7/1/2025, 12:00:00 AM ~ 7/2/2025, 12:00:00 AM (UTC)

Recent Announcements

AWS Clean Rooms supports incremental and distributed training for custom modeling

AWS Clean Rooms now supports two enhancements to its machine learning capabilities that help you train models more efficiently and at scale to generate predictive insights in a Clean Rooms collaboration. Incremental training enables you to build upon existing model artifacts to create new models, and distributed training allows you to train models across multiple compute instances simultaneously. These capabilities help data scientists and ML practitioners accelerate data collaboration and analysis while maintaining the privacy of the training datasets.\n With AWS Clean Rooms ML custom modeling, you and your partners can train and run inference on a custom ML model using collective datasets at scale without having to share sensitive intellectual property. With incremental training, you can leverage previously trained models to create new variants using expanded datasets, significantly reducing training time and compute resources. Additionally, distributed training lets you process large-scale datasets efficiently by distributing the training workload across multiple instances. AWS Clean Rooms ML helps you and your partners apply privacy-enhancing controls to safeguard your proprietary data and ML models while generating predictive insights—all without sharing or copying one another’s raw data or models. For more information about the AWS Regions where AWS Clean Rooms ML is available, see the AWS Regions table. To learn more, visit AWS Clean Rooms ML.

AWS re:Post Private launches channels for targeted and secure organizational collaboration

Today, AWS re:Post Private announces the launch of channels, designed to enhance collaborative knowledge sharing within companies. Channels allow companies to create secure, dedicated private spaces within their re:Post Private environment, tailored to specific teams, projects, or topics. With channels, companies invite relevant users to collaboratively solve problems and build a team-specific knowledge base. Teams can collaborate on specific topics without exposing content to the entire community in their company. Companies can manage access to channels using Identity and Access Management (IAM) Identity Center groups with centralized access management.\n Channels on re:Post Private are ideal for scenarios where companies need to create dedicated, topic-specific spaces for various business functions, such as legal departments or confidential projects. This feature is also valuable for companies supporting multiple agencies or clients, allowing them to establish separate, secure environments for each entity’s cloud requirements. The applicability of channels spans across industries, with notable benefits for the public sector and financial services, where discussing sensitive information within a secure, permission-controlled group is paramount. By leveraging channels, companies can ensure that confidential discussions and collaborative efforts remain contained within the appropriate teams, enhancing both security and efficiency in knowledge sharing. Channels are available to all re:Post Private customers globally. To get started with re:Post Private channels, visit re:Post Private page to learn more or speak with your AWS account team to request a demo.

AWS HealthImaging launches support for DICOMweb STOW-RS data imports

AWS HealthImaging announces support for storing DICOM P10 files to HealthImaging via the DICOMweb STOW-RS protocol. Now it’s easier than ever to import your medical imaging data to HealthImaging.\n This launch offers a synchronous data import action that is ideal for latency sensitive workflows, such as storing new medical imaging studies, annotations, and reports. With HealthImaging STOW-RS, you can import up to 1 GB of DICOM data per action. With this launch, AWS HealthImaging offers DICOMweb APIs for data import, search, and retrievals, which simplifies integrating HealthImaging with existing DICOMweb enabled applications. AWS HealthImaging is generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). AWS HealthImaging is a HIPAA-eligible service that empowers healthcare providers, life sciences researchers, and their software partners to store, analyze, and share medical images at petabyte scale. To learn more, see the AWS HealthImaging Developer Guide.

Amazon SageMaker Catalog adds AI recommendations for descriptions of custom assets

Amazon SageMaker Catalog, part of the next generation of Amazon SageMaker, now supports AI recommendations for descriptions—including table summaries, use cases, and column-level descriptions—for custom structured assets registered programmatically. This applies to a wide range of assets, for example, Iceberg tables in Amazon S3, or datasets from third-party and internal applications.\n Building on existing automated metadata capabilities for harvested assets from native services like AWS Glue and Amazon Redshift, this enhancement enables users to generate business-friendly descriptions for custom assets using large language models (LLMs) via Amazon Bedrock. With just a few clicks, users can trigger AI-generated suggestions, review and refine descriptions, and publish enriched asset metadata directly to the catalog. This helps reduce manual documentation effort, improves metadata consistency, and accelerates asset discoverability across organizations. Learn more about how to generate automated metadata for custom assets in our product documentation.

AWS announces new AWS Data Transfer Terminal location in Munich

Today, AWS announces the opening of a new AWS Data Transfer Terminal location within Equinix MU1 in Munich, Germany. This marks AWS’s first Data Transfer Terminal outside the United States and its debut in Europe. Data Transfer Terminal is a secure, physical location where you can bring your storage devices and upload data to AWS including Amazon Simple Storage Service (Amazon S3), Amazon Elastic File System (Amazon EFS), and others using a high throughput network connection.\n Data Transfer Terminals are ideal for customers who need to transfer large amounts of data to the AWS quickly and securely. Common use cases span various industries and applications, including training data for Advanced Driver Assistance Systems (ADAS) in the automotive industry, video production data for processing in the media and entertainment industry, migrating legacy data in the financial services industry, and uploading equipment sensor data in the industrial and agricultural sectors. Once uploaded, you can immediately leverage AWS services like Amazon Athena for analysis, Amazon SageMaker for machine learning, or Amazon Elastic Compute Cloud (Amazon EC2) for application development – reducing data processing time from weeks to minutes. To learn more, visit the Data Transfer Terminal product page and documentation. To get started, make a reservation at your nearby Data Transfer Terminal in the AWS Console.

AWS announces availability of ECS Optimized Windows Server 2025 AMIs

Amazon Web Services (AWS) has introduced Amazon ECS Optimized Windows AMIs compatible with Windows Server 2025, offering two distinct platforms: 2025-Core and 2025-Full. These AMIs are specifically engineered to support Windows container deployments on Amazon ECS. Each AMI comes ready-to-use with essential components and optimizations tailored for running containerized workloads, streamlining the container deployment process.\n Windows Server 2025 provides enhanced performance optimization and improved resource utilization compared to previous versions, allowing for more efficient container operations. It features advanced security capabilities, including better isolation between containers to prevent container escape attacks and stronger kernel boundaries between containers and host. Windows Server 2025 also introduces enhanced networking capabilities like network namespace isolation and better integration with the Host Netwroking Service (HNS) that enable faster container communication and reduced latency. Customers can find and launch Windows ECS instances directly from the Amazon EC2 Console or through API or CLI commands. Windows ECS Optimized AMIs can be run with all available pricing options for windows ECS instances and are enabled across all Public, AWS GovCloud (US) and China Regions of AWS. For more details on getting the best out of AWS EC2 instances running Windows Server 2025 check out the Windows on AWS page and the guide on AWS Windows ECS AMIs.

Amazon Q in Connect now supports 7 languages for proactive recommendations

Amazon Q in Connect, a generative AI-powered assistant for customer service, now supports 6 additional languages for offering proactive recommendations for customer service agents to resolve issues quickly and accurately.\n Amazon Q in Connect detects customer intent during voice and chat interactions in Spanish, French, Portuguese, Mandarin, Japanese, and Korean, in addition to English. Amazon Q in Connect can also support end-customer self-service interactions across Interactive Voice Response (IVR) and digital channels in 26 languages. For the full list of supported languages, please see the Languages supported by Amazon Connect features. For region availability, please see the availability of Amazon Connect features by Region. To learn more about Amazon Q in Connect, please visit the website or see the help documentation.

AWS Transform now analyzes EBS costs, .NET complexity and expands chat guidance

Today, AWS Transform introduced three enhancements to help you better assess and plan your migration and modernization journey. These new features include enhanced assessments to analyze EBS cost, .NET agent to analyze code complexity, and an expanded interactive chat interface for .NET modernization guidance.\n First, AWS Transform assessments now includes Amazon Elastic Block Storage (EBS) cost analysis, enabling you to better understand and plan for storage costs in your migration initiatives. This enhancement helps you make more informed decisions about resource allocation and budget planning for your transformation projects. Second, AWS Transform for .NET now supports enhanced code assessment capabilities that help you accelerate modernization planning with greater confidence, efficiency, and time savings. You can view repository transformation complexity, receive transformation group recommendations, and view transformation assessment reports with natural language summaries, all within a single, unified experience. Finally, AWS Transform now expands chat capability to provide an interactive chat experience that allows you to query specific aspects of your assessment and .NET transformation progress in natural language. You can quickly access relevant information about your modernization journey, get clarification on recommendations, and receive contextual guidance for specific use cases. These new features are now available in the following AWS Regions: US East (N. Virginia) and Europe (Frankfurt). To learn more, visit the AWS Transform user guide and the frequently asked questions page.

Amazon Aurora now supports PostgreSQL 17.5, 16.9, 15.13, 14.18, and 13.21

Amazon Aurora PostgreSQL-Compatible Edition has added support for PostgreSQL versions 17.5, 16.9, 15.13, 14.18, and 13.21. The update includes PostgreSQL community’s product improvements and bug fixes, while introducing Aurora-specific enhancements: read replica optimizations to reduce downtime during cluster upgrades, new features for Babelfish, and security improvements.\n To use the new version, create a new Aurora PostgreSQL-compatible database with just a few clicks in the Amazon RDS Management Console. You can also upgrade your existing database . Please review the Aurora documentation to learn more about upgrading. Refer to the Aurora version policy to help you to decide how often to upgrade and how to plan your upgrade process. These releases are available in all commercial AWS Regions and the AWS GovCloud (US) Regions. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full MySQL and PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.

Amazon CloudWatch PutMetricData API now supports AWS CloudTrail data event logging

Amazon CloudWatch now supports AWS CloudTrail data event logging for the PutMetricData, GetMetricStatistics and ListMetrics APIs. With this launch, customers have full visibility into metric ingestion and egress activity to their AWS account for best practices in security, operational troubleshooting, and financial management.\n CloudTrail captures API activities related to Amazon CloudWatch PutMetricData and other metrics APIs as events. Using the information that CloudTrail collects, you can identify a specific request to any of the CloudWatch metric APIs, the IP address of the requester, the requester’s identity, and the date and time of the request. Logging CloudWatch PutMetricData and other metrics APIs using CloudTrail helps you enable operational and risk auditing, governance, and compliance of your AWS account. AWS CloudTrail logging for the PutMetricData, GetMetricStatistic and ListMetrics API actions is now available in all AWS Regions, including the AWS GovCloud (US) Regions. Data logging incurs charges according to AWS CloudTrail Pricing. To learn more about this feature, visit the Amazon CloudWatch documentation page. To enable logging for Amazon CloudWatch metrics data events, using the AWS CloudTrail Management Console, specify CloudWatch metric as the data event type, then choose the APIs that you want to monitor.

Amazon CloudFront announces support for HTTPS DNS records

Today, Amazon CloudFront announces support for HTTPS resource records in Amazon Route 53.HTTPS resource records allow domain name systems (DNS) such as Amazon Route 53 to provide additional information such as supported HTTP protocol versions and port numbers before the HTTP connection is attempted. This helps clients establish the initial connection using their preferred HTTP protocol to improve application performance and security.\n By using the HTTPS DNS records during DNS lookup, clients can discover the CloudFront capabilities that boost application performance and security. For example, clients can identify if HTTP/3 is enabled on the CloudFront distribution, without the need for additional round-trips (RTT) to negotiate HTTP protocols after the DNS lookup. This can reduce application load times, especially in regions with limited network infrastructure. By providing secure connection information upfront, HTTPS DNS records streamline the process of establishing secure connections to CloudFront distributions. Additionally, customers using Route 53 can benefit from free HTTPS record queries when using CloudFront alias records, reducing DNS costs. HTTPS DNS records are supported from all edge locations. This excludes Amazon Web Services China (Beijing) region, operated by Sinnet, and the Amazon Web Services China (Ningxia) region, operated by NWCD. To learn more about implementing this feature and its benefits, read our detailed blog post.

Amazon Connect Contact Lens is now available in AWS GovCloud (US-West)

Amazon Connect Contact Lens is now available in AWS GovCloud (US-West). Amazon Connect Contact Lens helps you to monitor, measure, and continuously improve contact quality and agent performance for a better overall customer experience. With Contact Lens conversational analytics, you can transcribe customer calls, analyze customer sentiment, discover top contact drivers, help redact sensitive data, and more, all natively within Amazon Connect. With Contact Lens performance evaluations, you can define custom evaluation criteria, evaluate up to 100% of agents’ contacts using insights from conversational analytics, and get aggregated insights to improve agent performance.\n With this launch, Contact Lens is available in all AWS regions where Amazon Connect operates. To learn more, please visit our documentation, our webpage, and pricing page. You can purchase Contact Lens along with other Amazon Connect AI capabilities through simplified channel-based pricing (e.g. by voice, by chat, by messaging).

Amazon Aurora MySQL and Amazon RDS for MySQL integration with Amazon SageMaker is now available

On June 30, 2025, AWS announced that Amazon Aurora MySQL-Compatible Edition and Amazon RDS for MySQL now support zero-ETL integration with Amazon SageMaker, enabling near real-time data availability for analytics workloads. This integration automatically extracts and loads data from MySQL tables into your lakehouse where it’s immediately accessible through various analytics engines and machine learning tools. The data synced into the lakehouse is compatible with Apache Iceberg open standards, enabling you to use your preferred analytics tools and query engines such as SQL, Apache Spark, BI, and AI/ML tools.\n Through a simple no-code interface, you can create and maintain an up-to-date replica of your MySQL data in your lakehouse without impacting production workloads. The integration features comprehensive, fine-grained access controls that are consistently enforced across all analytics tools and engines, ensuring secure data sharing throughout your organization. As a complement to the existing zero-ETL integrations with Amazon Redshift, this solution reduces operational complexity while enabling you to derive immediate insights from your operational data. Amazon Aurora MySQL and Amazon RDS for MySQL zero-ETL integration with Amazon SageMaker is now available in the US East (N. Virginia), US East (Ohio), US West (Oregon), Canada (Central), South America (Sao Paulo), Asia Pacific (Hong Kong), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), Europe (Frankfurt), Europe (Ireland), Europe (London), and Europe (Stockholm) AWS Regions. To learn more, visit What is zero-ETL. To begin using this new integration, visit the zero-ETL documentation for your database service: Aurora MySQL or RDS for MySQL.

Amazon Relational Database Service Custom (Amazon RDS Custom) for Oracle now supports Multi-AZ deployments

Amazon RDS Custom for Oracle now supports Multi-AZ deployments, providing high availability for business critical workloads. Amazon RDS Custom for Oracle is a managed service for running Oracle databases on AWS, with ability to customize the database environment and underlying operating system. With Multi-AZ deployments, RDS Custom for Oracle synchronously replicates data between two Availability Zones, and performs an automatic failover in case the primary database instance becomes unavailable so that customers benefit from higher availability.\n To set up an RDS Custom for Oracle database instance with Multi-AZ deployment, customers can specify their configuration when they create their database instance. RDS Custom automatically provisions primary and standby database instances in the different availability zones, and synchronously replicates data to the standby instance. If the primary database instance becomes unavailable, RDS Custom automatically fails over to the standby instance without any manual intervention. To learn more about Multi-AZ deployments, see Amazon RDS Custom for Oracle user guide. Multi-AZ deployment option is available in all AWS regions where RDS Custom for Oracle is available. For pricing details, refer to the RDS Custom for Oracle pricing page.

Amazon SageMaker Catalog adds AI recommendations for descriptions of custom assets

Amazon SageMaker Catalog, part of the next generation of Amazon SageMaker, now supports AI recommendations for descriptions—including table summaries, use cases, and column-level descriptions—for custom structured assets registered programmatically. This applies to a wide range of assets, for example, Iceberg tables in Amazon S3, or datasets from third-party and internal applications.\n Building on existing automated metadata capabilities for harvested assets from native services like AWS Glue and Amazon Redshift, this enhancement enables users to generate business-friendly descriptions for custom assets using large language models (LLMs) via Amazon Bedrock. With just a few clicks, users can trigger AI-generated suggestions, review and refine descriptions, and publish enriched asset metadata directly to the catalog. This helps reduce manual documentation effort, improves metadata consistency, and accelerates asset discoverability across organizations. Learn more about how to generate automated metadata for custom assets in our product documentation.

Amazon Connect launches segment creation from imported files

Amazon Connect Customer Profiles now enables organizations to create customer segments from imported CSV files. This new capability allows contact center managers and campaign managers to upload predefined customer lists, streamlining the creation of targeted segments for personalized engagement strategies.\n With this new feature, users can efficiently map CSV data to standard profile attributes powered by generative AI that automatically analyzes and organizes data from different formats, or create custom attributes as needed. The feature includes configurable profile expiry settings that allow organizations to set data retention periods of up to 90 days to maintain data quality and comply with governance requirements. When importing customer data, Customer Profiles utilize unique identifiers (such as customer IDs, email addresses, or phone numbers) to match and update existing profiles when possible, preventing duplicate records and ensuring customer information remains consolidated and current. Customers can now leverage these imported segments to drive multichannel outbound campaigns via SMS, phone calls, and email communications. Segment creation from imported files is available in US East (N. Virginia), US West (Oregon), Africa (Cape Town), Asia Pacific (Seoul), Asia Pacific (Tokyo), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central), Europe (Frankfurt) and Europe (London) AWS regions. To learn more, visit the Amazon Connect Customer Profiles webpage or see the Amazon Connect Customer Profiles documentation page.

Amazon Inspector now available in additional AWS Regions

Amazon Inspector is now available in Asia Pacific (Thailand), Middle East (UAE), Asia Pacific (Hyderabad), Asia Pacific (Malaysia), Asia Pacific (Melbourne), Mexico (Central), Israel (Tel Aviv), Canada West (Calgary), and Europe (Spain). Amazon Inspector is a vulnerability management service that continually scans AWS workloads including Amazon EC2 instances, container images, and AWS Lambda functions for software vulnerabilities and unintended network exposure across your AWS organization.\n With this expansion, Amazon Inspector extends its security coverage to these regions, designed to help customers automatically discover workloads, conduct continuous vulnerability assessments, and receive actionable security findings. The service is designed to detect newly launched Amazon EC2 instances, Lambda functions, and eligible container images pushed to Amazon ECR and scan them for software vulnerabilities and unintended network exposure. All accounts new to Amazon Inspector are eligible for a 15-day free trial to evaluate the service and estimate its cost. During the trial, all eligible Amazon EC2 instances, AWS Lambda functions, and container images pushed to Amazon ECR are continually scanned at no cost. After the trial period, you will be charged based on the number of scanned resources. Visit the Amazon Inspector pricing page for more details. To get started with Amazon Inspector visit our documentation or begin your free trial today.

AWS HealthImaging now supports DICOMweb BulkData

AWS HealthImaging announces support for DICOM BulkData to ensure consistent, low latency metadata retrievals. With this launch, DICOM metadata retrieved via DICOMweb WADO-RS actions will have large data elements substituted with BulkDataURIs.\n Medical imaging workflows demand low latency, and retrieving DICOM metadata is often a first step. Large DICOM data elements, such as private attributes and ICC profiles, can increase the size of metadata payloads, potentially slowing down retrieval and processing. With this launch, HealthImaging automatically replaces DICOM data elements over 1 MB in size with in-line BulkDataURIs, in accordance with the DICOMweb standard. Now users can retrieve compact DICOM metadata payloads with low latency, with flexibility to download large data elements through a standards-conformant API. AWS HealthImaging is generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). AWS HealthImaging is a HIPAA-eligible service that empowers healthcare providers, life sciences researchers, and their software partners to store, analyze, and share medical images at petabyte scale. To learn more, see the AWS HealthImaging Developer Guide.

Amazon Connect forecasting, capacity planning, and scheduling is now available in AWS GovCloud (US-West)

Amazon Connect forecasting, capacity planning, and scheduling is now available in AWS GovCloud (US-West). This feature helps you predict contact volumes, allocate agents efficiently, and ensure optimal agent scheduling to meet operational goals while minimizing overstaffing. Using machine learning, it anticipates contact volume and arrival rates, converts forecasts into staffing projections, and assigns daily shifts accordingly. By optimizing operations and helping meet service level goals, Amazon Connect forecasting, capacity planning, and scheduling helps businesses improve both agent productivity and customer satisfaction.\n To learn more, please visit our documentation, our webpage, and pricing page. You can purchase Amazon Connect forecasting, capacity planning, and scheduling along with other Amazon Connect AI capabilities through simplified channel-based pricing (e.g. by voice, by chat, by messaging).

Amazon Connect now provides enhancements to audio treatment while customers wait in queue

Amazon Connect now provides the ability to execute logic such as routing priority changes within a flow while continuing to play audio to customers waiting in queue. For example, when a customer is in queue listening to music or instructions, you can now periodically check metrics to determine whether to transfer them to a different queue or conditionally offer a callback, without having the check itself cause any interruption to the music.\n This enhancement to the Loop prompts block is available in all AWS regions where Amazon Connect is offered. To learn more about this feature, see the Amazon Connect Administrator Guide. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website.

Amazon QuickSight launches Trusted Identity Propagation (TIP) for Athena Direct Query

Amazon QuickSight now supports Trusted Identity Propagation (TIP) for Direct Query Datasets connecting to Amazon Athena data sources. With this capability customers can apply fine grained access controls using Lake Formation Rules to govern user access to data in QuickSight. TIP allows Authors to securely control rows and columns of data returned by queries allowing the same dashboard to be used across customers or departments. For further details, visit here.\n The new Athena Direct Query Trusted Identity Propagation is now available in Amazon QuickSight Standard and Enterprise Editions in all QuickSight regions - US East (N. Virginia and Ohio), US West (Oregon), Canada, Sau Paulo, Europe (Frankfurt, Ireland and London), Asia Pacific (Mumbai, Seoul, Singapore, Sydney and Tokyo), and AWS GovCloud (US-West).

Q-Index now supports seamless application-level authentication

We are excited to announce Q-Index now supports seamless application level authentication for its SearchRelevantContent (SRC) API, simplifying the end-user experience when using Q-Index to retrieve enterprise content.\n In the common Amazon Q-Index scenario where a 3rd party application integrates with the Q-Index SRC API, end-users first log into their application in order to use its core features, but when they need to get answers from their enterprise content, the SRC API implemented inside the 3rd party application requires the end-user to authenticate once again, this time against AWS IAM, in order to securely retrieve content from their enterprise knowledge sources. This two-stage authentication is redundant for the user. To simplify the user authentication experience, Q-Index’s support for seamless application authentication provides a Trusted Token Issuer (TTI) mechanism for developers to issue their own security tokens, trusted by the Q-Index SRC API. End users can therefore just login once into their 3rd party applications and get answers from enterprise content using Q-Index, without authenticating a second time to use this functionality. Q-Index’s support for seamless application authentication is available in the US East (N. Virginia), US West (Oregon), Europe (Ireland), and Asia Pacific (Sydney) AWS Regions. For more information, please consult our documentation.

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