Category: Uncategorized

A cloud vendor’s Cloud Financial Management (CFM) capabilities are crucial for your success in the cloud. Whether you’re planning future investments, optimizing current spending, or allocating costs across your organization, having the right CFM tools makes all the difference. AWS is proud to be recognized with the 1st place in forecasting and estimation use case, and top 3 in driving cost efficiency use case and promotion accountability use case in the latest 2025 Gartner Critical Capabilities for Cloud Financial Management Tools research.

Today, we are excited to announce new capabilities within AWS Billing and Cost Management that enable you to create custom billing views containing cost and usage data from multiple organizations. You can now share custom billing views with AWS accounts outside your organization and combine multiple custom billing views to create consolidated multi-source views. These features allow you to access cost management data across multiple organizations through AWS Cost Explorer and AWS Budgets from a single AWS account.

Accurately allocating cloud costs in AWS is essential for fostering accountability and maximizing the value derived from cloud investments. Cost allocation requires careful consideration of your organization’s structure, workload patterns, and financial requirements. Whether you’re utilizing AWS accounts, Cost Allocation Tags, Cost Categories, or Billing Conductor, the key is selecting patterns that align with your business needs while maintaining simplicity and scalability. Start with the fundamental building blocks of AWS cost allocation, then layer in more sophisticated approaches as your organization’s needs evolve. By implementing these prescriptive patterns thoughtfully, you can create the cost transparency and accountability needed to drive business value from your cloud investments. Remember that cost allocation is not a one-time exercise—regularly review and adjust your approach as your business grows and your cloud journey continues.

Savings Plans offer a flexible pricing model that provides you up to 72% savings on your AWS compute workload compared to on-demand prices. When your AWS footprint grows through organic expansion, regional scaling, mergers, acquisitions, or setting up AWS Organizations to align with your business requirements, understanding how the recommendations are made at payer and linked account levels helps you manage Savings Plans at scale. If you are managing a multi-account AWS Organization, you might have noticed that Savings Plan recommendations differ between your payer account (also known as management account) and linked account (also known as member account).

In this blog, we’ll explore a straightforward, automated approach to departmental cost allocation using AWS Organizations and AWS Lambda. The solution eliminates manual tracking and gives you clear visibility into departmental spending.

We are excited to release the aws-pricing-mcp-server, an open-source tool in the AWS Labs GitHub repository, that brings natural language pricing queries to your favorite AI assistants through the Model Context Protocol (MCP). Now you can simply ask “What would it cost to run three m5.large instances and a MySQL RDS database in us-west-2?” and get instant pricing answers using natural language queries without leaving your workflow.

As organizations expand, FinOps teams require a comprehensive overview of AWS Savings Plans commitments to maximize utilization efficiency. This solution involves implementing monitoring systems and automated alerts to identify underutilized Savings Plans within the eligible return period. In this blog post, we provide AWS CloudFormation templates that create AWS Step Functions state machine, Amazon Simple Notification Service (SNS) topic, Amazon EventBridge scheduler, and necessary AWS Identity and Access Management (IAM) roles to automate the monitoring of newly purchased Savings Plans and highlight those that are underutilized.

Navigating GPU resource constraints requires a multi-faceted approach spanning procurement strategies, leveraging AWS AI accelerators, exploring alternative compute options, utilizing managed services like SageMaker, and implementing best practices for GPU sharing, containerization, monitoring, and cost governance. By adopting these techniques holistically, organizations can efficiently and cost-effectively execute AI, ML, and GenAI workloads on AWS, even amidst GPU scarcity. Importantly, these optimization strategies will remain valuable long after GPU supply chains recover, as they establish foundational practices for sustainable AI infrastructure that maximizes performance while controlling costs—an enduring priority for organizations scaling their AI initiatives into the future.

Today, we’re excited to announce the general availability of the authenticated AWS Pricing Calculator in the AWS Billing and Cost Management Console. The new capability improves the accuracy of cost estimates for new workloads or modifications to your existing AWS usage by incorporating eligible discounts and commitment savings. You can now easily model cost changes for things such as migrating workloads between regions, modifying existing or planning new workloads, and planning for commitment purchases.

We’re excited to engage with the FinOps community at FinOps X 2025 in San Diego, June 2-5. If you’re looking to spend quality time with the AWS team, here’s where you can find us from reception parties on Monday evening, keynote, breakout sessions, booth, and customer meetings. Can’t wait to see you all soon!