The immersion DUV machine developed by Shanghai Yuliangsheng Technology, the semiconductor  manufacturing equipment specialist, will be shipped by Shanghai Aishengna Technology which has taken over Yuliansheng’s team. The intention is […]

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Agentic engineering is reshaping chip and system design and Nvidia is putting itself at the core of this movement with a concerted effort to deliver the tools and libraries designers […]

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AWS Clean Rooms now supports larger worker types of 32 vCPUs with 244 GB of memory for SQL analyses, allowing you to run more compute and memory-intensive workloads. Previously, the largest worker type available was 16 vCPUs with 120 GB of memory. Larger workers can help improve performance for complex queries on large datasets, optimizing costs for customers. For example, an advertiser collaborating with a publisher can use larger workers to run complex feature engineering across billions of records to train their multi-touch attribution model, accelerating time-to-value 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 .

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports restoring Transparent Data Encryption (TDE)-enabled SQL Server databases on Multi-AZ instances and instances configured with a read replica in the same region, using native backup and restore. Previously, TDE-enabled database restore was available only for Single-AZ instances, requiring you to disable TDE or migrate to a Single-AZ configuration before restoring encrypted databases.

You can restore TDE-enabled database backups directly to Amazon RDS for SQL Server Multi-AZ instances and instances configured with a read replica in the same region. Back up your existing TDE certificate, store it in Amazon S3, and restore it to your Amazon RDS instance with the TDE option enabled. Then, restore your TDE-enabled database backup from Amazon S3 using Amazon RDS native backup and restore. This simplifies your migration and recovery workflows when you require both encryption at rest with TDE and the high availability of Multi-AZ deployments.

This feature is available in all AWS Regions where Amazon RDS for SQL Server is supported. To learn more, see the Amazon RDS for SQL Server User Guide .

AWS Elemental MediaTailor now gives you direct control over ad decision server (ADS) timeout. Previously, changing these settings required contacting AWS Support. You can now configure individual HTTP ad request timeouts, total ad personalization time budgets for live, VOD, and live ad prefetch, and enable parallel ADS requests.

These settings allow you to optimize ad delivery performance for your specific workflows. For example, you can increase the personalization time budget for live events to improve ad fill rates or enable parallel ADS requests in VOD workflows to reduce overall response time for faster video startup. New prefetch-specific timeout settings give you additional granularity for livestream ad retrieval.

You can configure these settings through the AWS Elemental MediaTailor console, AWS CLI, or AWS SDKs using the new AdsPersonalizationTimeouts and AdsPersonalizationConcurrency parameters on your playback configurations.

This feature is available in all AWS Regions where AWS Elemental MediaTailor is available. 

To learn more about configuring ADS request timeouts, personalization time budgets, and concurrency, see Advanced settings in the AWS Elemental MediaTailor User Guide.

AWS announces the preview of the AWS Security Hub MCP App, a local Model Context Protocol (MCP) server that brings your Security Hub exposure findings directly into Claude Desktop.  This capability can help accelerates your security investigations by reducing context switching and manual triage, letting you explore and act on your exposures without leaving your AI-assisted workflow.

With the Security Hub MCP App, you can investigate your security posture in natural language: view your top exposure findings, drill into a finding’s attack path and expanded network path, examine correlated findings and affected resource configurations, and get remediation recommendations. Each tool call returns both a text summary for your AI agent to reason overover and an interactive visualization for you to verify in the same conversation. The MCP server runs locally on your machine using your existing AWS credentials, and every tool is read-only,– no changes are made to your environment.

The Security Hub MCP App is available at no additional cost to Security Hub customers. This feature is available in preview in all AWS commercial Regions that support Security Hub. To learn more, see the AWS Security Hub User Guide and the AWS Security Hub product page . For the full list of Regions, see the AWS Regional Services List .

Amazon GameLift Streams now supports Custom Aspect Ratio and Dynamic Resolution, giving you greater control over the streaming experience across diverse player devices and network conditions.

With Custom Aspect Ratio, you can configure a specific resolution per stream session to match your player’s device — including portrait, landscape, ultra-wide, and square aspect ratios. This eliminates letterboxing or pillarboxing, delivering native full-screen experiences on mobile phones, tablets, and non-standard displays. Specify any resolution from 320 to 4096 pixels per dimension (up to 1080p total pixel budget) using the DisplayConfiguration parameter in the StartStreamSession API. You can also try custom resolution from the AWS Console.

Dynamic Resolution automatically adapts stream quality when a player’s network bandwidth fluctuates. When bandwidth drops, the stream gracefully reduces resolution to maintain smooth playback without frame drops or disconnections — and automatically recovers to full quality when conditions improve. Dynamic Resolution is enabled by default for all new stream groups with no configuration required. Customers will need to download the new Web SDK.

Both features are available in all AWS Regions where Amazon GameLift Streams is offered. To learn more, see Custom stream resolution in the Amazon GameLift Streams Developer Guide. 
 
https://docs.aws.amazon.com/gameliftstreams/latest/developerguide/custom-stream-resolution.html

AWS Glue Data Quality now supports a new Distribution Analyzer that generates frequency distribution profiles for your data. Using this new Distribution Analyzer in the Data Quality Definition Language (DQDL), you can generate histograms for numeric columns and value distributions for categorical, date, and boolean columns. With support for custom bin counts, you can explore the shape and patterns of your data at the granularity that matters most to your use case.

Understanding how data is distributed is foundational to building reliable data pipelines. Distribution statistics help you quickly identify skewness, outliers, and unexpected patterns across your datasets, without writing custom code. The capability integrates directly with your existing DQDL rulesets, so you can add distribution profiling alongside your current data quality checks in a single evaluation run. Distribution statistics are stored in Amazon S3 for future querying through services like Amazon Athena, and are also surfaced through APIs, making it easy to integrate distribution insights into monitoring workflows and visualization tools, including SageMaker Unified Studio.

AWS Glue Data Quality distribution statistics are available in all AWS commercial regions and AWS GovCloud (US) regions.

To learn more about Glue Data Quality, visit the AWS Glue Data Quality documentation . To get started with using Distribution Analyzer, visit the Analyzers documentation .

AWS Glue Data Quality now supports anomaly detection for Catalog-based data quality evaluations and the ability to write evaluation results to AWS Glue Data Catalog (GDC) tables. These capabilities work across both ETL jobs and Catalog evaluations, giving you a consistent data quality experience regardless of workflow type.

With anomaly detection support for GDC, you can identify unexpected changes in data statistics such as sudden drops in distinct values or row count spikes in your GDC tables using ML-powered time-series forecasting, without writing rules with explicit thresholds. This is especially valuable for data engineers monitoring hundreds of tables in the GDC who need to surface issues automatically.

With results storage in GDC, Data Quality rule outcomes, profiling metrics, and anomaly predictions (with confidence bounds) are written back to GDC tables, creating a queryable record of all quality evaluations. Whether the evaluation runs in an ETL job or directly on a Catalog table, results can be queried at any time using standard SQL.

AWS Glue Data Quality anomaly detection and Catalog results storage are available in all AWS commercial regions and AWS GovCloud (US) regions.

To get started, visit the AWS Glue Data Quality documentation .

Amazon Neptune Database now supports tag-based access control (TBAC) for IAM, enabling customers to use AWS resource tags and IAM principal tags as conditions in IAM policies and Service Control Policies (SCPs) to control access to Neptune data-plane operations. Neptune already provides robust security through VPC isolation, TLS encryption, and IAM authentication, but customers managing multiple clusters at scale needed a dynamic, attribute-based mechanism to enforce organizational access boundaries. TBAC addresses this by allowing administrators to govern cluster access without enumerating specific cluster ARNs in every policy.

With TBAC, IAM principals can only perform `neptune-db:*` actions against Neptune clusters whose tags match their own — for example, a principal tagged `Project=FraudDetection` is automatically restricted to clusters sharing that same tag. This eliminates lateral access risk within shared VPC environments, enforces team and environment-level isolation across projects, and supports federated identity workflows using SAML or OIDC session tags from external identity providers. Granular permissions like neptune-db:QueryLanguage can be used alongside TBAC for more fine-grained access control.

This feature is available in all AWS Regions where Amazon Neptune is available and requires Neptune engine version 1.2.0.0 or later with IAM authentication enabled.

To learn more about configuring tag-based access control for Amazon Neptune, including how to tag your DB clusters and IAM principals and deploy organization-wide guardrails using SCPs, visit the Amazon Neptune documentation .