Kategorie: Amazon AWS

Amazon WorkSpaces Applications now supports host-to-client URL redirection

Amazon WorkSpaces Applications now supports host-to-client URL redirection, which automatically launches URLs from streaming sessions in the user’s local browser. Administrators can configure allow and deny URL patterns through the AWS Management Console to control which web content is redirected, enabling organizations to keep sensitive applications securely within the streaming environment while offloading resource-intensive content such as video streaming to local devices. With host-to-client URL redirection, organizations reduce the load on streaming infrastructure by shifting bandwidth-heavy web workloads to local devices, lowering infrastructure costs without impacting the end-user experience. The feature works for browser navigation and embedded links in applications such as Microsoft Word, with support for Chrome and Edge web browsers on the streaming host. URLs in the configured allow list open in the user’s local default browser automatically. Host-to-client URL redirection for Amazon WorkSpaces Applications is available in multiple AWS Regions including US East (N. Virginia and Ohio), US West (Oregon), Asia Pacific (Malaysia, Mumbai, Seoul, Singapore, Sydney, and Tokyo), Canada (Central), Europe (Frankfurt, Ireland, London, Milan, and Paris), South America (São Paulo), Israel (Tel Aviv), AWS GovCloud (US-West and US-East). To learn more about host-to-client URL redirection for Amazon WorkSpaces Applications, see host to client URL redirection. For more information about Amazon WorkSpaces Applications, visit the Amazon WorkSpaces Applications page.
Quelle: aws.amazon.com

Amazon CloudWatch Logs Insights supports querying by log group tags

Amazon CloudWatch Logs Insights query language now supports querying log groups using tags, making it easier to analyze logs without listing the log groups explicitly. In addition to querying logs by log group names, data sources, and facets, customers can now query using log group tags. Tags are key-value pairs that customers can assign to log groups to categorize them — for example, Environment: Production, Application: PaymentService, or Owner: TeamName. With this launch, customers can run a query across all log groups that share common tags. As log group tags are added or removed, queries automatically reflect the matching log groups, reducing operational overhead as environments grow. Querying by log group tags is available today in all commercial AWS Regions. To learn more, see the Amazon CloudWatch Logs documentation.
Quelle: aws.amazon.com

Amazon Quick upgrades the extension for Microsoft Outlook (Preview)

Today, AWS announces the preview of the Amazon Quick extension for Microsoft Outlook, which brings generative AI-powered productivity directly into your email and calendar workflows. With the extension, you can use natural language to summarize unread messages, organize your inbox, schedule meetings, and draft in-line responses all without leaving Outlook.
The Quick extension for Outlook helps you focus on what matters most by prioritizing emails, searching for specific discussions, and organizing messages into folders or flagging them for follow-up. Using conversational instructions, you can find optimal meeting times with coworkers and schedule meetings. For email threads, you can generate summaries, extract action items, and draft contextual replies that pull in relevant information from your Amazon Quick spaces and knowledge bases. You can also trigger actions in external applications using your configured integrations directly from Outlook.
The Amazon Quick extension for Microsoft Outlook is available in preview in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), Europe (Ireland), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (London).
To get started with Amazon Quick, visit the Quick website, and sign up for an account in minutes. Read the documentation to learn more, and install the Quick extension for Outlook from the Quick download page.
Quelle: aws.amazon.com

Amazon Quick now supports S3 tables bucket as a data source

Amazon Quick now supports Amazon S3 table buckets as a data source — enabling users to build dashboards, run conversational analytics, and explore Apache Iceberg tables stored in S3 table buckets. With no intermediate data warehouse or OLAP layers required, users can now interoperate with their lakehouse data in Amazon Quick for both agentic AI and BI workloads — all through a simplified data architecture.
Paired with Zero-ETL from sources like Salesforce, SAP, and Amazon Kinesis Data Firehose directly into S3 table buckets, users get near real-time insights with minimal pipeline dependencies. Getting started is straightforward: admins configure S3 table bucket permissions once, and authors can immediately create datasets and start building. S3 table bucket datasets are fully accessible through Amazon Quick’s Dataset Q&A — ask a natural language question and get answers grounded in your data lake as the source of truth.
Amazon S3 table buckets as a data source in Amazon Quick is now available in all AWS Regions where Amazon Quick is available. To get started, see this blog post.
Quelle: aws.amazon.com

Amazon Quick introduces Dataset Q&A for conversational analytics against enterprise data

Amazon Quick now supports Dataset Q&A — a conversational analytics capability that enables users to ask natural language questions directly against their enterprise data. Alongside Dashboard Q&A, Dataset Q&A provides a powerful new way to interact with data in Amazon Quick — letting anyone with dataset access explore their data and get meaningful, actionable insights using natural language, while respecting all governance rules including Row Level and Column Level Security policies set by data owners..
Dataset Q&A is powered by Amazon Quick’s text-to-SQL agent, which interprets user questions, identifies the right data, and generates precise SQL — all in a single conversational step. The agent works across various data sources users bring into Amazon Quick — generating engine- and dialect-aware optimized SQL against SPICE or AWS data assets such as Amazon Redshift, Amazon Athena, Aurora PostgreSQL, and Apache Iceberg tables stored in Amazon S3 table buckets. Data owners can enrich their datasets with custom instructions, business definitions, and field descriptions directly in Amazon Quick or through simple file uploads. These curated semantics, together with dataset metadata, are ingested into a knowledge graph that captures the meaning and relationships across data assets, enabling Quick’s orchestrator to accurately identify the most relevant datasets and generate the accurate SQL. The Dataset Q&A agent delivers accurate answers across a broad range of question types — from trend analysis and time-series comparisons to ranking, multi-condition analytical queries, and open-ended exploratory questions. Dataset Q&A also includes an Explain capability, allowing users to step through the reasoning behind each answer, inspect the underlying logic, and validate that the generated SQL correctly interprets their question before acting on the result.
Dataset Q&A is now generally available in all AWS Regions where Amazon Quick is available. To get started, see this blog post.
Quelle: aws.amazon.com

Amazon Quick generates dashboards from natural language prompts

Amazon Quick now generates dashboards from natural language prompts with Generate Analysis. You describe the dashboard you want, select up to three datasets, and review an editable plan before generation. Amazon Quick then produces organized sheets with visuals selected for your data, filter controls for exploring by different dimensions, and calculated fields such as year-over-year growth and month-over-month comparisons.. Generate Analysis reduces dashboard creation from hours of manual configuration to minutes.
With Generate Analysis, you can describe goals such as “create a sales performance dashboard with revenue trends, regional comparisons, and month-over-month growth” and receive a dashboard ready for refinement. The output works with existing publishing workflows, embedding, CI/CD pipelines, and point-and-click editing.
At launch, Generate Analysis is available to Enterprise subscription/Author Pro users. Authors also have promotional access to this capability through December 2026 as part of Amazon Quick Enterprise, provided their organization has not restricted access. Generate Analysis is now generally available in all AWS Regions where Amazon Quick is available.
To learn more, see Generating an analysis with natural language prompts in the Amazon Quick User Guide. To get started, open any dataset in Amazon Quick and choose Generate analysis.
Quelle: aws.amazon.com

AWS Entity Resolution launches support for incremental Machine Learning based matching workflows

AWS Entity Resolution launches support for Machine Learning (ML) based Incremental Matching workflows in General Availability, fundamentally transforming how enterprises process entity resolution at scale. Previously, adding even a single new record required customers to reprocess their entire dataset—a process that could take up to 2 days and cost thousands of dollars. This created a critical bottleneck that forced major businesses to seek costly workarounds or alternative solutions. 
With this enhancement, AWS Entity Resolution enables businesses to process only the new records added since their last workflow run. This launch provides dramatic efficiency gains: processing 1M incremental records in less than 1 hour which is a 95% reduction in processing time compared to current workloads , while also significantly reducing infrastructure costs. The feature supports incremental workloads up to 50M incremental records over datasets containing up to 1 billion historical base records, making AWS Entity Resolution viable for continuous, large-scale enterprise workloads that were previously economically unfeasible.
You can start using incremental ML workflows in all AWS Regions where AWS Entity Resolution is available. For more information on starting an incremental ML workflow, see our user guide. For more information about AWS Entity Resolution, visit our product page. 
Quelle: aws.amazon.com

OpenSearch UI supports cross-region data access to OpenSearch domains

Amazon OpenSearch Service now supports cross-region data access for OpenSearch UI, enabling users to access OpenSearch domains hosted in different AWS Regions from within a single OpenSearch UI application. Combined with the cross-account data access launch earlier this year, you can now query or build dashboards on OpenSearch domains in flexible combinations of accounts and Regions – without switching endpoints or replicating data. Cross-region data access is available for OpenSearch domains hosted in both public and Virtual Private Cloud (VPC) configurations. With cross-region data access, teams can build centralized analytics, search, and observability workflows across globally distributed deployments while keeping data in place – meeting data residency requirements, minimizing inter-region egress, and preserving each Region’s latency and availability characteristics. If you are using cross-cluster replication, you can now query both your primary and replica domains directly from a single OpenSearch UI application. Cross-region data access can be combined with cross-account data access, so a single OpenSearch UI application can connect to domains in different accounts, different Regions, or both. Cross-region data access supports both IAM and IAM Identity Center for end-user authentication. Cross-region data access to OpenSearch domains is available in all AWS Regions where OpenSearch UI is available. To learn more, see Cross-region data access to OpenSearch domains in the Amazon OpenSearch Service Developer Guide.
Quelle: aws.amazon.com

FreeRTOS 202604 LTS now available with enhanced security and MQTT v5.0

FreeRTOS 202604 LTS, a new Long Term Support release of the open-source real-time operating system for embedded devices, is now available. This release provides embedded systems developers and Internet of Things (IoT) device manufacturers with feature stability, security updates, and critical bug fixes for two years. It addresses key challenges in embedded systems, including memory safety, code quality, and protocol support. FreeRTOS kernel v11.3.0 introduces new hardware ports, security hardening, and expanded Memory Protection Unit (MPU) support, reducing the number of MPU regions claimed by FreeRTOS and allowing developers to reserve hardware regions for application-specific memory protection. Additionally, coreMQTT v5.0.2 adds MQTT v5.0 protocol support, enabling features like topic aliases for bandwidth-constrained devices and request/response patterns for interactive IoT applications. coreSNTP v2.0.0 brings year 2038 readiness, so devices deployed today can validate TLS certificates and timestamp data correctly throughout their operational lifetime. This release offers libraries verified for memory safety and MISRA-C compliance. The libraries improve robustness, portability, and reliability in embedded systems. Migration guides for coreMQTT and coreSNTP provide detailed guidance for updating to FreeRTOS 202604 LTS. For projects requiring critical fixes on the previous LTS version beyond its expiry, the FreeRTOS Extended Maintenance Plan is available. To learn more, visit the FreeRTOS LTS page and FreeRTOS LTS GitHub repository.
Quelle: aws.amazon.com

Amazon Bedrock AgentCore is now available in the South America (São Paulo) Region

Amazon Bedrock AgentCore is now available in the AWS South America (São Paulo) Region. Amazon Bedrock AgentCore is the platform to build, connect, and optimize agents. It helps engineers ship agents fast with any framework and any model, connect them to enterprise systems and tools, and optimize them continuously, with security enforced at the infrastructure layer that agents can’t bypass. With this expansion, customers in South America can deploy and operate agents closer to their end users, reducing latency and helping meet data residency requirements. AgentCore capabilities including agent runtime, identity, gateway, policy, observability, code interpreter, and browser tools are available in the São Paulo Region at launch. For more information on AgentCore, visit the AgentCore product page or the AgentCore Developer Guide. To learn about pricing, visit AgentCore pricing. For region availability, visit Supported AWS Regions.
Quelle: aws.amazon.com