Recent Announcements

AWS Lambda recursive loop detection is now available in Europe Sovereign Cloud

aws@amazon.com — Thu, 10 Sep 2026 20:00:00 GMT

AWS Lambda recursive loop detection is now supported for functions running in Europe Sovereign Cloud. Recursive loop detection automatically detects and stops recursive invocations between Lambda functions and other supported services, preventing unexpected billing caused by unintended recursive loops.

Customers use event sources such as Amazon S3, Amazon SQS, and Amazon SNS to build event driven applications that trigger Lambda functions. Misconfiguration or code defect can cause events to be sent back to the same source that triggered the Lambda function, causing recursive loops and unintended usage. When such a loop is detected, recursive loop detection automatically stops processing the event and sends you an AWS Health Dashboard notification with troubleshooting steps.

Recursive loop detection is enabled by default for Lambda functions using a supported SDK version. If your function intentionally uses recursive loops, you can use the PutFunctionRecursionConfig API to turn off recursive loop detection on your Lambda function.

To learn about recursive loop detection, visit Lambda documentation.

AWS Transform for .NET now generates unit tests for modernized code

aws@amazon.com — Thu, 10 Sep 2026 20:00:00 GMT

Today, AWS announced that AWS Transform for .NET can automatically generate unit tests for the code it modernizes. When enabled, AWS Transform generates unit tests that target the testable classes in your transformed .NET application, such as business logic and controllers, giving you an automated test safety net on the modernized code as part of the same job that performs the migration.

Modernizing a .NET Framework application to modern .NET produces a transformed, buildable codebase, but teams previously had to write test coverage for that modernized code by hand. With this launch, AWS Transform assesses your application for testability in parallel with the standard .NET assessment, plans which classes and methods to cover, and generates the corresponding unit test code, so you complete the migration with tests already in place. Unit test generation is opt-in: you can enable it at the start of a job or after transformation completes.

Unit test generation for AWS Transform for .NET is supported in the AWS Toolkit for Visual Studio extension. It is available in all AWS Regions where AWS Transform for .NET is supported. To get started, run a .NET transformation with AWS Transform for .NET in Visual Studio and choose to generate unit tests. To learn more, refer to Modernizing .NET in the IDE in the AWS Transform User Guide.

Amazon API Gateway now supports 1 MB execution logs with configurable delivery destinations

aws@amazon.com — Thu, 10 Sep 2026 20:00:00 GMT

Amazon API Gateway now supports configurable delivery destinations and larger log events for REST API execution logs. Previously, execution logs were delivered to a single API Gateway-managed CloudWatch Logs log group with log events truncated at 1 KB, limiting visibility into request and response data.

You can now route execution logs up to 1 MB to your own Amazon CloudWatch Logs log groups, Amazon S3 buckets, or Amazon Data Firehose streams, and deliver to multiple destinations simultaneously. For example, you can route execution logs to Amazon S3 in Apache Parquet format for cost-efficient long-term storage and analysis with Amazon Athena, while simultaneously delivering structured JSON logs to CloudWatch Logs for real-time alerting.

This feature is available in all AWS Regions where API Gateway REST APIs are available, including the AWS GovCloud (US) Regions. Execution logs delivered through this feature are charged at vended logs rates. For pricing details, see Amazon CloudWatch Pricing. You can set up delivery through the API Gateway console, AWS CLI, or AWS CloudFormation. To get started, see Amazon API Gateway documentation and AWS blog post.

AWS Lambda durable functions integrates with Pydantic AI

aws@amazon.com — Thu, 10 Sep 2026 18:45:00 GMT

Today, AWS Lambda durable functions announces an integration with Pydantic AI, an open source framework for building AI agents in Python. AWS Lambda durable functions saves your Pydantic AI agent's progress as it runs, so after an interruption like a timeout, your agent resumes from the last completed step instead of starting over. Your agent gains fault tolerance without you having to write the checkpoint and retry logic yourself.

With this integration, each model and tool call your agent makes is a durable execution step, so an interrupted run does not repeat calls that already completed. This matters when the work is expensive to repeat, such as a chain of model calls that reviews a set of documents or researches a topic across many sources, where starting over means paying again for tokens to do the same work. It also helps to avoid unwanted side-effects when resuming execution, such as billing a customer twice. Because your agent runs on AWS Lambda, you manage no servers and pay only for the compute it uses.

You can use this integration in any Python AWS Lambda durable function. It is available in all AWS Regions where AWS Lambda durable functions is available. To get started, install Pydantic AI and follow its AWS Lambda durability page. You can also find the integration details in the durable execution SDK reference. For more information about AWS Lambda durable functions, see the developer guide and the AWS Lambda product page.

Amazon MQ now supports RabbitMQ 4.3

aws@amazon.com — Thu, 10 Sep 2026 18:08:00 GMT

Amazon MQ now supports RabbitMQ version 4.3 which adds quorum queue feature enhancements such as compaction, increased priority levels, native delayed retries, and graceful consumer timeouts. RabbitMQ 4.3 also includes various bug fixes and performance improvements for memory management.

Quorum queues on RabbitMQ 4.3 performs compaction to reduce disk usage for queues and native support for 32 strict priority levels, compared to the relative 2 levels supported in previous RabbitMQ versions. Quorum queues can now automatically set failed messages aside and retry delivery after a set cooldown delay. Consumer timeouts have moved from global protocol channels to quorum queues and can be configured specific to the protocol now. Both consumer timeouts and delayed retries can be configured and managed by RabbitMQ Policies. Transient non-exclusive queues, Global QoS, and Classic queues v1 storage are no longer supported on RabbitMQ 4.3. Consumer timeouts also do not apply to classic queues.

To start using RabbitMQ 4.3 on Amazon MQ, simply select RabbitMQ 4.3 when creating a new broker using the m7g instance type through the AWS Management console, AWS CLI, or AWS SDKs. Amazon MQ automatically manages patch version upgrades for your RabbitMQ 4.3 brokers, so you need to only specify the major.minor version. To learn more about the changes in RabbitMQ 4.3, see the Amazon MQ release notes and the Amazon MQ developer guide. This version is available in all regions where Amazon MQ m7g type instances are available today.

Announcing second-generation single-rack AWS Outposts

aws@amazon.com — Thu, 10 Sep 2026 17:58:00 GMT

Today, AWS announces the general availability of second-generation single-rack AWS Outposts, a self-contained 42U rack that integrates compute, storage and networking into a single compact unit purpose-built for workloads requiring low latency, local data processing, and data residency in space and power constrained locations. A single-rack Outposts delivers up to 2,688 vCPU and 100 TB of Amazon Elastic Block Store (Amazon EBS) storage. Moreover, like multi-rack Outposts, single-rack Outposts support the latest x86-powered EC2 instances, including general purpose (M7i, M8i), compute-optimized (C7i, C8i), memory-optimized (R7i, R8i), and Outposts accelerated networking (Bmn-sf2e, Bmn-cx2, Bmn-cx3a) instances.

For organizations that operate in locations with limited rack space, such as manufacturing, gaming, and other industries, single-rack Outposts brings the latest AWS compute, storage, and networking features on-premises, and gives customers a direct path to modernize while leveraging their currently available space and power. Single-rack and multi-rack Outposts offer customers a consistent experience with the same AWS APIs, management console, automation, governance policies, and security controls across AWS Regions and on-premises locations.

For a current list of AWS Regions and countries/territories where Outposts racks are supported, check out the Outposts rack FAQs page. To get started, open the AWS Outposts console.

Amazon OpenSearch Serverless is now available on v0 by Vercel

aws@amazon.com — Thu, 10 Sep 2026 17:00:00 GMT

You can now build full-stack search and AI applications in minutes using Amazon OpenSearch Serverless on v0 by Vercel, an AI-powered platform that transforms your ideas into production-ready web applications. OpenSearch Serverless eliminates infrastructure management and automatically scales capacity up and down based on demand, so you can focus on building and not managing clusters. With this launch, you can use natural language prompts to build applications powered by OpenSearch Serverless for full-text search and vector search for retrieval-augmented generation (RAG) workloads, all without leaving the v0 interface.

To get started, simply describe what you want to build using a natural language prompt in v0 or visit OpenSearch Serverless in v0 to begin with Amazon OpenSearch Serverless pre-selected. v0 generates a complete full-stack application, automatically provisions an Amazon OpenSearch Serverless collection, indexes your data into the collection, and uses the Amazon OpenSearch Serverless endpoint for serving search queries. v0 handles the required environment variables and configuration, and loads provider-specific agent skills to generate code that follows recommended patterns. You can either prompt v0 to provision Amazon OpenSearch Serverless resources under a new AWS account or link to an existing AWS account.

You can create Vercel apps with Amazon OpenSearch Serverless in v0 in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Canada (Central), South America (São Paulo), Europe (Ireland), Europe (London), Europe (Paris), Europe (Frankfurt), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Asia Pacific (Osaka). To learn more, check out the Vercel announcement or visit the documentation for Amazon OpenSearch Serverless.

Amazon ECS expands IAM condition key support for RunTask and StartTask APIs

aws@amazon.com — Thu, 10 Sep 2026 16:52:00 GMT

Amazon Elastic Container Service (Amazon ECS) now supports the IAM condition keys for CPU and memory resources on the RunTask and StartTask APIs. Administrators can use these keys to enforce consistent CPU and memory limits across all methods of launching ECS tasks. This helps organizations prevent unexpected cost overruns and keep workloads aligned with their resource policies.
Previously, the ecs:task-cpu and ecs:task-memory condition keys were available only on the RegisterTaskDefinition, CreateService, and UpdateService APIs. These condition keys are now extended on the RunTask and StartTask APIs. Now, IAM policies that reference these condition keys are evaluated when tasks are launched through RunTask and StartTask as well, giving administrators a single, unified mechanism to control resource allocation across their ECS environments.

This enhancement is available in all AWS Regions where Amazon ECS is available, at no additional cost. To learn more about using condition keys with Amazon ECS, refer to our documentation.

Amazon Redshift RG instances now available in Europe (Zurich) Region

aws@amazon.com — Thu, 10 Sep 2026 16:00:00 GMT

Amazon Redshift RG instances, powered by AWS Graviton processors, are now available in the AWS Europe (Zurich) Region. RG instances deliver better performance, running data warehouse and data lake workloads up to 2.4x as fast as previous generation RA3 instances, at 30% lower price per vCPU. RG instances include Redshift's custom-built vectorized data lake query engine that processes Apache Iceberg and Parquet data on your cluster nodes, enabling you to run SQL analytics across your data warehouse and data lake using a single engine.

RG instances are available in four instance sizes, rg.large, rg.xlarge, rg.4xlarge and rg.12xlarge. Customers with existing RA3 clusters can upgrade them to RG using Snapshot & Restore, Elastic Resize, or Classic Resize. RG instances are available with flexible pricing options, including On-Demand, and 1-year and 3-year Reserved Instances with All Upfront, Partial Upfront, and No Upfront payment options. For pricing details, visit the Amazon Redshift pricing page.

To get started, refer to the following resources:

Amazon CloudWatch now supports network health indicator for TGW inter-Region peering using synthetic monitors

aws@amazon.com — Thu, 10 Sep 2026 11:00:00 GMT

With synthetic monitors in Amazon CloudWatch Network Monitoring, you can now determine whether a network performance issue on a path that crosses an AWS Transit Gateway inter-Region peering connection is caused by the AWS network. This helps network operators and application developers cut the time spent isolating the source of degradation on these paths.

Previously, for synthetic monitors, the network health indicator (NHI) covered only paths that connect through AWS Direct Connect. With this release, synthetic monitors extend it to paths that reach a destination in a peered Region over Transit Gateway inter-Region peering. For these paths, the indicator reflects the health of the AWS network path up to the Transit Gateway peering connection, and is published to your Amazon CloudWatch account so you can build dashboards and set alarms.

For the full list of AWS Regions where Network Monitoring for AWS workloads is available, visit the Regions list. To learn more, visit the Amazon CloudWatch Network Monitoring documentation.

AWS Elemental Inference now generates contextual metadata from live video in real time

aws@amazon.com — Thu, 10 Sep 2026 08:00:00 GMT

AWS Elemental Inference now generates contextual metadata from live video streams in real time, using AI to produce scene-level intelligence without custom machine learning infrastructure. The new capability analyzes live video in parallel with encoding to extract Interactive Advertising Bureau (IAB) content taxonomy categories, Global Alliance for Responsible Media (GARM) brand suitability signals, detected objects and actions, and shot and scene-level descriptions. Broadcasters and content platforms can now power contextual ad decisioning, media asset enrichment, and content discovery workflows using serverless, fully managed AI.

For contextual advertising, AWS Elemental MediaLive embeds the Elemental Inference feed ID into (Society of Cable Telecommunications Engineers) SCTE-35 ad markers in the live stream. At each ad break, AWS Elemental MediaTailor uses a Monetization Function to retrieve the scene-level signals for that feed ID and translate them into the targeting parameters ad servers expect. This enables context-aware ad decision-making without custom integration work, supporting use cases like contextual deal curation and brand suitability scores, resulting in improved monetization outcomes for publishers. For media asset management, detecting objects and actions, and shot and scene-level descriptions, provide automatic structured metadata generation for every scene and shot, building richer archives that power contextual content discovery, assisted editing workflows, and personalized content recommendations without manual logging or post-production metadata entry.

Contextual metadata is available today in the AWS Elemental MediaLive console in all AWS Regions where AWS Elemental Inference is available.

AWS Elemental MediaTailor now offers Yield Optimization to automatically fill ad breaks with Amazon Ads demand

aws@amazon.com — Thu, 10 Sep 2026 08:00:00 GMT

AWS Elemental MediaTailor now offers Yield Optimization, a new capability that automatically monetizes unused ad inventory with Amazon Ads demand during server-side ad insertion (SSAI) for livestreams. Available exclusively to publishers in the Amazon Publisher Services (APS) Streaming TV program, yield optimization turns unfilled ad breaks into monetized impressions at zero cost to enable and with no additional infrastructure required.

Because ads are stitched directly into the stream before reaching the viewer, they play seamlessly on every device. Key highlights:

- Built for scale: yield optimization is designed for large-scale live events such as professional league championships, with low latency and fast response times to maximize ad fill during peak viewership.

- Brand safe: demand is filtered by category to avoid competitive conflicts within the same ad break. publishers set their own price floors and category rules to maintain full control over which ads run in their streams.

- Simple to enable: configure yield optimization through the MediaTailor API or Console. No additional infrastructure or client-side changes are required.

- Performance visibility: monitor ad fill rate improvements using MediaTailor metrics in Amazon CloudWatch. Track revenue and earnings through the APS Publisher portal.

AWS Elemental MediaTailor yield optimization is available at no additional cost in all AWS Regions where MediaTailor is available, including US East (Ohio), US East (N. Virginia), US West (Oregon); Africa (Cape Town); Asia Pacific (Hyderabad, Malaysia, Melbourne, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo); Canada (Central); Europe (Frankfurt, Ireland, London, Paris, Stockholm); Middle East (UAE); and South America (São Paulo). To learn more, visit the AWS Elemental MediaTailor documentation.

AWS Elemental MediaLive adds support for A/B forensic watermarking

aws@amazon.com — Thu, 10 Sep 2026 08:00:00 GMT

AWS Elemental MediaLive now supports A/B forensic watermarking, enabling content owners to trace the source of unauthorized redistribution of live video content. A single MediaLive channel produces two synchronized output variants, each carrying a distinct visually transparent watermark that persists through re-encoding and screen capture. Downstream packaging and CDN infrastructure assembles these variants into unique per-session sequences that identify the origin of leaked content.

Forensic watermarking follows the DASH Industry Forum (DASH-IF) specification for A/B watermarking (European Telecommunications Standards Institute (ETSI) TS 104 002), ensuring interoperability with standards-compliant packagers and CDN infrastructure. Customers can configure watermarking on Common Media Application Format (CMAF) Ingest output groups through the MediaLive API or console. MediaLive delivers watermarked A and B variants via CMAF ingest to AWS Elemental MediaPackage or third-party packagers, enabling downstream per-session watermark assembly through compatible CDN infrastructure including Amazon CloudFront.

To learn more, visit the AWS Elemental MediaLive User Guide.

A/B forensic watermarking is available in all AWS Regions where AWS Elemental MediaLive is available.

AWS Elemental MediaTailor now supports Low-Latency HLS ad insertion

aws@amazon.com — Thu, 10 Sep 2026 08:00:00 GMT

AWS Elemental MediaTailor now supports Low-Latency HTTP Live Streaming (LL-HLS) ad insertion using HLS Interstitials. MediaTailor is a channel assembly and personalized ad insertion service for video providers that monetizes live streams, linear channels, and video-on-demand content. With this launch, video providers can insert ads into low-latency live streams while holding the reduced latency their viewers expect.

LL-HLS reduces live latency by delivering partial segments and letting players hold a playlist request open until the next segment part is ready, which requires media playlists to be cacheable at the content delivery network (CDN) edge. MediaTailor supports this using HLS Interstitials, which reference ads as a separate playlist instead of stitching them into each viewer's media playlist. Every viewer receives the same cacheable playlist, so MediaTailor sustains low-latency playback at scale and moves the ad decision server call off the manifest request path. This capability has been proven in production on live sporting events with multi-million views, and is ideal for live sports, news, betting and wagering, watch-party, and interactive live formats where latency is a product requirement.

Low-Latency HLS ad insertion is available in all AWS Regions where AWS Elemental MediaTailor is available. To learn more, visit the AWS Elemental MediaTailor product page and the MediaTailor server-guided ad insertion documentation. To get started, sign in to the MediaTailor console..

AWS Elemental introduces Dynamic Multiview for live video

aws@amazon.com — Thu, 10 Sep 2026 08:00:00 GMT

AWS Elemental MediaPackage now offers Dynamic Multiview, a server-side capability that composes multiple live video sources into viewer-selected tiled layouts on demand. Content providers can deliver multi-angle, multi-game, and personalized viewing experiences as standard HLS (HTTP Live Streaming) and DASH (Dynamic Adaptive Streaming over HTTP) streams playable on most modern consumer devices, televisions, and set top boxes without custom player development.

Dynamic Multiview operates entirely in the compressed domain, combining individually encoded sources without re-encoding or compositing. Customers encode each source once through AWS Elemental MediaLive, and MediaPackage assembles compositions on demand - only when viewers request them, eliminating the need to pre-encode combinations. Because the output is standard HLS and DASH, it plays natively on existing devices and players with no app changes or SDK integration required. The feature supports AVC and HEVC codecs, DRM encryption, SCTE-35 ad marker passthrough, and full-screen ad replacement.

To learn more, visit the Elemental Dynamic Multiview Reference Guide.

Dynamic Multiview is available in all AWS Regions where AWS Elemental MediaPackage and MediaLive are available.

AWS Storage Gateway now supports FIPS-compliant private connectivity for Amazon S3 File Gateway

aws@amazon.com — Thu, 10 Sep 2026 08:00:00 GMT

AWS Storage Gateway now supports FIPS 140-3 validated endpoints over AWS PrivateLink for Amazon S3 File Gateway. Previously, FIPS endpoints for File Gateway were available only over the public internet. Now you can keep FIPS-compliant traffic on the private AWS network, making it easier to use Storage Gateway for regulated workloads.

With this launch, your File Gateway can reach the Storage Gateway service endpoints privately through a FIPS interface VPC endpoint in your VPC. You can also create NFS and SMB file shares that reach Amazon S3 through an S3 FIPS interface endpoint, enabling FIPS-compliant private connectivity for your end-to-end file transfer workloads. To get started, create FIPS interface endpoints for Storage Gateway and Amazon S3 in your VPC, then choose the FIPS VPC endpoint option when activating your gateway and configuring your file shares. To activate a gateway with a FIPS PrivateLink endpoint, your gateway must be running software version 2.1.10 or later.

This launch is available in the eight AWS Regions where Storage Gateway offers FIPS endpoints: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Canada (Central), Canada West (Calgary), AWS GovCloud (US-East), and AWS GovCloud (US-West). To learn more, visit the AWS Storage Gateway User Guide or the product page.

Amazon EVS is now available in more regions

aws@amazon.com — Thu, 10 Sep 2026 07:00:00 GMT

Today, we're announcing that Amazon Elastic VMware Service (Amazon EVS) is now available in the Asia Pacific (Osaka), Asia Pacific (Taipei), Europe (Spain), and Israel (Tel Aviv) Regions. This expansion provides more options to leverage the scale and flexibility of AWS for running your VMware workloads in the cloud.

Amazon EVS lets you run VMware Cloud Foundation (VCF) directly within your Amazon Virtual Private Cloud (VPC) on EC2 bare-metal instances, powered by AWS Nitro. You can set up a complete VCF environment in just a few hours, enabling rapid workload migration to AWS to help you eliminate aging infrastructure, reduce operational risks, and meet critical timelines for exiting your data center. This launch supports all existing Amazon EVS features, including VCF 9.0 and 9.1 support to take advantage of the latest VMware features, such as memory tiering.

The added availability in these Regions gives your VMware workloads lower latency through closer proximity to your end users, compliance with data residency or sovereignty requirements, and additional high availability and resiliency options for your enhanced redundancy strategy.

To get started, visit the Amazon EVS product detail page and user guide.

Amazon Connect Customer now lets you set specific capacity limits for different types of Tasks and Emails

aws@amazon.com — Wed, 09 Sep 2026 21:00:00 GMT

Amazon Connect Customer now gives contact center managers the ability to set specific capacity limits for different kinds of work. Previously, concurrency settings were applied at the channel level so all contacts within a channel were treated the same regardless of complexity or effort required. With this launch, managers can classify Task and Email contacts into workload types based on complexity, priority, or business function, each with its own concurrency and interruption rules. For example, a manager can configure agents to handle up to 3 simple, low-effort Tasks concurrently while limiting complex, high-attention Tasks to 1 at a time.

Specific capacity limits for Task and Email channels are available in all AWS commercial and AWS GovCloud (US-West) regions where Amazon Connect Customer is offered. To learn more, see the Amazon Connect Customer Administrator Guide. To learn more about Amazon Connect Customer, visit the Amazon Connect Customer website.

AWS Transform for .NET modernization is now generally available via CLI

aws@amazon.com — Wed, 09 Sep 2026 20:00:00 GMT

Today, AWS announced the general availability of an AWS-managed transformation for .NET modernization in AWS Transform custom that you can trigger with a single one-line CLI command. You can run this transformation interactively, or script it into any existing pipeline or workflow to run autonomously. The CLI experience complements the existing AWS Transform for .NET experiences: the web application, Visual Studio IDE, Kiro Power, and MCP agents.

AWS Transform custom enables organizations to modernize and transform code at scale using AWS-managed and custom transformations. You can upgrade language versions, migrate frameworks, optimize performance, and analyze code bases using transformations that are ready to use or can be customized to meet your organization's specific requirements. These transformations benefit from continuous improvement, learning from each engagement to deliver more accurate and efficient results.

AWS Transform custom and AWS Transform for .NET are available in eight AWS Regions: US East (N. Virginia), Asia Pacific (Mumbai, Tokyo, Seoul, Sydney), Canada (Central), and Europe (Frankfurt, London).

The .NET modernization transformation includes 50,000 free agent minutes per month. View AWS Transform Pricing for pricing details and examples. To learn more, see AWS-Managed Transformations in the AWS Transform User Guide.

AWS Lambda now supports 90-minute function timeout on Lambda Managed Instances

aws@amazon.com — Wed, 09 Sep 2026 18:00:00 GMT

AWS Lambda now supports a 90-minute function timeout for asynchronous and event source mapping (ESM) invocations on Lambda Managed Instances (LMI), a 6x increase from the previous 15-minute limit. You can now run data processing, media transcoding, financial calculations, AI inference, and batch workloads on Lambda for jobs that require longer continuous execution, without re-architecting your applications.

Customers use Lambda to build serverless applications like event-driven processors, API backends, and data processing pipelines. For data-intensive workloads like media transcoding, financial calculations (such as Monte Carlo simulations), and AI inference that need longer continuous execution, Lambda's 15-minute function timeout limit required customers to adopt architectural workarounds. With today's launch, you can configure a function timeout of up to 90 minutes for asynchronous and ESM invocations on Lambda Managed Instances. Lambda Managed Instances lets you process multiple concurrent requests per instance, access specialized compute configurations, and drive cost efficiency through EC2 pricing advantages, without managing infrastructure. The increased function timeout also applies to invocations within Lambda durable functions, which allow you to checkpoint and replay steps for longer-running invocations. When invoked asynchronously, a multi-step durable execution can run for up to 1 year.

You can configure up to a 90-minute function timeout for asynchronous and ESM invocations via the AWS Lambda Console, AWS CLI, Lambda APIs, Infrastructure as Code tooling, or the Agent Toolkit for AWS. Synchronous invocations retain the existing 15-minute maximum timeout. This feature is available in all AWS Regions where Lambda Managed Instances is available.

To learn more about configuring the 90-minute function timeout, see the Lambda developer guide. For combining extended timeouts with checkpoint-and-replay resilience, see the durable functions documentation. For pricing details, see AWS Lambda Pricing. To learn more about AWS Lambda, visit aws.amazon.com/lambda.

AWS Lambda now supports Graviton5-powered EC2 instances on Lambda Managed Instances

aws@amazon.com — Wed, 09 Sep 2026 18:00:00 GMT

AWS Lambda now supports AWS Graviton5-powered C9g, C9gd, M9g, and M9gd instances on Lambda Managed Instances. You can now run your Lambda functions on the latest generation of Graviton processors, delivering up to 25% better compute performance compared to Graviton4-powered instances.

AWS Lambda Managed Instances lets you run Lambda functions on your AWS EC2 instances while maintaining Lambda's operational simplicity. With Lambda Managed Instances, you can access specialized compute configurations and drive cost efficiency through EC2 pricing advantages, without managing infrastructure. Lambda Managed Instances fully manages all infrastructure tasks, including instance lifecycle, OS and runtime patching, built-in routing, load balancing, and auto-scaling based on configurable parameters - so you can focus on writing code. Starting today, you can leverage Lambda Managed Instances with the latest Graviton5-powered instances, which deliver up to 25% better compute performance compared to the previous generation Graviton4-powered instances.

To get started, you can specify the desired Graviton5 instance type (C9g, C9gd, M9g, or M9gd) when you create a capacity provider. When you set the instance type to default, Lambda automatically includes Graviton5 instances in the list of instances it chooses from, based on your function’s configured architecture, memory size, and memory-to-vCPU ratio.

AWS Lambda Managed Instances supports C9g, C9gd, M9g, and M9gd instance types in all AWS Regions where both Lambda Managed Instances and these EC2 instances are available. To learn more, visit the Lambda Managed Instances documentation and AWS Lambda pricing.

Amazon Bedrock Managed Knowledge Base adds APIs and console support for debugging document-level access control

aws@amazon.com — Wed, 09 Sep 2026 16:03:00 GMT

AWS announces the CheckIngestedDocumentAcl and GetIngestedDocumentAcl APIs for Amazon Bedrock Managed Knowledge Base, giving customers a self-service way to debug document access issues and audit document-level permissions. When a user doesn't see an expected document in retrieval results for ACL-enabled data sources, it can be difficult to determine whether the cause is an access control misconfiguration or something else entirely. These new APIs and the accompanying console experience close that gap, enabling you to quickly diagnose and resolve permission issues without opening a support case.

CheckIngestedDocumentAcl lets you verify whether a specific user has access to a given ingested document, while GetIngestedDocumentAcl returns the full ACL attached to a document so you can audit exactly what permissions are configured and catch misconfigurations. The console also introduces a new Document Access Control section on the data source details page, where you can check access by entering a document ID and user email or retrieve a document's full ACL by document ID. Together, these capabilities give administrators the visibility they need to manage access control at scale across enterprise knowledge bases.

To learn more, see CheckIngestedDocumentAcl and GetIngestedDocumentAcl in the Amazon Bedrock API Reference. For more information about Amazon Bedrock Managed Knowledge Base, visit the Amazon Bedrock Knowledge Bases product page.

Amazon Quick adds always-on agents, a sharper feed, and enterprise controls

aws@amazon.com — Wed, 09 Sep 2026 15:51:00 GMT

Today, Amazon Quick offers new capabilities that make it easier to organize your work, govern it across an organization, and trust the answers it produces. These capabilities build on Amazon Quick across desktop and mobile, bringing enterprise-grade management, richer collaboration, and always-on intelligence to teams wherever they work.

Your agents no longer stop when you step away. Scheduled tasks and monitoring agents run in the cloud and deliver results to your feed even when your laptop is closed. A sharper activity feed adds top-level filters, an improved catch-up view, a daily briefing that refreshes three times a day, and search across up to seven days of feed data, so you see what needs you first. Administrators gain mobile device management support, custom per-user permissions, and Microsoft Purview data loss prevention integration. Teams can share files and publish agents and skills for others to discover and install, and browse a catalog of official skills. Quick spaces and Quick apps now run natively on the desktop, any indexed local folder can become a searchable space, and inline citations let you verify every answer against its source. Additionally, every Quick subscriber now gets more agent hours each month — Professional grows from 4 to 8 and Enterprise from 8 to 18 — combined into a single, simpler allotment.

New users can create an account for free and start using Quick in minutes.Or to learn more, visit the Amazon Quick product page.

Amazon Quick activity feed now available on iOS and Android mobile devices

aws@amazon.com — Wed, 09 Sep 2026 15:39:00 GMT

The Amazon Quick activity feed is now available on the Amazon Quick mobile app for iOS and Android, keeping you connected to your most important work from anywhere.

The activity feed is your single, prioritized view of everything that needs your attention across your enterprise communications and tools, so you don't have to check each one separately. Items requiring your attention populate the top of your feed, and instead of switching between apps, you can take action directly from within Quick. Never miss something time-sensitive, even when you're away from your desk. Your decide which notifications are important and which are noise. Over time, Quick learns your priorities and surfaces only the things that matter.

You can also ask Quick to post anything to your feed through a routine, pulling from any connected data source. For example, you can tell Quick “every morning at 7:30, tell me which customer meetings I have that day and give me 3 bullet points to prep”.

Additionally, as part of today's announcement, Amazon Quick retains context across the desktop and mobile applications. Any work you do on one surface carries over to the other, so you can start a chat or assign a task to an agent on your desktop, then review progress and continue the chat from your mobile device, picking up right where you left off when you're back at your computer.

The Amazon Quick mobile app is included with your existing Amazon Quick access at no additional cost.

Existing Quick customers can download the Quick mobile application for iOS from the Apple App Store, and Android from the Google Play Store. If you're new to Quick, visit the Quick Product Page to create an account for free in minutes.

Amazon Quick desktop app is now generally available on macOS and Windows

aws@amazon.com — Wed, 09 Sep 2026 15:23:00 GMT

The Amazon Quick desktop app is now generally available on macOS and Windows. The desktop app brings the full power of Amazon Quick to your computer, working directly with your local files and staying connected to your calendar, email, and business apps in the background. Quick keeps your conversations, context, and agents synchronized across the desktop and mobile applications, so work you start on one surface carries over to the other, enabling you to work wherever you want.

Additionally, with this release, Amazon Quick agents run continuously in the background, even after you close your computer, so long-running work keeps making progress while you're away. Start an agent before you leave the office, provide additional inputs from the mobile app during your commute home, and then review the final output when you arrive. Quick offers production-grade stability, maintains AWS SLA commitments, and offers the governance and administrative controls for deployments at enterprise scale.

The Amazon Quick desktop app is available in 7 regions, US East (N. Virginia), Asia Pacific (Sydney), US West (Oregon), Europe (Ireland), Europe (London), Asia Pacific (Tokyo), and Europe (Frankfurt)

Existing Quick users can download the desktop app from here. The Quick mobile application is available for free from the Apple App Store and Google Play Store.

Amazon Bedrock Managed Knowledge Base now supports Confluence Data Center as a native data source connector

aws@amazon.com — Wed, 09 Sep 2026 14:19:00 GMT

AWS announces the Confluence Data Center data source connector for Amazon Bedrock Managed Knowledge Base, a fully managed retrieval-augmented generation (RAG) service. Customers running self-hosted Confluence Data Center instances can now crawl blogs and pages from their Confluence spaces directly into their managed knowledge base. Previously, bringing Confluence Data Center content into Bedrock Knowledge Bases required building custom ingestion pipelines—now, you provide your instance credentials, and the connector handles data crawling, metadata extraction, and incremental sync automatically.
The Confluence Data Center connector gives your AI agents access to the institutional knowledge your teams already maintain in Confluence, including wiki pages and blog posts across spaces. You can use filters to scope crawls to specific spaces or content types, ensuring only relevant content is ingested and keeping your knowledge base focused and cost-efficient. This makes it easy to power internal assistants grounded in engineering documentation, runbooks, or team knowledge bases hosted on Confluence Data Center.
To learn more, see Confluence Data Center data source connector in the Amazon Bedrock User Guide. For more information about Amazon Bedrock Managed Knowledge Base, visit the Amazon Bedrock Knowledge Bases product page.

Amazon EBS Volume Clones now supports copying volumes across accounts

aws@amazon.com — Wed, 09 Sep 2026 10:00:00 GMT

Amazon Elastic Block Store (Amazon EBS) Volume Clones now supports copying EBS volumes across AWS accounts with re-encryption. You can copy EBS volumes to any AWS account, re-encrypting with an AWS Key Management Service (AWS KMS) key in the target account. This enables organizations that separate production and development workloads into different accounts to copy data across those account boundaries.

With cross-account copy, you can clone a production database volume into an isolated development account, giving developers a fresh copy of production data to experiment with safely. This capability also supports teams that require encryption key separation across environments, such as maintaining separate KMS keys for production and non-production accounts. Cross-account copy is supported for all volume types, including unencrypted volumes and volumes encrypted with customer managed keys.

To copy a volume across accounts, you first share the volume with the target account using AWS Resource Access Manager (AWS RAM), and then the target account creates a copy of the shared volume in the same Availability Zone. You can access this capability using the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. It is available in all AWS Regions that support Amazon EBS Volume Clones, including all Commercial Regions, the AWS GovCloud (US) Regions, AWS China Regions, and supported Local Zones.

To learn more, visit the Amazon EBS Volume Clones documentation.

AWS Private CA EKS add-on and Connector for AD now available in AWS GovCloud (US)

aws@amazon.com — Wed, 09 Sep 2026 08:00:00 GMT

AWS Private Certificate Authority (AWS Private CA) announces the availability of the AWS Private CA Connector for Kubernetes as a managed Amazon EKS add-on and the AWS Private CA Connector for Active Directory in AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions. These launches expand certificate automation capabilities available to AWS GovCloud (US) customers managing government workloads.

The AWS Private CA Connector for Kubernetes EKS add-on provides simplified installation, configuration, and lifecycle management through the EKS console, CLI, and API. The connector works with cert-manager to automate certificate requests, distribution to Kubernetes secrets, and renewal, enabling TLS for ingress controllers and securing service-to-service communication in service meshes such as Istio and Linkerd.

The AWS Private CA Connector for Active Directory enables AWS GovCloud (US) customers to use AWS Private CA as their certificate authority for Active Directory-enrolled objects. The connector provides automatic certificate issuance to domain-joined users, computers, and other objects through familiar Microsoft certificate enrollment interfaces, supporting enterprise scenarios including smart card authentication, LDAPS, and network device authentication (802.1x).

AWS Private CA secures private key material using FIPS 140-3 Level 3 hardware security modules (HSMs).

To get started, see the AWS Private CA product page, the Amazon EKS add-ons user guide, and the AWS Private CA Connector for Active Directory documentation.

AWS Systems Manager now diagnoses more issues that cause EC2 instances to be unmanaged

aws@amazon.com — Wed, 09 Sep 2026 08:00:00 GMT

Today, AWS Systems Manager extends its diagnosis capability to identify six additional categories of issues that can prevent Amazon EC2 instances and hybrid-activated nodes from becoming managed by Systems Manager. An instance must be managed by Systems Manager before you can patch it, run commands, connect with Session Manager, or collect inventory, and when an instance is unmanaged the cause can be difficult to isolate. The diagnosis previously covered network connectivity, and it now also identifies issues with IAM permissions, SSM Agent version, instance status checks, operating system configuration, Default Host Management Configuration, and hybrid activation.

With this broader coverage, more of your instances return a specific, actionable cause instead of an unidentified result, so you can bring your fleet under management faster. You run a diagnosis across your instances in the Systems Manager unified console experience, and Systems Manager reports the specific issues it finds in each category. Every diagnosed issue comes with step-by-step guidance to help you resolve it, and for some issues you can also run an AWS Systems Manager Automation runbook from the console to remediate the issue directly.

AWS Systems Manager diagnosis capability is available in all AWS Regions that are enabled by default. The capability runs as AWS Systems Manager Automation runbooks, so you pay standard Automation usage charges for the runbooks you run; see AWS Systems Manager pricing for details. To learn more, see the AWS Systems Manager User Guide, or visit the AWS Systems Manager product page.

AWS Entity Resolution adds record-level confidence scores for ML matching

aws@amazon.com — Wed, 09 Sep 2026 08:00:00 GMT

AWS Entity Resolution now provides record-level confidence scores for Machine Learning (ML) based matching workflows, giving you a per-record signal of how confident the model is in each individual identity match. Previously, all records within a match group carried the same group-level confidence score regardless of actual match quality — making it impossible to distinguish a near-certain match from a borderline one. This forced customers to apply a single confidence threshold across all records, limiting the number of resolved identities that could be activated downstream.

With record-level confidence scores, each resolved record now carries its own score reflecting actual match quality. This gives you the precision to qualify more records for activation by applying differentiated thresholds — using higher confidence for automated merges and lower thresholds to include additional records that still meet quality standards. The result is larger addressable audiences and improved lead conversions, while maintaining compliance-grade match transparency with audit-ready evidence for each resolved record. For incremental ML workflows, the existing RecordConfidenceLevel column now reflects the actual per-record score with no schema changes required.

You can start using record-level confidence scores in all AWS Regions where AWS Entity Resolution is available. For more information, see our user guide. For more information about AWS Entity Resolution, visit our product page.

Amazon Connect Customer Profiles now sends events when customers enter or exit segments

aws@amazon.com — Wed, 09 Sep 2026 08:00:00 GMT

Amazon Connect Customer Profiles now sends segment membership events, providing the ability to receive real-time and scheduled notifications when customer profiles enter or exit a segment, such as high-value customers or low-satisfaction customers. Previously, detecting when customer profiles joined or left a segment required exporting entire segments at regular intervals and running custom scripts to identify differences. This manual process consumed resources, introduced errors, and created multi-hour delays between a customer qualifying for a segment and downstream systems acting on it.

With segment membership events, Customer Profiles automatically evaluates and streams membership changes directly to your Amazon Kinesis Data Stream. For segments built with standard conditions, changes are detected in near real-time as profile attributes update. For enhanced segments (using Spark SQL), periodic snapshots evaluate membership at configurable intervals and notify you of changes. Each event includes the profile ID, segment name, operation type (joined or left), and whether the change detected occurred in real-time or during a scheduled run, giving you everything needed to activate outbound campaigns, personalization workflows, or retention actions within seconds instead of hours.

You can start using segment membership events in all AWS Regions where Amazon Connect Customer Profiles is available. To get started, configure an Amazon Kinesis Data Stream in your domain settings and subscribe your segments. For more information, see our admin guide. For more information about Amazon Connect Customer Profiles, visit our product page.

OpenAI GPT-6 Astra is now generally available on Amazon Bedrock

aws@amazon.com — Tue, 08 Sep 2026 22:49:00 GMT

Today, AWS announces the general availability of GPT-6 Astra from OpenAI on Amazon Bedrock. The latest and most capable model from OpenAI to date, GPT-6 Astra brings deeper reasoning and judgment, professional-quality writing and design, and advanced computer and browser use to demanding business workflows. It supports a context window of up to 1 million input tokens and can produce output aligned with organizational voice, templates, and standards. The Amazon Bedrock inference engine delivers the performance, security, and scale required for production workloads.

You can call GPT-6 Astra directly through supported Amazon Bedrock APIs or configure ChatGPT Work and Codex to use the model on Amazon Bedrock. Use it to build autonomous agents, analyze extensive document collections, investigate complex software issues, and create applications that require judgment across competing inputs. As part of this launch, OpenAI is also introducing new enterprise plugins for ChatGPT Work that extend Astra’s browser-use capabilities across common business applications. Established AWS controls help you secure workloads, govern access, and audit model invocation activity.

You can get started in the Amazon Bedrock console or programmatically supported Amazon Bedrock APIs. For information about supported AWS Regions, endpoints, APIs, features, inference profiles and pricing, see the Amazon Bedrock documentation. To explore what you can build with GPT-6 Astra, read the blog.

Amazon Timestream for InfluxDB 3 now supports custom plugins

aws@amazon.com — Tue, 08 Sep 2026 21:58:00 GMT

Amazon Timestream for InfluxDB now lets you run your own custom Python plugins on the managed versions of InfluxDB 3 Core and Enterprise editions. You host your plugin code in public or private repositories you control and the engine fetches and runs it in response to triggers, letting you implement logic specific to your workload without standing up separate external infrastructure.

Plugins run on the trigger types the processing engine already supports and with them, you can build custom data transformations, alerting, aggregation, and integrations with your own services, all running close to your data. Plugins execute in a managed Python environment that includes the standard library and Amazon-vetted packages , so you can move workload-specific processing into the database instead of operating a separate pipeline to do it.

To get started, set a plugin repository on a DB parameter group, apply that parameter group to your cluster, and create triggers that reference your plugin using the influxdb3 CLI or HTTP API; private repositories are authenticated with a token stored in AWS Secrets Manager. Custom plugins are available in all AWS Regions where Amazon Timestream for InfluxDB is available. To get started with Amazon Timestream for InfluxDB 3, visit the Amazon Timestream for InfluxDB console. For more information, see the Amazon Timestream for InfluxDB documentation and pricing page.

Amazon SageMaker Feature Store now supports individual feature updates to lower write latency

aws@amazon.com — Tue, 08 Sep 2026 21:19:00 GMT

Amazon SageMaker Feature Store is a fully managed capability that makes it easy to compute, store, and retrieve features for training and deploying AI models. SageMaker Feature Store now supports feature-level writes, a new capability for updating individual features in a record. Data scientists can now update one or more feature values in a single request, without rewriting the entire record.

Data scientists can use a single update call to replace the read-modify-write pattern their pipelines run today. Each write updates only the features in the request and leaves every other feature in the record unchanged, which lowers write latency and cost. When multiple pipelines write to the same feature group, each pipeline updates only the features it computes, so a streaming job and a nightly batch job can update the same record independently. This capability enables data scientists to update a single feature at high processing volumes, without building merge logic in their data ingestion pipelines.

This capability is now available in all AWS Regions where Amazon SageMaker Feature Store is available. For more information, see Amazon Feature Store Runtime, Standard V2 documentation and launch blog.

AWS Transform is now available in AWS GovCloud (US-West)

aws@amazon.com — Tue, 08 Sep 2026 21:00:00 GMT

AWS Transform is now available in the AWS GovCloud (US-West) Region, enabling government agencies and regulated organizations to plan and execute large-scale migrations to AWS. With this launch, customers operating in AWS GovCloud (US) can use the migration capabilities of AWS Transform to automate server migrations within an isolated environment designed to host sensitive data and regulated workloads. AWS Transform in this Region supports migrating servers to both AWS GovCloud (US-East) and AWS GovCloud (US-West) as target Regions.

Organizations migrating VMware, bare metal, Hyper-V, or database workloads can use AWS Transform to automate server replication and cutover, reducing the manual effort and risk involved in large-scale moves. This is particularly valuable for federal agencies, defense contractors, and regulated industries that must operate within the AWS GovCloud (US) boundary. Modernization, custom transformation, and assessment capabilities are not included in this regional launch and remain available in supported commercial Regions.

To get started, see the AWS Transform documentation or visit the AWS Transform product page.

Amazon API Gateway now supports mutual TLS for backend integrations

aws@amazon.com — Tue, 08 Sep 2026 19:16:00 GMT

You can now configure Amazon API Gateway REST APIs to present an AWS Certificate Manager (ACM) certificate to your backend during the TLS handshake, enabling mutual TLS (mTLS). Previously, API Gateway could present only a self-signed certificate that it generated; now you can use a certificate signed by a certificate authority you trust. Your integration endpoint validates this certificate during the handshake to confirm the connection comes from your API.

You can import a certificate into ACM from your existing public key infrastructure (PKI), or have ACM issue and manage one for you through AWS Private Certificate Authority. When a certificate is reimported or renewed in ACM, API Gateway propagates the update automatically, with no redeployment and no downtime. Combined with the existing inbound mTLS support for client connections, you can apply mutual authentication across both the client-to-API and API-to-backend connections, which is a common requirement in financial services, healthcare, and other regulated or zero-trust environments.

Mutual TLS for backend integrations is available in all commercial AWS Regions and the AWS GovCloud (US) Regions, where API Gateway REST APIs are available. You can configure it through the API Gateway console, AWS CLI, or AWS CloudFormation. To get started, see Amazon API Gateway documentation and AWS blog post.

Amazon RDS for MariaDB now supports community MariaDB minor versions 10.6.28, 10.11.19, 11.4.13, 11.8.9, and 12.3.3

aws@amazon.com — Tue, 08 Sep 2026 16:00:00 GMT

Starting today, Amazon Relational Database Service (Amazon RDS) for MariaDB now supports MariaDB minor versions 10.6.28, 10.11.19, 11.4.13, 11.8.9, and 12.3.3, the latest minors released by community MariaDB. In addition to operational improvements, these minor versions introduce support for post-quantum TLS (PQ-TLS) key exchange, providing you with post-quantum cryptography options for encrypting your data in-transit. We recommend upgrading to the newer minor versions to accept fixes for Common Vulnerabilities and Exposures (CVEs) in prior versions of MariaDB and to benefit from bug fixes, performance improvements, and new functionality added by the MariaDB community. Learn more about the enhancements in RDS for MariaDB in the RDS MariaDB release notes.

You can upgrade your database using Amazon RDS Blue/Green Deployments, in-place upgrade, or restore from a snapshot. To simplify operations at scale, enable automatic minor version upgrades and use the AWS Organizations Upgrade Rollout Policy to orchestrate upgrades across your clusters in phases. Learn more about performing version upgrades in the Amazon RDS User Guide. You can also migrate to RDS for MariaDB from external MariaDB sources using AWS Database Migration Service. Learn more about pricing details and regional availability at Amazon RDS for MariaDB.

Amazon RDS for MariaDB makes it simple to set up, operate, and scale MariaDB deployments in the cloud. Create or update a fully managed Amazon RDS for MariaDB database in the Amazon RDS Management Console.

Amazon Bedrock AgentCore Memory now supports direct ingestion to long-term memory

aws@amazon.com — Tue, 08 Sep 2026 16:00:00 GMT

Amazon Bedrock AgentCore Memory now lets developers submit content directly for long-term memory extraction without persisting it as a short-term memory event. The new IngestData API accepts content, fans it out to the memory's configured long-term memory strategies, and makes the resulting memory records available through the same retrieval operations used for any other long-term memory records, all without creating a short-term event.

Until now, all content had to be stored as a short-term memory event before extraction strategies could process it into long-term memory records. IngestData removes this requirement, enabling developers to adopt long-term memory independently of short-term memory.

IngestData supports both conversational payloads (messages with USER/ASSISTANT roles) and JSON payloads (behavioral events, activity logs, system events), and accepts optional metadata that feeds the same extraction pipeline as CreateEvent. After processing, developers can verify extraction results with ListMemoryRecords or RetrieveMemoryRecords, stream real-time notifications via Kinesis, and redrive failed extractions with ListMemoryExtractionJobs. To get started, see Direct ingestion to long-term memory in the Amazon Bedrock AgentCore Developer Guide. IngestData is available in all AWS Regions where Amazon Bedrock AgentCore Memory is supported.

AWS HealthOmics introduces resource fallback order for WDL workflows

aws@amazon.com — Tue, 08 Sep 2026 16:00:00 GMT

Today, AWS HealthOmics introduces the resource fallback directive, enabling you to define an ordered list of preferred accelerator types, including an option to fallback to CPU instances, for tasks in your Workflow Description Language (WDL) workflows. Researchers and bioinformaticians can use this directive to reduce time spent diagnosing and resubmitting runs due to accelerator constraints and keep production workflows running. AWS HealthOmics is a HIPAA-eligible service that helps healthcare and life sciences customers accelerate scientific breakthroughs at scale with fully managed bioinformatics workflows.

With resource fallback, you can prioritize your preferred accelerator for your task. When your preferred accelerator is unavailable, HealthOmics automatically moves through your specified alternatives in the fallback without resubmission. Each accelerator profile has a configurable timeout, giving you control over how long HealthOmics searches for that accelerator before moving to the next. Shorter timeouts help you move quickly through the fallback order, while longer timeouts increase the probability of reserving your preferred accelerator. You can also include a CPU profile as a final fallback to increase the likelihood of your task reserving an instance.

You can now use resource fallback for WDL workflows in all AWS HealthOmics Regions: US East (N. Virginia, Ohio), US West (Oregon), Europe (Frankfurt, Ireland, London), Israel (Tel Aviv), and Asia Pacific (Seoul, Singapore, Tokyo). To learn more, visit the advanced resource configuration documentation.

Dynamic Image Transformation for Amazon CloudFront adds four new features

aws@amazon.com — Tue, 08 Sep 2026 14:32:00 GMT

Today, AWS announced four new features for Dynamic Image Transformation for Amazon CloudFront (DIT), an AWS supported solution that helps customers transform images in response to their needs. Customers can now use enhanced smart cropping with custom label detection and advanced composition controls that preserve products, text, logos, and custom objects within cropped images. In addition, customers benefit from enhanced automatic image optimization that delivers appropriately sized images across every browser and device type, from phones and tablets to smart TVs, using CloudFront's multi-tier device detection to maximize optimization reach regardless of how users access content. DIT also introduces an interactive image transformation playground for testing and validating transformations, and achieves full feature parity between its ECS and Lambda architectures.

DIT's expanded smart cropping enables customers to combine multiple detection methods including faces, labels, text, logos, and custom Amazon Rekognition models, in a single request with configurable aspect ratios, padding, and gravity constraints prioritized by business need. Enhanced automatic optimization now uses a tiered detection approach, layering CloudFront's device classification headers and configurable fallbacks behind Client Hints, to eliminate the browser-support gap that left ~30% of traffic previously served unoptimized and extend right-sized image delivery beyond browsers to all device types. The image transformation playground displays transformed images with extended metrics including original and output dimensions, format, file size, compression ratios, and processing time, enabling customers to validate the performance of their transformation policies.

DIT is available in all commercial regions as well as the following four opt-in regions: Asia Pacific (Hong Kong), Middle East (Bahrain), Africa (Cape Town), Europe (Milan).

To learn more, visit the DIT solution page.

AWS Builder ID adds recovery options and multi-factor authentication for third-party logins

aws@amazon.com — Tue, 08 Sep 2026 08:00:00 GMT

AWS Builder ID, your personal profile for accessing AWS applications including AWS Builder Center, AWS Training and Certification, Amazon Quick and Kiro, now offers new ways to protect and recover your profile. You can add a recovery email and use new self-service options to regain access if you're locked out. You can also register multi-factor authentication (MFA) devices for any sign-in method, including third-party logins such as Google or Apple.

With these enhancements, you have more self-service options to recover your AWS Builder ID. Adding a recovery email provides a second verification factor that makes self-service recovery possible for more scenarios without the need to contact AWS Support. You can reset a forgotten password using a link sent to your primary or recovery email. If you lose access to your MFA device, you can regain access by verifying both your primary and recovery emails. If you use Google, Apple, GitHub or Amazon to sign in to Builder ID, you can now register MFA devices directly in AWS Builder ID, bringing the same strong account protection previously available to email and password users, and you can permanently switch your sign-in method to an email address and password if you lose access to the third-party account.

To learn more about AWS Builder ID and how to set up account recovery and MFA, visit the AWS Builder ID documentation.

Amazon EMR extends support at no additional cost for customers migrating off older releases

aws@amazon.com — Tue, 08 Sep 2026 08:00:00 GMT

Amazon EMR now gives you more time, at no additional cost, to migrate off older releases before they reach end of support. If you are actively migrating, your workloads on eligible releases keep receiving support while you move to a current release, with no opt-in and at no charge.

To give you more time to plan and migrate, Amazon EMR provides critical security fixes for releases 5.36 and 6.6 through 6.15 on a best-effort basis through June 30, 2027, and extended Standard Support for 7.0 through 7.10 releases through August 31, 2027. To receive an extension, contact AWS Support with your migration plan and any help you need with the upgrade.

This applies to all deployment models of Amazon EMR (EMR on EC2, EMR on EKS, and EMR Serverless), in all AWS Regions where Amazon EMR is available. For the full list of releases and their support dates, see the Amazon EMR standard support policy. To get the extended support, contact AWS Support with your migration plan, or use the Apache Spark Upgrade Agent to move your applications to a current release.

AWS announces Nx Plugin for AWS for scaffolding full-stack applications

aws@amazon.com — Tue, 08 Sep 2026 08:00:00 GMT

Version 1.0 of the Nx Plugin for AWS, an open source toolkit for scaffolding full-stack applications on AWS, is now available. AI assistants can stand up an application on AWS in minutes, but rarely get security, observability, and type-safety right in one pass. The plugin extends Nx, an open source, language-agnostic build system for monorepos, with generators that each build one part of an application on request, alongside the infrastructure to run it.

Generators cover AI agents and Model Context Protocol servers on Amazon Bedrock AgentCore, plus APIs, websites, and databases, built on proven open source frameworks in TypeScript and Python. Each writes out a working, deployable piece of your application, defining infrastructure as either AWS Cloud Development Kit (AWS CDK) constructs or Terraform modules, with recommended practices in place such as AWS WAF protection, access logging to Amazon CloudWatch, and AWS X-Ray tracing. The connection generator wires projects together with type-safe clients, so a breaking API change becomes a build error instead of a failed request in production.

Each generator produces the same result every time, making it a dependable foundation for an AI assistant to build on. The generated code belongs to you, with no runtime dependency on the plugin, and Nx migrations bring later improvements to workspaces you have customized.

The plugin is available under the Apache 2.0 license at no additional charge; you pay only for the AWS resources your applications use. To learn more, see the launch blog post and documentation.

Amazon RDS now supports the latest CU and GDR updates for Microsoft SQL Server

aws@amazon.com — Tue, 08 Sep 2026 07:30:00 GMT

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports the latest Cumulative Updates (CU) and General Distribution Release (GDR) updates for Microsoft SQL Server. This release includes support for Microsoft SQL Server 2016 SP3+GDR KB5102340 (RDS version 13.00.6500.1.v1), SQL Server 2017 CU31+GDR KB5102337 (RDS version 14.00.3540.1.v1), SQL Server 2019 CU32+GDR KB5102335 (RDS version 15.09.4480.2.v1), SQL Server 2022 CU26 KB5093420 (RDS version 16.00.4265.3.v1) and SQL Server 2025 CU7 KB5096981 (RDS version 17.00.4065.4.v1).

The GDR updates address vulnerabilities described in CVE-2026-47295, CVE-2026-47296, CVE-2026-54118, CVE-2026-55002. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5102340, KB5102337, KB5102335, KB5093420 and KB5096981. We recommend that you upgrade your Amazon RDS for SQL Server instances to apply these updates using Amazon RDS Management Console, or by using the AWS SDK or CLI. You can learn more about upgrading your database instance in the Amazon RDS SQL Server User Guide for upgrading your RDS Microsoft SQL Server DB engine.

Amazon S3 Object Lock now supports variable retention with event holds

aws@amazon.com — Tue, 08 Sep 2026 04:00:00 GMT

Amazon S3 Object Lock now supports variable retention, allowing you to apply write-once-read-many (WORM) protection to objects whose required retention period starts with a future event, such as a contract closing or an audit completing. You place an event hold with a retention duration on an object and S3 protects the object while the hold is in place. When you release the hold, S3 retains the object for the duration you specified. Unlike legal holds, which end protection immediately upon removal, event holds provide WORM compliance for the required retention period after the triggering event, so you can meet event-based retention requirements without retaining data longer than your policy requires.

You can apply event holds to individual objects, configure them as a bucket default, or apply them at scale with S3 Batch Operations. New AWS IAM and bucket policy condition keys let you control who can set or release holds and enforce minimum or maximum hold durations. AWS CloudTrail logs all hold operations and S3 Inventory reports hold status across your buckets.

Event holds for S3 Object Lock are available in all AWS Regions, including China Regions, at no additional charge. To learn more, read the AWS Storage Blog post, the S3 Object Lock overview page, and the S3 documentation. This capability has been assessed by Cohasset Associates for use in environments subject to SEC Rule 17a-4(f), FINRA Rule 4511, and CFTC Regulation 1.31.

Amazon MWAA Serverless is now available in AWS GovCloud (US)

aws@amazon.com — Fri, 04 Sep 2026 22:00:00 GMT

Amazon Managed Workflows for Apache Airflow (MWAA) Serverless is now available in AWS GovCloud (US-East) and AWS GovCloud (US-West). Amazon MWAA Serverless eliminates the operational overhead of managing Apache Airflow infrastructure by automatically provisioning and scaling compute resources on demand, with a pay-per-use model that charges only for actual workflow run time.

For a full list of supported regions, see the Amazon MWAA Serverless regions page. To learn more, see the Amazon MWAA Serverless documentation.

Amazon Bedrock Managed Knowledge Base introduces user-managed setup for SharePoint, OneDrive, and Confluence data sources

aws@amazon.com — Fri, 04 Sep 2026 21:29:00 GMT

AWS announces user-managed setup (3LO) for SharePoint, OneDrive, and Confluence data sources in Amazon Bedrock Managed Knowledge Base. Previously, configuring these data sources required generating 2LO credentials on the third-party side, which could be time-consuming and inaccessible for users who lack admin-level access to those systems. With user-managed setup, you simply sign in with your existing third-party credentials, and Amazon Bedrock Managed Knowledge Base handles authentication—allowing you to complete data source setup in just a few minutes.
This streamlined experience lowers the barrier to getting started with managed knowledge bases. Teams that want to quickly prototype an AI assistant grounded in their SharePoint documentation, OneDrive files, or Confluence wikis no longer need to coordinate with IT administrators to obtain service account credentials. User-managed setup complements the existing service account authentication, giving you a faster path to connect your data while still preserving the programmatic, enterprise-grade option for production workloads.
To get started, see the following resources:; SharePoint user-managed setup in the Amazon Bedrock User Guide, OneDrive user-managed setup in the Amazon Bedrock User Guide and, Confluence user-managed setup in the Amazon Bedrock User Guide

Amazon Bedrock Managed Knowledge Base now supports ServiceNow as a native data source connector

aws@amazon.com — Fri, 04 Sep 2026 21:14:00 GMT

AWS announces the ServiceNow data source connector for Amazon Bedrock Managed Knowledge Base, a fully managed retrieval-augmented generation (RAG) service. Customers can now connect their ServiceNow instance to crawl knowledge articles and service catalog items directly into their managed knowledge base. Previously, bringing ServiceNow content into Bedrock Knowledge Bases required building and maintaining custom ingestion pipelines—now, you simply provide your ServiceNow instance credentials, and the connector handles data crawling, metadata extraction, and incremental sync automatically.
The ServiceNow connector crawls knowledge articles and service catalog items, including file attachments, giving your AI agents access to the institutional knowledge already maintained in ServiceNow. You can scope crawls to specific knowledge bases, article categories, or service catalogs using sys ID inclusion lists, ensuring only relevant content is ingested. This makes it straightforward to power employee-facing IT assistants, HR helpdesks, or customer support agents grounded in your organization's up-to-date ServiceNow content.
To learn more, see ServiceNow data source in the Amazon Bedrock User Guide. For more information about Amazon Bedrock Managed Knowledge Base, visit the Amazon Bedrock Knowledge Bases product page.

Amazon Bedrock Managed Knowledge Base now supports automatic sync scheduling for data source connectors

aws@amazon.com — Fri, 04 Sep 2026 21:01:00 GMT

AWS announces automatic sync scheduling for Amazon Bedrock Managed Knowledge Base, a fully managed retrieval-augmented generation (RAG) service that handles data ingestion, storage optimization, and advanced retrieval without requiring you to manage vector databases or data pipelines. Previously, keeping your knowledge base current required manually triggering a sync each time your source data changed or building a custom solution. Now, you can configure daily, weekly, or monthly sync schedules for all native data source connectors, so your AI agents always retrieve the most up-to-date information.
With automatic sync scheduling, you can match your sync frequency to how often your source content changes. For example, set a daily sync for a rapidly evolving customer support knowledge base in Confluence, a weekly sync for SharePoint policy documents that update periodically, or a monthly sync for reference materials stored in Amazon S3. This eliminates the need to build and maintain custom scheduling workarounds, reducing operational overhead while ensuring your retrieval-augmented generation applications stay grounded in current enterprise data.
To learn more, see Sync scheduling for data sources in the Amazon Bedrock User Guide. For more information about Amazon Bedrock Managed Knowledge Base, visit the Amazon Bedrock Knowledge Bases product page.

Amazon EC2 now supports specifying compatible instance types on AMIs

aws@amazon.com — Fri, 04 Sep 2026 19:26:00 GMT

Amazon EC2 now enables AMI owners to define which instance types are compatible with their AMIs. Owners can specify supported instance types, unsupported instance types, or both — and any launch attempt on a non-permitted instance type is automatically blocked.

AMI owners now have a built-in way to prevent launches on instances that are not compatible with their AMIs. This reduces the risk of failed launches due to incompatible instance-AMI pairings. By default, an AMI can be launched on any instance type, so existing workflows remain unaffected until restrictions are explicitly applied.

This feature is available in all AWS Regions at no additional cost. To learn more, please visit the documentation.

Amazon GuardDuty adds optional threat detection rules

aws@amazon.com — Fri, 04 Sep 2026 17:01:00 GMT

Amazon GuardDuty now offers Custom Detection Rules, a library of 35 prebuilt, opt-in rules for CloudTrail management events that let you extend threat detection coverage to match your environment. Custom Detection Rules produces 26 unique finding types mapped to 10 MITRE ATT&CK® tactics, without the heavy lifting of log ingestion, normalization, or storage.

Some threat techniques, such as sharing an AMI externally, disabling flow logs, or signing in without MFA, could be meaningful indicators of compromise in some accounts but routine in others. Custom Detection Rules lets you enable these detections only where the activity is unexpected — expanding your TTP coverage tailored to your environment.

To get started, browse Custom Detection Rules via the GuardDuty console or API, and enable rules in dry-run mode to evaluate detection efficacy before going live.

Custom Detection Rules is available in all AWS commercial Regions and the AWS GovCloud (US) Regions. To learn more, see Amazon GuardDuty Custom Detection Rules. To receive programmatic updates on new Amazon GuardDuty features and threat detections, subscribe to the Amazon GuardDuty SNS topic.

Amazon ECS introduces Early Success Criteria for service deployments

aws@amazon.com — Fri, 04 Sep 2026 17:00:00 GMT

Amazon Elastic Container Service (Amazon ECS) now supports Early Success Criteria for rolling service deployments, giving you the flexibility to define when a deployment is considered successful based on your confidence level and the operational needs of your workload. This can help you complete deployments sooner and unblock subsequent deployments, CI/CD pipelines, and other dependent operations.

With Early Success Criteria, you configure the healthy percent - the proportion of desired tasks that must be running and healthy on the target service revision before the deployment is marked successful. For example, with a desired count of 100 and a healthy percent of 90%, Amazon ECS marks the deployment successful after 90 tasks are healthy and continues launching the remaining tasks through regular service scaling, outside the deployment lifecycle. This can benefit workloads running on specialized or constrained capacity, such as GPU-accelerated inference workloads, where hardware availability can extend task launch times. Early Success Criteria also gives you more control over how long deployment rollback monitoring applies, allowing it to protect the deployment until your configured success criteria are met while subsequent scale-out continues through regular service scaling. You can also choose how Amazon ECS handles source service revision cleanup using BLOCKING or DEFERRED. With BLOCKING, Amazon ECS completes source revision cleanup before declaring success. With DEFERRED, Amazon ECS declares success when the criteria are met and drains source revision tasks asynchronously outside the deployment. This benefits services with active long-lived connections or task scale-in protection, where source revision tasks may need to remain running without holding the deployment open.

The feature is available with the rolling deployment strategy in all AWS Commercial and AWS GovCloud (US) Regions. You can configure Early Success Criteria for new and existing Amazon ECS services using the AWS Management Console, AWS CLI, AWS SDKs, and infrastructure as code (IaC) tools. To learn more, see our documentation.

AWS MCP Server adds a serverless capability for AWS Lambda functions

aws@amazon.com — Fri, 04 Sep 2026 16:31:00 GMT

Today, AWS Model Context Protocol Server (AWS MCP Server) added a serverless capability so that coding agents such as Claude Code and Kiro can efficiently diagnose issues with your Lambda functions. The serverless capability helps you troubleshoot your running Lambda functions and their connected resources.

The AWS MCP Server, available through the Agent Toolkit for AWS or as a standalone installation, is a managed service that gives AI coding agents secure access to AWS services. With the new serverless capability in the AWS MCP Server, your coding agent inspects your Lambda function and its connected resources across Amazon API Gateway, Amazon EventBridge, Amazon S3, Amazon DynamoDB, Amazon SNS, Amazon SQS, and AWS Step Functions. The agent can correlate error signals against a 7-day baseline to pinpoint what changed, surface recurring errors to identify trends, retrieve the deployed configuration of your function and connected resources, provide a timeline of recent changes to track what happened, and analyze service latency across connected resources. As the agent gets comprehensive data in a single call, it consumes fewer tokens compared to orchestrating multiple API calls.

To get started, configure the Agent toolkit for AWS by running ‘aws configure agent-toolkit’ from the AWS CLI, or enable the AWS MCP Server directly.

The AWS MCP Server can access services in all commercial AWS Regions, while the AWS MCP Server itself runs in the US East (N. Virginia) and Europe (Frankfurt) Regions. The serverless diagnostic capabilities in the AWS MCP Server are available at no additional cost. To learn more, see the user guide.

Amazon EC2 C8g instances now available in additional regions

aws@amazon.com — Fri, 04 Sep 2026 14:06:00 GMT

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8g instances are available in AWS Asia Pacific (Taipei, New Zealand), and AWS GovCloud (US-East) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 C8g instances are built for compute-intensive workloads, such as high performance computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based machine learning (ML) inference, and ad serving. These instances are built on the AWS Nitro System, which oﬄoads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.

AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based Amazon C7g instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. C8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS).

To learn more, see Amazon EC2 C8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

AWS Transfer Family SFTP Connectors now support continuing file transfers during credential rotation

aws@amazon.com — Fri, 04 Sep 2026 08:00:00 GMT

AWS Transfer Family SFTP Connectors now continue running file transfers while you rotate the credentials used to authenticate with remote SFTP servers. You no longer need to update the connector to point to a new secret version each time a credential rotates, removing a manual step and helping avoid failed transfers during the rotation window.

Connectors can now retrieve credentials from an ordered list of AWS Secrets Manager version stages, such as the current and previous versions, during authentication. The connector automatically tries each version in the order you specify and proceeds with the first that succeeds, so transfers continue uninterrupted as credentials are rotated on either side. You configure this when you create or update a connector, and the connector's credentials must be stored in AWS Secrets Manager.

Support for continuing transfers during credential rotation is available in all AWS Regions where AWS Transfer Family SFTP Connectors are supported. To learn more, visit the AWS Transfer Family User Guide. Get started with AWS Transfer Family in the AWS Transfer Family console.

Amazon SageMaker AI Batch Transform now supports G6e instances

aws@amazon.com — Fri, 04 Sep 2026 08:00:00 GMT

Amazon SageMaker AI now supports Amazon EC2 G6e instances for batch transform. Batch Transform enables you to run predictions on datasets stored in Amazon S3 and is suited for large datasets that do not require a persistent inference endpoint.

Amazon EC2 G6e instances are powered by up to eight NVIDIA L40S Tensor Core GPUs with 48 GB of memory per GPU and third-generation AMD EPYC processors. G6e instances deliver improved performance for GPU-intensive workloads. With this launch, you can use G6e instances for GPU-intensive offline inference workloads, including large language models and diffusion models that generate images, video, and audio. To get started, select a supported ml.g6e instance type when creating a Batch Transform job through AWS SDKs, AWS CLI, or the CreateTransformJob API.

G6e support for Batch Transform is available in US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), and Asia Pacific (Hyderabad). To learn more, visit the Amazon SageMaker AI product page and see the Batch Transform documentation. For pricing information on these instances, please visit our pricing page.

Amazon EC2 C9g and C9gd instances are now available in Asia Pacific (Tokyo) region

aws@amazon.com — Thu, 03 Sep 2026 23:00:00 GMT

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C9g and C9gd instances, powered by AWS Graviton5 processors, are available in the Asia Pacific (Tokyo) region. AWS Graviton5 processors are the fifth generation of custom-designed CPUs, delivering the best price performance for compute-intensive workloads running on Amazon EC2.

C9g and C9gd instances deliver up to 25% better compute performance compared to AWS Graviton4-based C8g and C8gd instances. They are up to 30% faster for databases, up to 35% faster for web applications, and up to 35% faster for machine learning. These instances are built on the sixth-generation AWS Nitro System and are the first to feature the Nitro Isolation Engine, harnessing formal verification to provide mathematical assurance that customer workloads are isolated from each other and AWS operators, pioneering a new standard for mathematically proven cloud security.

C9g instances are ideal for workloads such as high-performance computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based machine learning (ML) inference, real time analytics, and ad serving. C9gd instances offer local NVMe-based SSD block-level storage for customers running compute-intensive workloads that also require high-speed, low-latency local storage for scratch space, temporary files, and caches.

C9g and C9gd instances are available for purchase in Asia Pacific (Tokyo) via Savings Plans, On-Demand, Spot instances, Dedicated instances, or Dedicated hosts. Level up your compute with AWS Graviton and get started today.

Amazon ECS Managed Daemons now support non-critical daemons

aws@amazon.com — Thu, 03 Sep 2026 22:01:00 GMT

Amazon Elastic Container Service (Amazon ECS) now support non-critical Managed Daemons for ECS Managed Instances. You can configure a daemon as non-critical so that your mission-critical application tasks continue running uninterrupted, even when a daemon fails, stops, or becomes unhealthy.

Amazon ECS Managed Daemons lets you centrally deploy and manage software agents independently of application deployments to ensure consistent coverage and compliance across your container infrastructure. For some mission-critical applications, uninterrupted execution of application tasks may matter more than auxiliary daemon functionality like logging or metrics collection. With this launch, you can now configure a managed daemon as non-critical so that its failure does not cause your application tasks to churn. When a non-critical daemon task fails, stops, or becomes unhealthy, the container instance remains active, your existing application tasks continue running uninterrupted, ECS continues placing new application tasks on it, and instance registration is never blocked, so your tasks launch immediately even when the daemon fails to start. Amazon ECS emits an EventBridge event when a daemon task fails to start and records service action logs for both critical and non-critical daemons, giving you full observability into daemon health.

To get started, you can use AWS Console, CLI, CloudFormation, or AWS SDKs to create a non-critical daemon by setting the critical parameter to false when creating or updating a daemon. Non-critical daemons are available in all AWS Regions where Amazon ECS Managed Daemons are supported. To learn more, refer to our documentation page.

Amazon EC2 M9g and M9gd instances are now available in four additional regions

aws@amazon.com — Thu, 03 Sep 2026 21:00:00 GMT

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M9g and M9gd instances, powered by AWS Graviton5 processors, are available in Europe (Ireland) and Asia Pacific (Singapore, Sydney, Tokyo) regions. AWS Graviton5 processors are the fifth generation of custom-designed CPUs, delivering the best price performance for memory-intensive workloads running on Amazon EC2.

M9g and M9gd instances deliver up to 25% better performance compared to AWS Graviton4-based M8g and M8gd instances. They are up to 30% faster for databases. These instances are built on the sixth-generation AWS Nitro System and are the first to feature the Nitro Isolation Engine, harnessing formal verification to provide mathematical assurance that customer workloads are isolated from each other and AWS operators, pioneering a new standard for mathematically proven cloud security.

M9g instances are ideal for workloads such as open-source databases, in-memory caches, big data analytics, and memory-intensive applications. M9gd instances offer local NVMe-based SSD block-level storage for customers running memory-intensive workloads that also require high-speed, low-latency local storage for scratch space, temporary files, and caches.

M9g and M9gd instances are available for purchase in these four regions via Savings Plans, On-Demand, Spot instances, Dedicated instances, or Dedicated hosts. Level up your compute with AWS Graviton and get started today.

Amazon EC2 P6-B200 instances are now available in the AWS Asia Pacific (Hyderabad) Region

aws@amazon.com — Thu, 03 Sep 2026 19:14:00 GMT

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) P6-B200 instances accelerated by NVIDIA Blackwell GPUs are available in the AWS Asia Pacific (Hyderabad) Region. These instances offer up to 2x performance compared to P5en instances for AI training and inference.

P6-B200 instances feature 8 Blackwell GPUs with 1440 GB of high-bandwidth GPU memory and a 60% increase in GPU memory bandwidth compared to P5en, 5th Generation Intel Xeon processors (Emerald Rapids), and up to 3.2 terabits per second of Elastic Fabric Adapter (EFAv4) networking. P6-B200 instances are powered by the AWS Nitro System, so you can reliably and securely scale AI workloads within Amazon EC2 UltraClusters to tens of thousands of GPUs.

P6-B200 instances are now available in p6-b200.48xlarge size in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), AWS GovCloud (US-West, US-East), and Asia Pacific (Hyderabad, Mumbai) Regions. To learn more about P6-B200 instances, visit Amazon EC2 P6 instances.

Amazon EC2 P6-B300 instances are now available in the AWS Asia Pacific (Jakarta) Region

aws@amazon.com — Thu, 03 Sep 2026 19:03:00 GMT

Starting today, Amazon Elastic Cloud Compute (Amazon EC2) P6-B300 instances are available in the AWS Asia Pacific (Jakarta) Region. P6-B300 instances provide 8xNVIDIA Blackwell Ultra GPUs with 2.1 TB high bandwidth GPU memory, 6.4 Tbps EFA networking, 300 Gbps dedicated ENA throughput, and 4 TB of system memory.

P6-B300 instances deliver 2x networking bandwidth, 1.5x GPU memory size, and 1.5x GPU TFLOPS (at FP4, without sparsity) compared to P6-B200 instances, making them well suited to train and deploy large trillion-parameter foundation models (FMs) including large language models (LLMs) with sophisticated techniques. The higher networking and larger memory deliver faster training times and more token throughput for AI workloads.

P6-B300 instances are now available in p6-b300.48xlarge size in the following AWS Regions: US West (Oregon), AWS GovCloud (US-East), US East (N. Virginia), Asia Pacific (Hyderabad, Jakarta, Seoul), and South America (Sao Paulo) Regions. To learn more about P6-B300 instances, visit Amazon EC2 P6 instances.

Amazon CloudFront announces API support for flat-rate pricing plans

aws@amazon.com — Thu, 03 Sep 2026 18:00:00 GMT

Starting today, customers can subscribe and manage flat-rate pricing plans programmatically using the AWS CLI, AWS SDKs, CloudFormation, CDK, or the PricingPlanManager API.

CloudFront flat-rate plans give you one monthly price covering global content delivery, WAF, DDoS, DNS, logging, and edge compute, with no usage-based overage charges regardless of traffic spikes or attacks. Previously, customers could only subscribe to flat-rate pricing plans using the console, which required manual steps when using the API or infrastructure as code (IaC) like CloudFormation to create and manage distributions. Now, customers can programmatically subscribe, upgrade, downgrade, and cancel flat-rate pricing plans using the API or IaC tools.

Paid plans support an optional two-phase activation flow: you first create the plan, then approve it to begin billing. This prevents you from being committed to charges before you confirm, and makes the API well-suited for automated workflows and agents that provision infrastructure on your behalf. Free plans activate immediately and don’t require approval. To learn more, refer to the Getting started with the PricingPlanManager API. There are no additional fees for using the API to manage flat-rate pricing plans.

Introducing Amazon Quick Max: 5x the usage for power users who want the most out of Quick

aws@amazon.com — Thu, 03 Sep 2026 17:17:00 GMT

Amazon Quick now offers Quick Max, a new plan for power users who want to get the absolute most out of Quick. With 5x the usage and 5x the storage of Plus, Max gives you the room to do more: more agents, more workflows, more of whatever makes Quick yours.

With Max, you can run large, concurrent workloads without interruption—all month long. It delivers more value per dollar the more you use it and is available with both monthly and annual billing options.

New to Amazon Quick? You can sign up for free in minutes. Already on Plus? Click your name at the bottom of the left navigation bar, then select "Upgrade plan" to switch to Max. To compare all available plans—Free, Plus, and Max—visit the Amazon Quick pricing page.

AWS Gateway Load Balancer now supports TCP Reset for faster failure recovery

aws@amazon.com — Thu, 03 Sep 2026 17:00:00 GMT

AWS Gateway Load Balancer (GWLB) now supports sending TCP Reset (RST) packets when a target becomes unhealthy, is deregistered, or when a flow's idle timeout expires. This feature helps reduce traffic interruptions from minutes to seconds by enabling TCP endpoints to quickly detect failed connections and establish new TCP flows through healthy targets.

Previously, when a GWLB target failed, existing TCP connections would continue to be forwarded to the unhealthy target (aka fail-open behavior). Client and server applications could experience interruptions lasting several minutes due to TCP retry and exponential back-off mechanisms built in the TCP stacks of clients or servers. When this capability is enabled, GWLB sends TCP Resets in response to the incoming traffic, indicating to the sender that a TCP connection is no longer viable. This allows TCP endpoints to recover in quickly.

TCP Reset is not enabled by default to ensure backward compatibility. You can enable it per target group using the AWS Management Console, AWS CLI, or API. Three triggers are supported independently for generating TCP Reset: target becomes unhealthy, target deregistration (after connection draining), and TCP idle timeout expiry.

This feature is available for all new and existing Gateway Load Balancers in all AWS Regions where GWLB is available. There is no additional charge for using this feature.

To learn more, visit this AWS blog, and GWLB User Guide here and here.

Amazon WorkSpaces Applications adds support for NVIDIA Blackwell GPU instances

aws@amazon.com — Thu, 03 Sep 2026 17:00:00 GMT

Amazon WorkSpaces Applications now supports Graphics G7 instances, powered by NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs and Intel Xeon Scalable (6th Gen) processors. G7 instances deliver up to 2.1× better performance for graphics-intensive workloads compared to previous generation G6 instances.

With Graphics G7, customers can stream demanding professional applications such as CAD/CAM, 3D rendering, scientific visualization, video editing, and AI-assisted design workflows at higher fidelity and frame rates. G7 instances feature 32 GB of GDDR7 GPU memory per GPU and 2.67× faster memory bandwidth, enabling streaming of larger, more complex 3D scenes and models. Six instance sizes are available, with 1 to 8 GPUs, vCPUs ranging from 8 to 192, and system memory from 32 GB to 768 GB.

Graphics G7 instances are available in US East (N. Virginia), US East (Ohio), and US West (Oregon). Additional regions will be added as availability expands.

To get started, select a Graphics G7 instance when launching an image builder or creating a new fleet in the Amazon WorkSpaces Applications console. For more information on available instance types, see WorkSpaces Applications Instance Families. To learn more about G7 GPU capabilities, visit the EC2 G7 Instance Types page. For pricing details, see Amazon WorkSpaces Applications Pricing.

Amazon Redshift rg.large instances now support single-node clusters

aws@amazon.com — Thu, 03 Sep 2026 16:03:00 GMT

Amazon Redshift rg.large instances, powered by AWS Graviton processors, now support single-node clusters. Single-node support for rg.large clusters is available on P204 or later patch versions. Customers can now create a single-node rg.large cluster for smaller workloads that do not require high availability, offering a cost-effective option to conduct proofs of concept and tests quickly.

RG instances deliver up to 2.4x faster performance running data warehouse and data lake workloads when compared to previous generation RA3 instances, at 30% lower price per vCPU. RG instances include Redshift's custom-built vectorized data lake query engine that processes Apache Iceberg and Parquet data on your cluster nodes, turning on SQL analytics across your data warehouse and data lake using a single engine.

These RG instances are available in the following AWS Regions: Africa (Cape Town), Asia Pacific (Hong Kong), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Osaka), Asia Pacific (Mumbai), Asia Pacific (Hyderabad), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Jakarta), Asia Pacific (Melbourne), Asia Pacific (Malaysia), Asia Pacific (Taipei), Asia Pacific (Thailand), Canada (Central), Europe (Frankfurt), Europe (Stockholm), Europe (Spain), Europe (Ireland), Europe (London), Europe (Paris), South America (São Paulo), US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), AWS GovCloud (US-East), AWS GovCloud (US-West) and Mexico (Central).

To learn more, visit the Amazon Redshift RG Instance Documentation, the RA3 to RG Upgrade Guide, and the Amazon Redshift pricing page.

Amazon Aurora MySQL 8.4.8 (compatible with MySQL 8.4.8) is now generally available

aws@amazon.com — Thu, 03 Sep 2026 16:01:00 GMT

Starting today, Amazon Aurora MySQL-Compatible Edition 8.4 will support MySQL 8.4.8. In addition to several security enhancements and bug fixes, Aurora MySQL 8.4.8 includes several improvements, such as support for post-quantum TLS (PQ-TLS) key exchange, transaction timeout, multi-source replication, and delayed replication. PQ-TLS provides you with post-quantum cryptography options for encrypting your data in-transit. Transaction timeout helps prevent performance issues caused by long-running transactions blocking innoDB purge.

Multi-source replication allows consolidation of data from multiple sources into a single replica to enable critical use-cases, such as merging shards, reporting, and backups. Delayed replication lets you set a configurable replication lag to protect against accidental data loss. To learn more about these replication features, please refer to the launch announcement. For more details, refer to the Aurora MySQL 8.4 and MySQL 8.4.8 release notes.

You can upgrade your databases during scheduled maintenance windows using automatic minor version upgrades. To simplify operations at scale, enable automatic minor version upgrades and use the AWS Organizations Upgrade Rollout Policy to orchestrate upgrades across your clusters in phases. You can perform minor version upgrades in-place or via snapshot restore. This release is supported in all AWS Regions where Aurora MySQL is available.

Amazon Aurora is designed for high performance and availability at global scale with full MySQL compatibility. It provides scale-to-zero serverless compute, Aurora Global Database for multi-Region resilience, Aurora I/O-Optimized for improved price performance on I/O-intensive workloads, and built-in security and continuous backups. To get started, take a look at Aurora’s getting started page.

Amazon Aurora MySQL now supports multi-source replication and delayed replication

aws@amazon.com — Thu, 03 Sep 2026 16:00:00 GMT

Starting today, Amazon Aurora MySQL supports two new replication capabilities: multi-source replication and delayed replication. Multi-source replication lets a single Aurora MySQL cluster replicate from multiple source databases at the same time, making it easier to consolidate data from separate MySQL databases. This enables critical use-cases, such as merging shards or aggregating data from separate databases (e.g. regional or departmental instances) into a central location for operational workflows, such as reporting and backups. To learn more, please refer to the MySQL multi-source replication documentation.

Delayed replication lets you configure a binlog replica to intentionally lag behind its source by a set period of time, giving you a simple safeguard against human error and logical data corruption. If a harmful change is made on the source, you can recover quickly by stopping replication to the replica before the change is applied and promoting it, without performing a full database restore. A delayed replica also provides a convenient fallback during upgrades and a way to inspect an earlier state of your data. To learn more, please refer to the MySQL delayed replication documentation.

Together, these capabilities give you greater flexibility and stronger data protection when replicating into Aurora MySQL. Multi-source replication and Delayed replication are supported on Aurora MySQL version 8.4.8 and higher, in all AWS Regions where Aurora MySQL is available. For additional information on Aurora MySQL disaster recovery, see the guidance from our solutions library. To learn more, please refer to Aurora MySQL 8.4 release notes.

Amazon Aurora is designed for high performance and availability at global scale with full MySQL compatibility. It provides scale-to-zero serverless compute, Aurora Global Database for multi-Region resilience, Aurora I/O-Optimized for improved price performance on I/O-intensive workloads, and built-in security and continuous backups. To get started, take a look at Aurora’s getting started page.

Amazon SageMaker Unified Studio Workflows support Python and Bash operators

aws@amazon.com — Thu, 03 Sep 2026 15:00:00 GMT

Amazon SageMaker Unified Studio Workflows now supports PythonOperator and BashOperator, enabling you to run custom Python functions and shell commands directly in your serverless workflows without provisioning separate compute resources. This eliminates the need to offload custom logic to Lambda or ECS for tasks like data transformations or shell script execution.

To get started, open a serverless visual workflow in your SageMaker Unified Studio project, search for PythonOperator or BashOperator in the task panel, and drag the node onto your canvas. Provide your Python or shell script files through the workflow settings, then point each operator to the function or command in your scripts. For example, configure PythonOperator to call a data transformation function or set BashOperator to run a shell command, all without leaving the visual canvas.

This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available. For more information, see Supported Regions for Amazon SageMaker Unified Studio.

To learn more, see Supported operators for Amazon MWAA Serverless workflows. To get started, see Serverless visual workflows in the Amazon SageMaker Unified Studio User Guide.

Amazon MWAA adds built-in monitoring with Amazon CloudWatch

aws@amazon.com — Thu, 03 Sep 2026 15:00:00 GMT

Amazon Managed Workflows for Apache Airflow (MWAA) now includes a built-in monitoring experience on the environment detail page in the AWS Management Console. A new metrics dashboard displays key Amazon CloudWatch metrics for your environment in one place, and each graph includes an optional toggle to overlay suggested warning ranges, helping you quickly identify conditions that may affect your environment's health and performance.

The environment detail page also now shows an alarms table that lists all Amazon CloudWatch alarms associated with your MWAA environment. You can use the one-click Create Recommended Alarms action to provision a curated set of alarms from an AWS-managed template, so you can start monitoring critical metrics without having to configure each alarm manually. This feature is available for Amazon MWAA Provisioned environments in all regions where Amazon MWAA is available. Standard Amazon CloudWatch pricing applies for metric queries and alarms.

To get started, open the AWS Management Console, review the Amazon MWAA supported regions, or visit the Amazon MWAA documentation to learn more.

Amazon Linux 2027 is now available in public preview

aws@amazon.com — Thu, 03 Sep 2026 08:00:00 GMT

Today, AWS announces the public preview of Amazon Linux 2027 (AL2027), the next version of the Amazon Linux operating system, purpose-built for cloud-native workloads on AWS with performance, scale, and security in mind. Built on AL2023's baseline, AL2027 is designed for customers running web applications, databases, containerized microservices, AI/ML workloads, and large-scale infrastructure who need a secure, stable, and AWS-native operating system.

AL2027 runs on kernel 7.1+, enables SELinux in enforcing mode as default, accelerates cryptographic performance with AWS-LC, and keeps builders current with the latest toolchains and language runtimes. For AI and machine learning workloads, it delivers access to accelerator drivers, including AWS Neuron driver support. The public preview gives customers hands-on access before general availability (GA) to experiment with new features, validate their applications, and provide direct feedback to the Amazon Linux team.

AL2027 Preview AMIs are available through the AWS Management Console across all commercial AWS Regions, with both x86-64 and ARM variants. Container base images are available on Amazon ECR Public Gallery. Customers can submit feedback through the AL2027 GitHub repository. For a full list of changes relative to AL2023, see the AL2027 documentation. To learn more, visit the Amazon Linux product page.

Amazon SES now supports S/MIME email signing

aws@amazon.com — Thu, 03 Sep 2026 07:00:00 GMT

Amazon Simple Email Service (SES) now supports Secure/Multipurpose Internet Mail Extensions (S/MIME) signing, giving you a way to help recipients verify your emails are authentic. An S/MIME signature lets recipients confirm that a message was sent by the holder of the From address and that its content was not altered in transit.

Previously, senders who needed S/MIME had to sign each message themselves before submitting it to SES, adding complexity to their sending. With this feature, you store your signing certificate in AWS Certificate Manager and enable S/MIME signing for your sender identity. SES then signs your messages automatically as you send, so you don't have to sign messages yourself beforehand. Recipients whose email clients don't support S/MIME can still read the message normally. This gives security-conscious senders a simple way to add digital signatures to their email while continuing to use their existing SES setup.

This feature is available in all AWS Regions where Amazon SES is available. To learn more about S/MIME signing in Amazon SES, visit the Amazon SES console or refer to the documentation.

Amazon S3 now supports PrivateLink for FIPS endpoints

aws@amazon.com — Thu, 03 Sep 2026 04:00:00 GMT

Amazon S3 now supports AWS PrivateLink for endpoints that have been validated under the Federal Information Processing Standard (FIPS) 140-3 program.

Customers with security and compliance requirements can use FIPS-validated cryptographic modules when connecting to S3 while keeping their traffic within their Virtual Private Cloud (VPC). To get started, create a new or edit an existing interface VPC endpoint for S3 and configure it to use the FIPS S3 endpoint.

AWS PrivateLink support for FIPS S3 endpoints is now available in the AWS US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Canada (Central), Canada West (Calgary), and AWS GovCloud (US) Regions, at no additional cost. To learn more, visit accessing AWS services through AWS PrivateLink, FIPS 140-3 Compliance, and S3 documentation.

AWS Transform announces general availability of Amazon FSx for NetApp ONTAP support

aws@amazon.com — Thu, 03 Sep 2026 03:00:00 GMT

AWS Transform for migrations adds Amazon FSx for NetApp ONTAP as a generally available storage target for block storage workloads, alongside Amazon EBS. With AWS Transform, you can now migrate block storage directly to FSx for ONTAP as part of the same migration wave that handles compute and networks, eliminating the need for intermediate storage platforms and separate migration tools.

Whether migrating from NetApp ONTAP, other block storage platforms, or VMware environments, your data access patterns and operational processes remain unchanged with FSx for ONTAP. Now your workloads run on a fully managed, production-ready shared storage service that combines ONTAP's enterprise capabilities with the scalability and resiliency of AWS. What previously required stitching together multiple tools is now a single migration workflow.

This capability is available in all AWS Transform supported target Regions and where Amazon FSx for NetApp ONTAP is supported. To get started, visit AWS Transform for migrations. To learn more about Amazon FSx for NetApp ONTAP, see the product page.

Web Search on Amazon Bedrock is now available in AWS GovCloud (US-West)

aws@amazon.com — Wed, 02 Sep 2026 17:52:00 GMT

The Web Search built-in server-side tool on Amazon Bedrock is now available in AWS GovCloud (US-West), helping bring grounded web results to compliance-sensitive government and public-sector workloads. Web Search helps supported OpenAI GPT models ground responses with information from the web. Responses include citations to the sources the model used so users can trace each claim back to its web origin. This can be especially valuable whenever an answer depends on information that changes over time or is more recent than a model's training data, such as current events, recent releases or live pricing. Because the tool runs inside Amazon Bedrock, you don't host a search index, manage crawlers, or write the tool-call loop yourself.

Web Search is designed to support the governance and data-handling standards AWS GovCloud (US) customers require. By default, it keeps your request data within the AWS boundary, serving results from a web index and cache maintained by Amazon. As an AWS-native capability governed by AWS Identity and Access Management (IAM), administrators can allow or deny it at the account or organization level and restrict it by Region, giving teams centralized control while keeping request data within the AWS boundary by default. To get started, add a tool of type web_search to the tools array in your OpenAI Responses API request using your existing OpenAI client library with an Amazon Bedrock API key. The model uses the tool only when it determines a request needs current information. At launch, Web Search in AWS GovCloud (US-West) supports GPT-5.4 , GPT-5.6 Terra and Luna models.

Web Search is available in AWS GovCloud (US-West), in addition to US East (N. Virginia), US East (Ohio), and US West (Oregon). To get started, see the Web Search technical blog. For implementation guidance, see the Web Search documentation. For pricing, see the Amazon Bedrock pricing page.

Amazon Connect Customer expands automated performance evaluations to Malay

aws@amazon.com — Wed, 02 Sep 2026 17:00:00 GMT

Amazon Connect Customer now automates evaluations of human and AI agents in Malay using generative AI. Managers define custom evaluation criteria in natural language and receive AI-generated evaluations with justifications in their preferred language. Performance evaluations also supports cross-language evaluation and can complete assessments in English, even when the conversation is in Malay. This enables multilingual contact centers to use a standardized evaluation framework across languages.

This feature is supported in 8 AWS regions including US East (N. Virginia), US West (Oregon), Europe (Frankfurt), Europe (London), Canada (Central), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Asia Pacific (Singapore). For information about Amazon Connect pricing, please visit our pricing page. To learn more, please visit our documentation and our webpage.

Amazon Quick adds new tool settings and Model Context Protocol (MCP) sync support for connectors

aws@amazon.com — Wed, 02 Sep 2026 16:54:00 GMT

Amazon Quick connectors let users leverage tools and services such as Outlook, Slack, Salesforce, Jira, and homegrown MCP servers directly into their workflows across chat, agents, apps, flows, and deep research. Today, Amazon Quick introduces new tool settings and MCP sync support that give admins and connector owners more control over how connectors are deployed and kept up to date.

Connector owners and admins can now selectively enable or disable individual tools within a connector to ensure only approved tools are available to end users. Additionally, new tool permission settings let connector owners decide which tools require consent before proceeding or give end users the flexibility to decide for themselves. Lastly, MCP sync keeps connectors current as external MCP servers add new tools, update descriptions, and evolve their capabilities, ensuring users always have the latest information to get their work done.

These features are available in all AWS Regions where Amazon Quick is available. To learn more, visit the Amazon Quick User Guide.

Amazon Connect Customer announces general availability of agentic CX designer

aws@amazon.com — Wed, 02 Sep 2026 16:00:00 GMT

Amazon Connect Customer announces the general availability of agentic CX designer, a no-code canvas for designing and deploying AI-powered self-service experiences. You can now build and launch voice and digital experiences that bring agentic and deterministic AI together to transform how you serve customers with the control and reliability enterprises demand. Your business teams users can go from designing conversations and integrating with the systems that run your business, to testing, to launching production-ready experiences in weeks, not months.

Agentic CX designer gives you the clarity of a flowchart with the power of a large language model. On a visual canvas you define the logic, guardrails, and integrations, and the model handles the natural conversation. For outcomes that have to be exact, such as eligibility, approvals, routing, or compliance, you define the workflow and the conversation follows it. You build, test, and deploy in the same place, so the team that designs an experience can validate it and put it into production without writing code or handing the work to engineering.

Second-generation AWS Outposts racks now in the AWS GovCloud (US) Regions

aws@amazon.com — Wed, 02 Sep 2026 16:00:00 GMT

Second-generation AWS Outposts racks are now supported in the AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions. Outposts racks extend AWS infrastructure, AWS services, APIs, and tools to virtually any on-premises data center or colocation space for a truly consistent hybrid experience.

Organizations from startups to enterprises and the public sector can now order their Outposts racks connected to the new supported regions, optimizing for their latency and data residency needs. Outposts allows customers to run workloads that need low latency access to on-premises systems locally while connecting back to their home Region for application management. Customers can also use Outposts and AWS services to manage and process data that needs to remain on-premises to meet data residency requirements. This regional expansion provides additional flexibility in the AWS Regions that customers’ Outposts can connect to.

To learn more about second-generation Outposts racks, read this blog post and user guide. For the most updated list of countries and territories and the AWS Regions where second-generation Outposts racks are supported, check out the Outposts rack FAQs page.

AWS CloudFormation now supports contract tests v2 for resource types

aws@amazon.com — Wed, 02 Sep 2026 15:23:00 GMT

AWS CloudFormation now supports contract tests v2, available through the --v2 flag of the cfn test command in the CloudFormation CLI. Previously, the contract test suite covered only basic scenarios around the CRUD handlers. Contract tests v2 adds deeper test scenarios that exercise your resource type implementation across each handler operation. All new resource types can run contract tests v2 through the test-type API during registry submission, and Java-based resource types can also run them locally with cfn test --v2, requiring only Docker and a built handler package.

Contract tests v2 introduces live-state verification that confirms actual resource state matches the requested state after create, update, and delete operations. Developers also benefit from schema backward-compatibility checks, test input linting that flags hardcoded Regions, account IDs, and partitions, and detailed HTML and JUnit XML reports for local contract test execution. These improvements significantly reduce iteration cycles by surfacing issues before registry submission.

Contract tests v2 is available in all AWS Regions where AWS CloudFormation is available. To learn more, visit the AWS CloudFormation contract tests documentation and the AWS CloudFormation product page.

AWS Config now supports 60 new resource types

aws@amazon.com — Wed, 02 Sep 2026 15:00:00 GMT

AWS Config now supports 60 additional AWS resource types across key services including Amazon Bedrock, Amazon EC2, Amazon SageMaker, and AWS Organizations. 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.

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 in Config rules and Config aggregators.

You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the resources are available:

Resource Types:

AWS::AppSync::ChannelNamespace	AWS::EC2::RouteServer	AWS::Organizations::Policy
AWS::AppSync::SourceApiAssociation	AWS::EC2::RouteServerEndpoint	AWS::Organizations::ResourcePolicy
AWS::Bedrock::EnforcedGuardrailConfiguration	AWS::EC2::RouteServerPeer	AWS::QuickSight::RefreshSchedule
AWS::Bedrock::Flow	AWS::EKS::PodIdentityAssociation	AWS::RDS::DBProxy
AWS::Bedrock::FlowVersion	AWS::ElasticLoadBalancingV2::ListenerRule	AWS::S3Vectors::Index
AWS::Bedrock::PromptVersion	AWS::GameLiftStreams::Application	AWS::SageMaker::Action
AWS::BedrockAgentCore::OAuth2CredentialProvider	AWS::GameLiftStreams::StreamGroup	AWS::SageMaker::Algorithm
AWS::BedrockAgentCore::PaymentManager	AWS::IdentityStore::Group	AWS::SageMaker::App
AWS::BedrockAgentCore::Policy	AWS::IoT::TopicRuleDestination	AWS::SageMaker::Context
AWS::BedrockAgentCore::PolicyEngine	AWS::Lightsail::Container	AWS::SageMaker::Hub
AWS::BedrockAgentCore::TokenVault	AWS::Lightsail::Database	AWS::SageMaker::MlflowApp
AWS::Chime::AppInstance	AWS::Lightsail::Distribution	AWS::SageMaker::ModelCard
AWS::CloudTrail::ResourcePolicy	AWS::Lightsail::Domain	AWS::SageMaker::ModelPackage
AWS::CodePipeline::Webhook	AWS::Lightsail::Instance	AWS::SES::MailManagerArchive
AWS::Config::OrganizationConformancePack	AWS::Lightsail::LoadBalancer	AWS::Transfer::WebApp
AWS::Connect::AgentStatus	AWS::Logs::ResourcePolicy	AWS::WorkSpacesWeb::TrustStore
AWS::Connect::EvaluationForm	AWS::MediaConnect::Bridge	AWS::WorkSpacesWeb::UserAccessLoggingSettings
AWS::Connect::View	AWS::NetworkManager::CoreNetwork	AWS::XRay::Group
AWS::Connect::ViewVersion	AWS::Organizations::Account	AWS::XRay::ResourcePolicy
AWS::EC2::NetworkPerformanceMetricSubscription	AWS::Organizations::Organization	AWS::XRay::SamplingRule

Amazon MemoryDB now supports AWS PrivateLink in the AWS GovCloud (US) Regions

aws@amazon.com — Wed, 02 Sep 2026 14:06:00 GMT

You can now use AWS PrivateLink to privately access Amazon MemoryDB from your Amazon Virtual Private Cloud (Amazon VPC) in the AWS GovCloud (US-West) and AWS GovCloud (US-East) Regions. AWS PrivateLink provides private connectivity between VPCs, AWS services, and on-premises networks, without exposing traffic to the public internet and securing your network traffic.

To use AWS PrivateLink with Amazon MemoryDB, you create an interface VPC endpoint for Amazon MemoryDB in your VPC using the Amazon VPC console, AWS SDK, or AWS CLI. With an interface VPC endpoint, you can privately access the Amazon MemoryDB APIs from applications inside your Amazon VPC. You can also access the VPC endpoint from other VPCs using VPC Peering or your on-premises environments using AWS VPN or AWS Direct Connect. To learn more, read the documentation, or get started in the Amazon VPC Console.

AWS User Experience Customization (UXC) is now available in all commercial AWS Regions

aws@amazon.com — Wed, 02 Sep 2026 13:00:00 GMT

AWS User Experience Customization (UXC) is now available in all commercial AWS Regions. UXC enables account administrators to set a custom account color and control which services and Regions appear in the AWS Management Console.

Previously, UXC was available only in US East (N. Virginia), requiring customers who manage these settings programmatically to direct API calls to that single Region. With today's expansion, customers can manage account customizations from any commercial AWS Region using the AWS CLI, AWS SDKs, or AWS CloudFormation — making it easier to configure the console experience alongside existing infrastructure automation.

UXC is available at no additional charge. To get started, see the AWS User Experience Customization documentation.

AWS Lambda now supports SnapStart for container image functions

aws@amazon.com — Wed, 02 Sep 2026 09:00:00 GMT

Starting today, AWS Lambda supports SnapStart for functions packaged as container images, reducing startup times from several seconds to as low as sub-second. Lambda SnapStart is an opt-in capability that makes it easier for you to build highly responsive and scalable applications without provisioning resources or implementing complex performance optimizations.

Customers deploy Lambda functions with container images to align with their organization's container-based deployment standards, or to package larger dependencies up to 10 GB. However, larger container images can experience startup times of several seconds as Lambda downloads image layers and initializes the runtime and application code. SnapStart addresses this by taking a snapshot of the initialized execution environment during function deployment, caching it, and resuming from it on invocation, instead of initializing from scratch. Previously, SnapStart was only supported for managed runtimes (Python, .NET, and Java). Starting today, customers can use SnapStart for container images to improve startup times for latency-sensitive workloads such as ML inference and interactive APIs.

Lambda SnapStart for container images is available in all commercial AWS Regions, except Asia Pacific (New Zealand) and Asia Pacific (Taipei).

You can activate SnapStart for new or existing container image functions using AWS Lambda API, AWS Console, AWS Command Line Interface (AWS CLI), AWS CloudFormation, AWS Serverless Application Model (AWS SAM), AWS SDK, and AWS Cloud Development Kit (AWS CDK). If you use an AWS base image for Lambda with Java (version 11+), Python (version 3.12+), or .NET (version 8+), the experience remains the same as with functions deployed as .zip file archives. For all other AWS base images for Lambda (for example, Node.js or Ruby) or custom base images, refer to the developer guide. For more information about SnapStart, see Lambda documentation. To learn more about pricing for SnapStart for container image functions, visit AWS Lambda Pricing.

Amazon SageMaker Unified Studio CI/CD adds notebook promotion and AI-assisted manifest generation

aws@amazon.com — Wed, 02 Sep 2026 08:00:00 GMT

Amazon SageMaker Unified Studio CI/CD expands its open-source deployment toolkit with two new capabilities: (1) an AI agent skill that automates manifest authoring, and (2) native notebook promotion across environments. Together, they help data teams go from project to production faster while maintaining best-practice defaults across stages.

AI-assisted manifest generation. The new generate-bundle-manifest agent skill inspects a project's connections, storage, and workflows and produces a ready-to-use deployment manifest. It applies least-privilege IAM guidance, substitutes environment variables in place of hardcoded resource identifiers, and sets safe defaults such as opt-in catalog handling. Teams can import the skill into their own agents to standardize how they package and promote SageMaker Unified Studio projects across development, test, and production accounts.

Native notebook promotion. The CI/CD toolkit now supports promoting native SMUS Notebooks alongside code, workflows, and catalog assets. Notebook promotion uses an in-place synchronization model that creates a notebook on first deployment and updates it on subsequent deployments, preserving run history across releases. Teams can promote every notebook in a project or select specific notebooks by ID, and a dry-run mode validates S3 connectivity, IAM permissions, and notebook counts before deployment. Notebook promotion integrates with the existing bundle, deploy, destroy, and dry-run commands and requires no changes to current pipeline structure.

Both capabilities are open source and available in all AWS Regions where Amazon SageMaker Unified Studio is offered.

To get started, visit the CICD-for-SageMakerUnifiedStudio repository on GitHub. For more information, see the CI/CD for Amazon SageMaker Unified Studio documentation.

Amazon RDS for SQL Server supports additional SQL trace flags

aws@amazon.com — Wed, 02 Sep 2026 07:00:00 GMT

Amazon RDS for SQL Server supports 18 additional SQL trace flags that you can enable through database parameter groups. Trace flags are configuration switches that modify SQL Server engine behavior — such as query optimizer cardinality estimation, lock escalation, statistics management, and memory handling — to allow database administrators to fine-tune performance and address workload-specific challenges. With this expansion, you have greater flexibility to optimize and stabilize your SQL Server workloads directly within your managed RDS environment.

The newly supported trace flags include: 647, 652, 1448, 3654, 4138, 4139, 7745, 8285, 8780, 9432, 9481, 9492, 9592, 11024, 11042, 12502, 12618, and 12656. These trace flags address scenarios such as query plan optimization, DDL performance improvements, availability group replication, Query Store behavior, automatic plan correction, and known engine bug mitigations. Because trace flags modify core SQL Server engine behavior, you should test them in a non-production environment before applying them to production instances. Some trace flags can impact system performance, increase memory usage, or change query execution plans in unexpected ways.

Trace flags are available in all AWS Regions where Amazon RDS for SQL Server is supported. To get started, update your RDS parameter group to enable the desired trace flags and apply it to your DB instance. To learn more, see Amazon RDS for SQL Server User Guide.

Amazon Quick now lets you build custom apps with natural language -

aws@amazon.com — Tue, 01 Sep 2026 21:37:00 GMT

Now generally available, Amazon Quick lets you build custom applications by simply describing them in natural language. Create project trackers, customer dashboards, and training portals in minutes instead of months. Whether you're a product manager, finance lead, HR partner, or ops analyst, you can now turn ideas into fully functional apps without writing any code. Tell Quick what you need, and it builds a live, connected application with real-time data from your existing business systems.

Quick connects directly to the tools and data your business already uses, including Salesforce, Jira, Asana, ServiceNow, Microsoft 365, Google Workspace, databases, and data warehouses. Your apps stay current automatically as underlying data changes, and every connection respects your organization's existing identity, authorization, and access control policies. Once built, you can publish and share apps instantly with specific users or your entire organization. Need to make a change like adding AI, updating the visual style, or connecting to another system? Just describe what you want and Quick handles it.

During preview, customers used Quick to replace spreadsheets and disconnected tools with purpose-built applications. New York Life built an e-learning portal for their Institutional Life team that consolidates onboarding, training, and compliance courses into a single experience. The Amazon Quick team tracks pipeline, customer requests, and adoption metrics in a weekly leadership review app that replaced manual data pulls from four different systems.

Building apps in Quick is available to Plus, Professional, and Enterprise customers starting September 1, 2026. To learn more, visit the Apps in Quick getting-started guide.

Amazon Bedrock AgentCore Identity now offers a managed consent portal

aws@amazon.com — Tue, 01 Sep 2026 21:29:00 GMT

Amazon Bedrock AgentCore Identity now offers a managed consent portal that eliminates the need for custom OAuth callback infrastructure when connecting agents to third-party tools and services.

Developers using AgentCore Gateway to connect agents with services such as GitHub, Salesforce, and Slack previously had to build, host, and maintain custom OAuth callback infrastructure to complete OAuth 2.0 three-legged authorization (3LO) flows. The new managed consent portal eliminates this undifferentiated heavy lifting for agent developers and platform administrators.

Each AgentCore Gateway receives its own managed consent portal with a dedicated hosted web client and credential provider list. Platform admins can share a portal URL with their team before sessions begin, granting consent for agents to call external tools on their behalf. End users can view their connection status at any time through a self-service interface without contacting an administrator.

Developers using agent IDE-based clients, which cannot natively present OAuth consent URLs or handle post-consent session binding, can now use the managed consent portal as a dedicated authorization surface for these workflows.

This feature is available in all commercial regions where Bedrock AgentCore Identity is available.

To learn more, visit the Amazon Bedrock AgentCore Identity documentation.

AWS Deadline Cloud now supports sharing job bundles

aws@amazon.com — Tue, 01 Sep 2026 20:16:00 GMT

AWS Deadline Cloud now supports sharing job bundles, giving teams a simple way to distribute and reuse render job templates without manual file distribution. Deadline Cloud is a fully managed service that helps teams run compute-intensive workloads in the cloud for visual effects, animation, product design, simulation, and gaming.

Job bundles define the jobs you submit to Deadline Cloud, including the job template, parameters, and asset references. Previously, sharing a bundle with teammates meant distributing files through shared drives or manual copying. Now, you can publish a bundle to your queue directly from the submitter or the command line, and it immediately becomes available to everyone with access to that queue. Shared bundles are packaged as portable archives and stored in the queue's existing job attachments bucket in Amazon S3, so there is no additional infrastructure or configuration to set up. This makes it easy for pipeline teams to publish standard, ready-to-submit job templates that artists can pick up and use.

You can browse bundles shared on your queue, on your local filesystem, or from your job submission history. You can preview each bundle's name, description, steps, and parameters before selecting it. New CLI commands let you manage shared bundles from the command line and integrate bundle sharing into pipeline scripts.

This feature is available in all AWS Regions where Deadline Cloud is available. To get started, visit the AWS Deadline Cloud documentation.

Amazon CloudWatch Database Insights now supports self-managed PostgreSQL

aws@amazon.com — Tue, 01 Sep 2026 19:00:00 GMT

Today, AWS announces support for self-managed PostgreSQL databases in Amazon CloudWatch Database Insights. Using CloudWatch Database Insights, you can now monitor your self-managed PostgreSQL instances running on Amazon EC2, alongside Amazon RDS and Amazon Aurora, to give you a complete view of your database fleet in a single console.

Amazon CloudWatch Database Insights is a database observability solution that provides a curated experience to help you monitor database fleet health, diagnose issues, and resolve performance bottlenecks. With support for self-managed databases, you use the Amazon CloudWatch agent to collect health and performance data from your self-managed PostgreSQL instances. Your database appears in the Database Insights fleet view with live performance data, including database load, wait event analysis, query-level statistics, and host metrics. Monitor and troubleshoot your self-managed PostgreSQL instances using the same familiar Database Insights console and workflows you already use for your AWS-managed databases.

Amazon CloudWatch Database Insights support for self-managed PostgreSQL is available in all AWS Commercial Regions. To get started, see Monitoring Self-Managed Databases in the Amazon CloudWatch User Guide. For pricing details, see the Amazon CloudWatch pricing page.

Amazon Kinesis Data Streams now supports a dry run feature to validate API requests

aws@amazon.com — Tue, 01 Sep 2026 19:00:00 GMT

Amazon Kinesis Data Streams now supports a dry run feature to check whether an API request would succeed without executing the operation. Customers can now set the new optional parameter ‘DryRun’ to true in their API requests to validate permissions before interacting with a stream in production.

Previously, customers had no safe way to test whether their application had the correct permissions to access a stream. They would often send a request engineered to fail after checking permissions, such as a PutRecord request with a payload deliberately larger than the maximum supported size. This approach was fragile as it depended on current service limits, and if those limits ever changed, the request could unexpectedly succeed, writing unintended records into the production stream and into any downstream consumers. Now, customers can simply set the parameter ‘DryRun’ to true to indicate they only want to validate the API request. If all checks complete successfully, the API returns a ‘DryRunOperationException’, confirming the request would have succeeded without the ‘DryRun’ parameter.

The dry run feature is available for five APIs (PutRecord, PutRecords, GetRecords, GetShardIterator, and SubscribeToShard) in all AWS Regions where Amazon Kinesis Data Streams is available. For more information about dry run, see Test your permissions and request inputs with dry run in the Amazon Kinesis Data Streams Developer Guide. To get started with dry run, see the Amazon Kinesis Data Streams API Reference.

AWS Marketplace reduces listing fee for professional services in multi-product solutions

aws@amazon.com — Tue, 01 Sep 2026 18:00:00 GMT

AWS Marketplace now offers a 0% listing fee for professional services purchased as part of a qualifying multi-product solution. This builds on the recent reduction of professional services listing fee to 0.5%. It further lowers the cost for any Partner that transacts services through AWS Marketplace, while retaining the billing benefits that come with it.

Over the past year, AWS Marketplace has built a set of capabilities purpose-built for discovering and purchasing services. Customers can find the right Partner through AI-powered discovery in Agent Mode, combine software and services in a single transaction through multi-product solutions, and pay through variable payment models like time-and-materials. The 0% fee for professional services within a multi-product solution complements these capabilities and further reduces the cost for Partners to sell solutions through AWS Marketplace.

A multi-product solution qualifies for the 0% fee when its professional services are combined with at least one other valid, paid subscription. The fee applies to new subscriptions, while existing subscriptions continue at their original terms. This applies to all commercial AWS Regions where AWS Marketplace operates.

To get started, Partners can review seller documentation and list multi-product solutions through AWS Partner Central . Customers can explore multi-product solutions directly on AWS Marketplace.

AWS Backup now supports protecting more than 1,000 Amazon S3 buckets per account

aws@amazon.com — Tue, 01 Sep 2026 18:00:00 GMT

AWS Backup now supports backup and restore of more than 1,000 Amazon S3 buckets per account, matching the Amazon S3 bucket quota configured for your account.

Previously, AWS Backup for Amazon S3 supported up to 1,000 buckets per account. With this launch, AWS Backup supports backing up all general purpose buckets in your account. Existing backup plans and configurations continue to work with no changes required if you are using default AWS Backup managed policies. For details on the required permissions for custom policies, see the AWS Backup documentation.

This capability is available in all AWS commercial and AWS GovCloud (US) Regions. To get started, visit the AWS Backup console.

Amazon Connect Customer dashboards now support compact mode

aws@amazon.com — Tue, 01 Sep 2026 17:00:00 GMT

Amazon Connect Customer now offers compact mode on the analytics dashboards, increasing data density so supervisors can see more of their operational data without scrolling. Compact mode reduces widget size, font, and minimizes filters to maximize screen space. For example, a supervisor on a 13-inch laptop toggles compact mode, which reduces row height, enabling them to view all team agents on the widget without scrolling and spot non-adherent agents faster.

Compact mode on dashboards is available in all AWS regions where Amazon Connect Customer is offered. To learn more about Amazon Connect Customer analytics dashboards, see the Amazon Connect Customer Administrator Guide. To learn more about Amazon Connect Customer, visit the Amazon Connect Customer website.

AWS Marketplace now supports auto-renewals for private offers

aws@amazon.com — Tue, 01 Sep 2026 15:00:00 GMT

AWS Marketplace now supports auto-renewals for private offers. This capability helps sellers and buyers maintain active software and service subscriptions without re-negotiation or re-purchasing at the end of the term. Negotiated pricing and contract terms carry forward automatically when buyers and sellers agree to renew. This helps reduce procurement overhead and prevent unintended lapses in subscriptions.

When creating a private offer, sellers define the renewal terms and choose how pricing carries forward: renewal with no price change, renewal with a fixed price change, or a price change within a defined range. Buyers can opt in or out during initial offer acceptance, and can update their preferences later as their business needs change. Before automatically renewing the subscription, AWS Marketplace notifies both parties and provides a comparison of the current and upcoming terms, including any pricing changes. Either party can opt out of an upcoming renewal before the renewal decision deadline. Buyers can map a purchase order to any renewal to maintain procurement controls. Both parties are notified when a renewal completes successfully.

This capability is generally available in all commercial AWS Regions for sellers creating direct private offers with contract pricing. No additional setup or onboarding is required. To learn more, see the AWS Marketplace Seller Guide and the AWS Marketplace Buyer Guide . Sellers can configure auto-renewing private offers in the AWS Marketplace Management Portal . Buyers can manage subscriptions and renewals in the AWS Marketplace Console .

Amazon MWAA supports Apache Airflow version 3.3.1

aws@amazon.com — Tue, 01 Sep 2026 15:00:00 GMT

Amazon Managed Workflows for Apache Airflow (MWAA) now supports Apache Airflow version 3.3.1, the latest release of the popular open-source workflow orchestration framework. Amazon MWAA is a managed orchestration service for Apache Airflow that makes it easier to set up and operate end-to-end data pipelines in the cloud.

Apache Airflow 3.3 introduces stateful tasks and multi-language support. With the new Task and Asset State Store, tasks can now persist durable state across retries and reruns, enabling cursor tracking and crash-safe reconnection to long-running jobs. The Language Task SDK (experimental) lets teams write task logic in Java or Go while keeping orchestration in Python. Additional improvements include expanded asset partitioning, pluggable retry policies, and bulk actions for DAG runs and task instances. Apache Airflow 3.3.1 also delivers stability, security, and UI improvements on top of these capabilities.

You can launch a new Apache Airflow 3.3.1 environment on Amazon MWAA, or upgrade from 3.2 or later, with a few clicks in the AWS Management Console in all currently supported Amazon MWAA regions. To learn more about Apache Airflow 3.3.1, visit the Amazon MWAA documentation and the Apache Airflow 3.3.1 change log in the Apache Airflow documentation.

Apache, Apache Airflow, and Airflow are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.

Claude Fable 5.1, Anthropic's new frontier model is now available on AWS

aws@amazon.com — Tue, 01 Sep 2026 14:30:00 GMT

Claude Fable 5.1 is generally available on AWS and brings Anthropic's most capable frontier model to all customers. Fable 5.1 delivers frontier intelligence for ambitious tasks across coding, scientific research, and enterprise workflows. A clear improvement over Claude Fable 5, Fable 5.1 is a step up in intelligence on the hardest reasoning tasks, providing better judgement on ambiguous work and fewer confident wrong answers. Claude Mythos 5.1, the same underlying model as Claude Fable 5.1 with its full cyber and bio capabilities retained for cybersecurity and biology research, is available with limited access.

Claude Fable 5.1 is built for long-running, high-stakes work that runs for hours and spans many applications. It can own more of a software project on its own, handling features across an entire codebase, code review, and performance work over sessions that run for hours. If it gets stuck, it says so instead of reporting success, and it is less likely to take shortcuts like disabling a failing test. It takes analysis from the first question to the finished document, and it is Anthropic's strongest model yet for knowledge work.

Anthropic has designated Fable 5.1 a Covered Model, a category of Claude models that carry additional data retention, safety review, and access policies wherever they're offered. Enterprise Frontier Safeguards (EFS) built in partnership between AWS and Anthropic, will let eligible customers use Covered Models while keeping their data in a cloud environment they control. Read the launch blog to learn more.

Customers have two ways to access Claude Fable 5.1: Amazon Bedrock and Claude Platform on AWS. To learn more, see the Amazon Bedrock documentation, regional availability, and Claude Platform on AWS documentation..

Claude Fable 5.1, Anthropic's new frontier model is now available on AWS GovCloud (US)

aws@amazon.com — Tue, 01 Sep 2026 14:00:00 GMT

Claude Fable 5.1 is generally available on Amazon Bedrock in AWS GovCloud (US) and brings Anthropic's most capable frontier model to regulated industry customers. Fable 5.1 delivers frontier intelligence for ambitious tasks across coding, scientific research, and enterprise workflows.

To learn more, see the Amazon Bedrock documentation, and regional availability pages.

Amazon CloudWatch now supports warm-up periods for alarms

aws@amazon.com — Tue, 01 Sep 2026 08:00:00 GMT

Amazon CloudWatch now lets you configure a warm-up period for metric alarms and log alarms, delaying alarm evaluation for a set time after the alarm is created. This reduces noise from missing data while a new resource or service starts up and begins publishing metrics. For example, a team that provisions a new microservice and its alarms together through a CI/CD pipeline can attach a warm-up period so alarms do not page the on-call engineer while the service is still starting up and has not yet published metrics.

Previously, when you created an alarm before the underlying metric was reporting data, CloudWatch evaluated the alarm right away using its "treat missing data" setting. For resources that take time to begin emitting metrics, such as a newly deployed application or service, this could cause the alarm to transition state and run actions on missing data during startup, triggering unnecessary notifications. A warm-up period fixes this by giving you two ways to hold off evaluation during startup: wait a fixed duration you set before evaluation begins, or let CloudWatch start evaluating automatically as soon as the metric actually has enough data to fill the alarm's evaluation window.

You set the warm-up period with the WarmUpConfiguration parameter when you create or update an alarm. Specify a warm-up duration from 1 to 2,880 minutes (2 days). By default, the alarm ends warm-up early and begins evaluating as soon as enough data fills its evaluation window. Additionally, you can optionally require the alarm to wait the full duration before evaluating.

Warm-up periods are available in all AWS Regions where Amazon CloudWatch is offered at no additional charge beyond standard CloudWatch alarm pricing.

To get started, see Alarm warm-up periods and Create an alarm that uses a warm-up period in the Amazon CloudWatch User Guide.

Amazon RDS Custom now supports the latest CU and GDR updates for Microsoft SQL Server

aws@amazon.com — Tue, 01 Sep 2026 07:30:00 GMT

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now supports the latest Cumulative Updates (CU) and General Distribution Release (GDR) updates for Microsoft SQL Server. This release includes support for SQL Server 2019 CU32+GDR KB5102335 (RDS version 15.00.4480.2.v1) and SQL Server 2022 CU25 + GDR KB5101347 (RDS version 16.00.4262.2.v1).

The GDR updates address vulnerabilities described in CVE-2026-47295, CVE-2026-47296, CVE-2026-54118, CVE-2026-55002. For additional information on the improvements and fixes included in these updates, see Microsoft documentation for KB5101347, KB5102335. You can upgrade your Amazon RDS Custom for SQL Server instances to apply these recommended updates using Amazon RDS Management Console, or by using the AWS SDK or CLI. To learn more about upgrading your database instances, see Amazon RDS Custom User Guide.