Category: Uncategorized

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!

As we continue our five-part series on optimizing costs for generative AI workloads on AWS, our third blog shifts our focus to Amazon Bedrock. In our previous posts, we explored general Cloud Financial Management principles on generative AI adoption and strategies for custom model development using Amazon EC2 and Amazon SageMaker AI. Today, we’ll guide you through cost optimization techniques for Amazon Bedrock, AWS’s fully managed service that provides access to leading foundation models. We’ll explore making informed decisions about pricing options, model selection, knowledge base optimization, prompt caching, and automated reasoning. Whether you’re just starting with foundation models or looking to optimize your existing Amazon Bedrock implementation, these techniques will help you balance capability and cost while leveraging the convenience of managed AI models.

If you or your organizations are in the midst of exploring generative AI technologies, it’s important for you to be aware of the investment that comes with these advanced applications. While you are aiming at the expected return on your generative AI investment, such as, operational efficiency, increased productivity, or improved customer satisfaction, you should also have a good understanding of levers you can use to drive cost savings and enhanced efficiency. To guide you through this exciting journey, we will publish a series of blog posts filled with practical tips to help AI practitioners and FinOps leaders understand how to optimize the costs associated with your generative AI adoption with AWS.

In this article, we will show you how to define a chargeback mechanism that allocates Savings Plans purchased in the management account, linked accounts or both to recipient accounts of Savings Plan discounts. You can identify accounts that received Savings Plans discounts and the appropriate amount to chargeback to them based on their specific usage.

In this blog post, we discuss how Amazon used AWS Billing Conductor to build a custom solution, enabling them to view their AWS cost at internal rates in AWS Cost Explorer and AWS Cost and Usage Report (CUR).

With re:Invent 2024 in the books, and over 50 launch announcements, here are four that we’re most excited about. The overarching theme of these launches appears to be leveraging Amazon’s automation capabilities to optimize costs and improve efficiency for customers.

With great pleasure, I am happy to share with you the ten features recently added to the AWS Cloud Financial Management portfolio of services. We hope that these ten new features will help accomplish your daily FinOps tasks more effectively. These new features are like our holiday gifts to you. Enjoy your holiday and these special gifts from us. We look forward to hearing about your experiences with them.