Schlagwort: cloud computing

Claude Opus 4.8 is now available on AWS

AWS  now offers Claude Opus 4.8 — Anthropic’s most capable generally available model to date — delivering meaningful advances across agentic coding, professional knowledge work, and long-running autonomous tasks for developers and enterprises building production AI applications.
Claude Opus 4.8 can perform longer autonomous runs, deeper reasoning, and consistency to be trusted with production work. For coding, the Opus 4.8 reads codebases like an engineer, plans before it edits, and holds context across long sessions in real repositories. For agentic tasks, it is better at finding paths around obstacles instead of stalling, recovering from its own errors, and knowing when to ask for help versus when to keep going. For knowledge work, it better synthesizes across long documents and complex sources, self-checks its output, and delivers structured deliverables that hold up to review.
Customers have two ways to access Claude Opus 4.8: Amazon Bedrock and Claude Platform on AWS.
Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Opus 4.8 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see 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

Amazon Connect Customer expands generative AI-powered post-contact summaries to eight new languages

Amazon Connect Customer now supports generative AI-powered post-contact summaries in eight additional language families: Portuguese, French, Italian, German, Spanish, Chinese, Japanese, and Korean. Post-contact summaries also now support non-US variations of English, including British English, Australian English, and other regional locales, ensuring summaries reflect locally appropriate spelling and terminology.
Generative AI-powered post-contact summaries provide agents and managers with concise, structured overviews of customer conversations across voice, chat, and email channels, eliminating the need to read full transcripts. With this expansion, organizations can automatically generate summaries in the language of the conversation, helping agents complete after-contact work faster and enabling managers to review contacts across languages. For example, a global support organization can now generate post-contact summaries for calls handled in French, German, or Japanese, giving supervisors visibility into service quality across all regions.
The newly supported languages are available in all AWS Regions where Amazon Connect Customer post-contact summaries are available. To learn more, refer to View generative AI-powered post-contact summaries in the Amazon Connect Customer Administrator Guide. To learn more about Amazon Connect Customer, visit the Amazon Connect Customer website.
Quelle: aws.amazon.com

AWS Organizations emits CloudTrail events for account membership changes

AWS Organizations now automatically emits CloudTrail events to your management account whenever accounts join or leave your organization. These new events—AccountJoinedOrganization and AccountDepartedOrganization—provide security teams and cloud administrators with enhanced visibility into organizational membership changes, helping detect unauthorized activities and potential security incidents that previously could go unnoticed. 
The AccountJoinedOrganization event captures how an account joined an organization (Created or Invited) and the join timestamp, while the AccountDepartedOrganization event records how an account departed —Left for accounts that departed voluntarily, Removed for accounts removed by the management account, or  Cleaned for accounts that were permanently closed along with the departure timestamp. 
You can leverage these events to create CloudWatch alarms or Amazon EventBridge rules for real-time notifications, enabling rapid response to suspicious organizational changes. This capability supports critical use cases including fraud detection, compliance auditing, security monitoring, and incident investigation across your AWS environment.
Quelle: aws.amazon.com

Amazon EMR now supports Apache Spark 4.0.2 in general availability

Amazon EMR now supports Apache Spark 4.0.2 across all three deployment models. With Spark 4.0.2, you can build and maintain data pipelines more easily with ANSI SQL and VARIANT data types, enforce fine-grained access control (FGAC) at the row level or column level, strengthen compliance and governance frameworks with Apache Iceberg v3 table format, and deploy new real-time applications faster with enhanced streaming capabilities. With Spark 4.0.2, you can build data pipelines, making data engineering accessible to a broader range of users through standard ANSI SQL support, eliminating the need to learn Spark-specific syntax. Spark 4.0.2 natively supports JSON and semi-structured data through VARIANT data types, providing flexibility for handling diverse data formats. You can enforce fine-grained access control (FGAC) on both read and write operations for AWS Lake Formation registered tables in your Apache Spark jobs. Building on these security capabilities, Apache Iceberg v3 table format provides stronger transaction guarantees and tracks data lineage, creating the audit trails required for regulatory compliance. Enhanced streaming controls simplify management of complex stateful operations and improve monitoring, enabling you to deploy real-time applications for fraud detection, personalization, and other time-sensitive use cases faster.
Apache Spark 4.0.2 is available in all regions where EMR is available. If you are upgrading your existing EMR application, you can use Apache Spark upgrade agent to accelerate your upgrades. To learn more about Apache Spark 4.0.2 on Amazon EMR, visit the Amazon EMR release notes, or get started by creating an EMR application with Spark 4.0.2 from the AWS Management Console.
Quelle: aws.amazon.com

SageMaker Notebook Instances now support P5.4xl instance types

We are pleased to announce general availability of Amazon EC2 P5.4xl instances on SageMaker notebook instances.
Amazon EC2 P5.4xl instances are powered by NVIDIA H100 Tensor Core GPUs and deliver high performance in Amazon EC2 for deep learning (DL) and high performance computing (HPC) applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce cost to train ML models by up to 40%. Customers can use P5 instances for training and deploying complex large language models (LLMs) and diffusion models powering generative AI applications. These applications include question answering, code generation, video and image generation, and speech recognition.
Amazon EC2 P5.4xl instances are available on SageMaker notebook instances in the AWS US East (N. Virginia and Ohio), US West (Oregon), Asia Pacific (Mumbai, Tokyo, Jakarta) and South America (São Paulo) regions.
Visit developer guides for instructions on setting up and using JupyterLab and CodeEditor applications on SageMaker Studio and SageMaker notebook instances.
Quelle: aws.amazon.com