Kategorie: Amazon AWS

AWS Cost Explorer launches Natural Language Query capabilities powered by Amazon Q

AWS Cost Explorer now brings Amazon Q Developer’s generative AI capabilities directly into your cost analysis workflows. You can now use natural language queries to ask Amazon Q questions about your AWS cost and usage data. In addition to providing answers to your question, you now also receive automatically updated visualizations in Cost Explorer. This enables faster cost analysis, reduces time to insights, and makes cost visibility accessible to every team member.
With this launch, you can start your cost analysis with the new suggested prompts in Cost Explorer. These prompts include commonly asked cost questions like “Show me my top spending services for this month.” Amazon Q provides detailed insights while Cost Explorer simultaneously updates with the corresponding visualization, filters, and groupings. You can also ask custom questions in your own words using the new ‘Ask Question’ button, exploring your spending patterns conversationally. Cost Explorer automatically updates charts and tables when analysis is based on your cost and usage data. When Amazon Q compiles insights from additional datasets such as pricing or anomaly detection, visualizations are displayed in Amazon Q’s new artifacts panel. You can continue the conversation with follow-up questions while maintaining full context, allowing you to go from a quick cost check to a deep investigation without switching tools or breaking your workflow.
Natural language cost analysis for AWS Cost Explorer is available today in all commercial AWS Regions at no additional charge. To learn more, visit AWS Cost Explorer. To get started, see the user guide.
Quelle: aws.amazon.com

Amazon FSx for OpenZFS is now available in the AWS Asia Pacific (Melbourne) Region

Customers can now create Amazon FSx for OpenZFS file systems in the AWS Asia Pacific (Melbourne) Region, providing fully managed shared file storage built on the OpenZFS file system. Amazon FSx makes it easier and more cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx for OpenZFS provides fully managed, cost-effective, shared file storage powered by the popular OpenZFS file system, and is designed to deliver sub-millisecond latencies and multi-GB/s throughput along with rich ZFS-powered data management capabilities (like snapshots, data cloning, and compression). To learn more about Amazon FSx for OpenZFS, visit our product page, and see the AWS Region Table for complete regional availability information.
Quelle: aws.amazon.com

AWS announces general availability of Smithy-Java client framework

AWS today announced the general availability of Smithy-Java, an open-source Java framework for generating type-safe clients and standalone classes from Smithy models. Smithy-Java addresses one of the most consistently requested capabilities from enterprise Smithy users: production-grade Java SDK generation. The framework allows you to generate clients from models and async patterns that increase cognitive load and maintenance burden for developers building modern Java applications.
Built on Java 21’s virtual threads, Smithy-Java provides a blocking-style API that is both simpler to use and competitive in performance with complex async alternatives. Key benefits include auto-generated type-safe clients from Smithy, protocol flexibility with runtime protocol swapping for gradual migration paths. The GA release includes the Java client code generator, support for AWS SigV4 and all major AWS protocols (AWS JSON, REST-JSON, REST-XML, AWS Query, and Smithy RPCv2-CBOR), standalone type code generation for sharing types across multiple services or data modeling, and a dynamic client that can call Smithy services without a codegen step.
The framework pioneers two architectural innovations: schema-driven serialization that reduces SDK size while improving performance, and binary decision diagrams (BDD) for endpoint rules resolution delivering significant latency improvements. Internal Amazon teams have already built complete services in weeks rather than months using Smithy-Java, with service teams depending on it internally. The framework is ideal for organizations invested in the Smithy ecosystem, teams requiring protocol-agnostic development, and developers building new services with generated server stubs.
To learn more, visit our blog post and follow the Smithy Java Quickstart guide.
Quelle: aws.amazon.com

Amazon WorkSpaces Personal now supports unique DNS names for PrivateLink

Amazon WorkSpaces Personal now provides unique, publicly resolvable Domain Name System (DNS) names for each AWS PrivateLink Virtual Private Cloud (VPC) endpoint, enabling enterprise customers to deploy WorkSpaces across multiple AWS VPCs and accounts without DNS resolution conflicts. Each interface VPC endpoint now receives a globally unique AWS-managed DNS name in addition to the previous generic DNS name that was shared across all endpoints. This enhancement enables customers to route traffic appropriately in multi-account environments with centralized DNS infrastructure. Customers can now deploy WorkSpaces Personal directories across different VPCs and AWS accounts while maintaining proper security isolation, eliminating the DNS name collision that previously prevented customers from using separate interface VPC endpoints across accounts. The publicly resolvable DNS names simplify configuration while maintaining security, as they resolve to private IP addresses accessible only from within the respective VPC. The unique DNS names are automatically managed by AWS throughout their lifecycle, requiring no additional Route 53 configuration or custom DNS management. This feature is available in all AWS regions where PrivateLink is available in Amazon WorkSpaces Personal. To learn more, see Amazon WorkSpaces PrivateLink documentation. For configuration details, refer to the WorkSpaces Administration Guide. Existing customers will automatically benefit from this enhancement, as the system maintains backward compatibility with previous DNS configurations.
Quelle: aws.amazon.com

Amazon Verified Permissions now supports policy store aliases and named policies and policy templates

Today, AWS announces support for policy store aliases and named policies and policy templates in Amazon Verified Permissions, simplifying multi-tenant deployments and day-to-day policy management. Amazon Verified Permissions is a fine-grained authorization service that helps you manage and enforce permissions across your applications using Cedar policies. These new capabilities eliminate the need to maintain separate mapping tables for associating tenant identifiers with policy store IDs or tracking individual policy and template IDs.
With policy store aliases, multi-tenant application developers can assign a human-readable alias based on a tenant identifier and use it in any API call, removing the need for a lookup table. Similarly, named policies and policy templates let you reference policies by meaningful names instead of system-generated IDs, making it easier to manage authorization logic as your application grows.
Amazon Verified Permissions policy store aliases and named policies and templates are available in all AWS Regions where Amazon Verified Permissions is available. For a full list of supported Regions, see Amazon Verified Permissions endpoints and quotas.
To get started, see Policy store aliases and Creating static policies in the Amazon Verified Permissions User Guide, or visit the Amazon Verified Permissions API Reference.
Quelle: aws.amazon.com

Amazon Bedrock Guardrails announces general availability of cross-account safeguards

Amazon Bedrock Guardrails now enables centralized enforcement of safety controls across all AWS accounts within an organization through cross-account safeguards. Amazon Bedrock Guardrails offers configurable safeguards that help block up to 88% of harmful multimodal content from both input prompts and model responses, while filtering hallucinated responses from foundation models. Central security teams and administrators can now automatically implement these controls for all foundation model interactions in Amazon Bedrock across their organization, eliminating the operational overhead of manually configuring guardrails for each account. With cross-account safeguards, you can specify a guardrail ID from your management account in a new Amazon Bedrock policy that automatically enforces configured safeguards across all member entities including organizational units (OUs) and individual accounts for all model invocations with Amazon Bedrock. This enables operational efficiency through automatic enforcement from a single control point in your management account. You can implement organization-level enforcement for uniform baseline protection, account-level controls for specific departmental requirements, and application-specific safeguards that complement organizational policies, with the union of multiple guardrails enforced during model inference calls. Organizational safeguards in Amazon Bedrock Guardrails is now available in all AWS commercial and GovCloud regions where Bedrock Guardrails is supported. You can access this capability through the AWS management console or using the supported APIs. To learn more about implementing centralized guardrails enforcement across your organization, read the News blog, visit the Amazon Bedrock Guardrails documentation, and explore the Amazon Bedrock Guardrails service page.
Quelle: aws.amazon.com

Amazon SageMaker Data Agent introduces charting capabilities and support for materialized views

Amazon SageMaker Data Agent now supports interactive charting, SQL analytics on Snowflake data sources, and materialized view management in Amazon SageMaker Unified Studio notebooks. Data Agent now provides a complete analytics workflow that goes beyond code generation, enabling you to explore AWS and external data sources, visualize results, and optimize query performance, all with natural language prompts.
You can ask “plot monthly revenue trends by region for 2025″ and Data Agent generates an interactive chart directly in your notebook, where you can hover over data points, and modify without writing code. When your analysis spans AWS and Snowflake, you can query Snowflake tables through external connections and join them with your AWS Glue Data Catalog data in a single prompt. Additionally, you can ask “analyze my notebook and suggest which queries would benefit from materialized views” and the agent recommends optimizations based on your query patterns, creates the views, and sets refresh schedules.
To get started, open a notebook in your SageMaker Unified Studio project and use the Data Agent chat panel. These features are available in all AWS Regions where Amazon SageMaker Unified Studio is supported. To learn more, see SageMaker Data Agent in the SageMaker Unified Studio User Guide.
Quelle: aws.amazon.com

AWS Glue Schema Registry is now available in three more AWS regions

You can now use the AWS Glue Schema Registry, a serverless and free feature of AWS Glue, in the Asia Pacific (Jakarta), Europe (Spain), and Europe (Zurich) regions to validate and control the evolution of streaming data using registered Apache Avro, JSON, and Protobuf schema formats.
The Schema Registry acts as a centralized repository for managing data format and structure between decoupled applications in data streaming systems. By using it, you can eliminate data validation logic and cross-team coordination, improve streaming data quality, and reduce downstream application failures. Through Apache-licensed serializers and deserializers, the Schema Registry integrates with C# and Java applications developed for Apache Kafka/Amazon Managed Streaming for Apache Kafka, Amazon Kinesis Data Streams, Apache Flink/Amazon Kinesis Data Analytics for Apache Flink, and AWS Lambda. 
To get started, visit the AWS Glue Schema Registry documentation. For a full list of AWS Regions where AWS Glue Schema Registry is available, see the AWS Regional Services List.
Quelle: aws.amazon.com

Apache Spark troubleshooting and upgrade agents now available as Kiro powers

The Apache Spark troubleshooting agent and upgrade agent for Amazon EMR are now available as Kiro powers, bringing one-click access to AI-assisted Spark operations directly in Kiro. With these powers, data engineers can reduce troubleshooting time from hours to minutes and compress Spark version upgrades from months to weeks. When a Spark job fails, the troubleshooting power identifies the root cause by analyzing logs, metrics, and configurations across EMR on EC2 and EMR Serverless, and provides specific code recommendations for PySpark applications. The upgrade power automates Spark version upgrades, such as moving from EMR 6.5 to EMR 7.12, by handling code transformation and dependency resolution through remote validation and data quality comparison on EMR. Both powers connect to Spark agents through MCP Proxy for AWS with IAM role-based authentication, and all actions are recorded in AWS CloudTrail for full auditability..
The Apache Spark troubleshooting and upgrade powers are available with Amazon EMR in all AWS commercial regions. To get started, install the Apache Spark troubleshooting power or the upgrade power from the Kiro IDE. For more information, see the troubleshooting agent and upgrade agent documentation.
Quelle: aws.amazon.com

Amazon CloudWatch introduces PromQL querying with Query Studio Preview

Amazon CloudWatch announces Query Studio in public preview, a unified query and visualization experience that brings native PromQL querying to CloudWatch for the first time. Query Studio combines PromQL and CloudWatch Metric Insights in a single interface, enabling you to query AWS vended metrics and OpenTelemetry metrics using the language you prefer without switching between consoles. Query Studio provides a visual form builder with autocomplete and a code editor with syntax highlighting, making it accessible to both new and experienced users. For example, a team running applications on Amazon EC2 can correlate their custom OpenTelemetry application metrics with EC2 vended metrics side by side, quickly spot issues across their stack, and create alarms or add charts to dashboards directly from their query results. Amazon CloudWatch Query Studio is available in public preview in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), Asia Pacific (Singapore), and Europe (Ireland). Standard CloudWatch dashboard pricing applies, see pricing page for details. To get started, open Query Studio from the Metrics console or dashboard edit mode in the Amazon CloudWatch console. Learn more on the Amazon CloudWatch documentation page.
Quelle: aws.amazon.com