Tag: SysAdmin

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 capabili

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 b

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 dat

Amazon SageMaker AI now features an agentic experience that transforms model customization from a months-long process into a workflow completed in days or hours. Customers building an AI solution need to carefully frame their use case goals and success criteria, prepare data, choose the right models, configure, run, and analyze multiple experiments with various models and fine tuning techniques. Once a suitable model candidate that meets the success criteria is identified, they need to figure out the most cost performant way to deploy the model. Throughout this workflow customers need to manage the undifferentiated heavy lifting of setting up the infrastructure to train and deploy the models. The new capability now enables developers to use natural language interactions with coding agents to streamline the entire journey from use case definition to production deployment of a high quality model. The agentic experience, based on SageMaker AI model customization agent skills,

AWS Payment Cryptography now supports cross account sharing of keys using resource-based policies (RBP).  With this new feature, customers can more easily manage cryptographic keys across multiple accounts both internal and external to their company, providing more flexibility to manage keys at scale.  With AWS Payment Cryptography, you can simplify cryptography operations in your cloud-hosted payment applications with a service that grows elastically with your business and has been assessed as compliant with PCI PIN Security and Point-to-Point Encryption (P2PE) requirements. Many customers utilize multiple AWS accounts to delineate different workloads, applications or use cases for payment processing following AWS PCI DSS Guidance.  While this pattern i

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 AgentCo

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 T

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 an

Amazon CloudFront now supports WebSockets traffic through Virtual Private Cloud (VPC) origins, enabling you to use CloudFront as the single entry point for real-time applications hosted entirely in private subnets. WebSockets support extends VPC origins to applications that require persistent, bidirectional connections between clients and servers, such as chat platforms, collaborative editing tools, live dashboards, and IoT device management systems. Previously, customers running real-time applications over WebSockets had to keep their origins in public subnets and use Access Control Lists and other mechanisms to restrict access to their WebSockets-enabled servers. Customers had to spend ongoing effort to implement and maintain these solutions. Now, customers can place their Application Load Balancers (ALB), Network Load Balancers (NLB), and EC2 instances serving WebSockets traffic in private subnets accessible only through their CloudFront distributions. CloudFront serves

Today, we're announcing the General Availability of the AWS for SAP MCP Server on Amazon Bedrock AgentCore, purpose-built to connect AI agents directly to SAP ERP systems, securely and at scale. Built on the Model Context Protocol (MCP) and SAP's Open Data Protocol (OData) standards, this solution addresses the challenge of making SAP business data and processes accessible to AI agents while maintaining enterprise-grade security and comprehensive Observability. Organizations running SAP systems can now empower their AI agents to interact with various SAP processes including finance, procurement, logistics, and supply chain operations. By leveraging SAP ERP business data, the AWS for SAP MCP Server enables AI agents to create, read, update, and delete SAP business objects such as sales orders, purchase orders, materials, and finance documents. Deployed on the fully managed Amazon Bedrock AgentCore Runtime, the server handles session isolation, private connectivity, an