Kategorie: Amazon AWS

Amazon EKS Provisioned Control Plane now delivers faster pod autoscaling

Amazon EKS now delivers faster pod autoscaling across all Provisioned Control Plane clusters by increasing Horizontal Pod Autoscaler (HPA) sync concurrency to up to 40 times the default Kubernetes value. This reduces the time it takes for HPA-driven workloads to scale in response to increased load, enabling faster responsiveness to demand. The Kubernetes Horizontal Pod Autoscaler (HPA) continuously monitors workload metrics and adjusts pod counts to match demand. In clusters running hundreds or thousands of HPA objects, the speed at which the Kubernetes control plane processes these objects determines how quickly workloads scale in response to changing demand. The HPA sync concurrency setting controls how many HPA objects the control plane evaluates in parallel. By increasing this value, Provisioned Control Plane clusters now process more HPA objects simultaneously, reducing the time between detecting increased load and scaling out pods. This enhancement is available to all customers using EKS Provisioned Control Plane and requires no configuration changes. To learn more about this enhancement, see EKS Provisioned Control Plane in the EKS User Guide.
Quelle: aws.amazon.com

Amazon GameLift Streams now supports Custom Aspect Ratio and Dynamic Resolution

Amazon GameLift Streams now supports Custom Aspect Ratio and Dynamic Resolution, giving you greater control over the streaming experience across diverse player devices and network conditions.
With Custom Aspect Ratio, you can configure a specific resolution per stream session to match your player’s device — including portrait, landscape, ultra-wide, and square aspect ratios. This eliminates letterboxing or pillarboxing, delivering native full-screen experiences on mobile phones, tablets, and non-standard displays. Specify any resolution from 320 to 4096 pixels per dimension (up to 1080p total pixel budget) using the DisplayConfiguration parameter in the StartStreamSession API. You can also try custom resolution from the AWS Console.
Dynamic Resolution automatically adapts stream quality when a player’s network bandwidth fluctuates. When bandwidth drops, the stream gracefully reduces resolution to maintain smooth playback without frame drops or disconnections — and automatically recovers to full quality when conditions improve. Dynamic Resolution is enabled by default for all new stream groups with no configuration required. Customers will need to download the new Web SDK.
Both features are available in all AWS Regions where Amazon GameLift Streams is offered. To learn more, see Custom stream resolution in the Amazon GameLift Streams Developer Guide.    https://docs.aws.amazon.com/gameliftstreams/latest/developerguide/custom-stream-resolution.html
Quelle: aws.amazon.com

AWS Glue Data Quality now supports distribution statistics for data profiling

AWS Glue Data Quality now supports a new Distribution Analyzer that generates frequency distribution profiles for your data. Using this new Distribution Analyzer in the Data Quality Definition Language (DQDL), you can generate histograms for numeric columns and value distributions for categorical, date, and boolean columns. With support for custom bin counts, you can explore the shape and patterns of your data at the granularity that matters most to your use case. Understanding how data is distributed is foundational to building reliable data pipelines. Distribution statistics help you quickly identify skewness, outliers, and unexpected patterns across your datasets, without writing custom code. The capability integrates directly with your existing DQDL rulesets, so you can add distribution profiling alongside your current data quality checks in a single evaluation run. Distribution statistics are stored in Amazon S3 for future querying through services like Amazon Athena, and are also surfaced through APIs, making it easy to integrate distribution insights into monitoring workflows and visualization tools, including SageMaker Unified Studio. AWS Glue Data Quality distribution statistics are available in all AWS commercial regions and AWS GovCloud (US) regions. To learn more about Glue Data Quality, visit the AWS Glue Data Quality documentation. To get started with using Distribution Analyzer, visit the Analyzers documentation.
Quelle: aws.amazon.com

AWS Glue Data Quality now supports anomaly detection and writing results to the AWS Glue Data Catalog

AWS Glue Data Quality now supports anomaly detection for Catalog-based data quality evaluations and the ability to write evaluation results to AWS Glue Data Catalog (GDC) tables. These capabilities work across both ETL jobs and Catalog evaluations, giving you a consistent data quality experience regardless of workflow type. With anomaly detection support for GDC, you can identify unexpected changes in data statistics such as sudden drops in distinct values or row count spikes in your GDC tables using ML-powered time-series forecasting, without writing rules with explicit thresholds. This is especially valuable for data engineers monitoring hundreds of tables in the GDC who need to surface issues automatically. With results storage in GDC, Data Quality rule outcomes, profiling metrics, and anomaly predictions (with confidence bounds) are written back to GDC tables, creating a queryable record of all quality evaluations. Whether the evaluation runs in an ETL job or directly on a Catalog table, results can be queried at any time using standard SQL. AWS Glue Data Quality anomaly detection and Catalog results storage are available in all AWS commercial regions and AWS GovCloud (US) regions. To get started, visit the AWS Glue Data Quality documentation.
Quelle: aws.amazon.com

Amazon Neptune now supports tag-based access control for IAM

Amazon Neptune Database now supports tag-based access control (TBAC) for IAM, enabling customers to use AWS resource tags and IAM principal tags as conditions in IAM policies and Service Control Policies (SCPs) to control access to Neptune data-plane operations. Neptune already provides robust security through VPC isolation, TLS encryption, and IAM authentication, but customers managing multiple clusters at scale needed a dynamic, attribute-based mechanism to enforce organizational access boundaries. TBAC addresses this by allowing administrators to govern cluster access without enumerating specific cluster ARNs in every policy. With TBAC, IAM principals can only perform `neptune-db:*` actions against Neptune clusters whose tags match their own — for example, a principal tagged `Project=FraudDetection` is automatically restricted to clusters sharing that same tag. This eliminates lateral access risk within shared VPC environments, enforces team and environment-level isolation across projects, and supports federated identity workflows using SAML or OIDC session tags from external identity providers. Granular permissions like neptune-db:QueryLanguage can be used alongside TBAC for more fine-grained access control. This feature is available in all AWS Regions where Amazon Neptune is available and requires Neptune engine version 1.2.0.0 or later with IAM authentication enabled. To learn more about configuring tag-based access control for Amazon Neptune, including how to tag your DB clusters and IAM principals and deploy organization-wide guardrails using SCPs, visit the Amazon Neptune documentation.
Quelle: aws.amazon.com

AWS Elemental MediaTailor adds configurable ad timeout and concurrency controls for improved ad fill and faster startup

AWS Elemental MediaTailor now gives you direct control over ad decision server (ADS) timeout. Previously, changing these settings required contacting AWS Support. You can now configure individual HTTP ad request timeouts, total ad personalization time budgets for live, VOD, and live ad prefetch, and enable parallel ADS requests.
These settings allow you to optimize ad delivery performance for your specific workflows. For example, you can increase the personalization time budget for live events to improve ad fill rates or enable parallel ADS requests in VOD workflows to reduce overall response time for faster video startup. New prefetch-specific timeout settings give you additional granularity for livestream ad retrieval.
You can configure these settings through the AWS Elemental MediaTailor console, AWS CLI, or AWS SDKs using the new AdsPersonalizationTimeouts and AdsPersonalizationConcurrency parameters on your playback configurations.
This feature is available in all AWS Regions where AWS Elemental MediaTailor is available. 
To learn more about configuring ADS request timeouts, personalization time budgets, and concurrency, see Advanced settings in the AWS Elemental MediaTailor User Guide.
Quelle: aws.amazon.com

AWS Security Hub MCP App brings exposure findings into your AI-assisted workflow (Preview)

AWS announces the preview of the AWS Security Hub MCP App, a local Model Context Protocol (MCP) server that brings your Security Hub exposure findings directly into Claude Desktop.  This capability can help accelerates your security investigations by reducing context switching and manual triage, letting you explore and act on your exposures without leaving your AI-assisted workflow.
With the Security Hub MCP App, you can investigate your security posture in natural language: view your top exposure findings, drill into a finding’s attack path and expanded network path, examine correlated findings and affected resource configurations, and get remediation recommendations. Each tool call returns both a text summary for your AI agent to reason overover and an interactive visualization for you to verify in the same conversation. The MCP server runs locally on your machine using your existing AWS credentials, and every tool is read-only,– no changes are made to your environment.
The Security Hub MCP App is available at no additional cost to Security Hub customers. This feature is available in preview in all AWS commercial Regions that support Security Hub. To learn more, see the AWS Security Hub User Guide and the AWS Security Hub product page. For the full list of Regions, see the AWS Regional Services List.
Quelle: aws.amazon.com

AWS Lambda now publishes logs for Lambda Managed Instances capacity providers

AWS Lambda now publishes logs for Lambda Managed Instances (LMI) capacity providers to Amazon CloudWatch Logs, giving you visibility into scaling activity and instance lifecycle operations. LMI enables you to run Lambda functions on Amazon EC2 instances while maintaining serverless operational simplicity. Capacity providers are resources that let you define compute resources that Lambda provisions on your behalf. With capacity provider logs, you can monitor, troubleshoot, and optimize these managed EC2 instances, helping you quickly diagnose provisioning issues and understand scaling behavior.
Customers use LMI to operate high-volume, predictable workloads with specialized compute configurations and achieve cost efficiency through EC2 pricing options like Savings Plans and Reserved Instances. With this launch, Lambda automatically generates logs for compute resources managed by capacity providers and delivers them to CloudWatch Logs. Lambda publishes structured JSON logs capturing instance lifecycle events like launches, terminations, and health checks. This structured format lets you identify failed operations and provisioning errors through CloudWatch Logs filtering, helping you resolve issues quickly and shorten debugging cycles.
The capacity provider logs are available in all AWS Commercial Regions where LMI is available. The logs are enabled by default for all capacity providers. You can view your capacity provider logs by visiting the Lambda console’s capacity provider page. You can use the Lambda API, Lambda console, AWS CLI, AWS SAM, or AWS CloudFormation to change capacity provider log configuration. Standard Amazon CloudWatch Logs charges apply. To learn more, visit the AWS Lambda Managed Instances product page and documentation. 
Quelle: aws.amazon.com

Amazon Kinesis Data Streams now supports scaling down ingest capacity with warm throughput

Amazon Kinesis Data Streams is a serverless streaming data service that makes it easy to capture, process, and store data streams at any scale. On-demand streams automatically increase ingest capacity in response to rising data ingest usage. With On-demand Advantage mode, you can proactively manage stream capacity using warm throughput to prepare streams for sudden changes in data traffic. We are extending warm throughput with the ability to also scale down ingest capacity, giving you full control to scale your stream’s write throughput up or down.
To scale down, simply set a lower warm throughput value on your on-demand stream. The stream adjusts to the requested capacity or the amount needed to support peak data ingest usage in the last hour, whichever is higher. This ensures your stream always retains sufficient capacity for current traffic while releasing excess capacity you no longer need. As a result, you get optimal stream-processing performance and cost efficiency. 
Warm throughput scale-down is available at no additional cost for all on-demand streams with On-demand Advantage mode enabled.  For more information about On-demand Advantage, see Choose the right mode to stream in in the Amazon Kinesis Data Streams Developer Guide. To get started with the feature, see Update a stream. For pricing details, see Amazon Kinesis Data Streams pricing.
The feature is available in all AWS Regions where Amazon Kinesis Data Streams On-demand Advantage is supported. 
 
Quelle: aws.amazon.com

Amazon EC2 Dedicated Hosts now support host resource groups without self-managed licenses

Starting today, customers can create Host Resource Groups (HRGs) for EC2 Dedicated Hosts without the previously required step of creating Self-Managed Licenses (SMLs) and associating AMIs through AWS License Manager.
This flexibility is particularly valuable for EC2 Mac Instance customers and for customers who need Dedicated Hosts for hardware-level isolation rather than Bring Your Own License (BYOL). Customers with BYOL workloads can continue to create HRGs with SMLs to ensure that only instances from associated AMIs can be launched on the host and track host-level license consumption.
To create an HRG without SML, uncheck the “Restrict to AMIs associated with self-managed license” option when creating a Host Resource Group in the EC2 Console, or set instance-launch-option to license-configuration-required via the AWS CLI.
This feature is available in all AWS Regions where Host Resource Groups are supported. To learn more, visit the Host Resource Group User Guide
Quelle: aws.amazon.com