AWS Cloud Financial Management
Author: Manoj Jayadevan
Manoj Jayadevan is Principal Product Manager at Amazon Web Services. He works on solving shared infrastructure cost allocation problems for AWS Cloud Customers. He holds a Bachelors degree in Electrical Engineering and a Master in Business Administration.
Using Kubernetes Labels to Split and Track Application Costs on Amazon EKS
We’re excited to announce support for Kubernetes labels in split cost allocation data for Amazon Elastic Kubernetes Service (EKS). With this launch, you can now import Kubernetes labels as user-defined cost allocation tags into split cost allocation data, allowing you to attribute the cost of your applications running on an Amazon EKS cluster using these labels in AWS Cost and Usage Reports (CUR). This enables you to allocate your Kubernetes costs based on your specific business requirements and organizational design.
Leveraging AWS Cost Allocation Capabilities to Meet your Business Needs
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.
Improve cost visibility of Machine Learning workloads on Amazon EKS with AWS Split Cost Allocation Data
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.