Implementing FinOps: reducing infrastructure costs with AWS Well-Architected reviews

A fitness chain with over 130 locations on the United States East Coast and more than 300,000 active users on its platform each month relies on a 100% digital solution with the primary goal of creating a unique experience for its customers. Through a seamless experience, the chain’s clients can hire personal trainers as well as switch monthly subscriptions. As part of its digital evolution, the chain has been investing continuously in technology, mainly in the area of Data Analytics and Machine Learning. 

The challenge 

In a data-driven environment, flexible data collection, as well as efficient processing and storage, are fundamental for business areas to understand client behavior. In this context, AWS is a strategic partner, providing on-demand computing to create hundreds of pipelines for data extraction and processing, as well as a solid infrastructure for storage and visualization. 

The organic growth of this data platform has led to a disproportionate increase in cloud costs compared to its growth. In this context, the client needs to optimize their infrastructure costs while maintaining the operation of their data processing pipelines.  

Solution 

The company, in partnership with AWS specialists, adopted a strategic cost optimization approach, taking advantage of the AWS native tools. 

• Granular analysis with AWS Cost Explorer: AWS Cost Explorer provided a comprehensive view of costs, allowing for the identification of services that contribute most to total expenditure. This detailed analysis enabled the prioritization of optimization actions.
• Smart Optimization with AWS Compute Optimizer: AWS Compute Optimizer, with its data-driven intelligence, recommended precise adjustments in resource scaling such as EC2 instances, EBS volumes, ECS services on Fargate, and Lambda functions. The tool not only suggested reductions but also recommended upgrades to newer instance generations, providing both cost savings and improved performance.
• Strategic Cleanup: a thorough analysis identified outdated or inactive workloads, resulting in the removal of resources like Lambda functions, CloudWatch Log Groups, EC2 instances, EBS volumes, and Redshift clusters. This strategic “cleanup” eliminated unnecessary expenses.
• Instance Generation Updates: in addition to resizing, the company implemented the Compute Optimizer’s recommendations to upgrade EC2 instance generations, taking advantage of the efficiency and performance benefits of AWS’s latest technologies.

Results  

The combination of these strategies resulted approximately 27% monthly savings, a remarkable achievement with no negative effect on platform stability or performance. The company realized the following benefits: 

• Significant Cost Reduction: approximately 27% savings on AWS monthly costs.
• Enhanced Performance: Upgrading instance generations not only reduced costs but also boosted platform performance.
• Maintained stability: the optimizations were implemented without compromising platform stability, ensuring a seamless user experience.
• Clear view and strategic action: AWS Cost Explorer provided a clear view of costs, allowing the company to make strategic decisions and to guide optimization efforts effectively. 

Conclusion 

By adopting a proactive and strategic approach with AWS native tools, the company achieved impressive cost optimization, consolidating its position in the fitness industry, and demonstrating the power of the cloud to promote efficiency and innovation.