Kategorie: Amazon AWS

Amazon DynamoDB global tables with multi-Region strong consistency now supports additional AWS Regions and cross-continent configurations

Starting today, Amazon DynamoDB global tables with multi-Region strong consistency (MRSC) is available in five additional AWS Regions: Canada (Central), Europe (Stockholm), Europe (Spain), Asia Pacific (Mumbai), and Asia Pacific (Singapore), bringing the total number of supported Regions to 15. You can now create an MRSC global table in any three-Region configuration across the 15 supported AWS Regions, configured with either three replicas or two replicas and one witness Region. This includes configurations that span North America, Europe, and Asia Pacific.
MRSC lets you build highly available multi-Region applications with a recovery point objective (RPO) of zero. By choosing replica Regions closer to your users in more geographies, you can route applications to nearby DynamoDB endpoints for strongly consistent reads while keeping your application available during Regional impairments. MRSC is ideal for global applications with strict consistency requirements, such as user profile management, inventory tracking, order state, and entitlement management.
To get started and view the complete list of supported Regions and configuration options, see the DynamoDB Developer Guide. To learn more about building resilient multi-Region applications, visit the DynamoDB global tables page.
Quelle: aws.amazon.com

Amazon EMR on EKS now supports IPv6 Amazon EKS clusters

Today, AWS announces that Amazon EMR on EKS now supports running workloads on IPv6 Amazon Elastic Kubernetes Service (Amazon EKS) clusters. Amazon EMR on EKS enables data platform and analytics teams to run open-source big data frameworks such as Apache Spark and Apache Flink on Amazon EKS. With IPv6 support, teams operating at scale can now run these workloads on IPv6 Amazon EKS clusters, giving them access to the vastly larger address space of IPv6 as their analytics workloads grow.
You can now scale large Spark and Flink workloads using the expanded IPv6 address space, which removes the need for IPv4 conservation workarounds such as secondary CIDR ranges or prefix delegation. High-executor jobs, such as 500-executor Spark jobs, can run concurrently without planning around address limits. To submit workloads, use StartJobRun, Spark Connect Interactive Endpoints, and Amazon SageMaker Unified Studio with no additional configuration, while the Flink, Livy, and Spark Operators are also supported. This capability is available at no additional cost, starting with Amazon EMR releases emr-7.14.0 and emr-spark-8.0.0.
IPv6 cluster support is available in all AWS Regions where Amazon EMR on EKS and IPv6 Amazon EKS clusters are available.
Amazon EMR on EKS IPv6 cluster support includes detailed setup instructions and documentation on supported submission models. Visit the Amazon EMR on EKS product page and the IPv6 documentation to learn more. 
Quelle: aws.amazon.com

Amazon Kinesis Data Streams announces Service-Managed Partition Keys for simplified data ingestion

Amazon Kinesis Data Streams now supports service-managed partition keys for On-Demand Standard and On-Demand Advantage streams, automatically distributing records across shards without requiring customers to specify partition keys to publish data. This capability simplifies data ingestion for workloads where record ordering is not required, eliminating hot partition keys and reducing time to production for streaming workloads.
Amazon Kinesis Data Streams is a serverless streaming data service that makes it easy to capture, process, and store data streams at any scale. Many streaming use cases such as log aggregation, metrics collection, and IoT telemetry do not require ordering guarantees and benefit from prewarmed capacity for instant scaling. Previously, customers generated random partition keys (such as UUIDs) to distribute data, but random partitioning can still produce uneven throughput across shards, causing throttling for some partition keys even when the stream has sufficient aggregate capacity. By opting into service-managed partition keys, customers no longer need to specify partition keys when publishing data to streams in on-demand mode. The service automatically distributes records based on available warm capacity, allowing customers to scale to gigabytes per second without maintaining any distribution logic. Customers who want to send records without specifying a partition key can simply upgrade to the latest AWS SDK or Kinesis Producer Library (KPL) version to benefit from this capability.
Service-managed partition keys for Amazon Kinesis Data Streams is available today in all AWS commercial regions at no additional cost. To get started, visit the Amazon Kinesis Data Streams documentation (https://aws.amazon.com/kinesis).
Quelle: aws.amazon.com

Amazon Connect Customer now provides routing step data in the analytics data lake

Amazon Connect Customer now provides routing step data in the analytics data lake, making it easier for customers to generate insights from routing decisions. Using the data lake, customers can leverage Amazon Athena and Amazon Quick to analyze trends, such as contacts queued and contacts joined at each routing step, without complex data pipelines. For example, an analyst can now report on how contacts progressed through each routing step, identify where agent matching criteria were relaxed, and measure the impact of routing step configurations on wait times and agent utilization.
Routing step data is available in all AWS regions where Amazon Connect Customer data lake is offered. To learn more about Amazon Connect Customer data lake, see the Amazon Connect Customer Administrator Guide.  To learn more about Amazon Connect Customer, visit the Amazon Connect Customer website. 
Quelle: aws.amazon.com

Amazon Bedrock Managed Knowledge Base now supports Salesforce and Zendesk as native data source connectors

AWS announces Salesforce and Zendesk data source connectors for Amazon Bedrock Managed Knowledge Base, a fully managed retrieval-augmented generation (RAG) service. Customers can now sync Salesforce knowledge articles and Zendesk articles and community posts directly into their managed knowledge base.

Previously, bringing content from these platforms into Bedrock Knowledge Bases required building custom ingestion pipelines—now, you provide your instance credentials, and the connectors handle data crawling, metadata extraction, and incremental sync automatically.

These connectors make it easy to build AI agents and assistants grounded in the support and product knowledge your teams already maintain in Salesforce and Zendesk. For example, power a customer-facing support bot with up-to-date Zendesk help center articles and community answers, or build an internal sales enablement assistant that retrieves relevant Salesforce knowledge articles during deal preparation. By keeping your knowledge base in sync with these platforms, your retrieval-augmented generation applications always reflect the latest content without manual intervention.

To learn more, see Salesforce data source connector and Zendesk data source connector in the Amazon Bedrock User Guide. For more information about Amazon Bedrock Managed Knowledge Base, visit the Amazon Bedrock Knowledge Bases product page.
Quelle: aws.amazon.com

Billing Transfer now supports automatic billing group creation for two-level transfers

AWS Billing Transfer users can now enable the Auto-Billing Transfer Billing Group Creation, a new AWS Billing Conductor preference that eliminates the manual billing group configuration in two-level billing transfer arrangements. Designed for AWS Distributors managing billing for downstream seller Partners and their end customers, this feature automatically creates billing groups when an end customer accepts a billing transfer from a downstream seller Partner, ensuring pro forma cost data is immediately available to the Partner, with no extra manual configuration.
Auto-Billing Transfer Billing Group Creation is a one-time preference configuration per inbound transfer relationship, enabling you to request the creation of a billing group for any new indirect transfer coming through your Partners’ account, as well as being able to specify an AWS Billing Conductor pricing plan for the billing groups created automatically. 
The preference is accessible through two new API operations and through the AWS Management Console in the Billing Transfer details page. 
To learn more about Auto-Billing Transfer Billing Group Creation and how to configure your billing transfer preferences, visit the AWS Billing Conductor documentation.
Quelle: aws.amazon.com

Amazon CloudWatch Omni: AI-first observability for agents and applications

AWS announces the general availability of Amazon CloudWatch Omni, an evolution of Amazon CloudWatch. Omni is an AI-powered observability experience organized around your teams and the applications they run, so that you can observe and troubleshoot your applications and agents in one place. It combines the interoperability of OpenTelemetry with the scale and reliability of CloudWatch. And it meets you wherever you work: a standalone web experience with single sign-on (SSO) for your team, or a local IDE extension for getting hands-on with your agents.
With CloudWatch Omni, you create spaces in your central accounts to see telemetry across your AWS accounts and Regions, as well as other clouds, including Azure workloads. Omni automatically discovers services, maps dependencies, and surfaces golden metrics to help streamline your operational workflows. Using Omni, you can interact with telemetry however you prefer: via chat, through a guided point-and-click path in the console, or directly from a tool of your choice leveraging Agent Toolkit for AWS. Ask a question in natural language and Omni finds the relevant telemetry, builds dynamic views of the signals you care about, and helps you get to root cause powered by AWS DevOps Agent. Prefer to drive yourself? Point and click through the signals that matter most, whether you’re investigating a degrading application or diving deep into a trace or evaluation.
Omni also features a dedicated agent observability experience with an evaluation-driven development workflow for AI workloads across frameworks including LangGraph, CrewAI, OpenAI Agents SDK, Vercel AI SDK, and Strands. For every prompt, model call, and tool invocation, Omni helps you evaluate quality and run experiments to validate fixes before you ship.
To get started, create your Omni space from the CloudWatch console, configure SSO, and sign in to the standalone web experience. Agent developers can install the free CloudWatch Omni extension for VS Code, Cursor, and Kiro to instrument, debug, and evaluate agents locally (no AWS account required). CloudWatch Omni is generally available in US East (N. Virginia), US West (Oregon) and Europe (Ireland). To learn more, see the Amazon CloudWatch Omni product page and documentation. For pricing, see the CloudWatch Omni pricing page.
Quelle: aws.amazon.com

AWS Security Hub AI Inventory adds Azure self-hosted instance support

AWS Security Hub AI Inventory now supports discovering and cataloging AI assets running on self-hosted instances in Microsoft Azure. This expansion extends Security Hub’s existing self-hosted discovery capabilities beyond AWS, enabling central security teams to gain a continuously updated, organization-wide view of AI assets and their security posture across multi-cloud environments.
Security Hub leverages the software bill of materials (SBOM) analysis from Amazon Inspector, which has been enhanced to identify inference endpoints, models, and AI agents installed on Azure virtual machines, including frameworks such as Ollama, vLLM, Hugging Face TGI, and others. Each discovered AI asset is mapped to its underlying infrastructure and correlated with security findings, enabling teams to filter, group, and query their AI inventory across both AWS and Azure environments.
This capability is included with Security Hub Essentials at no additional cost. It is available in all AWS commercial Regions where Security Hub is offered. To learn more, see the AWS Security Hub User Guide and the AWS Security Hub product page.
Quelle: aws.amazon.com

Claude Opus 5.5 is now available on AWS GovCloud (US)

AWS GovCloud (US) now offers Claude Opus 5.5, Anthropic’s most capable Opus model yet and, the first of the Claude 5.5 model family, a better collaborator that handles long-running coding and knowledge work, reporting back clearly on what it did, what it found, and what it needs next.
According to Anthropic, Claude Opus 5.5 completes tasks using fewer tokens than Claude Opus 5, at a lower price per token, with cheaper cache reads stacking on top of the efficiency gain. Claude Opus 5.5 is the enterprise workhorse, a clear step up from Opus 5 on the work teams count on Opus to do. It handles long-running coding and knowledge work, and reports back like a good teammate, surfacing what it did, what it found, and what it needs from you. It thinks adaptively on every request, deciding how much effort each task needs.  
Amazon Bedrock gives you Opus 5.5’s advanced capabilities with zero data retention (ZDR) support by default. It keeps your data within AWS infrastructure with regional data residency and provides access through a unified service with AWS-managed features like Guardrails and Knowledge Bases. To learn more, see the Amazon Bedrock documentation and regional availability.
Quelle: aws.amazon.com

Claude Opus 5.5 is now available on AWS

AWS now offers Claude Opus 5.5, Anthropic’s most capable Opus model yet and, the first of the Claude 5.5 model family, a better collaborator that handles long-running coding and knowledge work, reporting back clearly on what it did, what it found, and what it needs next.
According to Anthropic, Claude Opus 5.5 completes tasks using fewer tokens than Claude Opus 5, at a lower price per token, with cheaper cache reads stacking on top of the efficiency gain. Claude Opus 5.5 is the enterprise workhorse, a clear step up from Opus 5 on the work teams count on Opus to do. It handles long-running coding and knowledge work, and reports back like a good teammate, surfacing what it did, what it found, and what it needs from you. It thinks adaptively on every request, deciding how much effort each task needs.
Customers have two ways to access Claude Opus 5.5: Amazon Bedrock and Claude Platform on AWS: Amazon Bedrock gives you Opus 5.5’s advanced capabilities with zero data retention (ZDR) support by default. It keeps your data within AWS infrastructure with regional data residency and provides access through a unified service with AWS-managed features like Guardrails and Knowledge Bases. To learn more, see the Amazon Bedrock documentation and regional availability.
Claude Platform on AWS gives you direct access to Anthropic’s native platform experience and capabilities via the AWS Console. Build, test, and deploy with the same APIs, features, and console experience you’d get working with Anthropic directly, unified with AWS billing and authentication. To get started, see the Claude Platform on AWS documentation.
Quelle: aws.amazon.com