Analyzing AWS Cost and Usage Reports using Athena
Ready for the real environment experience?
AWS Cost and Usage Reports (CUR) can be used to provide you with detailed insights on your AWS cloud costs by the hour, day, or month, by product or product resource, and/or by your custom defined tags. Analyzing the collected CUR data allows you perform cost optimization on your running costs, allowing you to spend less on more.
In this hands-on lab, you'll learn how to turn on and activate CUR. AWS typically takes up to 24 hours before the first CUR reporting data is delivered. This lab will conveniently use a sample set of CUR data, pre-loading the data and config files into an S3 bucket that you will have access to. Once reviewed, you will then launch the provided CUR CloudFormation template. The CUR CloudFormation template provisions a Glue Crawler, which itself is configured to scan the current S3 bucket for newly published CUR parquet data files on scheduled basis. These data files are picked up and automatically populated into an Athena database. With the Athena CUR database now established, you'll finally be shown how to run various SQL queries using the Athena Query Editor to analyze the CUR data for areas where cost optimization can be applied.
Upon completion of this intermediate level lab, you will be able to:
- Setup and establish AWS Cost and Usage Reports (CUR)
- Create an Athena database containing CUR data
- Analyze the CUR dataset using the Athena Query Editor
- Write various SQL reporting queries
- Cloud Architects
- Software Engineers
- FinOps Practitioners
Familiarity with the following will be beneficial but is not required:
- AWS CloudFormation
- Amazon S3
The following content can be used to fulfill the prerequisite:
Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).