AWS Billing Transfer users can now enable the Auto-Billing Transfer Billing Group Creation, a new AWS Billing Conductor preference that eliminates the manual billing group configuration in two-level billing transfer arrangements. Designed for AWS Distributors managing billing for downstream seller Partners and their end customers, this feature automatically creates billing groups when an end customer accepts a billing transfer from a downstream seller Partner, ensuring pro forma cost data is immediately available to the Partner, with no extra manual configuration. Auto-Billing Transfer Billing Group Creation is a one-time preference configuration per inbound transfer relationship, enabling you to request the creation of a billing group for any new indirect transfer coming through your Partners' account, as well as being able to specify an AWS Billing Conductor pricing plan for the billing groups created automatically.  The preference is accessible through two new API operations and through the AWS Management Console in the Billing Transfer details page.  To learn more about Auto-Billing Transfer Billing Group Creation and how to configure your billing transfer preferences, visit the https://docs.aws.amazon.com/billingconductor/latest/userguide/create-billing-group.html.

AWS Billing and Cost Management now offers the ListBillingViewSegments API, which returns the billing context of your account over a time period you specify. You can use the API to retrieve information about how your accounts are positioned in the billing hierarchy, such as management accounts, member accounts, or billing group primary accounts. You can also identify which accounts managed your billing relationship and the rate settings, either billable or pro forma, applied to your cost data. The API returns billing context only, not cost and usage data. You can call the API directly or through an AI agent. Your billing context can change mid-period. The API therefore divides the requested period into time segments, each with its effective date range. For example, an account starts as its own payer, then moves under another organization as a member account, and in a later month has its new payer manage its billing through AWS Billing Conductor. A request covering all three periods returns three segments, each identifying the accounts and billing settings that were in effect. ListBillingViewSegments is available in all commercial AWS Regions at no additional charge and supports primary billing views. To get started, visit the https://docs.aws.amazon.com/aws-cost-management/latest/APIReference/API_billing_ListBillingViewSegments.html.

AWS Billing and Cost Management now offers the ListBillingViewSegments API, which returns the billing context of your account over a time period you specify. You can use the API to retrieve information about how your accounts are positioned in the billing hierarchy, such as management accounts, member accounts, or billing group primary accounts. You can also identify which accounts managed your billing relationship and the rate settings, either billable or pro forma, applied to your cost data. The API returns billing context only, not cost and usage data. You can call the API directly or through an AI agent. Your billing context can change mid-period. The API therefore divides the requested period into time segments, each with its effective date range. For example, an account starts as its own payer, then moves under another organization as a member account, and in a later month has its new payer manage its billing through AWS Billing Conductor. A request covering all three periods returns three segments, each identifying the accounts and billing settings that were in effect. ListBillingViewSegments is available in all commercial AWS Regions at no additional charge and supports primary billing views. To get started, visit the AWS Billing API Reference.

AWS Billing Transfer users can now enable the Auto-Billing Transfer Billing Group Creation, a new AWS Billing Conductor preference that eliminates the manual billing group configuration in two-level billing transfer arrangements. Designed for AWS Distributors managing billing for downstream seller Partners and their end customers, this feature automatically creates billing groups when an end customer accepts a billing transfer from a downstream seller Partner, ensuring pro forma cost data is immediately available to the Partner, with no extra manual configuration. Auto-Billing Transfer Billing Group Creation is a one-time preference configuration per inbound transfer relationship, enabling you to request the creation of a billing group for any new indirect transfer coming through your Partners' account, as well as being able to specify an AWS Billing Conductor pricing plan for the billing groups created automatically.  The preference is accessible through two new API operations and through the AWS Management Console in the Billing Transfer details page.  To learn more about Auto-Billing Transfer Billing Group Creation and how to configure your billing transfer preferences, visit the AWS Billing Conductor documentation.

Starting today, Split Cost Allocation Data for Amazon EKS now allows you to import up to 50 Kubernetes custom labels per pod as cost allocation tags. You can attribute costs of your Amazon EKS cluster at the pod level using custom attributes, such as cost center, application, business unit, and environment in AWS Cost and Usage Report (CUR). With this new https://docs.aws.amazon.com/cur/latest/userguide/split-cost-allocation-data-kubernetes-labels.html, you can better align your cost allocation with specific business requirements and organizational structure driven by your cloud financial management needs. This enables granular cost visibility of your EKS clusters running multiple application containers using shared EC2 instances, allowing you to allocate the shared costs of your EKS cluster. For new split cost allocation data customers, you can enable this feature in the AWS Billing and Cost Management console. For existing customers, EKS will automatically import the labels, but you must activate them as cost allocation tags. After activation, Kubernetes custom labels are available in your CUR within 24 hours. You can use the https://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/scad-containers-dashboard.html to visualize the costs in Amazon QuickSight and the https://catalog.workshops.aws/cur-query-library/en-US/queries/container to query the costs using Amazon Athena. This feature is available in all AWS Regions where Split Cost Allocation Data for Amazon EKS is available. To get started, visit https://docs.aws.amazon.com/cur/latest/userguide/split-cost-allocation-data.html.

AWS has enabled Multi-Factor Authentication (MFA) for card registration in Japan to enhance payment security. Customers will need to perform MFA when registering new cards at sign-up or the AWS Billing and Cost Management Console. MFA provides an extra layer of security during card registration, helping protect customers against credit card fraud. This implementation supports all major card networks including: Visa, Mastercard, American Express, Diners Club, China UnionPay, and JCB. The authentication process uses 3D-Secure technology, which is the global standard for card payment security, ensuring safe and secure card registration for our customers. When adding or updating a new card in their AWS account, you will automatically be redirected to your card issuer’s authentication page to complete MFA. After successful authentication, your card will be registered and ready for use with AWS. This applies to both new customer sign-ups and existing customers adding new cards through the AWS Billing and Cost Management Console. For more information to manage payment verification, visit the AWS Billing and Cost Management https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/manage-cc-verification.html.  

In addition to the currencies already supported, AWS US customers can choose to pay in Chilean Peso (CLP), Colombian Peso (COP), and Uruguayan Peso (UYU). Similarly, AWS Europe customers can pay in Egyptian Pound (EGP), Nigerian Naira (NGN), Polish Zloty (PLN), Romanian Leu (RON), Ukrainian Hryvnia (UAH). Local currencies are important in localizing the payment experience for customers. With payments in their local currencies, customers can avoid foreign exchange costs associated making foreign currency payments. Also, it removes payment friction for customers in countries where local regulations put limits on the foreign currency amount a customer can access. Log in to your AWS account, go to the “Billing and Cost Management“ page, and select “Payment Preferences” under Preferences and Settings“ from the left navigation menu . Click ”Edit“ to change your default payment preferences, and select your preferred currency from the ”Payment currency“ drop down. Once you save your changes, AWS will generate your future invoices in the selected currency. Learn more about managing your AWS payments.

AWS announces significant improvements to AWS Cost Anomaly Detection, enhancing its ability to identify meaningful changes in your AWS spending patterns. This update delivers more consistent and reliable cost monitoring by better handling historical cost variations. With this improvement, Cost Anomaly Detection better understands your organization’s typical spend patterns. It distinguishes between one-time and recurrent cost events, while maintaining accuracy in detecting cost changes that require your attention These improvements are automatically applied to all AWS Cost Anomaly Detection monitors in all AWS Regions, except the AWS GovCloud (US) Regions and the China Regions. To learn more about AWS Cost Anomaly Detection and this enhancement, visit the AWS Cost Anomaly Detection https://aws.amazon.com/aws-cost-management/aws-cost-anomaly-detection/ and https://docs.aws.amazon.com/cost-management/latest/userguide/manage-ad.html.

Today, AWS announces the general availability of new capabilities within AWS Billing and Cost Management that enable customers to manage their AWS spend across multiple organizations through a single AWS account. Customers can now share custom billing views containing cost management data with other AWS accounts outside their organization. Additionally, customers can combine multiple custom billing views to create new consolidated views. These features enable FinOps teams to create custom billing views containing cost management data for multiple organizations. These views can then be used to access cost management data across multiple organizations through Cost Explorer or set up budgets to monitor AWS costs. With the new custom billing view capabilities, you can create consolidated views of cost management data spanning multiple organizations that can be accessed using AWS Cost Explorer and AWS Budgets, allowing you to monitor, analyze, and forecast spending patterns across multiple organizations. This helps customers operating multiple subsidiaries or business units as separate organizations on AWS manage their AWS spend through a single AWS account. Support for custom billing views containing cost management data for multiple organizations is available in all AWS Regions, excluding AWS GovCloud Regions and the AWS China Regions. To get started with custom billing views, visit Billing View within the Cost Management Preferences page in the AWS Billing and Cost Management console and create a new custom billing view. To get started visit the Billing View user guide.

AWS announces significant improvements to AWS Cost Anomaly Detection, enhancing its ability to identify meaningful changes in your AWS spending patterns. This update delivers more consistent and reliable cost monitoring by better handling historical cost variations. With this improvement, Cost Anomaly Detection better understands your organization’s typical spend patterns. It distinguishes between one-time and recurrent cost events, while maintaining accuracy in detecting cost changes that require your attention These improvements are automatically applied to all AWS Cost Anomaly Detection monitors in all AWS Regions, except the AWS GovCloud (US) Regions and the China Regions. To learn more about AWS Cost Anomaly Detection and this enhancement, visit the AWS Cost Anomaly Detection product page and User Guide.

Today, we are introducing automation rules, a new feature in AWS Compute Optimizer that enables you to optimize Amazon Elastic Block Store (EBS) volumes at scale. With automation rules, you can streamline the process of cleaning up unattached EBS volumes and upgrading volumes to the latest-generation volume types, saving cost and improving performance across your cloud infrastructure. Automation rules let you automatically apply optimization recommendations on a recurring schedule when they match your criteria. You can set criteria like AWS Region to target specific geographies and Resource Tags to distinguish between production and development workloads. Configure rules to run daily, weekly, or monthly, and AWS Compute Optimizer will continuously evaluate new recommendations against your criteria. A new dashboard allows you to summarize automation events over time, examine detailed step history, and estimate savings achieved. If you need to reverse an action, you can do so directly from the same dashboard. AWS Compute Optimizer automation rules are available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), and South America (São Paulo). To get started, navigate to the new Automation section in the AWS Compute Optimizer console, visit the AWS Compute Optimizer user guide documentation, or read the announcement blog to learn more.

Amazon Q Developer now offers enhanced cost management capabilities, enabling customers to analyze costs across a wider range of Cloud Financial Management domains with more advanced analytical capabilities. Customers can now ask complex, open-ended questions about historical and forecasted costs and usage, optimization recommendations, commitment coverage and utilization, cost anomalies, budgets, free tier usage, product attributes, and cost estimation. Q can explore data, form hypotheses, and perform calculations to provide deeper insights with less time and expertise required. With these capabilities, FinOps practitioners, engineers, and Finance professionals can increase productivity by delegating more cost analysis and estimation tasks to Q. For example, customers can ask "Why did costs for this application increase last week?". Q will explore the data by retrieving costs and usage quantities by service, account, or resource, form hypotheses, gather data from multiple sources, and perform calculations ranging from simple period-over-period cost changes to unit economic metrics like effective cost per instance-hour. Q provides transparency on each API call it makes to retrieve data, including specific parameters used, and provides matching console links where customers can verify the data or dive deeper. To get started, open the Amazon Q chat panel from anywhere in the AWS Management Console and ask a question about your costs. To learn more, see https://docs.aws.amazon.com/cost-management/latest/userguide/ce-cost-analysis-q.html in the AWS Cost Management user guide.

Today, AWS announces the general availability of new capabilities within AWS Billing and Cost Management that enable customers to manage their AWS spend across multiple organizations through a single AWS account. Customers can now share custom billing views containing cost management data with other AWS accounts outside their organization. Additionally, customers can combine multiple custom billing views to create new consolidated views. These features enable FinOps teams to create custom billing views containing cost management data for multiple organizations. These views can then be used to access cost management data across multiple organizations through Cost Explorer or set up budgets to monitor AWS costs. With the new custom billing view capabilities, you can create consolidated views of cost management data spanning multiple organizations that can be accessed using AWS Cost Explorer and AWS Budgets, allowing you to monitor, analyze, and forecast spending patterns across multiple organizations. This helps customers operating multiple subsidiaries or business units as separate organizations on AWS manage their AWS spend through a single AWS account. Support for custom billing views containing cost management data for multiple organizations is available in all AWS Regions, excluding AWS GovCloud Regions and the AWS China Regions. To get started with custom billing views, visit Billing View within the Cost Management Preferences page in the AWS Billing and Cost Management console and create a new custom billing view. To get started visit the https://docs.aws.amazon.com/cost-management/latest/userguide/billing-view.html.

Amazon Web Services (AWS) announces that Amazon Q Developer now provides personalized cost optimization recommendations to help customers easily identify and implement savings opportunities. This new capability helps customers find and implement opportunities for rightsizing instances, purchasing Savings Plans and Reserved Instances, terminating idle resources, and more - all through natural language conversations. Amazon Q Developer combines recommendations from AWS Cost Optimization Hub with expert guidance to help customers accelerate their cost optimization journey and maximize savings. With this launch, customers can ask Amazon Q Developer questions like "How can I lower my AWS bill?" to receive prioritized recommendations based on potential savings, implementation effort, and performance risk. Customers can also ask detailed follow-up questions like "How was this recommendation calculated?" or "How was this instance identified as idle?", and receive narrative explanations including metrics, configurations, and customization options. Customers can also ask Amazon Q Developer to analyze their costs, check resource details, and receive step-by-step implementation guidance, completing more of their end-to-end cost optimization workflow through natural conversations. This feature is available in the US East (N. Virginia) region, and provides cost optimization recommendations spanning all commercial AWS Regions, except the China Regions, and the AWS GovCloud (US) Regions. To learn more about using Amazon Q Developer for cost optimization, see the https://docs.aws.amazon.com/amazonq/latest/qdeveloper-ug/chat-costs.html. To get started, simply open the Amazon Q chat panel in the AWS Management Console and ask about ways to optimize your costs.

Today, we are introducing automation rules, a new feature in AWS Compute Optimizer that enables you to optimize Amazon Elastic Block Store (EBS) volumes at scale. With automation rules, you can streamline the process of cleaning up unattached EBS volumes and upgrading volumes to the latest-generation volume types, saving cost and improving performance across your cloud infrastructure. Automation rules let you automatically apply optimization recommendations on a recurring schedule when they match your criteria. You can set criteria like AWS Region to target specific geographies and Resource Tags to distinguish between production and development workloads. Configure rules to run daily, weekly, or monthly, and AWS Compute Optimizer will continuously evaluate new recommendations against your criteria. A new dashboard allows you to summarize automation events over time, examine detailed step history, and estimate savings achieved. If you need to reverse an action, you can do so directly from the same dashboard. AWS Compute Optimizer automation rules are available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), and South America (São Paulo). To get started, navigate to the new Automation section in the AWS Compute Optimizer console, visit the AWS Compute Optimizer https://docs.aws.amazon.com/compute-optimizer/latest/ug/automation.html, or read the https://aws.amazon.com/blogs/aws-cloud-financial-management/introducing-automated-amazon-ebs-volume-optimization-in-aws-compute-optimizer/ to learn more.

AWS Cost Anomaly Detection now features an improved detection algorithm that enables faster identification of unusual spending patterns. The enhanced algorithm analyzes your AWS spend using rolling 24-hour windows, comparing current costs against equivalent time periods from previous days each time AWS receives updated cost and usage data. The enhanced algorithm addresses two common challenges in cost pattern analysis. First, it removes the delay in anomaly detection caused by comparing incomplete calendar-day costs against historical daily totals. The rolling window always compares full 24-hour periods, enabling faster identification of unusual patterns. Second, it provides more accurate comparisons by evaluating costs against similar times of day, accounting for workloads that have different morning and evening usage patterns. These improvements help reduce false positives while enabling faster, more accurate anomaly detection. This enhancement to AWS Cost Anomaly Detection is available in all AWS Regions, except the AWS GovCloud (US) Regions and the China Regions. To learn more about this new feature, AWS Cost Anomaly Detection, and how to reduce your risk of spend surprises, visit the AWS Cost Anomaly Detection https://aws.amazon.com/aws-cost-management/aws-cost-anomaly-detection/ and https://docs.aws.amazon.com/cost-management/latest/userguide/billing-getting-started.html.

https://aws.amazon.com/aws-cost-management/aws-cost-anomaly-detection/ now monitors spend on third-party foundation models running on Amazon Bedrock, such as Anthropic Claude and other provider-hosted models. Cost Anomaly Detection uses machine learning to detect and alert on unusual spend, and this launch extends that coverage to third-party model usage on Amazon Bedrock. Teams running production generative AI workloads now get automatic anomaly detection on their Amazon Bedrock model spend alongside the rest of their AWS costs. With this launch, Cost Anomaly Detection automatically evaluates your third-party Amazon Bedrock model costs through your AWS managed service monitor, with no setup required. When spend on a model changes unexpectedly, you receive an alert and a root-cause breakdown ranked by dollar impact across AWS service, account, Region, and usage type, so you can understand and act on generative AI cost changes as quickly as you do for any other AWS spend. This feature is available in all AWS commercial regions, except the AWS GovCloud and the China Regions. To learn more, see https://docs.aws.amazon.com/cost-management/latest/userguide/manage-ad.html in the AWS Billing and Cost Management User Guide.

Today, AWS announces the general availability of a self-service Invoice correction feature to update AWS invoices. This launch enables all AWS customers to correct key invoice attributes—including purchase order numbers, business legal name, and addresses — on their AWS invoices and get corrected invoices instantaneously. AWS customers can now access the new self-service Invoice correction feature directly from the AWS Billing and Cost Management console. This feature offers AWS customers a guided self-service workflow to update invoice attributes in their account settings and on select invoices. This feature gives AWS customers direct control over invoice corrections while reducing wait times and improving efficiency in managing their AWS accounts. AWS self-service Invoice Correction feature is generally available in all AWS Regions, excluding GovCloud (US) Regions and China (Beijing) and China (Ningxia) Regions. To get started with AWS self-service invoice correction feature, please visit the https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/getting-viewing-bill.html#view-invoices. 

Today, AWS announces a new pricing and cost estimation capability in Amazon Q Developer. Amazon Q Developer is the most capable generative AI-powered assistant for software development. With this launch, customers can now use Amazon Q Developer to get information about AWS product and service pricing, availability, and attributes, helping them select the right resources and estimate workload costs using natural language. When architecting new workloads on AWS, customers need to estimate costs so they can evaluate cost/performance tradeoffs, set budgets, and plan future spending. Customers can now use Amazon Q Developer to retrieve detailed product attribute and pricing information using natural language, making it easier to estimate the cost of new workloads without having to review multiple pricing pages or specify detailed API request parameters. Customers can now ask questions about service pricing (e.g., “How much does RDS extended support cost?”), the cost of a planned workload (e.g., “I need to send 1 million notifications per month to email, and 1 million to HTTP/S endpoints. Estimate the monthly cost using SNS.”), or the relative costs of different resources (e.g., “What is the cost difference between an Application Load Balancer and a Network Load Balancer?”). To answer these questions, Amazon Q Developer retrieves information from the AWS Price List APIs. To learn more, see Managing your costs using generative AI with Amazon Q Developer. To get started, open the Amazon Q chat panel in the AWS Management Console and ask a question about pricing.

Today, AWS announces the general availability of a self-service Invoice correction feature to update AWS invoices. This launch enables all AWS customers to correct key invoice attributes—including purchase order numbers, business legal name, and addresses — on their AWS invoices and get corrected invoices instantaneously. AWS customers can now access the new self-service Invoice correction feature directly from the AWS Billing and Cost Management console. This feature offers AWS customers a guided self-service workflow to update invoice attributes in their account settings and on select invoices. This feature gives AWS customers direct control over invoice corrections while reducing wait times and improving efficiency in managing their AWS accounts. AWS self-service Invoice Correction feature is generally available in all AWS Regions, excluding GovCloud (US) Regions and China (Beijing) and China (Ningxia) Regions. To get started with AWS self-service invoice correction feature, please visit the product details page.

Today, AWS announces that AWS Compute Optimizer now supports idle resource recommendations for NAT Gateways. With this new recommendation type, you will be able to identify NAT Gateways that are unused, resulting in cost savings. With the new unused NAT Gateway recommendation, you will be able to identify NAT Gateways that show no traffic activity over a 32-day analysis period. Compute Optimizer analyzes CloudWatch metrics including active connection count, incoming packets from source, and incoming packets from destination to validate if NAT Gateways are truly unused. To avoid recommending critical backup resources, Compute Optimizer also examines if the NAT Gateway resource is associated in any AWS Route Tables. You can view the total savings potential of these unused NAT Gateways and access detailed utilization metrics to verify unused conditions before taking action. This new feature is available in all https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ where AWS Compute Optimizer is available except the AWS GovCloud (US) and the China Regions. To learn more about the new feature updates, please visit Compute Optimizer’s https://aws.amazon.com/compute-optimizer/ and https://docs.aws.amazon.com/compute-optimizer/latest/ug/what-is-compute-optimizer.html.

Today, AWS’ Customer Carbon Footprint Tool (CCFT) has been updated to include Scope 3 emissions data and Scope 1 natural gas and refrigerants, providing AWS customers more complete visibility into their cloud carbon footprint. This update expands the CCFT to cover all three industry-standard emission scopes as defined by the Greenhouse Gas Protocol. The CCFT Scope 3 update gives AWS customers full visibility into the lifecycle carbon impact of their AWS usage, including emissions from manufacturing the servers that run their workloads, powering AWS facilities, and transporting equipment to data centers. Historical data is available back to January 2022, allowing organizations to track their progress over time and make informed decisions about their cloud strategy to meet their sustainability goals. This data is available through the CCFT dashboard and AWS Billing and Cost Management Data Exports, enabling customers to easily incorporate carbon insights into their operational workflows, sustainability planning, and reporting processes. To learn more about the enhanced Customer Carbon Footprint Tool, visit the CCFT Website, AWS Billing and Cost Management console or read the updated methodology documentation and release notes.

AWS Compute Optimizer now provides recommendations for Amazon Aurora DB instances. These recommendations help you identify idle database instances and choose the optimal DB instance class, so you can reduce costs for unused resources and increase the performance of under-provisioned workloads. AWS Compute Optimizer automatically analyzes Amazon CloudWatch metrics such as CPU utilization, network throughput, and database connections to generate recommendations for your DB instances running Amazon Aurora MySQL-Compatible Edition and Aurora PostgreSQL-Compatible Edition engines. If you enable https://aws.amazon.com/rds/performance-insights/ on your DB instances, Compute Optimizer will analyze additional metrics such as DBLoad and out-of-memory counters to give you more insights to choose the optimal DB instance configuration. With this launch, AWS Compute Optimizer now supports recommendations for Amazon RDS for MySQL, Amazon RDS for PostgreSQL, and Amazon Aurora database engines. This new feature is available in all https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ where AWS Compute Optimizer is available except the AWS GovCloud (US) and the China Regions. To learn more about the new feature updates, please visit Compute Optimizer’s https://aws.amazon.com/compute-optimizer/ and https://docs.aws.amazon.com/compute-optimizer/latest/ug/what-is-compute-optimizer.html.

Today, AWS announces that AWS Compute Optimizer now supports idle resource recommendations for NAT Gateways. With this new recommendation type, you will be able to identify NAT Gateways that are unused, resulting in cost savings. With the new unused NAT Gateway recommendation, you will be able to identify NAT Gateways that show no traffic activity over a 32-day analysis period. Compute Optimizer analyzes CloudWatch metrics including active connection count, incoming packets from source, and incoming packets from destination to validate if NAT Gateways are truly unused. To avoid recommending critical backup resources, Compute Optimizer also examines if the NAT Gateway resource is associated in any AWS Route Tables. You can view the total savings potential of these unused NAT Gateways and access detailed utilization metrics to verify unused conditions before taking action. This new feature is available in all AWS Regions where AWS Compute Optimizer is available except the AWS GovCloud (US) and the China Regions. To learn more about the new feature updates, please visit Compute Optimizer’s product page and user guide.