AWS(AMZN)

Amazon OpenSearch Service now supports MCP Apps, bringing observability workflows directly into compatible agentic IDEs such as Claude Desktop and VS Code. With this capability, your AI agent in local environment can investigate incidents using logs, traces, metrics, and alerts stored in OpenSearch domains, collections and Amazon Managed Service for Prometheus. You can easily review and verify the results in interactive MCP App visualizations without leaving your local environment. Each MCP App tool call returns a dual response, a concise text summary for your agent to reason over and an interactive visualization rendered in the same conversation thread for you to review. You can work alongside your observability agent from firing an alert, perform root cause analysis, exploring distributed traces, service maps, PromQL metric charts, and cross-signal correlations all within a single conversation. Available MCP App tools cover log, metrics and trace investigation, service performance, t

Amazon ECS Managed Daemons now support inter-task visibility and communication, enabling customers to deploy tracing, profiling, and security agents that require access to application processes and shared IPC resources on ECS Managed Instances . With this launch, you can configure two new settings in ECS daemon definitions: pidMode controls whether the daemon can see all processes on the instance, and ipcMode controls whether the daemon shares an IPC namespace with other containers on the instance. Setting either to "shared" grants the daemon access to the respective namespace; the default of "none" keeps daemons isolated from application containers and other tasks. These settings let you run process-aware and IPC-dependent agents as ECS daemons instead of embedding them as sidecars in application task definitions. ECS places exactly one daemon task per managed instance and starts daemons before application tasks, so platform teams can deploy and update agents independently with consis

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M9g and M9gd instances , powered by AWS Graviton5 processors, are generally available. AWS Graviton5 processors are the fifth generation of custom-designed AWS processors, delivering the best price performance for general purpose workloads running on Amazon EC2 . ​​M9g instances serve a broad range of general-purpose workloads including application servers, microservices, gaming, caching, and containers, while also delivering the performance needed for agentic AI use cases like real-time reasoning, code generation, and multi-step orchestration.   ​​M9gd instances offer local NVMe-based SSD block-level storage for customers that require high-speed, low-latency local storage, such as media processing, batch and log processing, and applications that need access to temporary storage including caches and scratch files.​ ​​​M9g and M9gd instances deliver up to 25% better compute performance compared to AWS Graviton4-based M8g and

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) P6-B200 instances accelerated by NVIDIA Blackwell GPUs are available in AWS GovCloud (US-East) Region. These instances offer up to 2x performance compared to P5en instances for AI training and inference. P6-B200 instances feature 8 Blackwell GPUs with 1440 GB of high-bandwidth GPU memory and a 60% increase in GPU memory bandwidth compared to P5en, 5th Generation Intel Xeon processors (Emerald Rapids), and up to 3.2 terabits per second of Elastic Fabric Adapter (EFAv4) networking. P6-B200 instances are powered by the AWS Nitro System, so you can reliably and securely scale AI workloads within Amazon EC2 UltraClusters to tens of thousands of GPUs. P6-B200 instances are now available in p6-b200.48xlarge size in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), AWS GovCloud (US-West) and AWS GovCloud (US-East) Region. To learn more about P6-B200 instances, visit Amazon EC2 P6 instances.

AWS today announces that AWS Cost and Usage Report 2.0 (CUR 2.0) now supports updates to data table configurations via the AWS Management Console and SDK/CLI. This capability allows customers to modify their existing exports to take advantage of new CUR 2.0 features without having to delete and recreate their exports. Previously, customers configured CUR 2.0 exports with specific table settings — including export content, time granularity, column selection, export format, and destination settings. When AWS introduces new features, such as additional columns and finer row-level granularity, existing export settings intentionally remained unchanged to protect ETL jobs that depended on a stable schema. However, customers who wanted to adopt these new capabilities and were ready for the new schema couldn't simply update their preference in existing export. They had to delete their existing export and create a new one with the new preference. With this launch, customers can update their tab

You can now create Amazon FSx for OpenZFS file systems with the Intelligent-Tiering storage class in 8 additional AWS Regions across the US, Europe, Asia Pacific, and South America. FSx Intelligent-Tiering is built for general-purpose file workloads such as file shares, archives, media libraries, and migrations from on-premises HDD storage. It automatically moves your data across three storage tiers (Frequent Access, Infrequent Access, and Archive) based on access patterns, and an optional SSD read cache keeps your active data fast. You get high performance for active workloads and low-cost storage for everything else, paying only for what you store with no capacity to manage. With FSx Intelligent-Tiering, you can save up to 85% compared to the FSx SSD storage class and up to 20% compared to on-premises HDD-based NAS. With this expansion, the FSx Intelligent-Tiering storage class is now available for FSx for OpenZFS file systems in the following additional AWS Regions: US West (N. Cali

Amazon SageMaker Unified Studio Notebooks now support Amazon EMR Serverless with Apache Spark Connect, giving data engineers and analysts more flexibility in choosing their Spark runtime for interactive analytics and data engineering workloads. In addition to Amazon Athena Spark, users can now leverage Amazon EMR Serverless as their Spark runtime, selecting the optimal engine based on their requirements. With this launch, you can run PySpark and Spark SQL on an EMR Serverless Spark Application in Notebook cells. Users can select their Spark runtime from the Notebook side panel, and the selected runtime applies to both Python and SQL cells. Additionally, users can leverage SageMaker Data Agent, the built-in AI assistant, to generate code and execution plans from natural language prompts, accelerating Spark development workflows with EMR Serverless. Organizations can leverage pre-initialized capacity to improve session start times, while benefiting from unified Spark UI monitoring across

You can now create Amazon S3 Access Grants in the AWS European Sovereign Cloud (Germany) Region. Amazon S3 Access Grants map identities in directories such as Microsoft Entra ID, or AWS Identity and Access Management (IAM) principals, to datasets in S3. This helps you manage data permissions at scale by automatically granting S3 access to end users based on their corporate identity. Visit the AWS Region Table for complete regional availability information. To learn more about Amazon S3 Access Grants, visit our product page .

Today, AWS announces the preview of AWS FinOps Agent, a frontier agent for FinOps practitioners and engineering teams that answers cost questions, surfaces optimization opportunities, automatically investigates cost anomalies, and runs recurring FinOps workflows on a schedule you define. With the AWS FinOps Agent, you can ask questions about your AWS costs and generate cloud cost reports for finance and engineering teams. The agent surfaces rightsizing, idle resource, and Savings Plans recommendations from AWS Cost Optimization Hub and AWS Compute Optimizer, and can open Jira tickets on your behalf. When a cost anomaly is detected, FinOps Agent can automatically investigate the root cause and can post the findings to a Slack channel, so engineering teams are notified without manual triage. AWS FinOps Agent (preview) is available in the US East (N. Virginia) Region and includes cost and usage data covering all AWS Regions, except AW

AWS is announcing the general availability of metal-48xl and metal-96xl sizes for Amazon Elastic Compute Cloud (Amazon EC2) M8in, M8ib, M8idn, M8idb, R8in, R8ib, R8idn, and R8idb instances. These instances are powered by custom sixth generation Intel Xeon Scalable processors, available only on AWS and feature the latest sixth generation AWS Nitro cards. These instances deliver up to 43% better compute performance per vCPU compared to previous generation M6in, M6idn, R6in, and R6idn instances. M8in, M8idn, R8in, R8idn instances deliver 600 Gbps network bandwidth, the highest network bandwidth among enhanced networking EC2 instances. M8in and R8in instances are ideal for workloads such as real-time big data analytics, distributed web scale in-memory caches, caching fleets for AI/ML clusters, and Telco applications such as 5G User Plane Function (UPF). M8idn and R8idn instances are ideal for network-intensive general purpose workloads requiring local storage, such as distributed compute,

Claude Fable 5 is generally available on AWS and makes Mythos-level capabilities available to all customers, with strong safeguards designed to make it safe for broader use. Fable 5 is state-of-the-art on nearly all tested benchmarks and delivers a step-change in autonomous knowledge work and coding for developers and enterprises building production AI applications. Claude Mythos 5, the same model without those safety classifiers, is available to a small group of customers who currently have access to Claude Mythos Preview. Claude Fable 5 can run for extended periods on complex knowledge work and coding tasks without intervention, representing a fundamental shift in the types of problems customers can solve with AI. It is built for professional tasks in finance, legal, marketing, sales, data, and engineering — proactively self-updating skills based on learnings, developing its own evaluation harnesses, and verifying its work before delivery.  Customers have two ways to access Clau