All news with #aws tag

Amazon S3 Batch Operations: Up to 10x Faster at Scale

⚡Amazon S3 Batch Operations now finishes jobs up to 10x faster and supports jobs that include up to 20 billion objects, accelerating large-scale storage tasks. S3 pre-processes objects, runs operations, and generates completion reports with no extra configuration or cost. Typical uses include copying between buckets, tagging for lifecycle policies, and computing checksums. The upgrade is available in all AWS Regions except China and GovCloud (US).

AWS AI Factories: Dedicated High-Performance AI Infrastructure

🚀 AWS AI Factories are now available to deploy high-performance AWS AI infrastructure inside customer data centers, combining AWS Trainium, NVIDIA GPUs, low-latency networking, and optimized storage. The service integrates Amazon Bedrock and Amazon SageMaker to provide immediate access to foundation models without separate provider contracts. AWS manages procurement, setup, and operations while customers supply space and power, enabling isolated, sovereign deployments that accelerate AI initiatives.

Amazon Bedrock AgentCore Adds Policy and Evaluations

🛡️ Amazon Web Services' AgentCore introduces preview features — Policy and Evaluations — to help teams scale agents from prototypes into production. Policy intercepts real-time tool calls via AgentCore Gateway and converts natural-language rules into Cedar for auditability and compliance without custom code. Evaluations offers 13 built-in evaluators plus custom model-based scoring, with all quality metrics surfaced in an Amazon CloudWatch dashboard to simplify continuous testing and monitoring.

AWS announces compute-optimized Amazon EC2 C8a instances

🚀 Amazon Web Services announced the general availability of Amazon EC2 C8a instances powered by 5th Gen AMD EPYC (Turin) processors with up to 4.5 GHz frequency. AWS says C8a delivers up to 30% higher performance, up to 19% better price-performance versus C7a, 33% more memory bandwidth, and up to 57% faster GroovyJVM performance for Java workloads. The family includes 12 sizes, two bare-metal options, and is built on the AWS Nitro System for high-performance compute use cases such as HPC, batch processing, ad serving, multiplayer gaming, and video encoding. C8a instances are initially available in US East (N. Virginia), US East (Ohio), and US West (Oregon) and can be purchased via Savings Plans, On-Demand, or Spot.

Amazon Bedrock Adds 18 Fully Managed Open Models Today

🚀 Amazon Bedrock expanded its model catalog with 18 new fully managed open-weight models, the largest single addition to date. The offering includes Gemma 3, Mistral Large 3, NVIDIA Nemotron Nano 2, OpenAI gpt-oss variants and other vendor models. Through a unified API, developers can evaluate, switch, and adopt these models in production without rewriting applications or changing infrastructure. Models are available in supported AWS Regions.

Amazon OpenSearch: GPU-Accelerated Auto-Optimized Vectors

🚀Amazon OpenSearch Service now offers GPU-accelerated, auto-optimized vector indexes that let teams build billion-scale vector databases in under an hour. Serverless GPU acceleration can speed index builds up to 10X while reducing indexing cost to roughly a quarter of previous expenses. Auto-optimize jobs evaluate k-NN algorithms, quantization, and engine settings against specified latency and recall targets to produce configuration recommendations without manual tuning. These capabilities support vector collections and OpenSearch 2.17+/3.1+ domains across multiple regions.

AWS previews EC2 C8ine instances for packet processing

🚀 Amazon Web Services previewed EC2 C8ine instances built on custom sixth-generation Intel Xeon Scalable processors (Granite Rapids) and the new Nitro v6 card. These instances are optimized for dataplane packet-processing workloads and can deliver up to 2.5× higher packet performance per vCPU versus prior C6in instances, with up to 2× higher internet-gateway bandwidth and up to 3× more ENIs. Targeted use cases include security virtual appliances, firewalls, load balancers, DDoS protection systems, and Telco 5G UPF. Preview access is available upon request through your AWS account team.

S3 Tables Gain Intelligent-Tiering Storage Class Now

🗃️ Amazon S3 Tables now support the Intelligent-Tiering storage class to automatically optimize table storage costs based on access patterns, without impacting performance or adding operational overhead. Data not accessed for 30 days moves to the Infrequent Access tier (≈40% lower cost), and after 90 days moves to Archive Instant Access (≈68% lower cost), enabling up to 80% storage savings. Automated table maintenance (compaction, snapshot expiration, unreferenced file removal) does not trigger tiering, and you can select Intelligent-Tiering per table or set it as the default for new tables in a table bucket across all regions where S3 Tables are available.

Bedrock AgentCore Runtime Adds Bi-Directional Streaming

🔁 Amazon Bedrock AgentCore Runtime now supports bi-directional streaming, enabling real-time, continuous conversations where agents listen and respond simultaneously and handle interruptions or context shifts mid-turn. This removes stop-start friction in voice and text agents and preserves context across exchanges. Built into AgentCore Runtime, the capability reduces months of engineering work required to implement streaming infrastructure, letting developers focus on agent experiences rather than plumbing. Available in nine AWS Regions with consumption-based pricing.

Amazon SageMaker AI Adds Serverless MLflow Support

🧠 Amazon SageMaker AI now offers a serverless MLflow capability that automatically scales to support experiment tracking and model development without infrastructure setup. The service scales up for demanding workloads and scales down during idle periods, reducing operational overhead. Administrators can enable cross-account access via Resource Access Manager (RAM). The feature integrates with SageMaker AI JumpStart, Model Registry, and Pipelines and is offered at no additional charge in select AWS Regions.

CloudWatch AgentCore Evaluations: Automated AI Agent Quality

🧭 Amazon CloudWatch now offers AgentCore Evaluations, an automated capability for assessing AI agent quality using real-world interactions. The feature includes 13 pre-built evaluators that measure dimensions such as helpfulness, tool selection, and response accuracy, and it also supports custom model-based scoring. Teams can access unified quality metrics, agent telemetry, and end-to-end traces in CloudWatch dashboards to correlate evaluations with prompts, logs, and traces for faster diagnosis and improvement.

AWS launches EC2 X8aedz memory-optimized instances

🚀 AWS announced the new Amazon EC2 X8aedz memory-optimized instances powered by 5th Gen AMD EPYC processors (Turin), offering up to 5 GHz peak CPU frequency and up to 2× compute performance versus X2iezn. Targeted at electronic design automation (EDA) workloads and relational databases that benefit from high single-thread performance and large memory footprints, X8aedz provides a 32:1 memory-to-vCPU ratio, local NVMe storage up to 8 TB, and sizes from 2 to 96 vCPUs including two bare-metal options. Instances are available in US West (Oregon) and Asia Pacific (Tokyo) and can be purchased via On‑Demand, Spot, or Savings Plans.

Amazon API Gateway Adds MCP Proxy for Agent Integration

🤖 Amazon API Gateway now supports the Model Context Protocol (MCP) via a proxy, enabling organizations to expose existing REST APIs to AI agents and MCP clients without modifying their applications. Integrated with Amazon Bedrock AgentCore's Gateway, the feature performs protocol translation, indexes APIs for semantic tool discovery, and eliminates the need to host additional intermediary infrastructure. It also enforces dual authentication to verify agent identities for inbound requests while managing secure outbound connections to REST endpoints. The capability is available in nine AWS Regions and follows Amazon Bedrock AgentCore pricing.

Amazon SageMaker Catalog Exports Asset Metadata to Iceberg

🔍 Amazon SageMaker Catalog now exports asset metadata as an Apache Iceberg table via Amazon S3 Tables, enabling teams to query catalog inventory with standard SQL without building custom ETL. The export includes technical fields (resource_id, resource_type), business metadata (asset_name, business_description), ownership details, and timestamps, partitioned by snapshot_date for time travel queries. The dataset appears in SageMaker Unified Studio and is queryable from Amazon Athena, Studio notebooks, AI agents, and BI tools. Available in all supported Regions at no additional SageMaker charge; you pay for S3 Tables storage and Athena queries.

CrowdStrike Leverages NVIDIA Nemotron on Amazon Bedrock

🔐 CrowdStrike integrates NVIDIA Nemotron via Amazon Bedrock to advance agentic security across the Falcon platform, enabling defenders to reason and act autonomously at scale. Falcon Fusion SOAR leverages Nemotron for adaptive, context-aware playbooks that prioritize alerts, understand relationships, and execute complex responses. Charlotte AI AgentWorks uses Bedrock-delivered models to create task-specific agents with real-time environmental awareness. The serverless Bedrock architecture reduces infrastructure overhead while preserving governance and analyst controls.

NETSCOUT Omnis Wins Overall Network Security Award

🔍 NETSCOUT’s Omnis Cyber Intelligence was named “Overall Network Security Solution of the Year” in the ninth annual CyberSecurity Breakthrough Awards. The platform delivers always-on, packet-based visibility using scalable deep packet inspection to continuously capture, analyze, and retain high-fidelity network metadata. Its on-sensor storage minimizes data movement and helps address compliance and sovereignty requirements while providing the historical context analysts need to investigate threats across cloud and on-premises environments.

AWS Transform gains data and activity analysis for mainframe

🔍 AWS Transform for mainframe adds data and activity analysis to extract detailed insights that drive the reimagining of legacy applications. The update provides automated code and data-structure analysis, activity analysis, technical documentation generation, business logic extraction, and intelligent code decomposition. An AI-powered chat interface lets users build flexible job plans—from full modernization workflows to analysis- or business-logic-focused jobs—so teams can prioritize and execute modernization more efficiently.

AWS Transform Adds Reimagine Capabilities for Mainframe

🔍 AWS announced new AWS Transform for mainframe reimagine capabilities that add data and activity analysis, business logic extraction, and intelligent code decomposition to support migration to cloud-native architectures. The service provides a comprehensive reverse-engineering workflow including automated code and data structure analysis and technical documentation generation. An AI-powered chat interface lets users choose predefined job plans—full modernization, analysis focus, or business-logic focus—or compose custom workflows. These capabilities are available today in multiple AWS Regions including N. Virginia, Mumbai, Seoul, Sydney, Tokyo, Canada (Central), Frankfurt, and London.

AWS Transform AI Agent for Full-Stack Windows Modernization

🔧 AWS Transform expands its .NET modernization agent into a full-stack Windows modernization agent that automates transformation of .NET applications and Microsoft SQL Server databases to Amazon Aurora PostgreSQL and deploys them to containers on Amazon ECS or Amazon EC2 Linux. The agent scans SQL Server instances in EC2 or RDS and .NET code in GitHub, GitLab, Bitbucket, or Azure Repos to produce editable modernization plans. It updates Entity Framework and ADO.NET data access code, migrates schemas and data, commits transformed code to a new branch, and supports supervised validation and deployment. Available in US East (N. Virginia).

AWS Transform Custom GA: Agentic AI for Code Modernization

🚀 AWS Transform Custom is now generally available, offering an agentic AI service to accelerate organization-wide code and application modernization at scale. The service automates repeatable transformations—version upgrades, runtime migrations, framework transitions, and language translations—often reducing execution time by over 80% while removing the need for specialist automation expertise. It provides out-of-the-box transformations for Python, Node.js, Lambda, AWS SDK updates, and Java 8→17, and supports custom transformation definitions using natural language, reference documents, and code samples. Teams can run autonomous transformations with a one-line CLI command, embed them into pipelines, and benefit from an agent that continuously learns from developer feedback and execution results. AWS Transform Custom is available in the US East (N. Virginia) region.