AWS IoT Device Management adds MQTT session data to connectivity status API

AWS IoT Device Management adds MQTT session data to connectivity status API, enabling you to troubleshoot connectivity issues and audit connection patterns across your Internet of things (IoT) device fleet. This launch brings AWS IoT Device Management’s existing connectivity status API to full parity with AWS IoT Core’s recently launched GetConnection API, enabling you to retrieve detailed connection and MQTT session information for the IoT device by its thing name. In addition to the connection status, timestamp, and disconnect reason already available, you now get visibility into MQTT session timeout and session expiry values, along with optional socket level details such as source and destination IP addresses, ports, and client VPC endpoint ID. Access to socket information is controlled through granular IAM policies, so you can restrict it to the teams that need it. A key advantage of the connectivity status API over AWS IoT Core’s GetConnection API is data retention. While GetConnection retains connection and session details for 30 minutes after a device disconnects, the connectivity status API stores this information indefinitely. This means you can investigate disconnect reasons, review session metadata, and troubleshoot issues long after a device goes offline. This enhancement is available in all AWS regions where AWS IoT Device Management is supported. AWS IoT Device Management only supports devices registered in AWS IoT Core Thing Registry. To learn more, visit the AWS IoT Device Management documentation and reference guide.
Quelle: aws.amazon.com

Amazon SageMaker Unified Studio now supports a localized experience in twelve languages

Amazon SageMaker Unified Studio enhanced its global accessibility by introducing support for twelve languages across the user interface. Supported languages include English (American), Chinese (Simplified and Traditional), French, German, Indonesian, Italian, Japanese, Korean, Portuguese (Brazilian), Spanish, and Turkish. With this launch, data engineers, analysts, and data scientists across global teams can navigate, build, and collaborate in the language they are most comfortable with, reducing friction and improving productivity. Your preferred language is automatically detected based on your browser’s default language settings. You can also set your preferred language by choosing ‘Language selector’ in your profile settings and selecting the language. The selected language applies across the entire SageMaker Unified Studio user interface. This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available, in both AWS IAM Identity Center-based and IAM-based domains. To learn more, visit the Amazon SageMaker Unified Studio documentation.
Quelle: aws.amazon.com

Amazon Keyspaces (for Apache Cassandra) now provides CDC iterator position

Amazon Keyspaces (for Apache Cassandra) now returns an iterator position in the GetRecords response for change data capture (CDC) streams, indicating whether a consumer has reached the tip of the stream or whether additional records may be available. Amazon Keyspaces is a scalable, serverless, and managed Apache Cassandra-compatible database service that lets customers run Cassandra workloads on AWS without managing infrastructure. CDC streams capture row-level changes to Keyspaces tables so customers can integrate with downstream analytics, replication, and event-driven applications.
Previously, customers polled CDC streams at a fixed cadence regardless of whether new records were available, leading to inefficient resource usage and unnecessary CDC consumption costs. With iterator position, customers can now adapt polling frequency based on whether the iterator is at the tip of the stream or has records pending, lowering CDC consumption costs while maintaining timely data processing. The GetRecords response now includes an iteratorDescription structure with an iteratorPosition field that returns either AT_TIP or BEHIND_TIP, enabling customers to optimize their data integration pipelines and event-driven architectures.
This feature is available in all AWS Regions where Amazon Keyspaces CDC is supported. To use it, customers need to update to the latest AWS SDK. To learn more, visit the Amazon Keyspaces product page and see Working with change data capture (CDC) streams in the Amazon Keyspaces Developer Guide.
Quelle: aws.amazon.com

ARC Region switch adds Amazon Aurora scaling and Amazon Neptune global database failover

Amazon Application Recovery Controller (ARC) Region switch helps customers orchestrate the failover of their multi-Region applications to achieve a bounded recovery time in the event of a Regional impairment. Today, we are announcing three new execution blocks — the Amazon Aurora serverless scaling execution block, the Amazon Aurora provisioned scaling execution block, and the Amazon Neptune global database failover execution block — which automate database scaling and failover for multi-Region workloads. Customers running Amazon Aurora global database in active-passive configurations typically maintain a scaled-down secondary cluster to minimize cost. During failover, they must manually right-size and scale the secondary cluster to handle production traffic before routing requests — adding critical minutes to recovery time. The new Amazon Aurora serverless and Amazon Aurora provisioned scaling execution blocks automate right-sizing and scaling the secondary cluster as part of the Region switch plan, so it’s ready for production traffic when failover completes. Customers running Amazon Neptune global database face a similar challenge: failover requires scripting or manually deciding whether to switchover or detach-and-promote depending on the outage type — all under the pressure of an active incident. The new Amazon Neptune global database failover execution block automates both planned switchover and unplanned failover scenarios within a single plan, eliminating custom scripting during recovery. All three blocks support cross-account orchestration, enabling a single plan to coordinate database operations across multiple accounts and Regions. To learn more, read documentation of Amazon Aurora provisioned scaling, Amazon Aurora serverless scaling and Amazon Neptune global database failover
Quelle: aws.amazon.com

OpenAI GPT-5.4 generally available on Amazon Bedrock in AWS GovCloud (US-West)

Amazon Bedrock now supports GPT‑5.4 from OpenAI in AWS GovCloud (US-West) — giving government and regulated industry customers access to OpenAI’s most capable frontier model for professional work, backed by the enterprise-grade security and goverment compliance scope of AWS GovCloud (US). 
GPT‑5.4 supports native computer-use capabilities, and deep reasoning across coding, documents, and multi-step agentic tasks — all running on Bedrock’s high-performance inference engine with isolated queues and durable state for fault-tolerant workloads. Your data stays in-partition and is never used to train models.
For Regional availability of  GPT-5.4 see the AWS Regions page. Read the launch blog to learn more, for documentation and a step-by-step walkthrough, see the Amazon Bedrock docs and the getting started blog.
Quelle: aws.amazon.com