Kategorie: Amazon AWS

AWS Deadline Cloud now supports sharing job bundles

AWS Deadline Cloud now supports sharing job bundles, giving teams a simple way to distribute and reuse render job templates without manual file distribution. Deadline Cloud is a fully managed service that helps teams run compute-intensive workloads in the cloud for visual effects, animation, product design, simulation, and gaming. 
Job bundles define the jobs you submit to Deadline Cloud, including the job template, parameters, and asset references. Previously, sharing a bundle with teammates meant distributing files through shared drives or manual copying. Now, you can publish a bundle to your queue directly from the submitter or the command line, and it immediately becomes available to everyone with access to that queue. Shared bundles are packaged as portable archives and stored in the queue’s existing job attachments bucket in Amazon S3, so there is no additional infrastructure or configuration to set up. This makes it easy for pipeline teams to publish standard, ready-to-submit job templates that artists can pick up and use.
You can browse bundles shared on your queue, on your local filesystem, or from your job submission history. You can preview each bundle’s name, description, steps, and parameters before selecting it. New CLI commands let you manage shared bundles from the command line and integrate bundle sharing into pipeline scripts.
This feature is available in all AWS Regions where Deadline Cloud is available. To get started, visit the AWS Deadline Cloud documentation.
Quelle: aws.amazon.com

Amazon Quick now lets you build custom apps with natural language -

Now generally available, Amazon Quick lets you build custom applications by simply describing them in natural language. Create project trackers, customer dashboards, and training portals in minutes instead of months. Whether you’re a product manager, finance lead, HR partner, or ops analyst, you can now turn ideas into fully functional apps without writing any code. Tell Quick what you need, and it builds a live, connected application with real-time data from your existing business systems.
Quick connects directly to the tools and data your business already uses, including Salesforce, Jira, Asana, ServiceNow, Microsoft 365, Google Workspace, databases, and data warehouses. Your apps stay current automatically as underlying data changes, and every connection respects your organization’s existing identity, authorization, and access control policies. Once built, you can publish and share apps instantly with specific users or your entire organization. Need to make a change like adding AI, updating the visual style, or connecting to another system? Just describe what you want and Quick handles it.
During preview, customers used Quick to replace spreadsheets and disconnected tools with purpose-built applications. New York Life built an e-learning portal for their Institutional Life team that consolidates onboarding, training, and compliance courses into a single experience. The Amazon Quick team tracks pipeline, customer requests, and adoption metrics in a weekly leadership review app that replaced manual data pulls from four different systems.
Building apps in Quick is available to Plus, Professional, and Enterprise customers starting September 1, 2026. To learn more, visit the Apps in Quick getting-started guide.
Quelle: aws.amazon.com

Amazon CloudWatch now supports warm-up periods for alarms

Amazon CloudWatch now lets you configure a warm-up period for metric alarms and log alarms, delaying alarm evaluation for a set time after the alarm is created. This reduces noise from missing data while a new resource or service starts up and begins publishing metrics. For example, a team that provisions a new microservice and its alarms together through a CI/CD pipeline can attach a warm-up period so alarms do not page the on-call engineer while the service is still starting up and has not yet published metrics.

Previously, when you created an alarm before the underlying metric was reporting data, CloudWatch evaluated the alarm right away using its “treat missing data” setting. For resources that take time to begin emitting metrics, such as a newly deployed application or service, this could cause the alarm to transition state and run actions on missing data during startup, triggering unnecessary notifications. A warm-up period fixes this by giving you two ways to hold off evaluation during startup: wait a fixed duration you set before evaluation begins, or let CloudWatch start evaluating automatically as soon as the metric actually has enough data to fill the alarm’s evaluation window.

You set the warm-up period with the WarmUpConfiguration parameter when you create or update an alarm. Specify a warm-up duration from 1 to 2,880 minutes (2 days). By default, the alarm ends warm-up early and begins evaluating as soon as enough data fills its evaluation window. Additionally, you can optionally require the alarm to wait the full duration before evaluating.

Warm-up periods are available in all AWS Regions where Amazon CloudWatch is offered at no additional charge beyond standard CloudWatch alarm pricing.

To get started, see  Alarm warm-up periods  and  Create an alarm that uses a warm-up period  in the Amazon CloudWatch User Guide.
Quelle: aws.amazon.com

Claude Fable 5.1, Anthropic's new frontier model is now available on AWS

Claude Fable 5.1 is generally available on AWS and brings Anthropic’s most capable frontier model to all customers. Fable 5.1 delivers frontier intelligence for ambitious tasks across coding, scientific research, and enterprise workflows. A clear improvement over Claude Fable 5, Fable 5.1 is a step up in intelligence on the hardest reasoning tasks, providing better judgement on ambiguous work and fewer confident wrong answers. Claude Mythos 5.1, the same underlying model as Claude Fable 5.1 with its full cyber and bio capabilities retained for cybersecurity and biology research, is available with limited access.
Claude Fable 5.1 is built for long-running, high-stakes work that runs for hours and spans many applications. It can own more of a software project on its own, handling features across an entire codebase, code review, and performance work over sessions that run for hours. If it gets stuck, it says so instead of reporting success, and it is less likely to take shortcuts like disabling a failing test. It takes analysis from the first question to the finished document, and it is Anthropic’s strongest model yet for knowledge work.
Anthropic has designated Fable 5.1 a Covered Model, a category of Claude models that carry additional data retention, safety review, and access policies wherever they’re offered. Enterprise Frontier Safeguards (EFS) built in partnership between AWS and Anthropic, will let eligible customers use Covered Models while keeping their data in a cloud environment they control. Read the launch blog to learn more.
Customers have two ways to access Claude Fable 5.1: Amazon Bedrock and Claude Platform on AWS. To learn more, see the Amazon Bedrock documentation, regional availability, and Claude Platform on AWS documentation..
Quelle: aws.amazon.com

Amazon MWAA supports Apache Airflow version 3.3.1

Amazon Managed Workflows for Apache Airflow (MWAA) now supports Apache Airflow version 3.3.1, the latest release of the popular open-source workflow orchestration framework. Amazon MWAA is a managed orchestration service for Apache Airflow that makes it easier to set up and operate end-to-end data pipelines in the cloud.
Apache Airflow 3.3 introduces stateful tasks and multi-language support. With the new Task and Asset State Store, tasks can now persist durable state across retries and reruns, enabling cursor tracking and crash-safe reconnection to long-running jobs. The Language Task SDK (experimental) lets teams write task logic in Java or Go while keeping orchestration in Python. Additional improvements include expanded asset partitioning, pluggable retry policies, and bulk actions for DAG runs and task instances. Apache Airflow 3.3.1 also delivers stability, security, and UI improvements on top of these capabilities.
You can launch a new Apache Airflow 3.3.1 environment on Amazon MWAA, or upgrade from 3.2 or later, with a few clicks in the AWS Management Console in all currently supported Amazon MWAA regions. To learn more about Apache Airflow 3.3.1, visit the Amazon MWAA documentation and the Apache Airflow 3.3.1 change log in the Apache Airflow documentation.
Apache, Apache Airflow, and Airflow are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.
Quelle: aws.amazon.com

Amazon Connect Customer dashboards now support compact mode

Amazon Connect Customer now offers compact mode on the analytics dashboards, increasing data density so supervisors can see more of their operational data without scrolling. Compact mode reduces widget size, font, and minimizes filters to maximize screen space. For example, a supervisor on a 13-inch laptop toggles compact mode, which reduces row height, enabling them to view all team agents on the widget without scrolling and spot non-adherent agents faster.
Compact mode on dashboards is available in all AWS regions where Amazon Connect Customer is offered. To learn more about Amazon Connect Customer analytics dashboards, 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 Timestream for InfluxDB is now available in 8 additional AWS Regions

You can now use Amazon Timestream for InfluxDB in the Africa (Cape Town), Asia Pacific (Bangkok), Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Asia Pacific (Seoul), Europe (Zurich), and Israel (Tel Aviv) AWS Regions. Timestream for InfluxDB makes it easy for application developers and DevOps teams to run fully managed InfluxDB databases on AWS for real-time time-series applications using open-source APIs.
Timestream for InfluxDB offers Multi-AZ high availability, read replicas, enhanced durability, and multi-node scaling — giving you flexible deployment options to match your workload as it evolves. Whether you’re starting with a single-node setup or scaling to a 15-node Enterprise cluster, you can right-size your infrastructure without re-architecting.
You can create your InfluxDB databases using the Amazon Timestream for InfluxDB console. AWS CLI, or AWS SDKs . Amazon Timestream for InfluxDB is available in the following AWS Regions. For more information, see the Amazon Timestream for InfluxDB documentation and pricing page.
Quelle: aws.amazon.com

Amazon Redshift now supports AWS IAM Identity Center authentication with enhanced VPC routing

Amazon Redshift now supports AWS IAM Identity Center authentication for provisioned clusters and serverless workgroups configured with enhanced VPC routing (EVR). You can access Amazon Redshift with single sign-on with your corporate credentials, and the traffic traverses Amazon Virtual Private Cloud (Amazon VPC) and stays on the AWS network. This is valuable for customers with data residency, regulatory, or network-isolation requirements that mandate no public internet egress for analytics.
With Redshift EVR, all traffic between your Redshift warehouse and other AWS services goes through your VPC, where you can govern it with security groups, network ACLs, and endpoint policies, and observe it in VPC Flow Logs. With this launch, Redshift validates and exchanges IAM Identity Center tokens over AWS PrivateLink interface VPC endpoints from inside your VPC, so authentication and authorization follows the same governed network path as the rest of your Redshift traffic. This feature also supports IAM Identity Center multi-Region replication for customers running Redshift in a different Region than their primary Identity Center instance.
Read the Amazon Redshift enhanced VPC routing documentation and the blog post to get started. This capability is available in all AWS Regions where both Amazon Redshift and IAM Identity Center are available. 
Quelle: aws.amazon.com

AWS Agent Registry agents and MCP servers now available in Amazon Quick

Today, Amazon Quick announces integration with AWS Agent Registry, enabling users to discover and use resources from their organization’s AWS Agent Registry directly within Amazon Quick. AWS Agent Registry supports MCP servers and agents, which users can now search and browse directly within Amazon Quick. After finding the agent or MCP server they need, users can enable it with a few clicks. Connection details are already populated from the registry. Once enabled, these resources can be shared with teams for use across chat, agents, apps, flows, and deep research. 
This integration bridges the gap between technical teams who build agents with Amazon Bedrock AgentCore and business users who work in Amazon Quick. Organizations no longer need to manually configure connections to agents and tools that already exist in their AWS Agent Registry. Business users get access through their familiar Amazon Quick workspace without duplicate effort. 
Amazon Quick integration with AWS Agent Registry is available in all AWS Regions where both Amazon Quick and Amazon Bedrock AgentCore are available. This includes US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland). 
To get started, open the Amazon Quick admin console and go to Manage account, Permissions, AWS Agent Registry to connect your registry. To learn more, see the Amazon Quick Integrations documentation and the AWS Agent Registry documentation.
Quelle: aws.amazon.com

Partner Revenue Measurement expands service coverage for User Agent string capability

Partner Revenue Measurement User Agent string now supports additional AWS services. Partner Revenue Measurement allows Partners to better understand their AWS revenue impact and product consumption patterns. Previously, the User Agent string capability measured AWS service consumption across select services. With this expansion, Partners can now measure attributed revenue across additional applicable AWS services that log control plane activity in AWS CloudTrail, significantly increasing the visibility Partners have into the revenue their solutions drive.
Partners who have already embedded a user agent (format APN_1.1/pc_<AWS Marketplace product-code>$) in their applications automatically benefit from the expanded coverage with no additional implementation needed. The additional service consumption measured through this expansion is now visible in the Attributed Revenue Dashboard, accessible through Partner Analytics in AWS Partner Central on the AWS Console. This User Agent string method complements Partner Revenue Measurement’s Resource Tagging and AWS Marketplace Metering integration capabilities.
Partner Revenue Measurement is generally available in all commercial regions. To learn more about User Agent string implementation or other Partner Revenue Measurement capabilities, review the onboarding guide and services supported.
Quelle: aws.amazon.com