Category: Compute

If you are new to AWS, you may be wondering how you can learn and experiment with cloud services while keeping your spend under your control. Budget Controls for AWS is an open-source solution designed to solve this problem. This solution was designed for customers new to AWS with no prior experience. It automatically watches your spending and takes actions you define when costs reach certain thresholds. Think of it as a safety net that can send you alerts, temporarily stop resources, or even delete them to prevent runaway costs.

We are excited to introduce split cost allocation support for accelerated workloads in Amazon Elastic Kubernetes Service (EKS). This enhancement to Split Cost Allocation Data for EKS enables customers to track container-level resource costs for accelerator-powered workloads. Split Cost Allocation Data now utilizes Trainium, Inferentia, NVIDIA and AMD GPUs, complementing existing CPU and memory cost tracking capabilities. This cost data is available in the AWS Cost and Usage Report (legacy and CUR 2.0), providing organizations with a consolidated view of their cloud expenditures. This feature is now available across all AWS commercial regions (excluding China regions) at no additional cost to customers.

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.

Amazon EC2 and SageMaker AI are two of the foundational AWS services for Generative AI. Amazon EC2 provides the scalable computing power needed for training and inference, while SageMaker AI offers built-in tools for model development, deployment, and optimization. Cost optimization is crucial since Generative AI workloads require high-performance accelerators (GPU, Trainium, or Inferentia) and extensive processing, which can become expensive without efficient resource management. By leveraging the below cost optimization strategies, you can reduce costs while maintaining performance and scalability.

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.

Starting today, AWS Compute Optimizer will give recommendations to clean up idle resources. AWS Compute Optimizer historically has been focused on providing rightsizing recommendations to save cost and improve performance. To help you drive further cost savings, we are expanding the focus to now include detecting and recommending cleanup of idle recommendations. With this launch, you will get recommendations for idle EBS volumes, ECS tasks on running on Fargate, EC2 instances, EC2 Auto Scaling groups, and RDS instances.

We’re excited to announce the release of AWS Cloud Financial Management digital training courses. These are four 1-hour courses that will get you familiarized with key AWS solutions to solve your daily FinOps needs, and equip you with cost optimization techniques for commonly used AWS services.

As many organizations are looking to achieve financial success through effective Cloud Financial Management (CFM) strategies, Infor, the global leading software provider, has been experimenting with different practices, from cost reporting to optimization. In this blog post, we will share their success and learning that helped achieve over $2 million in savings through automation and modernization initiatives.