manually correlating multiple metrics and logs, making it difficult to detect issues early. With these new insights, you can proactively monitor cluster health and take timely action.

Suboptimal Sharding Strategy detects shard imbalances caused by indices with too few shards relative to the number of data nodes, or by shards carrying disproportionately large amounts of data compared to others. It identifies the root cause of uneven workload distribution and provides recommendations to help you achieve optimal shard distribution for improved query performance and resource utilization. Similarly, Cluster Overload helps you identify elevated resource utilization, including CPU, memory, disk I/O, disk throughput, and disk utilization that can potentially lead to request throttling or rejections. It also provides scale-up recommendations so you can take timely action to protect your critical workloads.

These new insights are available at no additional cost for OpenSearch version 2.17 or later in all Regions where the OpenSearch UI is available. See the complete list of supported Regions here. To learn more, visit the Cluster Insights documentation or view the complete catalog of available insights.

Published: 2026-02-27 10:49:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/03/amazon-bedrock-projects-api-mantle-inference-engine/

Amazon Bedrock now supports OpenAI-compatible Projects API in the Mantle inference engine in Amazon Bedrock. Amazon Bedrock is a fully managed service that offers a broad selection of best-in-class foundation models from leading AI companies like Anthropic, Meta, and OpenAI, along with a broad set of specialized developer tools that make it easy to build and scale compelling generative AI applications. Mantle is Amazon Bedrock's distributed inference engine for large-scale model serving that supports OpenAI-compatible APIs.

With Projects API, customers who have more than one application, environment, or team can now create individual projects to achieve better isolation across all of them. You can assign different IAM-based access control to each project and add tags to each project for better cost visibility.

Projects are available for all customers using the OpenAI-compatible APIs, the Responses API and Chat Completions API, through the Mantle inference engine in Amazon Bedrock. There is no additional charge for using the Projects API. You pay only for the underlying model inference you consume. To get started with the Projects API in Amazon Bedrock, visit the Amazon Bedrock documentation. 

Published: 2026-02-26 23:06:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/lambda-durable-execution-java-preview/

Today, AWS announces the developer preview of the AWS Lambda Durable Execution SDK for Java. With this SDK, developers can build resilient multi-step applications like order processing pipelines, AI-assisted workflows, and human-in-the-loop approvals using Lambda durable functions, without implementing custom progress tracking or integrating external orchestration services.

Lambda durable functions extend Lambda's event-driven programming model with operations that checkpoint progress automatically and pause execution for up to a year when waiting on external events. The new Durable Execution SDK for Java provides an idiomatic experience for building with durable functions and is compatible with Java 17+. This preview includes steps for progress tracking, waits for efficient suspension, and durable futures for callback-based workflows.

To get started, see the Lambda durable functions developer guide and the AWS Lambda Durable Execution SDK for Java on GitHub. To learn more about Lambda durable functions, visit the product page.

On-demand functions are not billed for duration while paused. For pricing details, see AWS Lambda Pricing. For information about AWS Regions where Lambda durable functions are available, see the AWS Regional Services List.

Published: 2026-02-26 07:00:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-aurora-dsql-launches-playground/

Today, AWS announces a browser-based playground that enables developers to interact with an Amazon Aurora DSQL database without requiring an AWS account. With zero setup or infrastructure configuration, developers can create schemas, load data, and execute SQL queries directly form their browser.

The playground for Aurora DSQL provides an instant, ephemeral database environment, making it easy to experiment and learn. Built-in sample datasets help developers quickly explore core Aurora DSQL capabilities and get hands-on experience in minutes.

To start exploring, visit the playground for Aurora DSQL. To get started with your production workloads and learn more visit Amazon Aurora DSQL.

Published: 2026-02-25 18:00:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/aws-appconfig-new-relic-for-automated-rollback/

AWS AppConfig today launched a new integration that enables automated, intelligent rollbacks during feature flag and dynamic configuration deployments using New Relic Workflow Automation. Building on AWS AppConfig's third-party alert capability, this integration provides teams using New Relic with a solution to automatically detect degraded application health and trigger rollbacks in seconds, eliminating manual intervention.

When you deploy feature flags using AWS AppConfig's gradual deployment strategy, the AWS AppConfig New Relic Extension continuously monitors your application health against configured alert conditions. If issues are detected during a feature flag update and deployment, such as increased error rates or elevated latency, the New Relic Workflow automatically sends a notification to trigger an immediate rollback, reverting the feature flag to its previous state. This closed-loop automation reduces the time between detection and remediation from minutes to seconds, minimizing customer impact during failed deployments.

 

Published: 2026-02-24 16:00:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/aws-mediaconvert-introduces-video-probe/

Introducing Probe API, a powerful and free metadata analysis tool for AWS Elemental MediaConvert. Optimized for efficiency, Probe API reads header metadata to quickly return essential information about your media files, including codec specifications, pixel formats, color space details, and container information - all without waiting to process the actual video content. This analysis capability makes it an invaluable tool for content creators, developers, and media professionals who need to quickly validate files, automate workflows, or utilize Elementals' Step Functions to make encoding decisions based on source material characteristics.

For complete implementation details and usage examples, please visit the MediaConvert API Reference documentation. The Probe API can be utilized in any region where AWS Elemental MediaConvert is available, making it a versatile tool for streamlining your media workflow analysis.

To get started with Probe API and explore its capabilities, visit the AWS Elemental MediaConvert product page or consult the User Guide for comprehensive documentation.

Published: 2026-02-24 00:01:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-aurora-dsql-integrates-with-kiro-powers-and-agent-skills

Today, AWS announces Amazon Aurora DSQL integration with Kiro powers and AI agent skills, enabling developers to build Aurora DSQL-backed applications faster with AI agent-assisted development. These integrations bundle the Aurora DSQL Model Context Protocol (MCP) server with development best practices, so AI agents can help you with Aurora DSQL schema design, performance optimization, and database operations out of the box.

Kiro powers is a registry of curated and pre-packaged MCP servers, steering files, and agent hooks to accelerate specialized software development and deployment use cases. With the Kiro power for Aurora DSQL, agents have instant access to specialized knowledge, so developers can work confidently without any prior context, reducing trial-and-error development cycles. The power is available within the Kiro IDE for one-click installation.

The Aurora DSQL skill extends the same capabilities to additional AI coding agents through the Skills CLI. Developers can install the skill with a single command and select their preferred agents including Kiro CLI, Claude Code, Gemini, Codex, Cursor, Copilot, Cline, Windsurf, Roo, OpenCode, and more. When developers work on database tasks, the agent dynamically loads relevant skill guidance, including Aurora DSQL Postgres-compatible SQL patterns, distributed database design, and IAM authentication, eliminating the need to repeatedly provide the same context across conversations. As Aurora DSQL adds new features, future skill releases will include updated patterns and guidance, ensuring that agents always have current best practices.

For more information on the Aurora DSQL Kiro power and agent skills, visit the Aurora DSQL steering documentation and GitHub page. Get started with Aurora DSQL for free with the AWS Free Tier.

Published: 2026-02-18 18:00:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-bedrock-reinforcement-fine-tuning-openai

Amazon Bedrock now extends reinforcement fine-tuning (RFT) support to popular open-weight models, including OpenAI GPT-OSS and Qwen models, and introduces OpenAI-compatible fine-tuning APIs. These capabilities make it easier for developers to improve open-weight model accuracy without requiring deep machine learning expertise or large volumes of labeled data. Reinforcement fine-tuning in Amazon Bedrock automates the end-to-end customization workflow, allowing models to learn from feedback on multiple possible responses using a small set of prompts, rather than traditional large training datasets. Reinforcement fine-tuning enables customers to use smaller, faster, and more cost-effective model variants while maintaining high quality.

Organizations often struggle to adapt foundation models to their unique business requirements, forcing tradeoffs between generic models with limited performance and complex, expensive customization pipelines that require specialized infrastructure and expertise. Amazon Bedrock removes this complexity by providing a fully managed, secure reinforcement fine-tuning experience. Customers define reward functions using verifiable rule-based graders or AI-based judges, including built-in templates for both objective tasks such as code generation and math reasoning, and subjective tasks such as instruction following or conversational quality. During training, customers can use AWS Lambda functions for custom grading logic, and access intermediate model checkpoints to evaluate, debug, and select the best-performing model, improving iteration speed and training efficiency. All proprietary data remains within AWS’s secure, governed environment throughout the customization process.

Models supported at this launch are: qwen.qwen3-32b and openai.gpt-oss-20b. After fine-tuning completes, customers can immediately use the resulting fine tuned model for on-demand inference through Amazon Bedrock’s OpenAI-compatible APIs - Responses API and Chat Completions API, without any additional deployment steps. To learn more, see the Amazon Bedrock documentation.

Published: 2026-02-17 21:17:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/claude-sonnet-4.6-available-in-amazon-bedrock/

Starting today, Amazon Bedrock supports Claude Sonnet 4.6, which offers frontier performance across coding, agents, and professional work at scale. According to Anthropic, Claude Sonnet 4.6 is their best computer use model yet, allowing organizations to deploy browser-based automation across business tools with near-human reliability. Claude Sonnet 4.6 approaches Opus 4.6 intelligence at a lower cost. It enables faster, high-quality task completion, making it ideal for high-volume coding and knowledge work use cases. 

 

Claude Sonnet 4.6 serves as a direct upgrade to Sonnet 4.5 across use cases that require consistent conversational quality and efficient multi-step orchestration. For search and chat applications, it delivers reliable performance across single and multi-turn exchanges at a price point that makes high-volume deployment practical, maintaining quality standards while optimizing for scale. Developers can leverage Claude Sonnet 4.6’s for agentic workflows, seamlessly filling both lead agent and subagent roles in multi-model pipelines with precise workflow management and context compaction capabilities. Enterprise teams can use Claude Sonnet 4.6 to power domain-specific applications with professional precision, including spreadsheet and financial model creation that accelerates analysis workflows, compliance review processes that require meticulous attention to detail, and data summarization tasks where iteration speed and accuracy are paramount. Claude Sonnet 4.6 requires only minor prompting adjustments from Sonnet 4.5, ensuring smooth migration for existing implementations. 

 

Claude Sonnet 4.6 is now available in Amazon Bedrock. For the full list of available regions, refer to the documentation. To learn more and get started with Claude Sonnet 4.6 in Amazon Bedrock, read the About Amazon blog and visit the Amazon Bedrock console.

Published: 2026-02-17 15:43:00+00:00

Link: https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-mq-activemq-5-19/

Amazon MQ now supports ActiveMQ minor version 5.19, which introduces several improvements and fixes compared to the previous version of ActiveMQ supported by Amazon MQ. Amazon MQ manages the patch version upgrades for your brokers. All brokers on ActiveMQ version 5.19 will be automatically upgraded to the next compatible and secure patch version in your scheduled maintenance window.

If you are utilizing prior versions of ActiveMQ, such as 5.18, we strongly recommend you to upgrade to ActiveMQ 5.19. You can easily perform this upgrade with just a few clicks in the AWS Management Console. To learn more about upgrading, consult the ActiveMQ Version Management section in the Amazon MQ Developer Guide. To learn more about the changes in ActiveMQ 5.19, see the Amazon MQ release notes. This version is available across all AWS Regions where Amazon MQ is available.

Published: 2026-02-19 17:00:00+00:00