Pepperdata Saves Consumer Internet Company 33% for its Data Workloads on Amazon EKS
Pepperdata Saves Consumer Internet Company 33% for its Data Workloads on Amazon EKS
About the Client
A consumer Internet brand in the Fortune 500 that provides information and services related to financial transactions.
Challenge
The company’s executive leadership team and big data platform team embarked upon an optimization initiative to reduce the rising cost of its Apache Spark application workloads in its massively scaled Amazon EKS environment that was also running Karpenter and YuniKorn.
Solution
Pepperdata Capacity Optimizer’s real-time, automated resource optimization immediately reduced workload costs by providing the YuniKorn scheduler with real-time visibility into actual node utilization levels—enabling the scheduler to make more intelligent resource decisions and pack pending pods into nodes with existing capacity.
Pepperdata Capacity Optimizer also enhanced the efficiency of the Karpenter autoscaler by ensuring new nodes were spun up only when existing nodes were fully utilized.
Results
In just days, Capacity Optimizer delivered an initial 33 percent reduction of instance hours (vCPU hours) and then continued to deliver this cost reduction on an ongoing basis, equivalent to approximately $100,000 per month in savings.
Executive Summary
A consumer financial services brand in the Fortune 500 became concerned about ever-increasing costs to run its data workloads as its Amazon EKS environment continued to scale.
The company tapped Pepperdata Capacity Optimizer real-time, automated resource optimization to increase workload utilization levels and reduce costs without requiring any manual tuning or application code changes.
In just days, Pepperdata Capacity Optimizer increased the customer’s resource utilization to help the company run the same workloads with 33 percent less infrastructure—delivering a corresponding decrease in the cost as measured by reduced vCPU hours.
On top of achieving the company executive leadership team’s cost optimization goal during the two-week POV, Pepperdata Capacity Optimizer continues to deliver 33 percent cost savings results on an ongoing basis—translating into approximately $100,000 per month in reduced costs for this company.
By providing the YuniKorn scheduler with real-time visibility into actual node utilization levels, the scheduler could make more intelligent resource allocation decisions and launch more pods on nodes with available capacity.
Download the pdf to learn more or contact sales@pepperdata.com to get started with real-time, automated resource optimization.
