Category: AWS Cloud Financial Management

Cost transparencies and insights will help drive data-driven and informed decisions. This blog describes a flywheel approach that an enterprise can utilize to optimize their AWS spend and leverage those saving towards driving continuous innovation.

In this blog, we’ll walk you through an example of setting up a multilevel hierarchy in Cost Categories. We’ll use Amazon Athena to consolidate cost and usage data across all AWS services, accounts, tags, cost categories, and other fields from the AWS Cost and Usage Reports (CUR). 

In case you missed the launch announcement from AWS Cloud Financial Management solution category in Q2, this blog presents you a quick summary.

When it comes to cost optimization, you often focus on the top spenders, but the cost of the services that typically fall under the “Others” category can be just as high as the top cost drivers. It’s worth looking into the sources of these costs and identifying opportunities for cost and performance optimization. In this blog, I’ll use a few examples to demonstrate how you can dive deeper and understand the cost elements of these “other” services and what you can do to optimize the spend.

By using CUDOS and the CID Framework, Cvent provides its centralized governance teams with greater visibility across all organizational spend in a simple, cost-effective manner. More importantly, that same visibility is available to budget managers and engineers, which decentralizes the ownership of the budget details. Cvent’s mindset and processes are shifting from reactive spend investigation to proactive cost optimization during planning and deployment, which fosters a high degree of financial predictability expected from investors and shareholders.

This post will show how you can optimize your x86 Amazon Elastic Cloud Compute workloads with no architectural changes. We will focus on improving price-to-performance without introducing engineering overhead, large planning cycles and significant time investment. The optimizations mentioned today require no application engineering and can be done quickly. The focal point of this post is showing the benefits of running your x86 EC2 workloads on AMD based EC2 instances to achieve at least 10% cost savings.

The Customer Carbon Footprint Tool now supports the CSV download option, giving you the ability to review carbon footprint data in detail and ingest the data into other reporting systems for further analysis and information sharing. It has also lowered the carbon reporting threshold from one decimal place to three decimal places, which means the carbon emission data is now available at 0.00X metric tons of CO2e, from the previous 0.X metric tons of CO2e.

Effective cost tracking and allocation is crucial to operating in the cloud. With the right strategies and AWS tools, you can access and provide cost and usage data that aligns with your business objectives, helping you manage and optimize your cloud spend with increased understanding and accountability across your AWS bill. Learn about and see cost allocation strategies in action to help you understand your AWS bill.

Life sciences organizations are grappling with increased competition and the need to maintain profitability, while navigating a complex regulatory environment. To tackle these challenges, many are migrating to the cloud to accelerate innovation and enhance productivity. The Hackett Group evaluated the business benefits and trends of cloud adoption for life sciences organizations. 

We’re excited to announce that the cost data for Amazon Elastic Container Service (Amazon ECS) tasks and AWS Batch jobs is now available in the AWS Cost and Usage Reports (CUR). With AWS Split Cost Allocation Data, you can easily understand and optimize cost and usage of your containerized applications, and allocate application costs back to individual business entities based on how shared compute and memory resources are consumed by your containerized applications. Learn how to opt into and view your Split Cost Allocation Data.