Amazon Lightsail is now available in the Asia Pacific (Malaysia) Region

Starting today, Amazon Lightsail is available in the Asia Pacific (Malaysia) Region. This expansion brings the power and simplicity of Lightsail to customers in Malaysia and surrounding regions. With this launch, customers in Malaysia and nearby countries can now enjoy lower latency and better performance for their applications while meeting local data residency requirements. The new Region provides access to Lightsail’s full range of features including instances that meet your compute needs—from general purpose to compute-optimized and memory-optimized bundles—as well as managed databases, containers, load balancers and more, all with the same simple, predictable pricing that Lightsail customers love. Lightsail is available in these AWS Regions: US East (Ohio, N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt, Ireland, London, Paris, Stockholm), Asia Pacific (Malaysia, Jakarta, Mumbai, Seoul, Singapore, Sydney, Tokyo). To learn more about Regions and Availability Zones for Lightsail, please refer to the documentation. You can use this Region through the Lightsail Console, AWS Command Line Interface (CLI) and AWS SDKs.
Quelle: aws.amazon.com

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 SageMaker Unified Studio adds notebook import/export and developer acceleration features

Amazon SageMaker Unified Studio notebooks now support import/export capabilities, enabling migration from JupyterLab and other notebook platforms. This release also introduces developer acceleration features including cell reordering, keyboard shortcuts, cell renaming, and multi-line SQL support, designed to enhance productivity for data engineers and data scientists professionals working with notebook-based workflows.
The new import/export functionality supports .ipynb, .json, and .py formats while preserving cell types and metadata, making platform migration straightforward. You can export notebooks in four formats including Jupyter notebook with requirements (.zip), standard .ipynb, Python scripts (.py), and SageMaker Unified Studio native format (.json). Developer acceleration features enable you to reorder cells without copy-paste duplication, assign custom names to cells for improved navigation in large notebooks, use familiar keyboard shortcuts for faster development, and execute multiple SQL statements in a single cell with results displayed in separate tabs for easy comparison and analysis.
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the Amazon SageMaker Unified Studio marketing page and user guide. 
Quelle: aws.amazon.com

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