Tag: Tools

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 monito

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

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 tw

AWS Backup support for Amazon Elastic Kubernetes Service (EKS) is now available in the AWS European Sovereign Cloud (Germany) Region. This expansion brings fully-managed, policy-based data protection and recovery to your Amazon EKS clusters in this newly supported Region — including automated scheduling, retention management, immutable vaults, and cross-Region and cross-account copies. You can use AWS Backup for Amazon EKS to protect entire EKS clusters, specific namespaces, or individual persistent volumes using a centralized, agent-free solution that replaces custom scripts or third-party tools. Use AWS Backup to protect your clusters for disaster recovery, compliance requirements, or before EKS cluster upgrades. To get started, visit the AWS Backup console, refer to the AWS Backup documentation, or read the

Amazon EMR Serverless now supports interactive sessions with Spark Connect, enabling you to develop and run Apache Spark applications from managed notebooks in Amazon SageMaker Unified Studio, as well as your favorite notebook environments and IDEs such as Jupyter and Visual Studio Code. You can also monitor and debug active and completed sessions in the EMR console, and get granular cost and usage visibility for individual sessions.    An interactive session provides a persistent Spark context that seamlessly spans across cells and scripts, enabling you to blend local Python code execution with remote Spark operations within a unified environment. This is enabled by Spark Connect's client-server architecture, which decouples your application client from the Spark driver and allows you to maintain your preferred development environment and tooling while Spark infrastructure runs independently on EMR Serverless. This architecture unlocks workflows including

AWS Cost Explorer now supports 'Analyze with Amazon Q', a new capability that delivers comprehensive cost explanations for any report you configure in Cost Explorer. With a single button click you now can receive detailed analysis from Amazon Q Developer covering your cost trends, top cost drivers, and anomalies. All analysis uses your exact filters and time-period and provides guidance to discover optimization opportunities through follow-up questions. Previously, cost analysis required manual investigation across multiple filters and data points. With 'Analyze with Amazon Q', you simply configure your Cost Explorer view and click a single button. Amazon Q analyzes your current context and delivers explanations directly in its chat panel, adapting to what you're viewing: historical explanations for past dates, forecast explanations for future dates, or both for mixed periods. You can then ask follow-up questions to explore any insights related to your cost data in greater d

AWS Compute Optimizer now identifies idle resources for Amazon DynamoDB provisioned tables, Amazon ElastiCache (Redis and Valkey), Amazon MemoryDB, Amazon DocumentDB (provisioned and serverless), Amazon WorkSpaces, and Amazon SageMaker endpoints. This expansion enables you to detect unused resources across more of your AWS environment and identify potential cost savings. Compute Optimizer analyzes utilization metrics to determine whether a resource is idle. Customers can set this lookback period based on the nature of their workloads. For each resource type, Compute Optimizer evaluates service-specific signals such as consumed capacity, cache hits, active connections, and CPU utilization. When Compute Optimizer identifies potential idle resources, it surfaces these recommendations, along with detailed utilization metrics and estimated savings in the console, enabling you to evaluate recommendations before acting. You can also view idle resource recommendations across all AWS

Effective today, Amazon MSK Express Brokers support automatic topic creation with Kafka Streams. Customers can now deploy their Kafka Streams applications on Express Brokers without needing to manually pre-create or manage topics for stateful operations. MSK Express Brokers are designed to deliver up to three times more throughput per broker, scale up to 20 times faster, and reduce recovery time by 90 percent. Kafka Streams uses topics to store state and repartition data for stateful operations. Previously, customers running Kafka Streams with Express Brokers had to manually name and pre-create these topics before deploying their application. With this launch, these topics are created automatically when the application starts, simplifying deployment and reducing operational setup for Kafka Streams applications on Express Brokers. This capability is available today in all

Amazon DocumentDB (with MongoDB compatibility) now supports engine minor versions, starting with 5.0.1. This release delivers enhanced aggregation capabilities with new operators ($rand, $pow, $dateToParts, $dateFromParts), the active connections metric to monitor instances, and granular command-level performance metrics in CloudWatch (find, insert, findAndModify, update, etc.). For a full list of what's included, see release notes. Minor versions provide new features and bug fixes within the same major version, giving you more control over when and how you upgrade your clusters. We recommend upgrading to the latest minor version to benefit from these performance enhancements, bug fixes, and new capabilities. You can specify minor version 5.0.1 when creating a new cluster, or manually upgrade an existing 5.0.0 cluster to 5.0.1 using the AWS Management Console or AWS CLI (via the mo