All news with #product update tag

📦 AWS announced a new warm storage tier for Amazon Kinesis Video Streams, offering lower-cost storage for extended media retention while preserving sub-second access latency. The existing standard tier is now designated the hot tier and remains optimized for real-time, short-term use. Developers can configure fragment sizes to trade latency for ingestion cost, and both tiers integrate with Amazon Rekognition Video and Amazon SageMaker for continuous video analytics. The warm tier is available in all supported regions except AWS GovCloud (US).

🔒 Amazon Aurora PostgreSQL-Compatible Edition now supports PostgreSQL 17.6, 16.10, 15.14, 14.19, and 13.22, bringing community fixes plus Aurora-specific enhancements. The release introduces database-level Dynamic Data Masking (DDM) for 16.10 and 17.6 to mask sensitive column values at query time using role-based policies without altering stored data. Additional updates include a shared plan cache, improved performance and recovery-time-objective (RTO), and more reliable Global Database switchovers. New clusters can be created in the Amazon RDS console or existing databases upgraded; releases are available across all commercial AWS Regions and AWS GovCloud (US).

🔒 Amazon S3 Block Public Access now supports organization-level enforcement via AWS Organizations, enabling centralized standardization of public-access settings across member accounts. When attached at a root or OU the single policy configuration propagates to existing and new accounts, or it can be targeted to specific accounts for granular control. Policy attachment and enforcement are auditable through AWS CloudTrail, and the feature is available in the console and via CLI/SDK in supported regions at no additional charge.

🚀 Amazon SageMaker HyperPod is now generally available with new programmatic APIs that let administrators reboot or replace cluster nodes at scale. The BatchRebootClusterNodes and BatchReplaceClusterNodes APIs provide an orchestrator-agnostic way to recover unresponsive or degraded nodes for both Slurm and EKS clusters. Each API supports batch operations for up to 25 instances and complements existing orchestrator-specific workflows. The capabilities are currently available in US East (Ohio), Asia Pacific (Mumbai), and Asia Pacific (Tokyo) and are accessible via the AWS CLI, SDKs, or API calls.

🔔 AWS announced that AWS Compute Optimizer now provides idle resource recommendations for NAT Gateways, helping identify unused NAT Gateways and realize potential cost savings. The feature flags NAT Gateways that show no traffic over a 32-day analysis period by evaluating CloudWatch metrics such as active connection count and incoming packet metrics. Compute Optimizer also checks Route Table associations to avoid recommending critical backup resources and surfaces estimated savings and utilization details for validation before remediation.

🔔 AWS Health introduced two new event schema properties — actionability and persona — to help customers identify and prioritize operational notifications. Delivered via the AWS Health API and Health EventBridge, these fields let organizations programmatically flag events that require customer action and route them to relevant teams such as security or billing. Available across all AWS Commercial and GovCloud (US) Regions, the change streamlines integrations with monitoring, ticketing, and automation systems to improve triage and remediation workflows.

🔔 AWS now supports Apache Iceberg V3 deletion vectors and row lineage across key analytics services. These features — available in Amazon EMR 7.12, AWS Glue, SageMaker notebooks, Amazon S3 Tables, and the AWS Glue Data Catalog — accelerate data modifications and make it simpler to identify changed records. Enable V3 by setting the table property 'format-version = 3' in CREATE TABLE or by updating table metadata; supported AWS query engines will automatically use deletion vectors and row lineage.

🔒 Amazon CloudWatch now lets you enable deletion protection on log groups to prevent accidental or unintended removals. Once enabled, a log group cannot be deleted until protection is explicitly turned off, helping preserve audit, compliance, and operational logs. The feature is available in all AWS commercial Regions and can be configured during creation or applied to existing groups via the Console, AWS CLI, AWS CDK, and AWS SDKs.

🔐 AWS Secrets Manager now supports managed external secrets, a new secret type that standardizes storage and enables automated rotation for third-party application credentials such as Salesforce, Snowflake, and BigID. The feature separates rotation metadata from secret values and integrates directly with providers to remove the need for custom rotation functions. It leverages existing IAM, CloudWatch, CloudTrail, GuardDuty, and KMS controls and follows standard Secrets Manager pricing with no additional charge.

🔧 The Amazon SageMaker AI MCP Server now provides tools to set up and manage HyperPod clusters, allowing AI coding assistants to provision and operate clusters for distributed training, fine‑tuning, and deployment. It automates prerequisites and orchestrates clusters via Amazon EKS or Slurm with CloudFormation templates that optimize networking, storage, and compute. The server also delivers lifecycle operations — scaling, patching, diagnostics — so administrators and data scientists can manage large-scale AI/ML clusters without deep infrastructure expertise.

🔒 Amazon Aurora PostgreSQL-Compatible Edition now supports minor PostgreSQL releases 17.6, 16.10, 15.14, 14.19, and 13.22. The update introduces Dynamic Data Masking (DDM) for versions 16.10 and 17.6, masking column values at query time via role-based policies without changing stored data. It also adds a shared plan cache and delivers improved performance, faster RTO, and better Global Database switchover behavior. These versions are available in all commercial AWS Regions and AWS GovCloud (US); you can create new clusters or upgrade existing databases through the RDS console.

🔁AWS Glue now supports zero-ETL for self-managed database sources, enabling no-code replication from Oracle, SQL Server, MySQL, and PostgreSQL hosted on-premises or on EC2 to Amazon Redshift. The feature auto-creates ongoing integrations to simplify setup, reduce operational overhead, and eliminate much of the engineering work previously required to build ingestion pipelines. It is available in multiple AWS Regions and aims to save teams weeks of engineering effort.

🆕 AWS Lambda now supports creating serverless applications with Node.js 24, available as both a managed runtime and a container base image. AWS will automatically apply updates to the managed runtime and base image as they become available, and the runtime is offered in all Regions including GovCloud (US) and China. The release emphasizes modern async/await handlers and removes callback-based handlers; Lambda@Edge and Powertools for AWS Lambda (TypeScript) are also supported, and standard AWS deployment tools (Console, CLI, SAM, CDK, CloudFormation) can be used to deploy Node.js 24 functions.

⚡Microsoft will introduce a new Teams call handler, ms-teams_modulehost.exe, that runs as a child process to manage the calling stack separately from the main ms-teams.exe application, improving startup times and in-meeting performance. The change is transparent to end users and requires no retraining. Administrators should allowlist the new process in security and endpoint protection systems and notify helpdesk staff to avoid false positives during the rollout.

🕒 Amazon Quick Flows now supports scheduled execution, allowing teams to automate repetitive workflows at specified times or custom intervals. You can configure flows to run daily, weekly, monthly, or on custom schedules and schedule any flow you can access—whether you created it or it was shared with you. Scheduling is set via the Quick Flows scheduling icon and is available now in IAD, PDX, and DUB. There are no additional charges beyond standard Quick Flows usage, and common use cases include recurring report generation, summarizing open items in external services, and producing daily meeting briefings.

⚡ Amazon SageMaker AI now supports EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency) speculative decoding to boost large language model inference throughput by up to 2.5x. The capability enables models to predict and validate multiple tokens in parallel rather than one at a time, preserving output quality while reducing latency. SageMaker automatically selects between EAGLE 2 and EAGLE 3 depending on model architecture and provides built‑in optimization jobs using curated or customer datasets. Optimized models can be deployed through existing SageMaker inference workflows without infrastructure changes, and the feature is available in select AWS Regions.

🛠️ AWS announces general availability of AWS Glue Data Quality preprocessing queries, enabling transformations before running data quality checks through the Glue Data Catalog APIs. The feature lets you create derived columns, filter datasets, perform calculations, and validate column relationships as part of the quality evaluation. This capability removes separate preprocessing steps, streamlines workflows, and tailors recommendations and rules to specific data subsets across commercial AWS Regions.

🔖 AWS has made AWS Glue Data Quality rule labeling generally available, allowing teams to attach custom key-value labels to data quality rules for better organization and targeted reporting. Labels can represent business context, team ownership, compliance tags, or priority and can be authored in DQDL. Queryable in rule outcomes, row-level results, and APIs, labels enable focused reports and streamlined remediation workflows across all commercial AWS Regions where the service is available.

🎙️ Amazon SageMaker AI Inference now supports bidirectional streaming, enabling real-time speech-to-text transcription that returns partial transcripts while audio is still being captured. Using the new Bidirectional Stream API, clients open an HTTP/2 connection to the SageMaker AI runtime, which automatically creates a WebSocket to your model container so audio frames and interim transcripts flow continuously. Any container that implements a WebSocket handler per the SageMaker AI contract works out of the box, allowing real-time models such as Deepgram to run without modification. The feature eliminates weeks or months of custom streaming infrastructure work so teams can focus on model accuracy, latency tuning, and agent behavior.

🔁 Amazon EC2 now offers interruptible On‑Demand Capacity Reservations (ODCRs), allowing reservation owners to temporarily make unused reserved capacity available to other internal workloads while retaining the ability to reclaim it. Consumers using interruptible ODCRs receive an interruption notice to allow graceful shutdown or checkpointing. The capability targets flexible, fault‑tolerant tasks such as batch processing, data analysis, and machine learning training, is available at no additional cost, and CloudFormation support is coming soon.