Kategorie: Amazon AWS

AWS Security Agent now supports email-based MFA for penetration testing

AWS Security Agent (now part of AWS Continuum) now enables penetration testing of applications that use email-based multi-factor authentication (MFA) as part of their login flow. Previously, applications requiring one-time codes or verification links sent by email were out of scope for automated pentesting because the agent had no mechanism to intercept those messages. This launch expands coverage for penetration testing customers whose target applications rely on email-based authentication.
To use this feature, AWS Security Agent generates a unique forwarding address per credential, allowing you to route your application’s MFA emails directly to the agent using a forwarding rule in your existing email provider. During a pentest, the agent automatically reads the forwarded message and submits the code or link to complete authentication — no email account credentials are stored, preserving a strong privacy posture. This capability complements existing TOTP support, giving customers a unified solution for testing applications across multiple MFA methods.
This feature is available in all AWS Regions where AWS Security Agent is supported.
To learn more, visit the AWS Security Agent product page and the AWS Security Agent User Guide. 
Quelle: aws.amazon.com

AWS Transform for migrations automates post-launch actions

AWS Transform now automates the configuration and execution of post-launch actions through the migration workflow. Define actions at the account level and apply them automatically to each source server across your target accounts, including multi-account migrations. Automating these actions removes the slow, error-prone work of configuring them server by server, so your team moves more servers with less hands-on effort.
Post-launch actions run through AWS Systems Manager (SSM) immediately after test or cutover launch. You can use predefined actions or bring your own SSM document. For source server bulk configurations, the migration inventory file now includes a new structure for post-launch actions, making it easier to review and modify actions per source server.
The AWS Transform for migrations agent automates your migration configuration end to end, including replication templates, EC2 launch templates, EC2 right-sizing, and post-launch actions, with the flexibility to create and edit any of these at the source server level. 
This new capability is available in all AWS Regions where AWS Transform is offered.
To learn more, please visit the AWS Transform User Guide.
Quelle: aws.amazon.com

AWS Glue Data Quality makes ETL anomaly detection free and improves anomaly predictions

AWS Glue Data Quality now offers improved anomaly detection with a new observation mode that reduces detection of false anomalies and removes pricing for anomaly detection in ETL jobs. Customers using notebook-based or exploratory workflows now benefit from smarter anomaly detection that gracefully handles irregular data arrival intervals. This new capability avoids over-extrapolating trends by using a constant baseline instead of a linear trend, delivering more accurate alerts and reducing noise so teams can focus on genuine anomalies. The new anomaly detection observation mode is particularly useful for exploratory data analysis, datasets with flat or random patterns, workloads without predictable trends and cases where you run data quality checks on varying schedules or in interactive environments like notebooks. Additionally, anomaly detection for AWS Glue ETL jobs is now available at no additional cost, so you can monitor data quality anomalies across all your Glue pipelines without worrying about pricing. These improvements are available in all AWS commercial regions and AWS GovCloud (US) regions. To get started, visit the AWS Glue Data Quality documentation. To learn more about pricing, see the AWS Glue pricing page.
Quelle: aws.amazon.com

Amazon Keyspaces (for Apache Cassandra) is now available in the Canada West (Calgary) Region (ca-west-1)

Amazon Keyspaces (for Apache Cassandra) is now available in the Canada West (Calgary) Region (ca-west-1), allowing customers in the Canada West Region to build Cassandra-compatible applications with lower latency while keeping their data within the Region to meet data residency requirements. 
Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. 
This regional expansion enables organizations in Canada to build highly scalable, low-latency applications using familiar Cassandra Query Language (CQL) without the operational burden of managing Cassandra clusters.
To learn more about on Keyspaces, visit the Amazon Keyspaces documentation.
Quelle: aws.amazon.com

AWS Lambda announces scalable network bandwidth up to 3,000 Mbps for functions outside a VPC

AWS Lambda now supports scalable network bandwidth for Lambda functions, enabling faster data transfer to and from your execution environment for latency-sensitive workloads. This feature enables functions outside a VPC configured with 2 GB of memory or more to access network bandwidth that scales proportionally, from 625 Mbps at 2 GB up to 3,000 Mbps at 10 GB. Customers use Lambda to build latency-sensitive data processing workloads, which need to transfer large volumes of data – up to several terabytes – from external data sources into the function’s execution environment for processing. As data volume and performance requirements grow, the existing limit of 625 Mbps can constrain data transfer speeds to and from an execution environment. With this launch, network throughput increases proportionally from 625 Mbps at 2 GB up to 3,000 Mbps at 10 GB, helping reduce function execution times and per-invocation costs while improving end-user experience. To get started, submit a request through AWS Service Quotas under the Network bandwidth per execution environment quota to enable scalable network bandwidth on your account. Once enabled, bandwidth will scale automatically based on your function’s memory configuration for all functions outside a VPC in your account. Scalable network bandwidth for functions outside a VPC is available at no additional charge in all commercial AWS Regions. To learn more, visit the Lambda quotas page. 
Quelle: aws.amazon.com

Amazon Aurora serverless now scales faster to support agentic AI and other bursty workloads

Amazon Aurora serverless now delivers higher initial capacity during scale-up events, reaching up to 12 ACUs within a second and continuing to scale up to 256 ACUs as your workload grows. When the workload finishes, Aurora serverless automatically scales down to zero. This makes it especially well-suited for agentic AI applications, which typically have bursts of activity, long idle windows, and unpredictable traffic patterns. Aurora serverless handles all of it automatically, scaling capacity with your agents, so you only pay for what you use. This enhancement is enabled by default on all Aurora serverless clusters running on platform version 3 or 4, with no configuration changes required. Existing clusters on platform versions 1 and 2 can upgrade directly to the latest platform version 4 to benefit from these improvements. You can verify your cluster’s platform version in the AWS Management Console under the instance configuration section, or via the RDS API’s ServerlessV2PlatformVersion parameter. For pricing details and Region availability, visit Amazon Aurora Pricing. To learn more, read the Aurora serverless scaling documentation, and get started by creating an Aurora serverless database in just a few steps in the AWS Management Console.
Quelle: aws.amazon.com

AWS IAM Identity Center makes managment of AWS account access optional for new organization instances

AWS IAM Identity Center now lets you decide whether to enable management of AWS account access when you create a new organization instance. This allows you to use IAM Identity Center to manage access to AWS applications only, without the need to manage access to AWS accounts. This feature is available at the time of initial configuration of an IAM Identity Center instance and does not affect existing IAM Identity Center instances.
IAM Identity Center enables you to connect your workforce identities to AWS once and offer AWS application owners across your organization streamlined access management. Application end users benefit from single sign-on, user awareness, and consistent authentication experience across AWS applications. Previously, this meant you also needed to manage access to AWS accounts. With this release, account management is now optional. When you choose not to enable management of AWS accounts, IAM Identity Center does not provision its service-linked role into your member accounts, which reduces the access surface in your environment. You can enable account management permissions later through instance settings or the UpdateInstance API. 
This capability is available in all AWS Regions where IAM Identity Center is available. To get started, see Configure instance settings in the IAM Identity Center User Guide.
Quelle: aws.amazon.com

Amazon DynamoDB now supports real-time vector search

Today, AWS announces the general availability of vector search for Amazon DynamoDB, a new feature to index and search vectors in real time. As vector datasets grow into the billions or trillions, vector search at scale traditionally trades off search speed, scale, and accuracy: latency climbs with vector count unless you accept lower recall or throughput. DynamoDB now supports native vector search with single-digit millisecond latency at 99%+ recall and is designed for any scale, even trillions of vectors. With DynamoDB vector search, you store vector embeddings alongside your other attributes and generate them using a model of your choice, including models available on Amazon Bedrock. You create a vector index and run approximate nearest neighbor searches, pick the vector index partition key to scale, and filter on attributes to scope results. You get the same serverless benefits you rely on today: zero infrastructure management, zero downtime, zero maintenance windows, and pay for only what you use. You can already use DynamoDB to store memory for AI agents, and with vector search you can now add semantic retrieval over that memory for agentic grounding, along with product similarity search, personalized advertising, retrieval augmented generation, and recommendation systems, with predictable performance. To learn more, visit the AWS News Blog, Amazon DynamoDB product page, and Amazon DynamoDB Developer Guide.
Quelle: aws.amazon.com

AWS Marketplace adds AI Insights so buyers can understand pricing before they buy

You can now understand how a product’s pricing works before you buy it. Available in the pricing section of the listing in AWS Marketplace, AI Insights explains each product’s pricing in plain language: what a pricing unit maps to, how your bill changes as usage scales, how multiple pricing dimensions combine into one cost, and what is and isn’t included. Answering these questions used to mean having to visit multiple websites and piecing together pricing details on your own. Now the context sits on the listing, so you can evaluate pricing and move to purchase without switching tabs.
AI Insights cites sources so you can see where the explanations come from. AI Insights draws from the pricing the seller publishes on the Marketplace listing, and additional pricing context on the seller’s public website.
AI Insights is live today on most listings where external pricing context is available. It is available in all commercial AWS Regions where AWS Marketplace is available. To see it, open any product listing on the AWS Marketplace website and scroll to the pricing section. Sellers can review what appears on their listing and request edits at any time through the Contact Us form linked in the AI Insights page on the AWS Marketplace Seller Guide.
Quelle: aws.amazon.com

Run interactive workloads on Amazon EMR on EC2 with Spark Connect

Amazon EMR on EC2 now supports interactive Apache Spark sessions with Spark Connect. Data engineers and data scientists can develop and debug Apache Spark applications interactively from managed notebooks in Amazon SageMaker Unified Studio and their own IDEs, such as Jupyter and Visual Studio Code, with each session running on dedicated EMR on EC2 clusters. You can also monitor and debug active and completed sessions in the EMR console.
 
An interactive session provides a persistent Spark context that spans across cells and scripts, letting you blend local Python code execution with remote Spark operations. Spark Connect’s client-server architecture decouples your application client from the Spark driver and allows you to maintain your preferred development environment and tooling while Spark infrastructure runs on the cluster. This architecture supports workflows including ad hoc data exploration, iterative step-by-step debugging, and incremental PySpark job development before deploying to production. For observability, you get real-time session monitoring via the Spark UI, history tracking through the Spark History Server, and session management from the EMR console or API/CLI/SDK.
 
Interactive Sessions is available on Amazon EMR on EC2 with AWS runtime for Apache Spark (emr-spark-8.0) and later, in all AWS Regions where Amazon EMR is available, except the AWS GovCloud Regions and the China Regions. The Amazon SageMaker Unified Studio experience is available in supported regions. To get started, visit the Interactive sessions with Spark Connect guide or the Amazon SageMaker Unified Studio Getting Started guide.
Quelle: aws.amazon.com