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AWS Recent Announcements Note
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AWS Recent Announcements

AWS (Amazon Web Services) provides various services under its umbrella including compute, storage, security, and application services. Here are some recent announcements and updates: 1. AWS Outposts: AWS Outposts is a fully managed service that offers infrastructure consisting of compute, storage, and database capabilities. The latest update includes launch of Outposts in various countries. 2. AWS Lambda: Provides a compute service on-demand resource. Recent updates include enhancements for concurrency control and integration with Amazon API Gateway. 3. Amazon S3: Offers durable storage. Recent updates include the launch of the application migration API and encryption for snapshots. 4. AWS Billing: Allows you to view detailed billing information, and recent updates include improvements in billing details. 5. AWS Config: Provides resource monitoring, reporting, and auto-remediation for AWS resources. Recent updates include a notification action and AWS Step Functions. 6. AWS Multi-Region Access Point for Amazon S3: Multi-Region Access Points for S3 provide a global namespace to deliver a fast, secure, and resilient storage service. 7. Amazon Route 53: Provides domain registration and DNS service. Recent updates include support for multi-Region Access Points for S3. 8. AWS Lake Formation: A data engineering, data transformation and data governance service. Recent updates include creation of workflows and database credentials connection using JDBC drivers. 9. Amazon EMR: A big data processing service used for data processing, analytics, machine learning (ML) etc. Recent updates include cluster versioning and bug fixes. 10. AWS Step Functions: A service for coordinating the components of distributed applications and microservice-oriented architectures. Recent updates include enhanced task token input handling and auto-replace.
Recent Announcements aws.amazon.com
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RSS Hunter RSS Hunter • Aug 19, 2024

Thread Of Notes

AWS Continuum now supports credential testing and accessible domain suggestions

AWS Continuum for penetration testing is a frontier agent that proactively secures applications throughout the development lifecycle by offering on-demand, customized penetration testing with real exploitability testing. Developers and security teams can now test login credentials and receive suggested domains before a penetration test runs. This makes it easier to configure an accurate network scope from the start, reducing misconfiguration and wasted test cycles. Previously, identifying all the URLs your application reaches required manual effort, and authentication failures were only discovered after a full test cycle completed, costing time and resources. With this launch, when you add login credentials during test configuration, AWS Continuum authenticates into your application exactly as a real user would, capturing every accessible domain reached during login and surfacing them as in-scope URL suggestions. You can review accessible domains, validate credentials, and confirm the agent covers the right endpoints, all before the real test begins. Accessible domains are returned regardless of whether the credential test succeeds, fails, or times out. You can learn more about this feature in our updated documentaiton. This capability is available in all regions where AWS Continuum for penetration testing is available and is detailed on the AWS Continuum product page.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-security-agent/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 18

Amazon ECS Express Mode now supports AWS Graviton (ARM64) workloads

Amazon Elastic Container Service Express Mode now supports specifying ARM64 as the CPU architecture for your service, making it easy to deploy ARM-based container images on AWS Graviton-powered compute and benefit from up to 40% better price-performance compared to x86-based instances. Amazon ECS Express Mode makes it easy to rapidly launch containerized applications, including web applications and APIs, by orchestrating and managing the cloud architecture for your application. You provide your container image, and ECS Express Mode handles the rest, configuring networking, load balancing, auto scaling, and deployments, and providing your application with an auto-generated URL. With ARM64 architecture support, you can choose the compute architecture that fits your workload, whether you're optimizing for cost with Graviton, matching your existing fleet, or deploying images built natively for ARM. You can configure the CPU architecture for new and existing Amazon ECS Express Mode services using the AWS Management Console, AWS CLI, AWS SDKs, and infrastructure as code (IaC) tools. This capability is available in all AWS commercial Regions and AWS GovCloud (US) Regions. To learn more, see the ECS Express Mode documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-ecs-express-mode-arm-architecture/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 18

AWS Resilience Hub adds three new capabilities

The next generation of AWS Resilience Hub is a central location in the AWS that helps platform engineering and site reliability teams assess and strengthen the resilience of their workloads running on AWS. It provides automated dependency discovery, generative AI-powered failure mode analysis, modular resilience policies, resilience testing, and organization-wide resilience posture reporting. Today, AWS Resilience Hub adds three new capabilities: EKS labels support for service input sources, dependency insights, and resilience policy sharing through AWS Organizations. EKS labels support for service input sources. Resilience Hub now supports EKS labels within a namespace as a service input source, allowing customers to use their existing Kubernetes labeling conventions to scope exactly which resources Resilience Hub discovers and uses during failure mode analysis. This ensures assessments stay aligned with how teams organize their EKS workloads. Dependency insights. Customers who enable dependency discovery can now generate dependency insights, a new generative AI-powered capability that analyzes discovered application dependencies and highlights meaningful patterns. Dependency insights surfaces new dependencies, identifies cross-Region dependencies, and flags unusual usage patterns. This helps teams accelerate dependency analysis and identify potential new risks. Resilience policy sharing through AWS Organizations. Resilience Hub now supports sharing resilience policies through AWS Organizations, enabling central teams to build and manage policies that can be applied across multiple accounts. This provides organization-wide observability into which services are using each policy, making it easier to monitor adoption and ensure consistent resilience posture across the organization. To get started, visit the  AWS console. To learn more, see the product page or visit the documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/resilience-hub-eks-dependency-policy/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 18

AWS RTB Fabric now supports configurable Availability Zone affinity

AWS RTB Fabric now supports configurable Availability Zone (AZ) affinity for responder gateways. With this capability, you can configure how your partners connect to your responder gateway: either in their own Availability Zone or to any Availability Zone that the gateway spans. This launch helps advertising technology (AdTech) companies use their infrastructure more efficiently—with no extra charges on RTB Fabric. Demand-side platforms (DSPs) and supply-side platforms (SSPs) run their bidding systems across multiple Availability Zones. Previously, AWS RTB Fabric sent each request to available gateway capacity in the requester's own Availability Zone (AZ), so capacity in other AZs could go unused. Now you can set a client routing policy to control this: prefer the requester's own AZ to avoid added latency of crossing a boundary, or use every AZ that the responder gateway spans to give each requester access to more gateway capacity. Configurable Availability Zone affinity is available in all AWS Regions where AWS RTB Fabric is available. See the AWS RTB Fabric User Guide for fleet requirements before enabling. AWS RTB Fabric helps you connect with your AdTech partners such as Amazon Ads, GumGum, Kargo, MobileFuse, Sovrn, TripleLift, Viant, Yieldmo, and more in three steps while delivering single-digit millisecond latency through a private, high-performance network environment. RTB Fabric reduces standard cloud networking costs by up to 80% and does not require upfront commitments. AWS RTB Fabric is generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland). See the AWS RTB Fabric Product Page to learn more.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-rtb-fabric-configurable-availability-zone-affinity/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 18

Kimi K3 by Moonshot AI is now generally available on Amazon Bedrock

Amazon Bedrock continues to expand its open weight model portfolio with the same security and governance that customers rely on. Today, Kimi K3 from Moonshot AI is generally available on Amazon Bedrock, giving you a powerful new option for coding and knowledge work. According to Moonshot AI, Kimi K3 is its most capable model and the first open model to reach 2.8 trillion parameters. It combines native vision capabilities with a 1-million-token context window, making it well suited to long-running coding sessions across large repositories, multi-document analysis including scanned pages and screenshots, and extended agent workflows. Moonshot AI reports an approximate 2.5x improvement in scaling efficiency over Kimi K2. On Amazon Bedrock, Kimi K3 runs within the same security boundary as proprietary models, and the same controls for access, encryption, and auditing across your model portfolio. Kimi K3 is the first open weight model on Amazon Bedrock to support explicit prompt caching, helping reduce latency and input costs when reusing context across model calls. Kimi K3 is available in all AWS Regions where Amazon Bedrock is available through cross-Region inferencing. To get started, visit the Amazon Bedrock Console. To learn more, see the Amazon Bedrock documentation and read the launch blog post.
https://aws.amazon.com/about-aws/whats-new/2026/09/moonshot-ai-kimi-k3-on-amazon-bedrock/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 18

Amazon SNS now supports message payloads up to 1 MiB

Amazon Simple Notification Service (Amazon SNS) now supports message payloads up to 1 MiB, a 4x increase from the previous 256 KiB limit, so you can publish larger messages to your SNS topics. Amazon SNS is a fully managed pub/sub messaging service that enables you to decouple and scale microservices, distributed systems, and serverless applications. As workloads such as application integration, IoT, and generative AI increasingly exchange larger volumes of data in a single message, the previous 256 KiB limit required customers to offload or split payloads before publishing. With this launch, you can publish message payloads up to 1 MiB by setting the new MaximumMessageSize topic attribute on both SNS Standard and SNS FIFO topics. Topics with MaximumMessageSize set above 256 KiB support Amazon SQS, Amazon Data Firehose, and AWS Lambda subscriptions, with up to 100 total subscriptions per topic. Amazon SNS 1 MiB support is available today in all AWS Regions where Amazon SNS is available. To learn more about sending large payloads with Amazon SNS, see the Amazon SNS Developer Guide.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-sns-1mib-support aws.amazon.com
RSS Hunter RSS Hunter • Sep 18

The new AgentCore Runtime is now available in Amazon Bedrock AgentCore

Today, AWS announces the availability of the next generation of AgentCore Runtime, the serverless microVM compute within Amazon Bedrock AgentCore. The new Runtime delivers elastic memory management that reclaims unused memory throughout the session so you pay for actual usage rather than the peak, and consistent cold start times regardless of container image size or concurrency. You get the serverless model you already rely on: no pre-provisioning, scale to zero, hardware-enforced session isolation, and pay only for what you use - now with lower costs and faster starts. With the new Runtime, each session starts with a small, efficient memory profile. Additional memory is allocated on demand as the workload needs it, and memory that is no longer actively used is reclaimed rather than held until the session ends. For cold starts, the new Runtime prepares the agent environment once and snapshots it. Every new instance restores from that snapshot instead of repeating the full startup sequence, keeping start times consistent regardless of image size. In testing, the new Runtime delivered a P75 cold start of 1.9 to 2.0 seconds for container images from 200 MB to 2 GB, compared to 5.4–30 seconds with V1. The new AgentCore Runtime is available in the following regions: us-east-1, us-east-2, us-west-2, eu-west-1, and ap-northeast-1. To get started, set platformVersion to V2 when creating or updating a runtime. To learn more, visit the AgentCore Runtime documentation or the AWS News Blog. For pricing details, visit AgentCore pricing.
https://aws.amazon.com/about-aws/whats-new/2026/09/new-agentcore-runtime-generally-available aws.amazon.com
RSS Hunter RSS Hunter • Sep 18

AWS PrivateLink announces Tunnel Endpoints to access network segments

AWS PrivateLink customers can now use VPC endpoint to privately and securely access network segments in another VPC/account. They can use a ‘tunnel’ endpoint, a new type of VPC endpoint, to tunnel into the network segment and access resources located within it. AWS PrivateLink is a highly available and scalable technology that enables private access across VPC and account boundaries to load balanced services, appliances, and resources such as databases and domains. Prior to this launch, customers who wanted to share their resources with another party such as an external vendor had to do it one at a time by creating a Resource Configuration for every resource. Now, customers can create a Resource Configuration to represent a CIDR range in their network, and share it with a vendor via AWS Resource Access Manager (RAM). The vendor can then create a tunnel endpoint and use GENEVE encapsulation to tunnel through it into the customer’s VPC to access resources located in CIDR range specified by the customer. There is an hourly charge for the tunnel endpoint and a per-GB charge for data processed through it. Please refer to the pricing page for AWS PrivateLink.   The capability is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Africa (Cape Town), Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Jakarta), Asia Pacific (Malaysia), Asia Pacific (Melbourne), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Canada West (Calgary), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Milan), Europe (Paris), Europe (Spain), Europe (Stockholm), Europe (Zurich), Mexico (Central), South America (São Paulo). To learn more about this capability and get started, please refer to the AWS PrivateLink documentation.
https://aws.amazon.com/about-aws/whats-new/2026/9/privatelink-tunnel-endpoint/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 18

AWS Transfer Family now supports source IP preservation for SFTP servers behind a Network Load Balancer (NLB)

AWS Transfer Family now preserves the client's source IP address using Proxy Protocol v2 (PPv2) when you place a Network Load Balancer (NLB) in front of your SFTP server that uses a VPC-hosted endpoint. You can now retain visibility of the client's source IP for IP-based auditing, access controls, and compliance when you use your own NLB. Previously, an NLB replaced the client's source IP with its own private IP address, so your Transfer Family logs and events recorded the NLB's address instead of the client's source IP. Because the NLB's private IP was the address presented to your custom identity provider during authentication, you couldn't authorize users based on their true source IP. With this launch, you can enable source IP preservation on your SFTP server so that the client's source IP is preserved. The preserved source IP is recorded in your logs and events and presented to your custom identity provider during authentication. You can enable the feature on each Transfer Family server individually through the console, CLI, or API. Source IP preservation for SFTP servers is available in all AWS Regions where AWS Transfer Family is available. To get started, visit the AWS Transfer Family console or use the AWS CLI/SDK. To learn more, visit the Transfer Family User Guide.
https://aws.amazon.com/about-aws/whats-new/2026/09/transfer-family-sftp-source-ip-nlb/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

AWS HealthOmics now supports IAM session policies

AWS HealthOmics now supports IAM session policies, enabling you to restrict permissions for individual runs without creating and managing multiple IAM roles. Until now, there was no way to dynamically scope down permissions for a single run, requiring you to create a separate IAM role for each tenant or run. AWS HealthOmics is a HIPAA-eligible service that helps healthcare and life sciences customers accelerate scientific breakthroughs with fully managed bioinformatics workflows. An IAM session policy is an inline policy that limits the maximum permissions of a run without modifying the underlying service role. Your effective permissions during a run are the intersection of permissions allowed by both the underlying identity-based policy and the temporary session policy. For example, if you operate a multi-tenant application, you can pass a session policy that limits a run's access to only that tenant's Amazon S3 buckets, without provisioning a dedicated IAM role for that tenant. You can also use IAM session policies to grant temporary access to specific Amazon S3 objects for a single run, and isolate access to sensitive resources on a per-run basis. IAM session policy support is available in all AWS Regions where AWS HealthOmics is available: US East (N. Virginia, Ohio), US West (Oregon), Europe (Frankfurt, Ireland, London), Israel (Tel Aviv), and Asia Pacific (Tokyo, Singapore, Seoul). To learn how to configure IAM session policies for your runs, visit the Permissions section of the  AWS HealthOmics User Guide. To learn more about the service, visit  AWS HealthOmics.
https://aws.amazon.com/about-aws/whats-new/2026/09/omics-iam-session-policy/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

AWS Batch now supports bulk job cancellation and termination

AWS Batch now supports bulk job cancellation and termination, enabling you to cancel or terminate up to 50 jobs with a single API call. The new CancelJobs, TerminateJobs, and TerminateServiceJobs APIs reduce the operational complexity of managing large-scale batch workloads, letting you act on groups of jobs at once and receive per-job results in a single response. Additionally, ListJobs now returns isCancelled and isTerminated fields, and ListServiceJobs returns isTerminated, making it easier to track the lifecycle state of your jobs. To get started, call CancelJobs for jobs in SUBMITTED, PENDING, or RUNNABLE states, or TerminateJobs and TerminateServiceJobs for jobs in any state, including STARTING and RUNNING. All three APIs accept up to 50 job IDs and work with individual and array jobs. You can access them through the AWS CLI or AWS SDKs. Bulk job cancellation and termination is available in all AWS Regions where AWS Batch is available. For more information, see CancelJobs, TerminateJobs, and TerminateServiceJobs pages in the AWS Batch API Reference Guide.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-batch-bulk-cancellation/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

Introducing Amazon EC2 T8i instances

AWS is announcing the general availability of new low-cost burstable Amazon EC2 T8i instances. These instances are powered by custom sixth generation Intel Xeon 6 processors, available exclusively on AWS, and built on the latest sixth generation AWS Nitro cards. T8i instances deliver up to 30% better price performance compared to previous generation T3 instances, and offer four sizes: nano, micro, small, and medium. These instances are designed for workloads requiring low to moderate CPU utilization, including data processing, login gateways, small databases, batch processing, event driven functions, CI/CD pipelines, microservices, and low traffic websites.   T8i instances deliver up to 70% higher compute performance, 1.25x higher network bandwidth, and 2.4x higher EBS bandwidth compared to T3 instances. They use the same CPU credit system as T3 with Standard and Unlimited modes, so existing T3 customers can upgrade to T8i and immediately benefit from better price performance, enabling them to lower their TCO. For customers new to AWS or migrating from on-premises, T8i instances provide one of the most cost-effective entry points to run a variety of workloads. T8i.micro and T8i.small are available under the AWS Free Tier. T8i instances are available in US East (N. Virginia, Ohio), US West (Oregon, N. California), Europe (Frankfurt, Ireland, London, Paris), Asia Pacific (Hyderabad, Malaysia, Mumbai, Seoul, Singapore, Sydney, Tokyo), and Canada (Central) regions. T8i instances are available to purchase via On-Demand instances, and Spot instances with Savings Plan option coming soon. To learn more, visit the Amazon EC2 T8i instances page.
https://aws.amazon.com/about-aws/whats-new/2026/09/ec2-t8i-instances-ga/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

Amazon S3 Express One Zone is now available in 7 additional AWS Regions

The Amazon S3 Express One Zone storage class is now available in 7 additional AWS Regions: Asia Pacific (Singapore), South America (Sao Paulo), US West (N. California), Canada (Central), Europe (Paris), Asia Pacific (Sydney), and Asia Pacific (Seoul). Amazon S3 Express One Zone is a high-performance, single-Availability Zone storage class purpose-built to deliver consistent single-digit millisecond data access for your most frequently accessed data and latency-sensitive applications. S3 Express One Zone delivers data access speed up to 10x faster and request costs up to 80% lower than S3 Standard. It enables workloads such as machine learning training, interactive analytics, and key-value caching in AI search engines to achieve fast data access with high durability and availability. With this expansion, S3 Express One Zone is now available in 15 AWS Regions. For pricing details, visit the S3 pricing page. To learn more, visit the product page and documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/s3-express-one-zone-7-regions/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

AWS Elastic Beanstalk introduces Cluster Mode to run multiple applications on shared infrastructure

AWS Elastic Beanstalk has introduced Cluster Mode, a new deployment option for managing multiple applications efficiently. This mode allows you to run several applications on shared infrastructure within your AWS account. You can provide your source code, Dockerfile, or container image for Elastic Beanstalk to containerize and manage. A new GitHub Action simplifies direct deployment from your repository into your CI/CD pipeline. Elastic Beanstalk handles infrastructure provisioning and ongoing operations, letting developers focus on their code. Standard Mode remains the existing deployment option supporting various platforms like .NET, Node.js, and Python. Cluster Mode, powered by Amazon EKS, runs multiple applications on pooled infrastructure, potentially reducing per-application costs. It features event-driven autoscaling, OpenTelemetry observability, AWS Secrets Manager integration, and default HTTPS. Users can set up Cluster Mode through the Elastic Beanstalk console, AWS CLI, or the GitHub Action. This feature is available in all commercial AWS Regions without additional charges, though you pay for the underlying AWS resources consumed.
https://aws.amazon.com/about-aws/whats-new/2026/09/elastic-beanstalk-cluster-mode/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

AWS Builder Center now available as mobile app on iOS and Android

AWS Builder Center is a platform that brings together the global builder community, offering articles, workshops, sandbox environments, events, and learning resources in one place. Previously limited to desktop and web access, the experience is now available as a mobile app on iOS and Android. Builders worldwide can stay connected and engaged with the community from anywhere, using their AWS Builder ID to remain signed in across sessions. The AWS Builder Center mobile app enables builders to browse trending articles, access 600+ AWS Skill Builder courses, and manage hands-on workshops with free sandbox environments directly from their mobile devices. Builders can follow AWS Heroes, Community Builders, and User Group Leaders, check Builder Loft event calendars on the go, and receive push notifications for subscribed topics and communities. The app also supports the Wishlist feature, allowing builders to submit and manage product feedback directly to AWS teams. The AWS Builder Center mobile app is available worldwide on the Apple App Store and Google Play Store. To learn more about the AWS Builder Center mobile app, visit the AWS Builder Center mobile page.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-builder-center-now-available-as-mobile-app/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

Amazon SES now supports tenant-level deliverability insights

Amazon Simple Email Service (SES) now supports tenant-level deliverability insights in Virtual Deliverability Manager (VDM). Tenant management allows email senders to isolate email sending across customers, business units, or applications. Previously, VDM provided deliverability metrics at the account, ISP, sending identity, and configuration set levels. Now, customers who use tenants and have enabled VDM can also monitor the deliverability of each tenant. The VDM dashboard adds a Tenants view with per-tenant metrics (send volume, deliveries, bounces, complaints, opens, and clicks) and a detail page that breaks those metrics down by mailbox provider and by associated identities and configuration sets. Customers can also search and export a tenant's sent messages, or query tenant metrics programmatically using the BatchGetMetricData API operation's new TENANT_NAME dimension. This helps senders identify the tenant causing a deliverability issue and correct it without impact to their other tenants. Virtual Deliverability Manager is available in all AWS Regions where Amazon SES is available. To learn more, visit the Amazon SES console or refer to the Virtual Deliverability Manager dashboard documentation in the Amazon SES Developer Guide.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-ses-vdm-tenants/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

Amazon Quick now generates individual sheets and builds analyses from an image

Amazon Quick now expands Generate Analysis with two new ways to create dashboards faster. You can generate a single sheet inside an existing analysis by describing it in natural language, and you can generate a new analysis from an image of an existing dashboard.   With Generate Sheet, you describe the sheet you want and Amazon Quick adds it to your current analysis with visuals selected for your data, filter controls, and calculated fields such as year-over-year growth and month-over-month comparisons. You can extend an analysis without building each visual by hand.   With generate an analysis from an image, you attach an image of a dashboard, including dashboards from other BI tools, to your prompt when you generate an analysis. Amazon Quick recreates it as an editable analysis, building what is supported in Amazon Quick. Both capabilities work with existing publishing workflows, embedding, CI/CD pipelines, and point-and-click editing.   At launch, Generate Sheet and generate analysis from an image are available to Enterprise subscription/Author Pro users. Authors also have promotional access to this capability through December 2026 as part of Amazon Quick Enterprise, provided their organization has not restricted access.   To learn more, see Generating an analysis with natural language prompts in the Amazon Quick User Guide. To get started, open an analysis and choose Generate Sheet, or attach an image to your prompt and choose Generate analysis.
https://aws.amazon.com/about-aws/whats-new/2026/09/generate-sheet-and-generate-analysis-from-an-image/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

Amazon Corretto 27 is now generally available

Amazon Corretto 27, a new feature release, is now available for download. Corretto is Amazon's free, multi-platform, production-ready OpenJDK distribution. This release includes G1 as the default garbage collector for consistent performance. It also features post-quantum hybrid key exchange for enhanced TLS 1.3 security. Compact object headers are now enabled by default to improve memory efficiency. Data redaction is added for Java Flight Recorder to protect sensitive information. Enhanced pattern matching, supporting primitive types, continues in preview. Structured concurrency is also refined in its preview state for better error handling. Lazy constants are available in preview for deferred initialization of immutable data. The Vector API, supporting high-performance mathematical operations, remains in incubator.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-corretto-27-generally-available/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 17

Amazon SageMaker AI now supports serverless model customization for NVIDIA Nemotron 3.5 Lightning

Amazon SageMaker AI now supports serverless model customization for the NVIDIA Nemotron 3.5 Lightning model using supervised fine-tuning (SFT), Direct Preference Optimization (DPO), and reinforcement fine-tuning (RFT). This is one of the latest open-weight models from NVIDIA and employs a hybrid Mixture-of-Experts architecture with 3B active parameters and 30B parameters in total. In addition to deploying this model on SageMaker AI, you can now adapt it to your specific domains and workflows. Model customization enables you to tailor foundation models with your proprietary data so a smaller, right-sized model can match frontier-model quality on your tasks, reducing cost and latency. You can use labeled data with SFT to improve accuracy on domain-specific tasks, preference data with DPO to align outputs with your organization's tone, or reward signals with RFT to enhance performance on new tasks. With serverless customization, SageMaker AI handles all infrastructure provisioning and training orchestration, so you can focus on your data and evaluation rather than cluster management, and only pay for what you use. Serverless model customization for NVIDIA Nemotron 3.5 Lightning on SageMaker AI is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland). To get started, navigate to the Models page in Amazon SageMaker Studio to launch a customization job, or use the SageMaker Python SDK for programmatic access. To learn more, see the Amazon SageMaker AI model customization documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-sagemaker-ft-nemotron-3-5-lightning/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

Amazon ECS deployment observability for Amazon ECS Managed Daemons in AWS Management Console

Amazon Elastic Container Service (Amazon ECS) now provides a consolidated deployment view for Amazon ECS Managed Daemons, giving you a single place to see how far a deployment has progressed, what is failing, and what could stop it. This helps you monitor Managed Daemon deployments at a glance and resolve issues faster, whether a rollout is in progress or you are reviewing what happened after it completed, eliminating the need to piece together deployment status from multiple sources. The deployment view presents a lifecycle timeline with timestamps at each step and the total deployment duration, including the rollback path if a deployment is interrupted. Progress bars for each capacity provider track instances completed, in progress, and remaining, as well as instances draining and being replaced when a capacity provider is removed. A monitoring panel shows deployment circuit breaker, deployment alarm, and container health check state, each with live Amazon CloudWatch alarm detail and whether it can stop the deployment. If a daemon task fails, the affected capacity provider shows the stop reason with links to the task, its logs, and the matching troubleshooting guide, including the failure that caused a rollback. The view also displays target and source revisions with instance counts, drain percentage, and bake time. This enhancement is available as a console-only view in all AWS Commercial Regions at no additional cost. To get started with Amazon ECS Managed Daemons, refer to our documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-ecs-daemon-deployment-console/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

AWS Client VPN is now supporting MacOS 27 Golden Gate

AWS Client VPN now supports MacOS 27 Golden Gate client with versions 6.0+ You can now run the AWS supplied VPN client on the latest MacOS versions. AWS Client VPN desktop clients are available free of charge, and can be downloaded here. AWS Client VPN is a managed service that securely connects your remote workforce to AWS or on-premises networks. It supports desktop clients for MacOS, Windows x64, Windows Arm64 and Ubuntu-Linux. With client version 6.0 onwards, Client VPN now supports the latest MacOS  Golden Gate 27.0. It already supports Mac OS version 13.0, 14.0, 15.0, and 26.0, Windows 10 (x64) and Windows 11 (Arm64 and x64), and Ubuntu Linux 22.04 and 24.04 LTS versions. To learn more about Client VPN: Visit the AWS Client VPN product page Read the AWS Client VPN documentation Read the AWS Client VPN user guide
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-client-vpn-macos-golden-gate/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

New AWS experience helps builders get started and ship faster

AWS has launched a simplified experience for builders to accelerate the process of turning ideas into running code on AWS. This new offering addresses the previous complexity of configuring extensive AWS service options for new projects. It streamlines sign-up by offering automatic environment configuration with sensible defaults, allowing immediate project implementation. Users can sign up using existing Google, GitHub, Apple, or Amazon credentials, often without requiring a credit card and receiving free AWS credits. Upon sign-up completion, a single prompt connects a coding agent to AWS, installing necessary tools and deploying resources using best practices. Collaboration is facilitated by inviting team members via email, with automatic access configuration. The new IAM role manager also allows AWS resources to automatically access other AWS services. To manage costs, users can set monthly spend limits for projects, with projects pausing if the limit is reached for the month. Additional projects can be easily created with their own distinct configurations and team members. Advanced features, such as multi-Region support and custom governance, can be activated without migration or downtime.
https://aws.amazon.com/about-aws/whats-new/2026/09/New-AWS-Builder-Experience aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

Amazon Connect Customer custom metrics now supports tag-based access control

Amazon Connect Customer now supports tag-based access control for custom metrics, so you can govern which users and roles can view, create, or modify each custom metric. As more teams across your organization adopt custom metrics, they end up editing the same shared library. Without controls, one person can change a metric that other teams count on. The usual fix is to give only a handful of people permissions to custom metrics, but that shuts out every other team that wants to start using them.   Now you can tag each metric, then use those tags to set access: a team gets full control of their own metrics, view-only access to another team’s, and no visibility into the metrics you restrict. Search follows the same access rules, so people only see the metrics they’re allowed to view or manage.
https://aws.amazon.com/about-aws/whats-new/2026/09/connect-customer-custom-metrics-tag/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

Amazon WorkSpaces adds support for NVIDIA Blackwell GPU instances

Amazon WorkSpaces Personal and Amazon WorkSpaces Core now support Graphics G7 bundles, built on NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs and Intel Xeon 6 processors. Graphics G7 delivers up to 2.1x better performance for graphics-intensive workloads compared to previous generation Graphics G6 bundles. Four bundle sizes are available, ranging from 8 vCPUs, 32 GB of memory, and one GPU up to 48 vCPUs, 192 GB of memory, and two GPUs. With Graphics G7, you can run demanding professional applications such as CAD/CAM, 3D rendering, scientific visualization, video editing, and AI-assisted design workflows at higher fidelity and frame rates. Each GPU provides 32 GB of GDDR7 memory, enabling larger and more complex 3D scenes and models. Graphics G7 bundles are available with Windows, including bring-your-own-license, and support both AlwaysOn and AutoStop running modes. Graphics G7 bundles are available for both WorkSpaces Personal and WorkSpaces Core 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 bundle when creating a workspace in the Amazon WorkSpaces console, or through your Workspaces Core partner solution. For more information on available instance types, see WorkSpaces Personal Instance Families. To learn more about G7 GPU capabilities, visit the EC2 G7 Instance Types page. For pricing details, see Amazon WorkSpaces Personal Pricing or Core Bundles Pricing.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-workspaces-nvidia-blackwell-gpu-instances/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

Amazon Connect Customer can now import evaluation form PDFs using AI

Amazon Connect Customer now lets managers import a PDF of an evaluation form from a third-party quality management application, and automatically recreates it in Connect using AI, making it easier to migrate an existing quality program into Connect. Instead of rebuilding an existing form question by question, you upload the PDF and choose the preferred scoring method, either percentage or points-based, and Connect Customer automatically extracts the sections, questions, answer options, and scoring into a draft evaluation form. You can also provide natural language instructions to import the form more accurately or to adjust it as it's created — for example, splitting a broad question into simpler ones — minimizing the manual edits needed before you activate the form. This feature is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Canada (Central), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Europe (Frankfurt). To learn more, please visit our documentation and our webpage. For information about Amazon Connect Customer pricing, please visit our pricing page.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-connect-customer-import-evaluation-form-PDF/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

AWS Elemental MediaTailor Monetization Functions adds ad response hooks

AWS Elemental MediaTailor now supports two additional lifecycle hooks for monetization functions: post ad decision server (ADS) response, and pre manifest insertion. MediaTailor is a video service that personalizes and inserts ads into live and on-demand streams. Monetization functions run customer-defined logic at defined points in an ad-personalized playback session, removing the need for a middleware tier between MediaTailor and the ADS. The post ADS response hook runs after MediaTailor parses an ADS response and resolves all Video Ad Serving Template (VAST) wrappers, before ads are selected and transcoded. Customers use it to call a secondary ad source when the primary ADS returns less demand than the ad break can hold, remove ads that their content or brand policies do not permit, and add house ads or promotions from their own marketing systems. The pre manifest insertion hook runs at the last point before MediaTailor returns the ad pod to the viewer, and receives every newly personalized ad break in a single invocation. Customers use it as a final check on what is about to play, including inserting a personalized slate when a break cannot be filled any other way. Pre-built recipes in the MediaTailor console give customers a starting point for each of these use cases. Both hooks are fail-open: on a timeout, expression error, or resource limit, MediaTailor discards the function output and continues with default ad insertion, so viewer playback is unaffected. The new hooks are available in all AWS Regions where AWS Elemental MediaTailor is available. To learn more, see Monetization Functions in the AWS Elemental MediaTailor User Guide and the MediaTailor pricing page. To get started, sign in to the AWS Elemental MediaTailor console.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-elemental-mediatailor-functions-ad-response-hooks aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

Amazon ECS extends Amazon S3 Files support to the Amazon EC2 compute type

Amazon Elastic Container Service (Amazon ECS) now supports Amazon S3 Files for tasks running on the Amazon EC2 launch type, enabling customers to connect their containerized applications directly to data in Amazon S3 as a shared file system. With this launch, customers running ECS workloads on EC2 instances can work with their S3 data using standard file system semantics, so file-based applications, AI agents, and data processing workloads run on S3 data with no code changes and without duplicating or staging files first. S3 Files support was previously available for ECS tasks on AWS Fargate and ECS Managed Instances, and now extends to the EC2 launch type, giving customers consistent access to S3 Files across all three ECS launch types. Amazon S3 Files, built on Amazon EFS, delivers a shared file system that connects AWS compute resources directly with data in Amazon S3, providing full file system semantics and low-latency performance without data leaving S3. S3 Files works with new and existing data in S3 buckets, with no migration required. Customers can mount an Amazon S3 Files volume in their Amazon ECS tasks to read and write data in an S3 bucket using standard file system operations, with no application code changes and no need to copy or stage data. Amazon S3 Files support is available in all AWS commercial Regions and the AWS GovCloud (US) Regions. To learn more, refer our documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-ecs-s3-files-ec2/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

Amazon Connect Customer now lets you create, manage, and search custom metrics through APIs

Amazon Connect Customer provides a library of standard metrics. Custom metrics let you go further; defining the measurements unique to your business. But managing them across various instances manually means definitions slowly drift until the numbers no longer align. A metric you can't trust is worse than no metric at all, because people still make decisions on it. Now you define a metric once and manage it programmatically through seven new API operations (CreateMetric, DeleteMetric, DescribeMetric, ListMetrics, SearchMetrics, UpdateMetricContent, and UpdateMetricMetadata) so your definitions stay consistent as you scale across queues, teams, and environments. For example, a customer experience leader noticing a drop in self-service completion rates can define a custom metric that tracks the percentage of interactions where customers abandon and request a live agent within 90 seconds. Using the API, an AI-powered operations assistant can automatically create the metric and publish it to a monitoring dashboard — no manual console work, no definition drift across environments. Every change is tracked in AWS CloudTrail, giving you a complete audit trail.
https://aws.amazon.com/about-aws/whats-new/2026/09/connect-customer-custom-metrics-apis/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

Amazon Keyspaces (for Apache Cassandra) is now generally available in 11 additional Regions

Amazon Keyspaces (for Apache Cassandra) is now generally available in 11 additional Regions, allowing customers in those Regions to build Cassandra-compatible applications with lower latency while keeping their data within the Region to meet data residency requirements..  Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage.  To find the list of new available Regions, see the following resources: AWS Capabilities by Region.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-keyspaces/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

Amazon Connect Talent is now generally available

Amazon Connect Talent is now generally available, giving talent acquisition leaders an AI-powered hiring solution that accelerates candidate selection at scale. Informed by decades of Amazon's hiring science, Amazon Connect Talent uses AI agents to conduct structured voice interviews, administer evidence based assessments, and score candidates consistently, freeing recruiters to focus on strategic decisions. Candidates interview 24/7 from any device. Recruiters review scores, transcripts, and detailed candidate evaluations generated by their AI teammate, empowering them to make faster hiring decisions with consistent objectivity. GA capabilities include competency based assessments, AI-led voice interviews with adaptive questioning, a brand-customizable mobile-first candidate portal, and system admin onboarding tools for easy deployment. Amazon Connect Talent scales to handle hiring surges, evaluating hundreds of candidates simultaneously. Amazon Connect Talent is now available in AWS US East (N. Virginia) and US West (Oregon) regions. To learn more, visit the Amazon Connect Talent page.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-connect-talent/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 16

AWS STS simplifies session token size limits and adds session token size monitoring

AWS Security Token Service (STS) now enforces a single 4,096-byte size limit on session tokens. Previously, STS enforced separate limits on session token size and passed-in parameters (i.e., inline policies, managed policies, and session tags). STS has removed that separation, providing more flexibility for larger combinations of session policies and session tags. Additionally, STS now returns response elements indicating session token size and percentage utilization relative to the token size limit. STS logs these values in AWS CloudTrail and publishes corresponding metrics in Amazon CloudWatch. A new optional API parameter also lets you generate larger session tokens (up to the 4,096-byte limit) to test whether your applications and infrastructure can handle them. These capabilities are available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the AWS European Sovereign Cloud Region. To learn more, please read the AWS Security Blogpost, AWS IAM User Guide, and AWS STS API Reference.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-sts/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

Monitor cost anomalies directly in Billing and Cost Management Dashboards with the new Detected Anomalies widget

Today, AWS Billing and Cost Management (BCM) announces support for the Detected Anomalies widget in BCM Dashboards. You can now review cost anomalies alongside cost and usage, budgets, cost efficiency, and reports for Savings Plans and Reserved Instance coverage and utilization. This provides a unified view of your spending, commitments, and cost anomalies in a single, tailored dashboard. The Detected Anomalies widget displays the number of anomalies detected and their total cost impact relative to your month-to-date spend, giving you immediate context on each anomaly's scale. For each anomaly, you can review the cost impact, root cause, and duration. Choose a look-back period of 30, 60, or 90 days, and filter by severity, service, account, and region so that each dashboard shows the anomalies most relevant to that account. By adding one or more Detected Anomalies widget to a BCM Dashboard, finance teams and cloud administrators can monitor anomalies from their existing cost management workflows. The widget links directly to the AWS Cost Anomaly Detection console so you can easily investigate an anomaly and record your assessment. It is fully integrated with dashboard exports and can be included in scheduled email reports or downloaded as a CSV or PDF for offline analysis. It is also included with cross-account dashboard sharing. The Detected Anomalies widget for BCM Dashboards is available in all commercial AWS Regions at no additional charge. To learn more, visit our User Guide.
https://aws.amazon.com/about-aws/whats-new/2026/09/monitor-detected-anomalies-using-dashboards aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

AWS Direct Connect announces flat-rate pricing for dedicated connections

AWS Direct Connect now offers flat-rate pricing for its dedicated 10 Gbps and 100 Gbps connections. Previously, customers paid based on port hours and data transfer out, which could lead to unpredictable costs for high-volume users. This new pricing model introduces a single fixed monthly fee that removes data transfer charges within a chosen tier. This simplifies budgeting for network architects and IT teams who require predictable expenses. The flat-rate pricing is determined by the connection bandwidth and the geographic scope selected. Five geographic tiers are available, ranging from same-metro to global coverage. A new port-pair concept is also introduced, which provides built-in resiliency by including a second, redundant connection at no extra cost. This port-pair configuration is recommended for increased reliability. Flat-rate pricing is available globally at all AWS Direct Connect locations, excluding China. It applies only to Dedicated Connections and customers can switch between billing modes at any time. More details can be found on the AWS Direct Connect Flat-Rate Pricing, User Guide, and Pricing Guide pages.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-direct-connect-announces-flat-rate-pricing/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

AWS Billing Conductor now supports custom rates and usage tier pricing configurations

AWS Billing Conductor now lets you define custom rate pricing for AWS services, including defining custom usage tiers to configure rates by the desired usage volume.  Customers and Partners using AWS Billing Conductor to model commercial agreements with subsidiaries, affiliates, or end customers can now more easily reflect their negotiated pricing on pro forma billing data. Using SKU-scoped pricing rules, you can enter a custom rate and configure usage tier thresholds — instead of marking up or down from the public on-demand rates tied to pre-defined AWS usage tiers.  By configuring exact rates and tier breaks directly in a pricing rule, you no longer need to calculate percentage-based markups or markdowns against public on-demand pricing to model your commercial agreements. This gives you precise control over your pro forma billing configuration. Custom rates and custom usage tiers configuration via SKU-scoped pricing rules is available in all commercial AWS Regions, excluding the Amazon Web Services China (Beijing) Region, operated by Sinnet, and the Amazon Web Services China (Ningxia) Region, operated by NWCD. To learn more, visit the AWS Billing Conductor product page, or review the User Guide.
https://aws.amazon.com/about-aws/whats-new/2026/09/AWS-Billing-Conductor-custom-rates-usage-tier aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

AWS Step Functions adds new AWS service integrations automatically, starting with AWS Lambda MicroVMs

AWS Step Functions now automatically adds AWS SDK integrations for new AWS services and capabilities within weeks of their release, starting with AWS Lambda MicroVMs, AWS Lambda Core and others. Now, you can orchestrate the latest AWS services from your workflows without waiting for updates.    AWS Step Functions is a visual workflow service capable of orchestrating over 220 AWS services to help customers build distributed applications at scale. With the AWS Lambda Core and AWS Lambda MicroVMs service integrations, you can orchestrate agentic workflows without writing custom coordination code. You can use Step Functions to launch Lambda MicroVMs, which provide isolated, secure execution environments for each agent task with built-in retries if an environment fails to start. You can run multiple tasks simultaneously using Step Functions Parallel or Map states and automatically terminate environments when the task completes. You can use Lambda Core to configure the private networking those MicroVM environments need to securely reach your internal databases or APIs in the same workflow.   This expansion also includes AWS Partner Central Revenue Measurement, AWS Resilience Hub V2, AWS Support Authorization and Amazon SageMaker Job Runtime. Going forward, new AWS services will automatically appear as Step Functions integrations within weeks of their release with no additional configuration or action required. As updates will be continuous, we will no longer publish What's New posts to highlight new AWS SDK service integration updates.   These enhancements are now generally available in all AWS Regions where AWS Step Functions is available. Specific services and API actions are subject to the availability of the target service in the AWS Region. To learn more about AWS Step Functions SDK integrations, visit the Developer Guide, or see the full list of supported services at AWS SDK service integrations, and integration release history.
https://aws.amazon.com/about-aws/whats-new/2026/06/aws-step-functions-integrations/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

Amazon SageMaker AI now supports instance preference lists for training and processing jobs

Today, Amazon SageMaker AI announces instance preference lists for training and processing jobs, making it easier and faster to find compute capacity for your workloads. Many AI training, fine-tuning, and data processing workloads run comparably well on any of several instance types or sizes. However, before now, you had to name only one instance type at the time of job submission and wait for SageMaker to find that specific instance for your job. For high-demand GPUs during peak periods, where wait times can be unpredictable, customers sometimes had to build complex retry logic or concurrently submit multiple jobs with different instance types to find the first available option. Now you can simply provide a prioritized list of the instance types your workload accepts, and SageMaker automatically runs your job on the first available configuration from your preferences. With this solution, your training or processing job will likely start sooner. To use this feature, you specify your instance type and count preferences in priority order when submitting the training or processing job. For example, your list might contain a preference of two instances of ml.g6.48xlarge or four instances of ml.g5.48xlarge. SageMaker works through the list and launches your job on the first configuration where capacity is available. You can also configure the capacity sourcing from on-demand sources or from your reserved SageMaker Flexible Training Plans within the same job submission. This feature simplifies the process of getting compute for your jobs during high-demand periods and reduces the undifferentiated manual retrying you would otherwise do, all within the SageMaker training and processing job APIs you already use. Instance preference lists for SageMaker training and processing jobs is available today in all AWS Regions where SageMaker is available through the SageMaker CLIs, APIs, SDKs and Console UI. To learn more, see our documentation or our launch blog.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-sagemaker-training-processing-instance-pref-lists/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

Analyze your CloudTrail events using natural language in Amazon Q Console

AWS CloudTrail, a service that records API activity across your AWS account for security auditing, compliance, and operational troubleshooting, now integrates with Amazon Q Console to help you investigate your AWS account activity using natural language. You can ask Amazon Q Console questions about your CloudTrail configuration, query your logged events for security investigations, and troubleshoot operational issues without writing queries or manually parsing log files. With this integration, you can ask Amazon Q Console to check whether your CloudTrail trails are properly configured, identify gaps in your logging coverage, and confirm which data event sources you are tracking. You can investigate security concerns by asking who accessed a specific IAM role, what changes were made to your VPC configuration, or whether there were unauthorized access attempts in the past week. For operational troubleshooting, you can ask Amazon Q Console to find who created or deleted specific resources, identify which API calls are generating errors, trace activity from a specific IP address, or determine why your bill spiked. Amazon Q Console can query your CloudTrail trails, associated CloudWatch log groups, and event data stores on your behalf, providing answers grounded in your actual account activity rather than generic documentation.  This integration is available in all AWS commercial regions where Amazon Q Console is supported. To get started, open Amazon Q in AWS Management Console and ask questions about your CloudTrail configuration or account activity. For more information, visit the AWS CloudTrail documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/cloudtrail-amazon-q-console/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

Amazon Connect Customer now enables agents to bid on preferred shifts

Amazon Connect Customer now enables agents to bid on preferred shifts, giving them more control over their work schedules. Schedulers first establish agent ranking either by uploading a CSV file or generating a randomized ranking. Connect Customer then uses forecasted demand and shift profiles to generate available shifts and presents them to agents to rank. For example, in a Monday–Friday 6AM–10PM shift profile with 9-hour shifts, required shifts are 6AM–3PM (500 agents), 9AM–6PM (800 agents), and 1PM–10PM (600 agents). Once the bidding window closes, Connect Customer automatically assigns each agent to their highest-ranked available shift while using agent ranking as a tiebreaker. Shift bidding gives agents a structured way to influence their own schedules, while reducing the time schedulers spend on manual shift assignments, improving both agent satisfaction and scheduling efficiency. This feature is available in all AWS Regions where Amazon Connect Customer agent scheduling is available. To learn more about Amazon Connect Customer agent scheduling, click here.
https://aws.amazon.com/about-aws/whats-new/2026/09/amazon-connect-customer-shift-bidding/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

AWS Glue zero-ETL now captures archived Salesforce records

AWS Glue zero-ETL integrations for Salesforce now capture archived records in your target tables, giving you a complete replica of your Salesforce data for analytics and reporting. Archived records are identified and reflected accurately through the isArchived field, so your analytical data stays fully in sync with your Salesforce source. This is especially valuable for high-volume entities that Salesforce archives automatically, such as Events, Tasks, and Activities, giving you complete visibility into this data in your analytical data stores. This feature applies to your zero-ETL integrations with no action required. New integrations capture archived records automatically from the moment the integration is created. For existing integrations, AWS Glue automatically backfills archived record status, with no re-sync, reconfiguration, or schema change needed. Your existing pipelines continue running uninterrupted while the isArchived field is populated accurately on your behalf. This feature is available in all AWS Commercial and AWS GovCloud (US) Regions where AWS Glue zero-ETL integrations for Salesforce are supported. To get started, create or continue using an AWS Glue zero-ETL integration for Salesforce using the AWS Glue console, CLI, or SDK. To learn more, see AWS Glue zero-ETL documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/glue-zero-etl-archived-salesforce/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 15

AWS improves regional resiliency for root user sign-in

AWS root user sign-in is now served across US East (N. Virginia), US East (Ohio), and US West (Oregon), with sign-in traffic distributed across all three Regions. This change reduces reliance on US East (N. Virginia) and improves resiliency during service disruptions. AWS automatically routes your root user sign-in to a supported Region without requiring you to select a Region or change how you sign in. This improvement is available now for all AWS accounts. In AWS CloudTrail, ConsoleLogin events for root user sign-ins are recorded in the Region that processed the sign-in request. To maintain full visibility into root user sign-in activity, update your monitoring and alerting to cover US East (N. Virginia), US East (Ohio), and US West (Oregon). To learn more, see the AWS Sign-In documentation and the CloudTrail ConsoleLogin event reference.
https://aws.amazon.com/about-aws/whats-new/2026/09/root-user-regional-resiliency/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 14

Qwen3.6-35B-A3B-NVFP4 and Wan2.1-T2V-1.3B-Diffusers models now available on Amazon SageMaker JumpStart

Amazon SageMaker JumpStart now offers two new foundation models, expanding AI capabilities for AWS customers. NVIDIA's Qwen3.6-35B-A3B-NVFP4 is optimized for agentic coding and long-context reasoning. This model, a quantized variant of Alibaba's Qwen3.6-35B-A3B, features a Mixture-of-Experts architecture with 35 billion total parameters. It activates only 3 billion parameters per token, supporting a vast 262K-token context window. Quantized to NVFP4, it significantly reduces memory usage while maintaining performance. The model excels at preserving context across conversation turns and multi-step agent tasks. Alibaba's Wan2.1-T2V-1.3B-Diffusers model specializes in text-to-video generation. Built with a diffusion transformer and a Video Variational Autoencoder, it produces high-quality video clips from text prompts. This 1.3 billion parameter model requires minimal VRAM, making it accessible for consumer-grade hardware. It can generate a 5-second 480p video in about four minutes on an RTX 4090. Both models can be easily deployed through SageMaker JumpStart with just a few clicks. Customers can find them in the SageMaker console or deploy them using the SageMaker Python SDK.
https://aws.amazon.com/about-aws/whats-new/2026/01/qwen3.6-35b-a3b-nvfp4-wan2.1-t2v-1.3B-diffusers-jumpstart/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 14

Ministral-3-3B-Instruct-2512 and Ministral-3-8B-Instruct-2512 models now available on Amazon SageMaker JumpStart

Mistral AI's Ministral-3-3B-Instruct-2512 and Ministral-3-8B-Instruct-2512 models are now accessible via Amazon SageMaker JumpStart. These models are designed for edge deployment and resource-limited environments, offering a compact yet powerful AI solution. The Ministral-3-3B model is optimized for ultra-lightweight edge use cases with multimodal understanding. It features a 3.4B language model and a 0.4B vision encoder, fitting within 8GB of VRAM. This model supports a 256K-token context window and excels in vision analysis and multilingual instructions. It also demonstrates strong system prompt adherence and native function calling capabilities. The Ministral-3-8B model provides frontier-class performance in a compact 8B package. It includes an 8.4B language model and a 0.4B vision encoder, requiring 12GB of VRAM. This model utilizes interleaved sliding-window attention for efficient inference. Both models offer impressive multilingual support, agentic capabilities, and function calling. Customers can easily deploy these models through SageMaker JumpStart for various AI applications.
https://aws.amazon.com/about-aws/whats-new/2026/01/ministral-3-3b-instruct-2512-ministral-3-8B-Instruct-2512-jumpstart/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 14

Gemma-4-31B-it-assistant and Gemma-4-31B-IT-NVFP4 models now available on Amazon SageMaker JumpStart

Google DeepMind's Gemma-4-31B-it-assistant and NVIDIA's Gemma-4-31B-IT-NVFP4 models are now accessible through Amazon SageMaker JumpStart. These models provide the powerful Gemma 4 31B dense architecture for enterprise use cases. The assistant-tuned Gemma-4-31B-it-assistant excels in multimodal reasoning, coding, and agentic workflows. It accepts text and image inputs, supports a vast context window, and handles over 140 languages. This variant ranks highly on open model leaderboards, outperforming larger models. It utilizes a hybrid attention mechanism and native function calling for autonomous agents. NVIDIA's Gemma-4-31B-IT-NVFP4 offers the same capabilities but with a significantly reduced memory footprint. Quantized to 4-bit FP4 precision using NVIDIA's ModelOpt, it requires less memory and offers faster inference. This optimized version maintains high quality and is suitable for cost-effective production deployments. SageMaker JumpStart allows users to deploy these models easily with minimal clicks. Customers can access these models via the SageMaker console or the SageMaker Python SDK.
https://aws.amazon.com/about-aws/whats-new/2026/01/gemma-4-31b-it-assistant-gemma-4-31b-it-nvfp4-jumpstart/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 14

granite-speech-4.1-2b, kanana-2-30b-a3b-instruct, and OpenFold3 models now available on Amazon SageMaker JumpStart

Amazon SageMaker JumpStart now offers three new foundation models: BM's granite-speech-4.1-2b, Kakao's kanana-2-30b-a3b-instruct, and the OpenFold Consortium's OpenFold3. These models enhance the AI capabilities available to AWS customers. Granite-speech-4.1-2b is designed for efficient multilingual automatic speech recognition and translation. It supports several languages and achieves a low word error rate with real-time processing. Kanana-2-30b-a3b-instruct specializes in bilingual Korean-English instruction following and agentic AI. This model utilizes a Mixture-of-Experts architecture for improved throughput and supports long context lengths. It is built to act as a proactive AI collaborator. OpenFold3 offers all-atom biomolecular complex structure prediction for various molecules. Developed by researchers at Columbia University, it models multi-chain complexes and heterogeneous interactions. This capability is valuable for drug design and scientific research. Customers can easily deploy these models through SageMaker JumpStart with minimal effort. Access to these models is available via the SageMaker console or the SageMaker Python SDK. Further details can be found in the Amazon SageMaker JumpStart documentation.
https://aws.amazon.com/about-aws/whats-new/2026/01/granite-speech-4.1-2b-edge-kanana-2-30b-a3b-instruct-openfold3-jumpstart/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 14

AWS Glue zero-ETL adds target table property ownership and conflict detection

AWS Glue zero-ETL integrations now detect table property conflicts and track integration ownership. When you configure a source table and target catalog, Glue associates the resulting table properties with the owning integration, so two integrations can no longer be pointed at the same target table without your knowledge. This works across Amazon S3 Tables and SageMaker Lakehouse catalogs. Data teams running multiple zero-ETL integrations gain predictable control over where each source table lands. If you attempt to create or modify an integration whose table properties are owned by another integration, Glue identifies the owning integration and guides you to choose a different target or update the existing one, so your pipelines stay isolated and your data lands exactly where you intend. This feature is available in all AWS Commercial and AWS GovCloud (US) Regions where AWS Glue zero-ETL integrations are supported. To learn more, refer to the AWS Glue Developer Guide and get started in the AWS Glue console.
https://aws.amazon.com/about-aws/whats-new/2026/09/glue-zero-etl-ownership-conflicts/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 14

AWS End User Messaging now supports Dynamic Flows in WhatsApp

AWS End User Messaging now supports dynamic WhatsApp flows so you can turn WhatsApp conversations into rich, interactive experiences that end-users complete directly in WhatsApp. Instead of pushing end-users to a website or a separate form to complete an interactive experience, you can instead guide them through an appointment booking, lead generation, sign-up, survey or a transaction directly in the chat. Customers can start building a flow using one of Meta's stater templates with familiar building blocks like text inputs, date pickers, drop downs, and buttons, or customize the flow from scratch. With dynamic flows, each screen can call your own HTTPS endpoint in real time, so you can show live availability, and personalize each step in the flow for your end-users. You build and manage flows entirely in AWS End User Messaging Social, through the console or APIs. Define a flow with a JSON schema, then deliver it with a message template to reach customers where they are. WhatsApp flows are available in all regions where End User Messaging Social is available. To get started, see the User Guide.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-end-user-messaging-whatsapp-dynamic-flows aws.amazon.com
RSS Hunter RSS Hunter • Sep 14

AWS End User Messaging strengthens SMS deliverability with automatic failover

AWS End User Messaging is advancing its deliverability capabilities in phone pools. Now, customers sending through phone pools automatically benefit from automatic failover to the next best performing number in the pool when SMS delivery is impacted from downstream disruptions. SMS deliverability can be affected by drops or delays when trying to reach the end recipient while it's being routed from AWS to messaging providers and eventually mobile carriers. These disruptions can hit the most important parts of your messaging program, including delivery notifications, one-time passcodes, reminders, and other time-sensitive messages. AWS End User Messaging watches for delivery delays, message failures, or drops in conversion and reroutes traffic to a more optimized delivery path. Customers do not need to take any action to receive this benefit for phone pools. If you are not sending through phone pools today, you can create one by following these instructions. This capability is available in all AWS Regions where AWS End User Messaging is available. To learn more, see the AWS End User Messaging SMS User Guide.
https://aws.amazon.com/about-aws/whats-new/2026/09/aws-end-user-messaging-improves-deliverability aws.amazon.com
RSS Hunter RSS Hunter • Sep 14

AWS Elemental MediaLive enables frame-accurate pipeline locking for streams without timecode

AWS Elemental MediaLive now supports Video Aligned Locking, a new feature to synchronize video pipelines without requiring timecode from the source. Previously, achieving frame-accurate locking across video outputs required investing in specialized hardware or managing complex, external synchronization workflows. While timecode is generally standard for highly produced, traditional broadcast content, it is often unavailable and difficult to manage in typical digital streaming workflows. The new capability uses visual signatures to automatically identify and align specific frames across multiple video streams, enabling customers to achieve frame-accurate input switching across standard pipeline channels, as well as linked, cross-region single-pipeline channels. Video Aligned Locking supports outputs including HLS, MediaPackage, CMAF Ingest, UDP and SRT. To learn more about how to configure this feature, visit the Requirements for Video Aligned Locking documentation. For a deeper dive into channel synchronization, visit the guide on Implementing Pipeline Locking.
https://aws.amazon.com/about-aws/whats-new/2026/09/medialive-pipeline-locking/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 12

Amazon EC2 X2idn instances are now available in Asia Pacific (Hong Kong)

Memory-optimized Amazon Elastic Compute Cloud (Amazon EC2) X2idn instances are now available in Asia Pacific (Hong Kong) Region. These instances, powered by 3rd generation Intel Xeon Scalable Processors and built with AWS Nitro System, are designed for memory-intensive workloads and deliver improvements in performance compared to previous generation X1 instances. These instances are SAP-certified for running Business Suite on HANA, SAP S/4HANA, Data Mart Solutions on HANA, Business Warehouse on HANA, SAP BW/4HANA, and SAP NetWeaver workloads on any database.
https://aws.amazon.com/about-aws/whats-new/2026/09/ec2-x2idn-asia-pacific-hong-kong/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 11

Amazon SageMaker HyperPod now supports model caching for faster inference autoscaling and reduced cold starts

Amazon SageMaker HyperPod now supports model caching, an inference optimization that pre-loads model weights and container images onto cluster nodes so pods start in seconds instead of minutes. When running LLM inference at scale for workloads like chat assistants, agentic pipelines, RAG, and document analysis, cold start is a real bottleneck. Deployments and scale-out events spend most of their time downloading container images and model weights. As model size increases, this gets worse, with large models taking tens of minutes before they can serve traffic. Model caching solves this with two independent capabilities. The weights cache stores model weights on local NVMe so pods read from fast local storage instead of pulling from S3 or FSx over the network. The image cache pre-pulls the container image so pods skip the ECR download entirely. If a pod lands on a node without a warm cache, it falls back to pulling from the original source automatically, so there is no risk of pods getting stuck or failing. Benchmarks across models from 57 GB to 145 GB show around 60% faster scale-out, and the image cache cuts over two minutes of image-pull time (97% reduction). The benefit grows with model size while retaining the reliability of the original source path. Customers enable model caching through the HyperPod Inference Operator by adding a modelCacheConfig section to their InferenceEndpointConfig or JumpStartModel resource. The operator handles the full lifecycle with no manual setup or cleanup. Model caching is now generally available in all regions where SageMaker HyperPod is available. To get started, see the SageMaker HyperPod documentation.
https://aws.amazon.com/about-aws/whats-new/2026/09/sgm-hyperpod-model-caching-inf/ aws.amazon.com
RSS Hunter RSS Hunter • Sep 11