Kategorie: Amazon AWS

Amazon Bedrock now offers Claude Mythos 5.2 to Eligible Customers in AWS GovCloud (US)

Amazon Bedrock, the platform for building generative AI applications and agents at production scale, now offers Claude Mythos 5.2 to eligible customers in AWS GovCloud (US). Claude Mythos 5.2 is Anthropic’s most advanced AI model to date for use cases across cybersecurity, software coding, and complex reasoning tasks. The model can identify sophisticated security vulnerabilities in software and demonstrate exploitability. It can also comprehend large codebases and deliver actionable findings with less manual guidance than previous AI models. This enables security teams to accelerate defensive cybersecurity work, find and fix security vulnerabilities in the world’s most critical software, and address them before threats emerge. Claude Mythos 5.2 is the first of Anthropic’s AI models with powerful cybersecurity capabilities to be available in AWS GovCloud (US).
Claude Mythos 5.2 is available to eligible customers in AWS GovCloud (US) Regions through Amazon Bedrock. Access is limited to allow-listed organizations; to get started, visit Anthropic’s Cyber Verification Program. 
Quelle: aws.amazon.com

Claude Fable 5.2 is now available on AWS GovCloud (US)

Claude Fable 5.2 is now available on AWS GovCloud (US) and brings Anthropic’s most capable generally available model for technical work to regulated customers. Fable 5.2 sets a new standard on the hardest projects in coding, math, and science, and Anthropic recommends it for fields like software engineering, scientific research, and finance, where judgment, iteration, and accuracy are critical. Claude Mythos 5.2, the same underlying model as Claude Fable 5.2, with its full cyber and bio capabilities retained for cybersecurity and biology research, is available through Anthropic’s verification programs.
Claude Fable 5.2 can work for hours and up to days unattended, driving autonomous work and taking on bigger, more challenging projects. It takes on large, loosely defined engineering problems across multiple repositories and monorepos, tests its own work as it goes, and is more willing to question inherited conclusions, so it finds root causes previous Claude models miss. In Anthropic’s testing, it coordinated hundreds of subagents as a lead agent and flagged results that don’t reproduce. Beyond coding, it develops new analytical methods for scientific research and brings frontier reasoning to quantitative finance.
Anthropic has designated Fable 5.2 and Mythos 5.2 as covered models, which require data retention for safety monitoring. Until Enterprise Frontier Safeguards is available, eligible customers can use Fable 5.2 with zero data retention. Visit the Amazon Bedrock abuse detection page to learn more about details regarding data retention for these models.
To learn more, see the Amazon Bedrock documentation, and regional availability.
Quelle: aws.amazon.com

Amazon MSK Replicator is now available in AWS GovCloud (US-East, US-West) Regions

You can now use Amazon MSK Replicator in the AWS GovCloud (US-East, US-West) Regions to replicate streaming data across Amazon MSK clusters and from external Apache Kafka clusters including on-premises, self-managed on AWS, or other cloud providers to Amazon MSK Provisioned clusters.
MSK Replicator is a feature of Amazon MSK that automates data replication between Kafka clusters, eliminating the need to manage custom replication infrastructure or configure open-source tools. With MSK Replicator, you can easily build regionally resilient streaming applications for increased availability and business continuity. MSK Replicator provides automatic asynchronous replication across Kafka clusters, eliminating the need to write custom code, manage infrastructure, or setup cross-region networking. MSK Replicator automatically scales the underlying resources so that you can replicate data on-demand without having to monitor or scale capacity. MSK Replicator also replicates the necessary Kafka metadata including topic configurations, Access Control Lists (ACLs), and consumer group offsets. If an unexpected event occurs in a region, you can failover to the other AWS Region and seamlessly resume processing.
You can get started with MSK Replicator from the Amazon MSK console or the Amazon CLI. To learn more, visit the MSK Replicator documentation, product page, and pricing page.
Quelle: aws.amazon.com

Amazon Redshift expands SUPER data type to store strings up to 16 million bytes

Amazon Redshift now supports individual strings up to 16 million bytes within SUPER data types. Once you opt in through a database parameter, this enhancement applies when ingesting structured or semi-structured data from JSON, PARQUET, TEXT, and CSV source files, and when transforming data through extract load and transform (ELT) processes. Previously, individual strings within SUPER data types were limited to 65,535 bytes.
Storing large individual strings in the SUPER data type helps avoid complex pre-loading transformations needed to store the source data in Amazon Redshift. You can now directly ingest large individual strings greater than 65,535 bytes without extra processing (for example, lengthy documents like terms and conditions and contracts), making them queryable using SQL. Once the data is in Amazon Redshift, you can use the flexibility of PartiQL language to explore and navigate through the data or use string functions to transform the data. Functions such as JSON_PARSE, CONCAT, and LISTAGG can now take input strings and return output strings up to 16 million bytes in length.
This enhancement is available in all AWS Regions, including the AWS GovCloud (US) Regions, where Amazon Redshift is available. See the AWS Region Table for more details. To learn more, please visit our documentation or blog.  
Quelle: aws.amazon.com

Agent Registry is now generally available in AWS GovCloud (US-West) Region

AWS Agent Registry, available through Amazon Bedrock AgentCore, is now available in the AWS GovCloud (US-West) Region.
AWS Agent Registry is a fully managed discovery service that gives your organization a central catalog for organizing, curating, and discovering resources. You can publish MCP servers, tools, agents, agent skills, and custom resources to a searchable registry, and control what becomes discoverable through an approval workflow. People and AI agents can then find the right tools and agents through hybrid search, catalog browsing, and a native MCP endpoint.
With Agent Registry in AWS GovCloud (US-West), public sector organizations and their partners get a single governed inventory of the agents and tools in their environment. Approval workflows and AWS CloudTrail audit logs support their compliance and oversight requirements.
To get started, see the AWS Agent Registry documentation.
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Kimi K3.1 Pro (Highspeed) now available on Amazon Bedrock

Today, Kimi K3.1 Pro from Moonshot AI is available on Amazon Bedrock, expanding our open weight model portfolio with the security and governance that customers rely on. Customers using Amazon Bedrock can now run agentic use cases such as coding and document processing on Kimi K3.1 Pro (Highspeed), which delivers high output tokens per second (OTPS) for faster, more responsive results.
According to Moonshot AI, Kimi K3.1 Pro is an open-weight, natively multimodal agentic model with a 1-million-token context window, and its most capable 3-trillion-parameter-class model to date. Moonshot AI reports improvements in coding, 3D creation, financial research, and other agentic work. On Amazon Bedrock, it runs within the same security boundary as proprietary models and supports explicit prompt caching to reduce latency and input costs.
Kimi K3.1 Pro is available in all AWS Regions where Amazon Bedrock is available through cross-Region inference. To get started, visit the Amazon Bedrock console. To learn more, see the Amazon Bedrock documentation.
Quelle: aws.amazon.com

Amazon Simple Email Service is now available in six new AWS Regions

Amazon Simple Email Service (Amazon SES)  is now available in the Asia Pacific (New Zealand, Melbourne, Taipei, Thailand), Mexico (Central), EU (Spain). Customers can now use these new Regions to leverage Amazon SES to send emails and, if needed, to help manage data requirements.
Amazon SES is a scalable, cost-effective, and flexible cloud-based email service that allows digital marketers and application developers to send marketing, notification, and transactional emails from within any application. To learn more about Amazon SES, visit this page .
With this launch, Amazon SES is available in 35 AWS Regions globally: US East (N. Virginia, Ohio), US West (N. California, Oregon), AWS GovCloud (US-West, US-East), Asia Pacific (Osaka, Mumbai, Hyderabad, Sydney, Singapore, Seoul, Tokyo, Jakarta, Malaysia, New Zealand, Melbourne, Taipei, Thailand), Canada (Central, Calgary), EU (Ireland, Frankfurt, London, Paris, Stockholm, Milan, Zurich,Spain), Middle East (Bahrain, UAE), Israel (Tel Aviv), South America (Sao Paulo), Mexico (Central) and Africa (Cape Town).
For a complete list of all of the regional endpoints for Amazon SES, see  AWS Service Endpoints  in the AWS General Reference.
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AWS Glue Data Catalog now supports catalog-vended credentials with Apache Iceberg REST catalog federation

AWS Glue Data Catalog now supports external catalog’s vended credentials in Apache Iceberg REST catalog federation. You can now read external Iceberg tables from Amazon Athena, Amazon EMR, Amazon Redshift, and AWS Glue using coarse-grained table grants in your external Iceberg catalog.
Glue Data Catalog already federates to external Iceberg REST catalogs through an AWS IAM role that you configure with access to your Amazon S3 buckets. This enhancement in Glue Data Catalog provides another way to connect to an external Iceberg catalog and read only the tables that the external catalog authorizes. It uses temporary security credentials that are scoped to the Amazon S3 storage prefix and vended by your external Iceberg catalog. AWS Lake Formation manages access control when you query an external table using any AWS analytics engine, letting you restrict access further down to specific rows and columns and share external Iceberg tables across AWS accounts.
This feature is available through the AWS Lake Formation Management Console, AWS CLI, and the AWS Glue and Lake Formation SDKs. This feature is available in all commercial AWS Regions where Glue and Lake Formation are supported. To learn more, visit the documentation.
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Capacity Reservation Resource Groups now support Amazon EC2 Capacity Blocks and interruptible Capacity Reservations in AWS GovCloud (US) Regions

Starting today, you can add Amazon EC2 Capacity Blocks for ML and interruptible Capacity Reservations to Capacity Reservation Resource Groups in AWS GovCloud (US) Regions. Amazon EC2 offers different reservation offerings such as On-Demand Capacity Reservations (ODCRs), interruptible Capacity Reservations, and Capacity Blocks for ML. Previously, a Capacity Reservation Resource Group could only include ODCRs. Now you can add any type of Capacity Reservation to a Capacity Reservation Resource Group, making it easier to launch EC2 instances across your entire portfolio of reserved capacity.
To use this feature, create a Capacity Reservation Resource Group, add any Capacity Reservation to it, and then target the group in your launch request. When using EC2 Fleet and EC2 Auto Scaling groups, you can also specify your prioritization preferences across reservation types, and configure automatic fall back to EC2 On-Demand capacity when there is no capacity remaining across your reservations.
There are no additional charges for using this feature. With the addition of AWS GovCloud (US) Regions, this feature is now available in all AWS Regions where Capacity Blocks for ML and interruptible ODCRs are supported, excluding China Regions. To get started, see Capacity Reservation Resource Groups and the Capacity Reservations user guide.
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AWS launches support for amortization of EC2 Capacity Blocks for ML

AWS Data Exports for Cost and Usage Report (CUR) 2.0 and AWS Cost Explorer now amortize the upfront fee for Amazon EC2 Capacity Blocks for ML across the duration of each reservation. You can see the amortized cost of each instance launched into a Capacity Block and the amortized cost of unused capacity, so you can attribute your upfront fee to the workloads that used it and identify capacity that went unused.
Previously, a Capacity Block’s upfront fee appeared as a single charge on the purchase date, making it difficult to see how that cost was spread across usage over the reservation. Now the amortized cost appears alongside your instance usage, so you can allocate GPU costs to the teams, projects, and applications that ran on the reserved capacity. You can also see what share of your reservation went unused and plan future Capacity Block purchases. In CUR 2.0, the amortized costs appear in the reservation_amortized_upfront_fee_for_billing_period, reservation_effective_cost columns, and reservation_net_effective_cost shows the amortized cost after discounts. In Cost Explorer, select the amortized cost view to see Capacity Block costs allocated for the reservation.
 Amortization for Capacity Blocks is available at no additional charge in all AWS Regions except the AWS GovCloud (US) Regions and the China Regions. To learn more, see the CUR 2.0 data dictionary and exploring your data using Cost Explorer.
Quelle: aws.amazon.com