In my last Week in Review post, I mentioned how much time I’ve been spending on AI-Driven Development Lifecycle (AI-DLC) workshops with customers this year. A common theme in those sessions is the need for better cost visibility. Teams are moving fast with AI, but as they go from experimenting to full production, finance and […]

Today, AWS announces the addition of cost analysis capabilities to Amazon Q Developer, allowing customers to retrieve and interpret their AWS cost data through natural language interactions. Amazon Q Developer is a generative AI-powered assistant that helps customers build, deploy, and operate applications on AWS. The cost analysis capability helps users of all skill levels to better understand and manage their AWS spending without previous knowledge of AWS Cost Explorer. Customers can now ask Amazon Q Developer questions about their AWS costs such as "Which region had the largest cost increase last month?" or "What services cost me the most last quarter?". Q interprets these questions, analyzes the relevant cost data, and provides easy-to-understand responses. Each answer includes transparency on the Cost Explorer parameters used and a link to visualize the data in Cost Explorer. This feature is now available in all AWS Regions where Amazon Q Developer is supported. Customers can access it via the Amazon Q icon in the AWS Management Console. To get started, see the AWS Cost Management user guide.

Today, AWS announces that AWS Cost Explorer now empowers customers with three key improvements: two generally available enhancements, including an 18-month forecasting horizon extending from the previous 12-month limit, and improved machine learning models that analyze up to 36 months of historical data (vs. previous 6 months) to identify seasonal patterns and long-term growth trends, and plus a new public preview feature offering AI-powered explanations that provide transparency into forecast methodology. AWS Cost Explorer helps customers analyze and manage their cloud spending through detailed cost and usage reports with forecasting capabilities. These enhancements provide the extended visibility needed for annual budget planning cycles. These capabilities enable finance teams to account for seasonal patterns, holiday peaks, and business cycles with enhanced accuracy and present forecasts with greater stakeholder confidence. The AI explanations help teams understand and communicate the key drivers behind their cost projections, making it easier to identify optimization opportunities and build executive buy-in for cloud investments. You can access the 18-month forecasting horizon directly through the AWS Cost Explorer console or via the GetCostForecast API. AI-powered explanations are currently available in the console only during public preview. To learn more about this enhanced feature, see https://aws.amazon.com/aws-cost-management/aws-cost-explorer/, user guides, and thehttps://aws.amazon.com/blogs/aws-cloud-financial-management/introducing-18-month-forecasting-and-explainable-ai-insights-in-aws-cost-explorer/. 

In my last Week in Review post, I mentioned how much time I’ve been spending on AI-Driven Development Lifecycle (AI-DLC) workshops with customers this year. A common theme in those sessions is the need for better cost visibility. Teams are moving fast with AI, but as they go from experimenting to full production, finance and […]

AWS Cost Explorer now supports 'Analyze with Amazon Q', a new capability that delivers comprehensive cost explanations for any report you configure in Cost Explorer. With a single button click you now can receive detailed analysis from Amazon Q Developer covering your cost trends, top cost drivers, and anomalies. All analysis uses your exact filters and time-period and provides guidance to discover optimization opportunities through follow-up questions. Previously, cost analysis required manual investigation across multiple filters and data points. With 'Analyze with Amazon Q', you simply configure your Cost Explorer view and click a single button. Amazon Q analyzes your current context and delivers explanations directly in its chat panel, adapting to what you're viewing: historical explanations for past dates, forecast explanations for future dates, or both for mixed periods. You can then ask follow-up questions to explore any insights related to your cost data in greater detail as Amazon Q maintains full conversation context throughout. 'Analyze with Amazon Q' is available in all commercial AWS Regions at no additional charge. To get started, visit the https://console.aws.amazon.com/cost-management/home console, or view the https://docs.aws.amazon.com/cost-management/latest/userguide/ce-what-is.html.

https://aws.amazon.com/aws-cost-management/aws-cost-anomaly-detection/ now includes AI-powered cost investigation, which uses Amazon Q to analyze the root cause of detected cost anomalies. Investigating a cost change typically requires correlating cost data with AWS CloudTrail events and resource activity, which can take hours. Cost investigation delivers a plain-language explanation in minutes, helping FinOps practitioners and engineering teams move from alert to action faster. When you investigate an anomaly, Amazon Q determines whether the cost change is usage-driven or rate-driven, identifies the contributing services, accounts, and regions, and for usage-driven changes, correlates with AWS CloudTrail to attribute the change to specific API calls and IAM principals. For organizations with a CloudTrail organization trail, the investigation works across all member accounts automatically. You can continue the conversation with follow-up questions to explore patterns or drill into specific resources.  AI-powered cost investigation is available today in all commercial AWS Regions at no additional charge. Cross-account investigations that use an organization-wide CloudTrail trail delivered to Amazon CloudWatch Logs might incur standard CloudWatch Logs Insights charges based on data scanned. To get started, navigate to AWS Cost Anomaly Detection in the https://console.aws.amazon.com/costmanagement/ and choose Investigate with Amazon Q on any detected anomaly. To learn more, see https://docs.aws.amazon.com/cost-management/latest/userguide/investigating-ad.html in the AWS Billing and Cost Management User Guide. 

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 https://aws.amazon.com/aws-cost-management/aws-cost-explorer/. To get started, see the https://docs.aws.amazon.com/cost-management/latest/userguide/ce-what-is.html.

Starting today, AWS Billing Conductor customers gain greater flexibility when using custom line items. Customers can now create service-specific custom line items scoped at either one AWS service or to a set of selected AWS service and can choose how these line items are presented in the pro forma billing artifacts, such as Bills Page, Cost Explorer and Cost and Usage Records. These enhancements enable customers to create more precise and tailored charge-back and re-billing strategies that better reflect their pricing structures and improve the traceability experience for pro forma users. Customers can use this functionality to apply percentage discounts on Saving Plans fees or allocate shared flat support charges under AWS Support service. Service specific custom line items are available for standard billing group regardless of the type of pricing plan selected, and for billing-transfer billing groups exclusively when customer-managed pricing plans are selected. To start, use AWS Billing Conductor console or APIs, create a custom line item and specify the cost reference value (one or multiple AWS services) and the display setting options (itemized or consolidated under your service of choice). To learn more about custom line items visit https://docs.aws.amazon.com/billingconductor/latest/userguide/what-is-billingconductor.html. This feature is available now in all AWS commercial Regions, excluding AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD.

Today, AWS announced the release of a model context protocol (MCP) server for Billing and Cost Management, now available in the https://github.com/awslabs/mcp/tree/main/src/billing-cost-management-mcp-server. The Billing and Cost Management MCP server allows customers to analyze their historical spending, find cost optimization opportunities, and estimate the costs of new workloads using the AI agent or assistant of their choice. Artificial intelligence is transforming the way that customers manage FinOps practices. While customers can access AI-powered cost analysis and optimization capabilities in Amazon Q Developer in the console, the Billing and Cost Management MCP server brings these capabilities to any MCP-compatible AI assistant or agent that customers may be using, such as https://docs.aws.amazon.com/amazonq/latest/qdeveloper-ug/qdev-mcp.html, the https://kiro.dev/docs/mcp/ IDE, https://code.visualstudio.com/docs/copilot/chat/mcp-servers, or https://support.anthropic.com/en/articles/10949351-getting-started-with-local-mcp-servers-on-claude-desktop. This MCP server gives these clients rich capabilities to analyze historical and forecasted cost and usage data, identify cost optimization opportunities, understand AWS service pricing, find cost anomalies, and more. The MCP server not only provides access to AWS service APIs; it also provides a dedicated SQL-based calculation engine allowing AI assistants to perform reliable, reproducible calculations — ranging from period-over-period changes to unit cost metrics — and easily handle large volumes of cost and usage data. You can download and integrate the open-source server with your preferred MCP-compatible AI assistant. The server connects securely to the AWS Billing and Cost Management services using standard AWS credentials with minimal configuration required. To get started, visit thehttps://github.com/awslabs/mcp/tree/main/src/aws-pricing-mcp-server.

AWS announces Cost Comparison, a new AWS Cost Explorer capability that helps customers understand cost changes between two months. Cost Comparison automatically detects significant cost changes between two months and surfaces the key factors driving these changes. With this launch, customers can now effortlessly gain insights into their monthly cost changes across their organization and quickly identify key drivers of spending changes. Cost Comparison streamlines the time-consuming process of cost analysis by automatically identifying the most substantial cost changes across services, accounts, and Regions. It eliminates the need to switch between different views in Cost Explorer or export data to spreadsheets for manual comparison. The feature provides detailed breakdowns of cost drivers, including usage changes, credits, refunds, and volume discounts impacts. A new Top Trends widget on the AWS Billing and Cost Management console home page shows the top 10 cost variations between the previous two months. For deeper analysis, customers can use the new Compare view within AWS Cost Explorer. This view offers comprehensive cost analysis capabilities, with insights into cost drivers that reveal changes between any two selected months in usage, credits, refunds, and volume discount impacts. Cost Comparison is available at no additional cost in all AWS commercial Regions, excluding AWS China Regions. To get started, customers can visit the AWS Billing and Cost Management console and view the Top Trends widget on the home page, or navigate to Cost Explorer and choose "Compare" in the Report Parameters panel. To learn more, see the https://docs.aws.amazon.com/cost-management/latest/userguide/ce-cost-comparison.html.

Today, AWS announces the addition of cost analysis capabilities to Amazon Q Developer, allowing customers to retrieve and interpret their AWS cost data through natural language interactions. Amazon Q Developer is a generative AI-powered assistant that helps customers build, deploy, and operate applications on AWS. The cost analysis capability helps users of all skill levels to better understand and manage their AWS spending without previous knowledge of AWS Cost Explorer. Customers can now ask Amazon Q Developer questions about their AWS costs such as "Which region had the largest cost increase last month?" or "What services cost me the most last quarter?". Q interprets these questions, analyzes the relevant cost data, and provides easy-to-understand responses. Each answer includes transparency on the Cost Explorer parameters used and a link to visualize the data in Cost Explorer. This feature is now available in all AWS Regions where Amazon Q Developer is supported. Customers can access it via the Amazon Q icon in the AWS Management Console. To get started, see the https://docs.aws.amazon.com/cost-management/latest/userguide/ce-q-overview.html.  

Today, AWS announces Cost Explorer historical data retention for accounts in billing groups.   Customers can use AWS Billing Conductor and Billing Transfer to map accounts to billing groups, enabling them to view billing data priced at the pro forma rates supplied by the payer account or Bill-Transfer account. Previously, the billing group configuration resulted in restricted access to historical billing data (priced at AWS billable rates) for accounts mapped to billing groups. With this launch, accounts included in billing groups retain access to their historical billing data in Cost Explorer at their original billable rates. Accounts previously on-boarded to Billing Conductor and Billing Transfer will gain access to their historical data with no additional action required. This enables reporting continuity for customers opting into AWS Billing Conductor and Billing Transfer. Billing Transfer is available today in all AWS Regions, excluding the GovCloud, China (Beijing) and China (Ningxia) Regions. To learn more about using Billing Transfer to centralize billing and cost management across your multi-organization environment, visit https://aws.amazon.com/aws-cost-management/aws-billing-transfer/, https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/orgs_transfer_billing.html, https://docs.aws.amazon.com/cost-management/latest/userguide/what-is-costmanagement.html, and news blog.

Today, AWS announces Cost Explorer historical data retention for accounts in billing groups.   Customers can use AWS Billing Conductor and Billing Transfer to map accounts to billing groups, enabling them to view billing data priced at the pro forma rates supplied by the payer account or Bill-Transfer account. Previously, the billing group configuration resulted in restricted access to historical billing data (priced at AWS billable rates) for accounts mapped to billing groups. With this launch, accounts included in billing groups retain access to their historical billing data in Cost Explorer at their original billable rates. Accounts previously on-boarded to Billing Conductor and Billing Transfer will gain access to their historical data with no additional action required. This enables reporting continuity for customers opting into AWS Billing Conductor and Billing Transfer. Billing Transfer is available today in all AWS Regions, excluding the GovCloud, China (Beijing) and China (Ningxia) Regions. To learn more about using Billing Transfer to centralize billing and cost management across your multi-organization environment, visit Billing Transfer product page, AWS Billing documentation, AWS Cost Management documentation, and news blog.

AWS Cost Explorer now supports 'Analyze with Amazon Q', a new capability that delivers comprehensive cost explanations for any report you configure in Cost Explorer. With a single button click you now can receive detailed analysis from Amazon Q Developer covering your cost trends, top cost drivers, and anomalies. All analysis uses your exact filters and time-period and provides guidance to discover optimization opportunities through follow-up questions. Previously, cost analysis required manual investigation across multiple filters and data points. With 'Analyze with Amazon Q', you simply configure your Cost Explorer view and click a single button. Amazon Q analyzes your current context and delivers explanations directly in its chat panel, adapting to what you're viewing: historical explanations for past dates, forecast explanations for future dates, or both for mixed periods. You can then ask follow-up questions to explore any insights related to your cost data in greater detail as Amazon Q maintains full conversation context throughout. 'Analyze with Amazon Q' is available in all commercial AWS Regions at no additional charge. To get started, visit the AWS Cost Explorer console, or view the user guide.

AWS Cost Anomaly Detection now includes AI-powered cost investigation, which uses Amazon Q to analyze the root cause of detected cost anomalies. Investigating a cost change typically requires correlating cost data with AWS CloudTrail events and resource activity, which can take hours. Cost investigation delivers a plain-language explanation in minutes, helping FinOps practitioners and engineering teams move from alert to action faster. When you investigate an anomaly, Amazon Q determines whether the cost change is usage-driven or rate-driven, identifies the contributing services, accounts, and regions, and for usage-driven changes, correlates with AWS CloudTrail to attribute the change to specific API calls and IAM principals. For organizations with a CloudTrail organization trail, the investigation works across all member accounts automatically. You can continue the conversation with follow-up questions to explore patterns or drill into specific resources.  AI-powered cost investigation is available today in all commercial AWS Regions at no additional charge. Cross-account investigations that use an organization-wide CloudTrail trail delivered to Amazon CloudWatch Logs might incur standard CloudWatch Logs Insights charges based on data scanned. To get started, navigate to AWS Cost Anomaly Detection in the AWS Billing and Cost Management console and choose Investigate with Amazon Q on any detected anomaly. To learn more, see Investigating anomaly root causes with Amazon Q in the AWS Billing and Cost Management User Guide.

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.

Starting today, AWS Billing Conductor customers gain greater flexibility when using custom line items. Customers can now create service-specific custom line items scoped at either one AWS service or to a set of selected AWS service and can choose how these line items are presented in the pro forma billing artifacts, such as Bills Page, Cost Explorer and Cost and Usage Records. These enhancements enable customers to create more precise and tailored charge-back and re-billing strategies that better reflect their pricing structures and improve the traceability experience for pro forma users. Customers can use this functionality to apply percentage discounts on Saving Plans fees or allocate shared flat support charges under AWS Support service. Service specific custom line items are available for standard billing group regardless of the type of pricing plan selected, and for billing-transfer billing groups exclusively when customer-managed pricing plans are selected. To start, use AWS Billing Conductor console or APIs, create a custom line item and specify the cost reference value (one or multiple AWS services) and the display setting options (itemized or consolidated under your service of choice). To learn more about custom line items visit AWS Billing Conductor documentation. This feature is available now in all AWS commercial Regions, excluding AWS China (Beijing) Region, operated by Sinnet, and AWS China (Ningxia) Region, operated by NWCD.

Today, AWS announced the release of a model context protocol (MCP) server for Billing and Cost Management, now available in the AWS Labs GitHub repository. The Billing and Cost Management MCP server allows customers to analyze their historical spending, find cost optimization opportunities, and estimate the costs of new workloads using the AI agent or assistant of their choice. Artificial intelligence is transforming the way that customers manage FinOps practices. While customers can access AI-powered cost analysis and optimization capabilities in Amazon Q Developer in the console, the Billing and Cost Management MCP server brings these capabilities to any MCP-compatible AI assistant or agent that customers may be using, such as Q Developer CLI tool, the Kiro IDE, Visual Studio Code, or Claude Desktop. This MCP server gives these clients rich capabilities to analyze historical and forecasted cost and usage data, identify cost optimization opportunities, understand AWS service pricing, find cost anomalies, and more. The MCP server not only provides access to AWS service APIs; it also provides a dedicated SQL-based calculation engine allowing AI assistants to perform reliable, reproducible calculations — ranging from period-over-period changes to unit cost metrics — and easily handle large volumes of cost and usage data. You can download and integrate the open-source server with your preferred MCP-compatible AI assistant. The server connects securely to the AWS Billing and Cost Management services using standard AWS credentials with minimal configuration required. To get started, visit the AWS Labs GitHub repository.

AWS announces Cost Comparison, a new AWS Cost Explorer capability that helps customers understand cost changes between two months. Cost Comparison automatically detects significant cost changes between two months and surfaces the key factors driving these changes. With this launch, customers can now effortlessly gain insights into their monthly cost changes across their organization and quickly identify key drivers of spending changes. Cost Comparison streamlines the time-consuming process of cost analysis by automatically identifying the most substantial cost changes across services, accounts, and Regions. It eliminates the need to switch between different views in Cost Explorer or export data to spreadsheets for manual comparison. The feature provides detailed breakdowns of cost drivers, including usage changes, credits, refunds, and volume discounts impacts. A new Top Trends widget on the AWS Billing and Cost Management console home page shows the top 10 cost variations between the previous two months. For deeper analysis, customers can use the new Compare view within AWS Cost Explorer. This view offers comprehensive cost analysis capabilities, with insights into cost drivers that reveal changes between any two selected months in usage, credits, refunds, and volume discount impacts. Cost Comparison is available at no additional cost in all AWS commercial Regions, excluding AWS China Regions. To get started, customers can visit the AWS Billing and Cost Management console and view the Top Trends widget on the home page, or navigate to Cost Explorer and choose "Compare" in the Report Parameters panel. To learn more, see the AWS Cost Explorer documentation.