Kategorie: Amazon AWS

AWS SAM now supports WebSocket APIs for Amazon API Gateway

AWS Serverless Application Model (AWS SAM) now supports WebSocket APIs for Amazon API Gateway, enabling you to define complete WebSocket APIs with minimal configuration in your SAM template.
AWS SAM is a collection of open-source tools that make it easy for you to build and manage serverless applications. WebSocket APIs are critical for real-time applications such as chat, live dashboards, AI/LLM streaming, and IoT. However, SAM previously did not support WebSocket APIs, requiring you to manually configure all of the underlying resources in AWS CloudFormation. This made it difficult to debug common issues such as missing IAM permissions for Lambda functions. Now, SAM handles all of this automatically, generating the required resources and permissions from your template. The new resource provides feature parity with API Gateway WebSocket APIs, including IAM and Lambda authorization, custom domains, RouteSettings, Models, and StageVariables. Globals support lets you share common configuration across multiple WebSocket APIs.
To get started, add the AWS::Serverless::WebSocketApi resource type to your SAM template. Define your routes by specifying Lambda function handlers for $connect, $disconnect, and $default routes, along with any custom routes your application requires. SAM automatically wires up the integrations and permissions for each route. You can also configure authorization, stage settings, and custom domains directly within the resource definition.
To learn more, visit the SAM developer guide.
Quelle: aws.amazon.com

AWS SAM CLI adds BuildKit support for AWS Lambda functions packaged as container images

AWS Serverless Application Model Command Line Interface (SAM CLI) now supports BuildKit for building container images from Dockerfiles, enabling faster, more efficient container image builds for Lambda functions packaged as container images.
SAM CLI is a command-line tool for building, testing, debugging, and packaging serverless applications locally before deploying to AWS Cloud. Developers packaging Lambda functions as container images often need advanced build features provided by BuildKit to optimize their images for production. However, SAM CLI previously did not support BuildKit features. Now, with BuildKit support in SAM CLI, you can utilize multi-stage builds to create smaller final images without development dependencies, improved caching to reduce rebuild times, and better parallelization of build steps. BuildKit also enables cross-architecture builds, allowing you to build container images targeting both x86_64 and arm64 (AWS Graviton2) instruction set architectures from the same development machine. You can also use Docker secrets during builds, keeping sensitive data such as credentials and API keys out of your final image layers.
To get started, download or update SAM CLI to version 1.159.0 or later and use the –use-buildkit flag with sam build. This feature works regardless of whether you are using Docker or Finch with SAM CLI, unlocking the full set of BuildKit capabilities.
To learn more, visit the SAM CLI developer guide.
Quelle: aws.amazon.com

Amazon Aurora DSQL now supports the JSON data type with compression

Amazon Aurora DSQL introduces support for the PostgreSQL JSON data type with optional compression. With JSON data type support, you can now use code and tools that depend on PostgreSQL’s JSON type with Aurora DSQL without modification, making it easier to store semi-structured data alongside relational data. You can use the JSON data type when creating or modifying tables to store semi-structured data such as API payloads, configuration objects, or event logs. With PostgreSQL compression enabled by default, larger JSON payloads are stored more efficiently, helping reduce storage costs. For details on the supported data types, see the Aurora DSQL documentation. Get started with Aurora DSQL for free with the AWS Free Tier. For information about Regional availability, see the AWS Region table. To learn more about Aurora DSQL, visit the webpage.
Quelle: aws.amazon.com

Amazon FSx is now available in the AWS Asia Pacific (New Zealand) Region

Amazon FSx, a fully-managed service that makes it easy and cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud, is now available in the AWS Asia Pacific (New Zealand) Region.
Amazon FSx lets you choose between four widely-used file systems: NetApp ONTAP, Windows File Server, Lustre, and OpenZFS. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx is built on the latest AWS compute, networking, and disk technologies to provide high performance and lower TCO. And as a fully managed service, it handles hardware provisioning, patching, and backups — freeing you up to focus on your applications, your end users, and your business.
To learn more about Amazon FSx, visit our product page, and see the AWS Region Table for complete regional availability information.
Quelle: aws.amazon.com

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