AWS Recent Announcements

Amazon Relational Database Service (Amazon RDS) for Oracle now supports Oracle Application Express (APEX) version 26.1. Amazon RDS for Oracle is a managed database service that makes it simple to set up, operate, and scale Oracle Database deployments in the cloud. Oracle APEX is a low-code development platform that enables developers to build scalable, secure enterprise applications with modern user interfaces. To learn more about the latest features of Oracle APEX 26.1, see Oracle’s APEX Release 26.1 documentation. For more details on supported Oracle APEX versions and how to add or modify Oracle APEX options for your RDS for Oracle database, visit the Amazon RDS for Oracle APEX Documentation. Oracle APEX version 26.1 is available in all AWS regions where Amazon RDS for Oracle is available. See Amazon RDS for Oracle Pricing for regional availability.

Amazon Simple Email Service (SES) now makes it easier to support mobile deep linking with the new ses:custom-path HTML attribute. When you add this attribute to an <a> tag, SES carries your path segment through to the tracking URL, so mobile operating systems can match it to your app’s Universal Links (iOS) or App Links (Android) configuration. This enables you to use mobile deep linking without disabling engagement tracking. This feature is available in all AWS Regions where Amazon SES is available. To use this feature, you need a custom redirect domain for click tracking with an Apple App Site Association (AASA) or Digital Asset Links verification file hosted on that domain. Then, add the ses:custom-path attribute to links in your HTML emails. To learn more, see Configuring custom domains to handle open and click tracking and the Amazon SES email sending metrics FAQs in the Amazon SES Developer Guide.

AWS Billing and Cost Management (BCM) Dashboards now include Managed Dashboards. These are a collection of preconfigured and read-only dashboards located in your dashboard list. They deliver actionable cost insights with your account data pre-populated without setup.  There are five curated dashboards. Cost Overview & Trends tracks your spending patterns across services, accounts, and regions over 12 months with forward-looking forecasts. Compute and Database dashboards show your spend pattern within each service category, pairing cost breakdowns with relevant commitment coverage and utilization metrics in a single view. Reservations and Savings Plans dashboards show how well your purchased commitments are performing across all eligible services, quantifying gaps and underutilization in monetary terms.  All managed dashboards are read-only and maintained by AWS. You can duplicate any dashboard to create a fully editable custom copy, add individual widgets to your existing dashboards, and export via PDF or CSV. Whether you are starting your FinOps journey or looking for a standardized baseline across accounts, Managed Dashboards give you cost visibility without setup so you can focus on analysis and action rather than configuration.  AWS Managed Dashboards are available in all commercial AWS Regions at no additional cost. To get started, navigate to Dashboards in the AWS Billing and Cost Management console or view the user guide. 

AWS Client VPN introduces a rebuilt AWS VPN Client v6.0.x which offers new features like command-line interface (CLI) support, enterprise administrative controls, and faster connection establishment time, making it easier you to automate VPN connectivity and centralize device management across your organization. The AWS VPN Client CLI provides full feature parity with the GUI. You can now script VPN connections into your automation workflows and infrastructure-as-code deployments. Previously, integrating VPN connectivity into automated environments required third-party tooling or manual intervention. This feature eliminates that by supporting background CLI operations. Previously, you had to distribute VPN profiles among all users in your organization, which could be managed by any user without permissions. Now, with administration controls on AWS client, you can centralize VPN policy enforcement by scoping profiles to specific users, manage global profiles available to all users on a device, and enforce approved VPN configurations across your organization. The client is rebuilt with OpenVPN3, delivering faster connection establishment across all supported operating systems. You can use both the GUI and CLI together as both run concurrently and VPN connections persist independently of either interface. The rebuilt client v6.0 onwards maintains full backward compatibility with existing AWS Client VPN endpoints, so no endpoint changes are required. The updated AWS VPN Client is available today for Windows (x64/ARM), macOS (x64/ARM), and Linux (x64). There are no additional charges beyond standard pricing of AWS Client VPN. Download the latest client version 6.0.x for macOS, Windows and Linux to start using it.  To learn more about Client VPN, visit the AWS Client VPN product page or read the documentation.

Amazon Redshift now offers rg.large and rg.12xlarge instance sizes for RG instances in the AWS GovCloud (US-West) and AWS GovCloud (US-East) Regions. 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.large and rg.12xlarge instance sizes are available on patch version P202 and later. Customers can resize existing RG or RA3 clusters to these new instance sizes using Elastic Resize or Classic Resize. Customers with existing RA3 clusters can also upgrade to RG using Snapshot & Restore. RG instances are available in four instance sizes: rg.large, rg.xlarge, rg.4xlarge, and rg.12xlarge. 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 Redshift RG Instance Documentation  RA3 to RG Upgrade Guide  Amazon Redshift Pricing

AWS GovCloud (US) now offers Claude Opus 5 — the most advanced Opus model yet, and compatible with zero data retention (ZDR) — bringing a step-change in coding, long-running agents, and complex professional work to teams building at the highest level. Claude Opus 5 is available via the bedrock-runtime endpoint in both AWS GovCloud (US) regions, and available via the bedrock-mantle endpoint in AWS GovCloud (US-West) Claude Opus 5 delivers advances in coding, understanding and navigating codebases like an experienced engineer and writing production-quality code while adapting its strategy as it works. It powers dependable agents that run for hours and even overnight, finding paths around obstacles, recovering from errors, and reaching their objectives. And it brings deeper reasoning to long documents and higher accuracy to complex analysis, with the largest gains on document-heavy enterprise work.  Amazon Bedrock offers Claude Opus 5 with zero data retention (ZDR) enabled by default, giving you Opus’ top-tier intelligence while meeting your data governance requirements. It keeps your data within AWS infrastructure with regional data residency and provides access through a unified service with AWS-managed features like Guardrails and Knowledge Bases. To learn more, see the Amazon Bedrock documentation and regional availability.

Today, Amazon Quick announces the general availability of Microsoft 365 extensions for Excel, PowerPoint, Word, and Outlook. These extensions enable Quick to perform tasks directly within users’ M365 environments, using AI to handle complex local tasks such as redlining documents, building financial models, creating presentation-ready decks, and managing Outlook inboxes. The Excel extension helps with complex spreadsheet analysis, creating pivot tables and charts, and importing and cleaning data. The PowerPoint extension helps you create and refine presentations from Quick data using organization-defined templates. The Word extension generates formatted documents with Word primitives, makes sweeping edits with track changes enabled, and participates as a reviewer in comments. The Outlook extension performs inbox and calendaring tasks such as prioritizing emails, organizing your inbox, scheduling meetings, and drafting replies using your Quick data and entire inbox context. These extensions transform daily work across teams. Finance teams can build complex models by describing what they need. Sales teams can draft proposals that automatically pull from CRM data. Marketing teams can create branded presentations without manual formatting. Legal teams can streamline contract reviews. Operations teams can manage email workflows and schedule meetings intelligently, and IT teams can automate routine data analysis that previously required manual effort. Amazon Quick Microsoft 365 extensions are available in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), Europe (Ireland), Asia Pacific (Tokyo), and Europe (Frankfurt). To learn more, see Amazon Quick for Microsoft 365: Agentic AI where you work, and download extensions on the Quick download page.

Today, AWS announces support for AWS Local Zones in Spot placement score, helping you identify locations where your Spot capacity request is most likely to succeed. Spot placement score evaluates your target capacity and compute requirements and returns scores for AWS Regions or Availability Zones. Previously, Spot placement scores excluded local zone capacity information when reporting zonal and regional scores. Now, you can optionally request local zones to be included in the zonal and regional score responses giving you a broader view of your Spot capacity options. You can use Spot placement score through EC2 Spot Console, AWS CLI, or SDK. To learn more about Spot placement score see Spot placement score documentation.

Security teams can now access Daybreak Red and Daybreak Blue from OpenAI on Amazon Bedrock. Both are part of Daybreak, the cyber defense initiative from OpenAI that gives defenders governed access to frontier AI for cybersecurity work. Daybreak Blue is the starting point for most security teams across defensive workflows including vulnerability discovery, detection engineering, and incident response. Daybreak Red is designed for advanced, authorized tasks such as vulnerability research, exploit reproduction, and mitigation development. For these tasks, a lower refusal threshold matched by stronger identity verification, monitoring, and access controls improves the speed and depth of an investigation. Both models run on Bedrock’s next-generation inference engine with zero-operator access (ZOA) enforced at the chip. Your inference data is not used for model training, and neither model requires you to opt into sharing your data with OpenAI. Daybreak Red: GPT-5.6 Cyber and Daybreak Blue: GPT-5.6 Sol are now available to eligible customers on Amazon Bedrock in the following AWS Region: US East (Ohio). Access to the models requires enrollment in Daybreak access from OpenAI. To enroll, contact OpenAI or reach out to your AWS account team for guidance on eligibility. Once approved, work with your account team to request access on AWS. To learn more, read the blog.

AWS Certificate Manager (ACM) now enables you to change the domain validation method on your existing ACM issued public TLS certificates from e-mail to DNS, without reissuing the certificate or changing its existing Amazon Resource Name (ARN). Due to the Certification Authority/Browser (CA/B) Forum’s mandated deprecation of email-based domain validation for publicly trusted certificates, effective March 15, 2028, ACM will phase out its support for email validation throughout 2027. ACM will no longer issue email-validated certificates starting March 31 2027, and stop renewing email-validated certificates on September 30 2027. More details on ACM’s deprecation of email validation can be found on the AWS Security Blog. By switching to DNS validation now, you can transition ahead of that deadline and enable fully automated renewals through DNS validated certificates. Your certificate ARN remains unchanged after switching from e-mail to DNS validation, so existing ARN references in your CI/CD pipelines, load balancer configurations, and other AWS service integrations continue to work without modification. To switch the validation method, use the ACM console or the  UpdateCertificateOptions API. ACM provides a CNAME record for each domain in the certificate (the same mechanism used when provisioning new certificates with DNS validation) and you have up to 72 hours to add the records to your DNS configuration. You can monitor the validation status of each domain via the console or the ListCertificateDomainValidations API. We recommend DNS validation for new certificates, and HTTP validation for Amazon CloudFront distributions.. This feature is available in all AWS Regions where ACM certificates are available. To get started, refer to  Migrating from email to DNS validation in the AWS Certificate Manager User Guide.

Amazon S3 now includes the specific AWS Identity and Access Management (IAM) and AWS Organizations policy Amazon Resource Name (ARN) in HTTP 403 Access Denied error messages for same-account and same-organization requests. This helps you quickly identify the exact policy responsible for a denied request and remediate the issue directly. Previously, S3 access denied error messages included the policy type and reason for denial, but when multiple policies of the same type existed, you still had to manually inspect each one to pinpoint the root cause. Now the error message includes the specific policy ARN for explicit deny cases, covering Service Control Policies (SCPs), Resource Control Policies (RCPs), identity-based policies, session policies, and permission boundaries. This capability is available in all AWS Regions, including the AWS GovCloud (US) Regions and the AWS China Regions. To learn more about how to troubleshoot access denied errors in Amazon S3, visit the S3 User Guide and the IAM troubleshooting documentation.

AWS Clean Rooms now supports minimum aggregation thresholds for the Custom analysis rule type. Minimum aggregation helps protect the privacy of individual data subjects by preventing queries from returning results about individuals or small groups. With this launch, organizations can enforce minimum aggregation on custom SQL queries, ensuring that every row a query outputs represents at least the specified number of distinct values (e.g., user IDs). Data providers in a collaboration can specify their identity column and a minimum identity count to enforce on a query’s output, with the option to set a higher threshold for specific columns. Previously, enforcing minimum aggregation thresholds on custom SQL required data providers to rely on pre-approved analysis templates and manual code reviews before queries could run. Now, data providers can configure the minimum aggregation threshold for custom SQL using the Custom analysis rule type, without using pre-structured queries or manual approval processes. Additionally, data providers can specify which columns can be filtered or joined across datasets. For example, a publisher collaborating with an advertiser for media planning use cases can enable ad-hoc queries to run on their data—and small, rural zip codes with fewer than 1,000 common users can be automatically filtered out from the result to help protect user privacy.  AWS Clean Rooms helps companies and their partners easily analyze and collaborate on their collective datasets without revealing or copying one another’s underlying data. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.

Amazon Quick now offers approval policies, giving administrators governance controls over how assets are shared within their organization. With approval policies, administrators can require designated approvers to review and approve share requests before access is granted, helping organizations ensure that sharing of sensitive assets is deliberate, compliant, and auditable. Administrators can create approval policies scoped to specific asset types, including knowledge bases, spaces, and custom chat agents. When a user submits a share request for an asset covered by a policy, it is routed to the assigned approver group for review. Approvers can evaluate the asset directly before approving or denying the request, and all workflow events are captured in AWS CloudTrail for full auditability. For custom chat agents, approvers can review and act on the entire dependency package in a single request. This feature is available for Professional and Enterprise plans, in all AWS Regions where Amazon Quick agentic capabilities are supported. For more information, see the AWS Region table. Learn more about Amazon Quick by visiting the Quick website. To learn more about approval policies, see Approval policies in the Amazon Quick User Guide. 

Amazon Quick now enables administrators to set per-user limits on index storage and agent hours, giving them direct control over subscription costs. With limits management, administrators can create limit profiles that cap per-user consumption, helping prevent unexpected overage charges and ensuring subscription entitlements are used efficiently across their organization. For example, an organization deploying Quick enterprise-wide to thousands of users can set account-level limit profiles to establish cost-predictable baselines, then assign higher limits to specific roles that require more agent hours. Administrators can create and assign limit profiles at the user, role, or account level, with a priority hierarchy that ensures the right users get the right capacity. When a user reaches their limit, new consumption is blocked while existing content is preserved. This feature is available for Professional and Enterprise plans, in all AWS Regions where Amazon Quick agentic capabilities are supported. For more information, see the AWS Region table. Learn more about Amazon Quick by visiting the Quick website. To learn more about limit profiles, see Limits management in the Amazon Quick User Guide. 

Today, AWS announces the addition of an interactive map view to AWS Global View in the AWS Management Console, providing a visual way to explore AWS Global Infrastructure. Previously, customers had to scan through a list of AWS locations in AWS Global View. With this new capability, customers can toggle between the interactive map view and the existing list view, making it easier to visualize their global AWS infrastructure footprint.  When customers select the map view, they will see all AWS Regions and AWS Local Zones plotted on an interactive map. This capability helps customers make informed infrastructure planning decisions by visualizing already enabled AWS locations and the full range of AWS locations available to them, all in a single glance. This capability is available across all public AWS Regions. To get started, navigate to the Regions and Zones page in AWS Global View console. For more information, see the AWS Global View documentation.

Amazon Elastic Kubernetes Service (Amazon EKS) now supports configuring parameters for Kubernetes control plane components including the scheduler, controller manager, and API server. You can tune pod placement strategies to improve resource utilization, adjust how quickly horizontal pod autoscaling responds to changes in demand, set resource lifecycle parameters such as event retention duration, and more. Cluster administrators now have more control over Kubernetes control plane parameters beyond the defaults. For example, you can set the scheduler’s node resource fit strategy parameter to MostAllocated, which packs pods onto nodes that are already well utilized and helps you run the same workloads on fewer nodes. The default LeastAllocated strategy spreads pods across nodes, and you can keep it where headroom matters more than density. You can configure Kubernetes control plane parameters in any AWS Region where Amazon EKS is available. For the full list of configurable parameters and to learn more, see Control plane configuration in the Amazon EKS User Guide.

Today, AWS announces the general availability of role manager, a capability in AWS Identity and Access Management (IAM) that automatically sets up the IAM roles your AWS services need. When you set up a supported service in the console, role manager creates a default role on your behalf, or reuses one that already exists in your account if it already matches the required permissions. You can enable or disable role manager at any time, as well as inspect the AWS-managed templates that role manager deploys on your behalf. Role manager supports 6 AWS service consoles at launch, including AWS Lambda and Amazon EventBridge. For example, when you create an AWS Lambda function, role manager applies the AWS-managed template for that workflow. Roles created via role manager appear in the IAM console as standard IAM roles that you fully control, and you can identify the ones role manager created. When you are ready to tighten permissions, you can disable role manager and use IAM Access Analyzer to refine each role to only the permissions it needs. Role manager is available in all AWS Regions, except the AWS GovCloud (US) Regions and the China Regions. To learn more, see How AWS IAM role manager rethinks the starting point for IAM roles on the AWS Security Blog, or Create roles automatically with role manager in the IAM User Guide.

Amazon Connect Customer now lets agents view and self-assign queued agent-first callbacks alongside emails, tasks, and chats. This gives agents the option to prioritize work that needs immediate follow-up or for which they already have relevant context. For example, an agent familiar with a customer’s issue can assign the callback to themselves, avoiding another handoff and helping resolve the issue faster. This feature is available in all AWS Regions where Amazon Connect Customer is available. To learn more about how to use queued callbacks, refer to our documentation Access the Worklist app and Set up queued callbacks. For more information about Amazon Connect Customer, visit our product page.

Amazon Quick custom permissions now include deny by default, a governance setting that automatically restricts new AI capabilities before they reach users. Previously, new AI capabilities were available to all users on release, requiring administrators to react after the fact. With deny by default, administrators restrict the AI capability category in a custom permissions profile and assign it to users, roles, or the entire account. Quick then denies any new AI capability at launch for those users. Restricting a category also restricts existing capabilities in it. Administrators explicitly allow each capability when ready. The restriction applies only to the profile you configure. Configure deny by default in Manage account in Amazon Quick or through the AWS CLI. To learn more, see Custom permissions deny by default. Deny by default is available in all AWS Regions where Amazon Quick is available.

Amazon Quick now integrates with Microsoft Purview to enforce data loss prevention (DLP) policies across your Quick environment. Organizations need to ensure that sensitive files aren’t shared outside approved channels. With this integration, IT administrators and security teams can apply their existing Purview sensitivity labels to automatically control how files are handled in Quick capabilities such as chat, spaces, and knowledge bases. Administrators can configure enforcement actions (block, warn, or allow) for each sensitivity label, giving organizations granular control over sensitive file sharing across Quick. For example, a financial services company can block files labeled “Highly Confidential” from being uploaded to shared spaces while allowing “Internal” files with a warning notification. With this integration, customers can extend their existing Microsoft Purview governance policies into Quick without additional tools. This feature is available in all AWS Regions where Amazon Quick agentic capabilities are supported. For more information, see the AWS Region table. To learn more, see Data loss prevention in the Amazon Quick User Guide. 

We are excited to announce the general availability of Amazon Nova Multimodal Embeddings, a state-of-the-art embedding model for agentic RAG and semantic search, in AWS GovCloud (US-West). It is the first unified embedding model that supports text, documents, images, video, and audio through a single model, to enable cross-modal retrieval with leading accuracy.  Managing and searching across different content types traditionally required multiple specialized embedding models, leading to complexity, higher costs, and data silos. Amazon Nova Multimodal Embeddings maps diverse content types into a unified space with leading accuracy, helping break down these silos. Developers can build cross-modal applications that search video archives using complex queries, find relevant product images based on customer questions, or search financial documentation that contain both infographics and text explanations, all using a single embedding model.  The model supports inputs of up to 8K tokens in length and video/audio segments up to 30 seconds, with the capability to segment larger files. Multiple output embedding dimensions allow organizations to balance accuracy and performance with storage and computation costs. Organizations can choose between synchronous API for near real-time applications and asynchronous API for efficient processing of larger files, enabling them to optimize for both latency-sensitive and high-volume workloads.  To learn more, see the user guide. To get started with Nova Multimodal Embeddings in Amazon Bedrock, visit the Amazon Bedrock console in AWS GovCloud (US-West).

Today, AWS announces that Amazon Quick’s agentic AI capabilities are now available in AWS GovCloud (US-West), bringing an agentic AI teammate to government and regulated-industry teams within an isolated, FedRAMP Class D (formerly High) authorized environment. Building on the analytics and business intelligence capabilities already available to customers in AWS GovCloud (US), Quick now turns questions into actions, helping teams drive mission-critical decisions faster without switching applications. With this launch, teams can build custom chat agents tailored to mission-specific workflows — including procurement, ATO compliance, and grants management — while keeping data hosted and processed entirely within the AWS GovCloud (US-West) Region. Spaces enforce least-privilege access by scoping information to the appropriate program office or mission area, ensuring analysts only access mission-relevant data. Quick also integrates with tools teams already rely on, including Microsoft 365, SharePoint, and OneDrive via GCC High connectors, as well as browser extensions. AWS GovCloud (US) Regions are isolated AWS Regions operated by U.S. citizens on U.S. soil, purpose-built to host sensitive data and regulated workloads. Customers can address the most stringent U.S. government security and compliance requirements, including the FedRAMP Class D (formerly High) baseline, Department of Defense Cloud Computing Security Requirements Guide (DoD SRG) Impact Levels 4 and 5, International Traffic in Arms Regulations (ITAR), Criminal Justice Information Services (CJIS), and Federal Information Processing Standard (FIPS) 140-3. Inference on authorized foundation models is processed within the AWS GovCloud (US-West) Region, and enterprise governance features are available at launch. With this launch, Amazon Quick’s agentic AI capabilities are available in 8 AWS Regions: US East (N. Virginia), US West (Oregon), Europe (Frankfurt, Ireland, London), Asia Pacific (Sydney, Tokyo), and AWS GovCloud (US-West).  To learn more, visit the Amazon Quick product page and AWS GovCloud (US) documentation

Starting today, Amazon EC2 R8a instances are now available in Canada (Central) Region. These instances, feature 5th Gen AMD EPYC processors (formerly code named Turin) with a maximum frequency of 4.5 GHz, deliver up to 30% higher performance, and up to 19% better price-performance compared to R7a instances. R8a instances deliver 45% more memory bandwidth compared to R7a instances, making these instances ideal for latency sensitive workloads. Compared to Amazon EC2 R7a instances, R8a instances provide up to 60% faster performance for GroovyJVM, allowing higher request throughput and better response times for business-critical applications. Built on the AWS Nitro System using sixth generation Nitro Cards, R8a instances are ideal for high performance, memory-intensive workloads, such as SQL and NoSQL databases, distributed web scale in-memory caches, in-memory databases, real-time big data analytics, and Electronic Design Automation (EDA) applications. R8a instances offer 12 sizes including 2 bare metal sizes. Amazon EC2 R8a instances are SAP-certified, and providing 38% more SAPS compared to R7a instances. To get started, sign in to the AWS Management Console. For more information about the new instances, visit the Amazon EC2 R8a instance page. 

Amazon Bedrock is a fully managed service that provides secure, enterprise-grade access to high-performing foundation models from leading AI companies, enabling you to build and scale generative AI applications. Amazon Bedrock now supports cost allocation by AWS Identity and Access Management (IAM) principal, including IAM users and roles, for model inference requests made through the bedrock-mantle endpoint. This extends the capability previously available for the bedrock-runtime endpoint, helping customers attribute inference costs across users, teams, projects, and applications. Customers can tag IAM users and roles with attributes such as team, project, or cost center, activate them as cost allocation tags, and analyze bedrock-mantle inference costs by those tags in AWS Cost Explorer or at the line-item level in AWS Cost and Usage Report 2.0 (CUR 2.0). To get started, activate your IAM principal tags in the AWS Billing and Cost Management console. Then filter or group costs by those tags in Cost Explorer, or create a CUR 2.0 data export and select Include caller identity (IAM principal) allocation data. This feature is available in all AWS Regions where the bedrock-mantle endpoint is available. To learn more, see Using IAM principal for cost allocation and IAM principal attribution in Amazon Bedrock.

NVIDIA’s LocateAnything-3B, Qwen’s Qwen-AgentWorld-35B-A3B, and Qwen’s Qwen3.5-122B-A10B models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These three models bring specialized capabilities spanning visual grounding, agent environment simulation, and large-scale multimodal reasoning, enabling customers to deploy high-performance, scalable AI solutions on AWS infrastructure. These models address different enterprise AI challenges with specialized capabilities: LocateAnything-3B is optimized for fast, high-quality visual grounding and object localization from natural language instructions. It uses a Parallel Box Decoding (PBD) framework that decodes bounding boxes and points as atomic units in a single step, preserving geometric coherence and unlocking substantial parallelism. It enables precise object localization, dense detection, and point-based localization across diverse domains in both Enterprise Intelligence and Physical AI applications. Qwen-AgentWorld-35B-A3B excels in simulating agent environments across seven interaction domains: tool calling, search, terminal, software engineering, Android, web, and OS interaction. It is the first language world model to cover all seven domains within a single model, predicting next environment states given an agent’s action and interaction history via long chain-of-thought reasoning—trained on over 10 million real-world interaction trajectories. Qwen3.5-122B-A10B provides high-performance multimodal reasoning with production-friendly efficiency. It features 122B total parameters with only 10B activated per token through a hybrid architecture integrating Gated Delta Networks with sparse Mixture-of-Experts (256 experts), delivering strong reasoning, coding, agents, and visual understanding performance with a native 262K context window and minimal latency overhead. With SageMaker JumpStart, customers can deploy any of these models with just a few clicks to address their specific AI use cases. To get started with these models, navigate to the SageMaker JumpStart model catalog in the SageMaker console or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the Amazon SageMaker JumpStart documentation.  

NVIDIA’s Nemotron 3.5 Lightning is now available on Amazon SageMaker JumpStart, giving AWS customers access to the fastest open model in its class for persistent agent workloads and rapid task execution. Nemotron 3.5 Lightning is engineered for persistent agents and high-throughput enterprise automation across domains including personal assistants, financial document processing, cybersecurity triage, and telecom operations. Built on a hybrid Mixture-of-Experts (MoE) architecture with 30B total parameters and just 3B active per forward pass, it achieves up to 4x the throughput (~410 tokens/sec) and 30% faster task completion over comparable models. Distilled from Nemotron 3 Ultra, it handles up to 1M tokens of context via DFlash speculative decoding and integrates directly with popular agent harnesses. The model is fully open-trained on open datasets thereby allowing enterprises to post-train for their own tools, workflows, and policies, and deploy with complete ownership across edge, on-premises, or cloud infrastructure. With SageMaker JumpStart, customers can deploy this model in a few clicks to power their specific AI workloads. To get started with these models, navigate to the SageMaker JumpStart model catalog in the SageMaker console or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the Amazon SageMaker JumpStart documentation.

AWS Secrets Manager now extends its managed external secrets capability to include Jenkins API Tokens and SonarQube Tokens, enabling you to automatically rotate these third-party credentials directly from the AWS console without writing any custom rotation code. For Jenkins, Secrets Manager mints a new token and revokes the old one only after the replacement is verified active, so your continuous integration and continuous delivery (CI/CD) jobs transition without interruption. Rotation supports both self-rotation, where the token being rotated authenticates its own replacement, and admin-assisted rotation, where a separate admin token performs the generate and revoke operations. For SonarQube, you can rotate three types of tokens — User Tokens, Global Analysis Tokens, and Project Analysis Tokens — via SonarQube’s Web API. User Tokens support self-rotation, while analysis tokens are rotated using an admin token. These integrations join existing managed external secrets support for BigID, Confluent Cloud, Datadog, GitLab, MongoDB Atlas, Okta, Paddle, Salesforce, and Snowflake. Jenkins and SonarQube managed external secrets are available in all AWS Regions where AWS Secrets Manager managed external secrets is supported. To learn more, visit the  AWS Secrets Manager managed external secrets documentation .

AWS Glue now provides direct access to Amazon SageMaker Unified Studio, helping data engineers and analysts move from viewing the catalog in the Glue console to querying their data, running data quality checks, and building data pipelines in SageMaker Unified Studio with a single click. This new integration helps customers who already work in the Glue console access data and AI capabilities in SageMaker Unified Studio. With this launch, SageMaker Unified Studio can now be accessed by a single click from S3 Tables, Athena, EMR, Redshift and Glue consoles. When working in the AWS Glue console to browse catalog tables or build ETL jobs, you now have one-click access to open SageMaker Unified Studio, and can immediately begin working with your data in the catalog or query your data using SageMaker Notebooks using the same IAM role. For Glue console customers who have not yet set up SageMaker Unified Studio, a new inline permissions panel helps you create and configure the required IAM policies directly within the setup workflow, without navigating to the IAM console and switching browser tabs. You can use your existing IAM role and customize the permissions in-context, reducing the steps required to get started. This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is supported. To get started, navigate to the AWS Glue console.

Amazon Connect Customer now provides a performance dashboard for cases that helps managers monitor case volume, resolution trends, and performance against service level agreement (SLA) targets. Managers can compare current and prior-period performance across metrics such as cases created, average resolution time, first-contact resolution percentage, and SLA achievement rate. They can also analyze trends across dimensions such as case template, assigned user, or assigned queue. For example, a manager can identify that the billing team missed more SLA targets for refund cases than in the prior period, investigate the causes, and prioritize process improvements. Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town). To learn more and get started, visit the Cases webpage and documentation.

AWS Clean Rooms now supports exporting privacy-enhanced analysis logs for SQL analyses, offering customers greater optimization and troubleshooting capabilities. With this launch, you can export privacy-enhanced analysis logs to an S3 bucket for SQL queries that ran in an AWS Clean Rooms collaboration, providing insight into Spark execution details that can help you optimize and troubleshoot your queries. Collaboration owners grant a member the ability to export analysis logs when they create a collaboration or submit a change request to grant the ability to a member of an existing collaboration. After a query runs, you can export the privacy-enhanced analysis logs to your desired S3 path. For example, a third-party measurement provider collaborating with a publisher can identify an anomalous data skew that is causing a query to run slower than usual, accelerating time-to-resolution and optimizing costs.  AWS Clean Rooms helps companies and their partners easily analyze and collaborate on their collective datasets without revealing or copying one another’s underlying data. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.