Cloud Computing Köln

AWS Security Hub now exports findings to S3 in CSV or JSON format

Today, AWS Security Hub announces support for exporting findings to Amazon S3 in CSV or JSON (OCSF) format. Security teams that need findings outside the console for use cases such as compliance reporting and audit evidence can now export findings from every findings page in the Security Hub console, including Threats, Exposure, Vulnerabilities, Posture Management, Sensitive Data, and All Findings, without building and maintaining their own extraction pipelines.
With this launch, you can start an export on demand from the findings page you are viewing and have Security Hub deliver the results to an S3 bucket in your account. You can choose CSV when you want to review or share findings in a spreadsheet or export in JSON if you need these findings in Open Cybersecurity Schema Framework (OCSF) format.
Findings export is available in all AWS Regions where AWS Security Hub is available. To learn more, visit the AWS Security Hub User Guide at https://docs.aws.amazon.com/securityhub/latest/userguide/securityhub-v2-findings-export.html.
Quelle: aws.amazon.com

Amazon S3 Vectors metadata pre-filtering is now available in AWS GovCloud (US) Regions

Amazon S3 Vectors metadata pre-filtering is now available in the AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions. Pre-filtering evaluates metadata filters before running similarity search, returning up to 5x more of the matching vectors when your filter is selective. S3 Vectors also adds a prefix match operator ($startsWith) for filtering on values like paths and URLs. Together, these improvements give your retrieval-augmented generation (RAG), agentic, and semantic-search applications more complete results when you filter, so your applications return more relevant answers.
S3 Vectors provides native support to store and query vectors in Amazon S3, delivering purpose-built, cost-optimized vector storage and query at billion-vector scale. With this launch, indexes in new vector buckets in the AWS GovCloud (US) Regions use metadata pre-filtering by default, with no change to how you write vectors with PutVectors or run filtered queries with QueryVectors. To use pre-filtering on an existing index, update it in place with the UpdateIndexMode API. You can also compare pre-filtering against your current filtering on the same index, using a per-query parameter on QueryVectors, before you update.
Metadata pre-filtering is available at no additional cost in all commercial AWS Regions where Amazon S3 Vectors is available, and in the AWS China Regions. We are in the process of deploying this change and plan to complete the deployment in the coming days. To get started, use the AWS CLI, AWS SDKs, or the Amazon S3 console. To learn more, visit the Amazon S3 Vectors documentation and the AWS News blog.
 
Quelle: aws.amazon.com

Anthropic Claude Sonnet 5.5 and Claude Opus 5.5 are now available on Kiro in AWS GovCloud (US)

Two new Anthropic models are now available in the Kiro IDE and CLI for the AWS GovCloud (US) Regions.
Claude Opus 5.5 is Anthropic’s most capable Opus model yet and a step up from Opus 5 on long-running agentic coding work. Opus 5.5 thinks adaptively on every request, deciding how much effort each task needs, and completes tasks with roughly 40% fewer tool calls and about half the tokens of Opus 5 in Kiro’s internal benchmarking. Available with a 1M context window and 2.0x credit multiplier, down from Opus 5’s 2.2x.
Claude Sonnet 5.5 is Anthropic’s fastest Sonnet model to date and a natural upgrade for teams already building on Sonnet 5. Output is more than 30% faster, real-world coding and knowledge work approaches Opus 5.5 performance, and clearer writing makes it a stronger collaborator, giving developers a cost-performance dial between maximum capability and higher throughput. Available with a 1M context window and 1.3x credit multiplier.
Ensure your IDE or CLI is updated to the latest version, then restart it to access the new models from the model selector. For more details, visit the GovCloud documentation, the monitoring and tracking guide, or contact your AWS account team. To learn more about Kiro, visit the Kiro product page.
Quelle: aws.amazon.com

Amazon Bedrock now supports reasoning summaries for OpenAI models

Amazon Bedrock now supports the reasoning.summary parameter for OpenAI models through the Responses API. This capability lets you request a human-readable summary of a model’s reasoning alongside its response, helping you understand its approach to complex tasks such as coding, analysis, and multi-step problem solving.
Reasoning summaries give developers additional context for evaluating responses, debugging applications, and showing users how a model approached a request. The summary is returned in the summary array of the reasoning output item, alongside the model’s answer.
This capability is available for all OpenAI models on Amazon Bedrock in all AWS Regions where OpenAI GPT models are available, including in-Region inference, geographic (GEO) cross-Region inference, and global cross-Region inference.
To learn more, see the OpenAI documentation on reasoning summaries. To get started with OpenAI GPT models on Amazon Bedrock, see documentation here.
Quelle: aws.amazon.com

Amazon EC2 R8g instances now available in additional regions

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in the AWS European Sovereign Cloud (Germany) region. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.
AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). 

 

To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.
Quelle: aws.amazon.com

Amazon EC2 R8gd instances are now available in additional regions

Amazon Elastic Compute Cloud (Amazon EC2) R8gd instances are available in AWS European Sovereign Cloud (Germany) region. These instances feature up to 11.4 TB of local NVMe-based SSD block-level storage and are powered by AWS Graviton4 processors, delivering up to 30% better performance over Graviton3-based instances. These instances are built on the AWS Nitro System and are a great fit for applications that need access to high-speed, low latency local storage. 

 

R8gd instances are available in 12 different sizes. They provide up to 50 Gbps of network bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). Additionally, customers can now adjust the network and Amazon EBS bandwidth on these instances by 25% using EC2 instance bandwidth weighting configuration, providing greater flexibility with the allocation of bandwidth resources to better optimize workloads. These instances offer Elastic Fabric Adapter (EFA) networking on 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes.
To learn more, see R8gd instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program. To get started, see the AWS Management Console.
Quelle: aws.amazon.com