AWS Recent Announcements

AWS Billing and Cost Management Dashboards now support scheduled email delivery for your reports. You can now automate report distribution on flexible recurring schedules, eliminating manual compilation work and ensuring financial insights reach decision-makers without requiring console access.” Scheduled email reports enable you to configure daily, weekly, or monthly delivery schedules for your dashboards. Recipients receive emails containing secure links to password-protected PDF reports optimized for offline viewing. Manage recipients through AWS User Notifications, and once configured, reports generate and distribute automatically on your chosen schedule. You can also access these capabilities programmatically through AWS SDKs and CLI tools. This feature is available at no additional cost in all commercial AWS Regions, excluding AWS China Regions. To get started, open the AWS Billing and Cost Management console, navigate to Dashboards, select a dashboard, and choose ‘Manage email reports’ from the Actions menu. For more information, see the Dashboards user guide and announcement blog post.

Amazon Timestream for InfluxDB now supports customer-defined maintenance windows, giving you control over when routine maintenance is performed on your InfluxDB databases. This feature is available for both InfluxDB 2 instances and InfluxDB 3 clusters across all supported editions. With this launch, you can specify a weekly maintenance window using a day-and-time format in your preferred timezone. Timestream for InfluxDB supports IANA timezone identifiers such as America/New_York, Europe/London, and Asia/Tokyo, and automatically handles Daylight Saving Time transitions so you don’t need to manually adjust your schedule. If you don’t specify a maintenance window, the service continues to manage maintenance timing automatically. You can set or update your preferred maintenance window when creating or modifying a resource using the Amazon Timestream for InfluxDB console, AWS CLI, or AWS SDKs. You can use Amazon Timestream for InfluxDB Customer-Defined Maintenance Windows in all Regions where Timestream for InfluxDB is offered. To get started with Amazon Timestream for InfluxDB, visit the Amazon Timestream for InfluxDB console. For more information, see the Amazon Timestream for InfluxDB documentation and pricing page.

Amazon Bedrock now supports cost allocation by IAM principal, such as IAM users and IAM roles, in AWS Cost and Usage Report 2.0 (CUR 2.0) and Cost Explorer. This enables customers to understand and attribute Bedrock model inference costs across users, teams, projects, and applications. With this launch, customers can tag their IAM users and roles with attributes like team, project, or cost center, activate them as cost allocation tags, and analyze Bedrock model inference costs by the tags in Cost Explorer or at the line-item level in CUR 2.0. To get started, tag your IAM users and roles and activate them as cost allocation tags in the Billing and Cost Management console. Then create a CUR 2.0 data export and select “Include caller identity (IAM principal) allocation data” or filter by tags in Cost Explorer. This feature is available in all AWS commercial Regions where Amazon Bedrock is available. To learn more, see Using IAM principal for Cost Allocation documentation. To get started with Amazon Bedrock, visit Amazon Bedrock documentation.

Amazon OpenSearch Service now provides a unified observability experience that brings together metrics, logs, traces, and AI agent tracing in a single interface. This release introduces native integration with Amazon Managed Service for Prometheus and comprehensive agent tracing capabilities, addressing the dual challenges of prohibitive costs from premium observability platforms and operational complexity from fragmented tooling. Site Reliability Engineers, DevOps Engineers, and Platform Engineering teams can now consolidate their observability stack without costly data duplication or constant context switching between multiple tools. You can now query Prometheus metrics directly using native PromQL syntax alongside logs and traces in OpenSearch UI’s observability workspace—without duplicating data. Combined with new application monitoring workflows powered by RED metrics (Rate, Errors, Duration) and AI agent tracing using OpenTelemetry GenAI semantic conventions, operations teams can correlate slow traces to application logs, overlay Prometheus metrics on service dashboards, and trace LLM agent execution—all without switching tools. This live query architecture delivers significant cost reduction compared to premium platforms while maintaining operational excellence. The new unified observability experience is available on OpenSearch UI in 20 AWS regions: US East (N. Virginia, Ohio), US West (N. California, Oregon), Asia Pacific (Hong Kong, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Europe (Frankfurt, Ireland, London, Milan, Paris, Spain, Stockholm), Canada (Central), and South America (São Paulo). To learn more, visit the OpenSearch Service observability documentation and direct query documentation.

Amazon S3 Lifecycle now prevents expiration and transition actions on objects that failed replication, helping you to coordinate replication configuration or permissions changes with actions defined in your lifecycle rules. Incorrect permissions or replication configuration can prevent objects from being replicated. With this change, S3 Lifecycle no longer expires or transitions objects that have failed replication, even if they match one of the lifecycle rules that you have defined. Once you have corrected your replication configuration or permissions, you can use S3 Batch Replication to replicate objects that previously failed. After successful replication, S3 Lifecycle will automatically process these objects according to your configured rules. This change applies automatically to all existing and new S3 Lifecycle configurations, across 37 AWS Regions, including the AWS China and AWS GovCloud (US) Regions. We are in the process of deploying this change and plan to complete the deployment in the coming days. To learn more, visit S3 Lifecycle documentation and S3 Replication troubleshooting documentation.

Amazon RDS Blue/Green Deployments now supports Amazon RDS Proxy, enabling faster application recovery during switchover by eliminating DNS propagation delays. Blue/Green Deployments create a fully managed staging environment (Green) that allows you to deploy and test production changes, keeping your current production database (Blue) safe. When ready, you can switchover to the new production environment and your applications begin accessing it immediately without any configuration changes. During a Blue/Green Deployment switchover for single-Region configurations, RDS Proxy actively monitors database instances and detects when the Green environment becomes the new production environment. This allows RDS Proxy to quickly redirect connections to the Green environment, enabling faster application recovery. You don’t need to modify your drivers or change your existing application setup. Amazon RDS Blue/Green Deployments with Amazon RDS Proxy is available for Amazon Aurora with MySQL compatibility, Amazon Aurora with PostgreSQL compatibility, Amazon RDS for MySQL, Amazon RDS for PostgreSQL, and Amazon RDS for MariaDB in all commercial AWS Regions where RDS Proxy is available. In a few clicks, update your databases using RDS Blue/Green Deployments via the Amazon RDS Console or Amazon CLI. To learn more, see Blue/Green Deployments overview in the Amazon RDS documentation.

AWS Agent Registry, available through Amazon Bedrock AgentCore, is now in preview — a private, governed catalog and discovery layer for agents, tools, skills, MCP servers, and custom resources within the organization. It gives teams complete visibility into their AI landscape, enabling them to discover existing agents and tools instead of rebuilding capabilities that already exist. The registry can be accessed via the AgentCore Console UI, APIs (AWS CLI, AWS SDK), or as an MCP server that builders can query and invoke directly from their IDEs. Registry supports both IAM and OAuth (Custom JWT) based access. Teams can register resources manually through the console or API, or use URL-based discovery, which automatically retrieves metadata such as tool schemas and capability descriptions from a live MCP server or agent endpoint. Records go through an approval workflow where administrators can approve records before they become discoverable, and they can plug the registry into their existing approval workflows to enforce governance policies. AWS CloudTrail provides complete audit trails of all registry access and administrative actions, ensuring compliance and security oversight. For discovery, the registry offers both semantic and keyword search, so developers can quickly find agents by describing their use case in natural language.  AWS Agent Registry (preview) is available in five AWS Regions where AgentCore is available: US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Sydney), Europe (Ireland), and US East (N. Virginia). Learn more about the registry through the blog, and deep dive using the documentation.

Today, AWS Marketplace announces the Discovery API, giving you programmatic access to product and pricing information across the AWS Marketplace catalog — including SaaS, AI agents and tools, AMI, containers, and machine learning models. With the Discovery API, buyers can embed catalog data into internal portals, enrich procurement tools with current pricing and offer terms, and streamline vendor evaluation workflows. Sellers and channel partners can surface product listings, public pricing, and private offer details directly within their own websites and storefronts — helping customers browse, compare, and move to purchase without leaving the partner experience. The API provides access to product descriptions, categories, pricing across public and private offers, and offer terms, so you can build experiences tailored to how your organization discovers and procures software through AWS Marketplace. The AWS Marketplace Discovery API is available in US East (N. Virginia), US West (Oregon), and Europe (Ireland). You can get started by configuring IAM permissions for your AWS account and calling the API through the AWS SDK. For more information, see the AWS Marketplace Discovery API Reference.

Amazon OpenSearch Serverless now supports Zstandard codecs for index storage, giving customers greater control over the trade-off between storage costs and query performance. With this launch, customers can configure Zstandard compression to achieve up to 32% reduction in index size compared to the default LZ4 codec, helping lower managed storage costs for data-intensive workloads. Customers running large-scale log analytics, observability pipelines, and time-series workloads on Amazon OpenSearch Serverless can benefit most from Zstandard compression where high data volumes make storage efficiency a significant cost driver. The Zstandard compression algorithm is available in two different modes in Amazon OpenSearch Serverless: zstd and zstd_no_dict. Customers can tune the compression level to balance their specific needs: lower levels (e.g., level 1) deliver meaningful storage savings with minimal impact on indexing throughput and query latency, while higher levels (e.g., level 6) maximize compression ratios at the cost of slower indexing speeds.  Zstandard codec support is available today in all AWS Regions where Amazon OpenSearch Serverless is supported. To get started, you can specify these codecs in your index settings at creation time. For more information, see the Amazon OpenSearch Serverless documentation.

AWS Private Certificate Authority (AWS Private CA) now supports customer managed permissions in AWS Resource Access Manager (AWS RAM). AWS Private CA lets you share certificate authorities (CAs) across accounts using AWS RAM so you can centralize your PKI instead of creating separate CAs in every account. With customer managed permissions, you can now select exactly which AWS Private CA API operations to allow when sharing a CA, granting only the specific operations each consuming account needs. Previously, you could only use AWS managed permissions, which provide predefined sets of actions and restrict cross-account issuers to specific certificate templates. Now you can select from read operations (e.g., DescribeCertificateAuthority, GetCertificate, and GetCertificateAuthorityCertificate) and write operations (e.g., IssueCertificate and RevokeCertificate) to tailor access for each consuming account or organizational unit. With customer managed permissions, cross-account issuers are not restricted to a specific certificate template. Customer managed permissions for AWS Private CA are available in all AWS Regions where AWS Private CA and AWS RAM are available. To learn more, see Customer managed permissions in RAM in the AWS Private CA User Guide and Creating and using customer managed permissions in the AWS RAM User Guide.

Starting today, Amazon EC2 Capacity Manager supports tag-based dimensions, enabling you to use tags from your EC2 resources to group and filter capacity metrics. EC2 Capacity Manager helps you monitor and optimize capacity usage across On-Demand Instances, Spot Instances, and Capacity Reservations. This launch also introduces Account Name as a new built-in dimension. You can activate up to five custom tag keys — such as environment, team, or cost-center — and use them alongside built-in dimensions like Region, Instance Type, and Availability Zone to group and filter capacity metrics by tag values in the console and APIs, and include tag data as additional columns in newly created S3 data exports. Capacity Manager also includes four Capacity Manager-provided tags by default: EC2 Auto Scaling group name, EKS cluster name, EKS Kubernetes node pool, and Karpenter node pool. The new Account Name dimension makes it easier to identify accounts when analyzing cross-account capacity data across your organization. This feature is available in all AWS Regions where EC2 Capacity Manager is available. To get started, navigate to the Settings tab in Capacity Manager and choose Manage tag keys, or use the AWS CLI. To learn more, see Managing monitored tag keys in the Amazon EC2 User Guide. For more information about Amazon EC2 Capacity Manager, visit the EC2 Capacity Manager documentation.

Starting today, domain name system (DNS) delegation for private hosted zone subdomains can be used with Route 53 inbound and outbound Resolver endpoints in AWS GovCloud (US) Regions. This allows you to delegate the authority for a subdomain from your on-premises infrastructure to the Route 53 Resolver cloud service and vice versa, enabling a simplified cloud experience across namespaces in AWS and on your own local infrastructure. Many AWS customers delegate subdomain management to individual teams while maintaining central control of apex domains. Previously, we launched Route 53 Resolver delegation support for private hosted zones in commercial AWS Regions, enabling customers to use standard name server records to delegate subdomain authority between Route 53 and on-premises DNS — eliminating the need for conditional forwarding rules across their organization. With today’s release, this delegation capability is now available for Route 53 Resolver endpoints in AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions as well. Inbound and outbound delegation is provided at no additional cost to Resolver endpoints usage. For more details on pricing, visit the Route 53 pricing page, and to learn more about this feature, visit the developer guide. 

Amazon SageMaker HyperPod task governance now supports gang scheduling, which ensures all pods required for a distributed training job are ready before training begins. Administrators can configure gang scheduling to prevent wasted compute from partial job runs and avoid deadlocks from jobs waiting for resources. Data scientists running distributed AI/ML training jobs on Amazon SageMaker HyperPod clusters using the EKS orchestrator require multiple pods to work together across nodes with pod-to-pod communication. When some pods start but others do not, jobs can hold onto resources without making progress, block other workloads, and increase costs. Gang scheduling resolves this by monitoring all pods in a workload and pulling the workload back if not all pods are ready within a set time. Pulled-back workloads are automatically requeued to prevent stalling. Administrators can adjust settings on the HyperPod Console, such as how long to wait for pods to be ready, how to handle node failures, whether to admit workloads one at a time to avoid deadlocks on busy clusters, and how retries are scheduled. This capability is currently available for Amazon SageMaker HyperPod clusters using the EKS orchestrator across the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Asia Pacific (Jakarta), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), Europe (Spain), and South America (São Paulo). To learn more, visit SageMaker HyperPod webpage, and HyperPod task governance documentation.

Amazon Interactive Video Service (Amazon IVS) Real-Time Streaming now supports redundant ingest, helping protect your live streams against source encoder failures and first-mile network issues. With redundant ingest, you can stream from two encoders simultaneously to a single stage with automated failover, ensuring uninterrupted delivery to your viewers. Redundant ingest is ideal for live events, 24/7 live streams, or any scenario where uninterrupted delivery is essential. This capability helps you maintain viewer engagement during unexpected disruptions and enables continuous 24/7 streaming.  Amazon IVS is a managed live streaming solution designed to make low-latency or real-time video available to viewers around the world. Visit the AWS region table for a full list of AWS Regions where the Amazon IVS console and APIs for control and creation of video streams are available. To learn more, please visit the Amazon IVS Real-Time Streaming RTMP ingest documentation page.

Amazon Elastic Kubernetes Service (Amazon EKS) managed node groups now support Auto Scaling warm pools, enabling you to maintain pre-initialized EC2 instances ready for rapid scale-out. This reduces node provisioning latency for applications with burst traffic patterns, time-sensitive workloads, or long instance boot times due to complex initialization scripts and software dependencies. With warm pools enabled, your EKS managed node group maintains a pool of instances that have already completed OS initialization, user data execution, and software configuration. When demand increases and the Auto Scaling group scales out, instances transition from the warm pool to active service without repeating the full cold-start sequence. You can configure instances in the warm pool as Stopped (lower cost, longer transition) or Running (higher cost, faster transition). You can also enable reuse on scale-in, which returns instances to the warm pool during scale-down instead of terminating them. Warm pools work with Cluster Autoscaler without requiring any additional configuration. You can enable warm pools through the EKS API, AWS CLI, AWS Management Console, or AWS CloudFormation by adding a warmPoolConfig to your CreateNodegroup or UpdateNodegroupConfig requests. Existing managed node groups that do not enable warm pools are unaffected. This feature is available in all AWS Regions where Amazon EKS is available, except for the China (Beijing) Region, operated by Sinnet and the China (Ningxia) Region, operated by NWCD. To get started, see the Amazon EKS managed node groups documentation.

Amazon Bedrock AgentCore Browser now supports OS-level interaction capabilities, enabling automation of browser workflows that require direct operating system control beyond Chrome DevTools Protocol (CDP) capabilities. This enhancement addresses automation scenarios where CDP alone is insufficient, such as mouse operations, print dialogs, native system alerts, and keyboard shortcuts. The feature serves AI agent developers, test automation engineers, and organizations building LLM-powered web interaction tools. The new capabilities provide automation through mouse operations (click, move, drag, scroll), keyboard operations (type, press, shortcuts like ctrl+a and ctrl+p), and full desktop screenshots, all at OS-level coordinates extending beyond the browser viewport. Key use cases include automated testing with system dialog handling, document management workflows, complex UI interactions with right-click menus, and vision-based AI agents that require complete browser environment visibility. This feature is available by default on all browser instances in all 14 AWS Regions where Amazon Bedrock AgentCore Browser is available: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Canada (Central). To learn more, visit the AgentCore Browser documentation. 

Amazon WorkSpaces Advisor is a new AI-powered tool that helps administrators quickly troubleshoot and resolve issues with Amazon WorkSpaces Personal. Using generative AI capabilities, it analyzes WorkSpace configurations, identifies problems, and provides actionable recommendations to restore service and optimize performance. WorkSpaces Advisor streamlines administrative workflows by reducing the time needed to investigate and fix common issues. Administrators can leverage AI-driven insights to proactively maintain their virtual desktop infrastructure, improve end-user experience, and minimize downtime across their WorkSpaces. Amazon WorkSpaces Advisor is now available in all AWS commercial regions where Amazon WorkSpaces is offered. Visit the Amazon WorkSpaces console to access WorkSpaces Advisor and begin troubleshooting your environment. Learn more in the feature blog and user guide.

Amazon OpenSearch Service now supports i8ge instances, which is the latest generation of storage optimized instances offering the best performance for storage-intensive workloads. Powered by AWS Graviton4 processors, I8ge instances deliver up to 60% better compute performance compared to previous generation Graviton2-based storage optimized Im4gn instances. I8ge instances use the latest third generation AWS Nitro SSDs, local NVMe storage that deliver up to 55% better real-time storage performance per TB while offering up to 60% lower storage I/O latency and up to 75% lower storage I/O latency variability compared to previous generation Im4gn instances. Built on the AWS Nitro System, these instances offload CPU virtualization, storage, and networking functions to dedicated hardware and software enhancing the performance and security for your workloads. I8ge instances are available of sizes up to 18xlarge and 45 TB instance storage. At 112.5 Gbps, these instances have the highest networking bandwidth among storage optimized instances available in Amazon OpenSearch Service. I8ge instances support all OpenSearch versions & Elasticsearch (open source) versions 7.9 and 7.10. Amazon OpenSearch Service supports i8ge instances in following AWS Regions : US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm), Asia Pacific (Malaysia), Asia Pacific (Mumbai), Asia Pacific (Singapore) and Asia Pacific (Sydney). For region specific availability & pricing, visit our pricing page. To learn more about Amazon OpenSearch Service and its capabilities, visit our product page.

Oracle Database@AWS is now generally available in five additional AWS Regions: EU-West-1 (Dublin), EU-West-2 (London), AP-South-1 (Mumbai), AP-South-2 (Hyderabad), and AP-Northeast-2 (Seoul). Oracle Database@AWS enables customers to access Oracle Cloud Infrastructure (OCI) managed Oracle Exadata systems within AWS data centers. With this launch, customers in Europe and Asia Pacific with in-region data residency requirements can migrate on-premises Oracle Exadata and Oracle Real Application Clusters (RAC) applications to AWS. Dublin, Mumbai, and Hyderabad are available with two Availability Zones (AZs), while London and Seoul are available with one Availability Zone. Additionally, CA-Central-1 (Canada Central) and AP-Southeast-2 (Sydney) now support two Availability Zones, providing enhanced high availability for production workloads. With this expansion, Oracle Database@AWS services are now available in twelve Regions: US-East-1 (N. Virginia), US-West-2 (Oregon), US-East-2 (Ohio), CA-Central-1 (Canada Central), EU-Central-1 (Frankfurt), EU-West-1 (Dublin), EU-West-2 (London), AP-Northeast-1 (Tokyo), AP-Southeast-2 (Sydney), AP-South-1 (Mumbai), AP-South-2 (Hyderabad), and AP-Northeast-2 (Seoul). To use Oracle Database@AWS services, request a private offer from Oracle through the AWS Marketplace, and use AWS Management Console to setup and use your databases. To learn more, visit Oracle Database@AWS overview and documentation.

AWS Lambda response streaming is now available in all commercial AWS Regions, bringing full regional parity for this capability. Customers in newly supported Regions can use the InvokeWithResponseStream API to progressively stream response payloads back to clients as data becomes available. Response streaming enables functions to send partial responses to clients incrementally rather than buffering the entire response before transmission. This reduces time-to-first-byte (TTFB) latency and is well suited for latency-sensitive workloads such as LLM-based applications as well as web and mobile applications where users benefit from seeing responses appear incrementally. Response streaming supports payloads up to a default maximum of 200 MB. With this expansion, customers in all commercial Regions can stream responses using the InvokeWithResponseStream API through a supported AWS SDK, or through Amazon API Gateway REST APIs with response streaming enabled. Response streaming supports Node.js managed runtimes as well as custom runtimes. Streaming responses incur an additional cost for network transfer of the response payload. You are billed based on the number of bytes generated and streamed out of your Lambda function over the first 6 MB. To get started with Lambda response streaming, visit the AWS Lambda documentation. 

AWS Cost Explorer now brings Amazon Q Developer’s generative AI capabilities directly into your cost analysis workflows. You can now use natural language queries to ask Amazon Q questions about your AWS cost and usage data. In addition to providing answers to your question, you now also receive automatically updated visualizations in Cost Explorer. This enables faster cost analysis, reduces time to insights, and makes cost visibility accessible to every team member. With this launch, you can start your cost analysis with the new suggested prompts in Cost Explorer. These prompts include commonly asked cost questions like “Show me my top spending services for this month.” Amazon Q provides detailed insights while Cost Explorer simultaneously updates with the corresponding visualization, filters, and groupings. You can also ask custom questions in your own words using the new ‘Ask Question’ button, exploring your spending patterns conversationally. Cost Explorer automatically updates charts and tables when analysis is based on your cost and usage data. When Amazon Q compiles insights from additional datasets such as pricing or anomaly detection, visualizations are displayed in Amazon Q’s new artifacts panel. You can continue the conversation with follow-up questions while maintaining full context, allowing you to go from a quick cost check to a deep investigation without switching tools or breaking your workflow. Natural language cost analysis for AWS Cost Explorer is available today in all commercial AWS Regions at no additional charge. To learn more, visit AWS Cost Explorer. To get started, see the user guide.

Starting today, Amazon Lightsail is available in the Asia Pacific (Malaysia) Region. This expansion brings the power and simplicity of Lightsail to customers in Malaysia and surrounding regions. With this launch, customers in Malaysia and nearby countries can now enjoy lower latency and better performance for their applications while meeting local data residency requirements. The new Region provides access to Lightsail’s full range of features including instances that meet your compute needs—from general purpose to compute-optimized and memory-optimized bundles—as well as managed databases, containers, load balancers and more, all with the same simple, predictable pricing that Lightsail customers love. Lightsail is available in these AWS Regions: US East (Ohio, N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt, Ireland, London, Paris, Stockholm), Asia Pacific (Malaysia, Jakarta, Mumbai, Seoul, Singapore, Sydney, Tokyo). To learn more about Regions and Availability Zones for Lightsail, please refer to the documentation. You can use this Region through the Lightsail Console, AWS Command Line Interface (CLI) and AWS SDKs.

Amazon SageMaker Unified Studio now supports Serverless Workflows in Identity Center domains.  With this launch, customers using Identity Center domains can orchestrate data processing tasks with Apache Airflow (powered by Managed Workflows for Apache Airflow) without provisioning or managing Airflow infrastructure. Serverless Workflows were previously available only in IAM-based domains.  Serverless Workflows automatically provision compute resources when a workflow runs and release them when it completes, so you only pay for actual workflow run time. Each workflow runs with its own execution role and isolated worker, providing workflow-level security and preventing cross-workflow interference. With Serverless Workflows, Identity Center domain customers also get access to the Visual Workflow experience with support for around 200 operators, including built-in integration with AWS services such as Amazon S3, Amazon Redshift, Amazon EMR, AWS Glue, and Amazon SageMaker AI. Serverless Workflows in Identity Center domains are available in all AWS Regions where SageMaker Unified Studio is supported. To learn more, visit the Serverless Workflows documentation.

Amazon Bedrock, the platform for building generative AI applications and agents at production scale, now offers Claude Mythos Preview in gated research preview as part of Project Glasswing. Claude Mythos Preview is Anthropic’s most advanced AI model to date, representing a fundamentally new model class with state-of-the-art capabilities across cybersecurity, software coding, and complex reasoning tasks. The model can identify sophisticated security vulnerabilities in software and demonstrate exploitability, comprehending large codebases and delivering actionable findings with less manual guidance than previous AI models. This enables security teams to accelerate defensive cybersecurity work, find and fix security vulnerabilities in the world’s most critical software, and address these issues before threats emerge. Claude Mythos Preview signals an upcoming wave of AI models with powerful cybersecurity capabilities. Anthropic and AWS are taking a deliberately cautious approach to release, prioritizing internet-critical companies and open-source maintainers whose software and digital services impact hundreds of millions of users. This approach gives defenders the opportunity to strengthen their codebases and share what they learn so the whole industry can benefit. Claude Mythos Preview is available in gated preview in the US East (N. Virginia) Region through Amazon Bedrock. Access is limited to an initial allow-list of organizations. If your organization has been allow-listed, your AWS account team will reach out directly. For AWS CISO Amy Herzog’s perspective on this launch and what it means for the future of cybersecurity, read Building AI Defenses at Scale: Before the Threats Emerge.

S3 Files delivers a shared file system that connects any AWS compute resource directly with your data in Amazon S3. With S3 Files, Amazon S3 is the first and only cloud object store that provides fully-featured, high-performance file system access to your data. It provides full file system semantics and low-latency performance, without your data ever leaving S3. That means file-based applications, agents, and teams can now access and work with your S3 data as a file system using the tools they already depend on. Built using Amazon EFS, S3 Files gives you the performance and simplicity of a file system with the scalability, durability, and cost-effectiveness of S3. You no longer need to duplicate your data or cycle it between object storage and file system storage. S3 Files maintains a view of the objects in your bucket and intelligently translates your file system operations into efficient S3 requests on your behalf. Your file-based applications run on your S3 data with no code changes, AI agents persist memory and share state across pipelines, and ML teams run data preparation workloads without duplicating or staging files first. Now, file-based tools and applications across your organization can work with your S3 data directly from any compute instance, container, and function using the tools your teams and agents already depend on.    Organizations store their analytics data and data lakes in S3, but file-based tools, agents, and applications have never been able to directly work with that data. Bridging that gap meant managing a separate file system, duplicating data, and building complex pipelines to keep object and file storage in sync. S3 Files eliminates that friction and overhead. Using S3 Files, your data is accessible through the file system and directly through S3 APIs at the same time. Thousands of compute resources can connect to the same S3 file system simultaneously, enabling shared access across clusters without duplicating data. S3 Files works with all of your new and existing data in S3 buckets, with no migration required.    S3 Files caches actively used data for low-latency access and provides up to multiple terabytes per second of aggregate read throughput, so storage never limits performance. There are no data silos, no synchronization complexities, and no tradeoffs. File and object storage, together in one place without compromise. S3 Files is now generally available in 34 AWS Regions. For the full list of supported Regions, visit the AWS Capabilities tool. To learn more, visit the product page, S3 pricing page, documentation, and AWS News Blog.

Amazon RDS for Oracle now supports M8i and R8i instances. These instances are powered by custom Intel Xeon 6 processors, available only on AWS, delivering the highest performance and fastest memory bandwidth among comparable Intel processors in the cloud. The M8i and R8i instances offer up to 15% better price-performance, and 2.5x more memory bandwidth compared to previous generation Intel-based instances. M8i and R8i instances are available for Amazon RDS for Oracle in Bring Your Own License model for Oracle Database Enterprise Edition (EE) and Oracle Database Standard Edition 2 (SE2) . To use the new M8i and R8i instances, you can modify your existing RDS database instance or create a new RDS database instance from the RDS Management Console, or using the AWS SDK or CLI. See Amazon RDS for Oracle Pricing for up-to-date pricing and regional availability.

Amazon Braket, the quantum computing service from AWS, now offers access to Rigetti’s Cepheus-1-108Q device, the first 100+ qubit superconducting quantum processing unit (QPU) available on Amazon Braket. Cepheus-1-108Q uses Rigetti’s modular multi-chip architecture, consisting of a 3×4 array of twelve 9-qubit chiplets with tunable couplers and intermodule couplers between chiplets. Cepheus-1-108Q introduces CZ (controlled phase) gates, replacing the iSWAP gates used on previous Rigetti QPUs. CZ gates provide higher resilience to phase errors common in superconducting systems, and Rigetti’s adiabatic CZ implementation further reduces leakage errors. These improvements enable customers to run deeper circuits for use cases such as chemical simulation, combinatorial optimization, and machine learning. Customers can build and run quantum programs using the Braket SDK or other frameworks such as Qiskit, CUDA-Q, and Pennylane. Pulse-level control is also available for researchers who need low-level hardware access to study noise, develop gates, or devise error mitigation schemes. Cepheus-1-108Q is available in the US West (N. California) Region. Get started by viewing the device on the Amazon Braket Management Console, reading our Amazon Braket documentation, or applying for AWS credits to support experiments on Amazon Braket through the AWS Cloud Credits for Research program.

Amazon Aurora PostgreSQL-Compatible Edition now supports PostgreSQL versions 17.9, 16.13, 15.17, and 14.22 that includes bug fixes from the PostgreSQL community and Aurora-specific enhancements. We recommend upgrading to the latest minor versions to address known security vulnerabilities and benefit from these improvements, as detailed in these release notes. You can upgrade your databases during scheduled maintenance windows using automatic minor version upgrades. To simplify operations at scale, enable automatic minor version upgrades and use the AWS Organizations Upgrade Rollout Policy to orchestrate thousands of upgrades in phases, first to development environments before upgrading production systems. You can also use Aurora’s zero-downtime patching to minimize downtime for minor version upgrades. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full PostgreSQL compatibility. It provides scale-to-zero serverless compute, Aurora Global Database for multi-Region resilience, Aurora I/O-Optimized for improved price performance on I/O-intensive workloads, and built-in security and continuous backups. To get started, take a look at our getting started page.

AWS Transfer Family announces Internet Protocol version 6 (IPv6) support for SFTP connectors, AS2 connectors, and Transfer Family web apps. This enhancement enables your connectors to reach remote servers and trading partners over IPv6 and allows end users to access Transfer Family web apps using IPv6. AWS Transfer Family offers fully managed support for file transfers over SFTP, AS2, FTPS, FTP, and web browser-based transfers. With IPv6 support for connectors, you can now reach trading partners and remote servers that have adopted IPv6, eliminating connectivity barriers as partners transition away from IPv4. For Transfer Family web apps, IPv6 support enables end users to upload and download files from IPv6-native networks and devices. With dual-stack support across both connectors and web apps, you can communicate with both IPv4 and IPv6 systems and transition at your own pace. AWS Transfer Family IPv6 support for SFTP connectors, AS2 connectors, and web apps is available in the majority of AWS regions where AWS Transfer Family is offered. For the full list of supported regions, visit the AWS Capabilities tool in Builder Center. To learn more, visit the Transfer Family User Guide.

AWS Certificate Manager (ACM) now provides a search bar in the console that customers can use to find certificates using one or more certificate parameters such as domain name, certificate ARN, and/or certificate validity. For example, ACM users who manages multiple certificates can search for certificates with specific domains that are due to expire soon. To get started, use the new SearchCertificates API, or navigate to the ACM console and use the search bar to search by one or more certificate parameters. This feature is available in all Public AWS, AWS China, and AWS GovCloud regions. To learn more about this feature, please refer to Search Certificates. You can learn more about ACM and get started here.