Case Study
FinTech
Cloud & DevOps
Digital Transformation

Helped a Leading FinTech Company Optimize Cost on Multiple Amazon EKS Clusters

About This Project

The Client was using Amazon EKS clusters to host a variety of microservices and applications. The pairing of Amazon EKS for managing the Kubernetes Control Plane and Amazon EC2 for flexible Kubernetes nodes creates an optimal environment for running containerized workloads. 

With the increasing scale of operations, optimizing costs across multiple EKS clusters has become a critical priority for them. We leveraged various tools and strategies to analyze, optimize, and manage EKS costs effectively while maintaining performance and reliability.

Services

Cloud & DevOps
Digital Transformation

Technologies

About the Client

Client is one of the leading financial technology companies that offers payment process services to businesses in Africa. It is trusted by more than 100,000+ businesses globally.

Understanding the Challenge

The client, a prominent financial technology company serving businesses in Africa, faced the challenge of managing escalating costs associated with their Amazon EKS clusters. As their operations expanded, they encountered complexities in effectively analyzing and optimizing costs across multiple EKS clusters. The lack of visibility into cost drivers and inefficient resource utilization posed significant hurdles in maintaining cost-effectiveness while upholding performance and reliability standards.

Velotio's strategic interventions and tailored solutions delivered tangible outcomes for us. By implementing cost optimization strategies and leveraging cutting-edge tools, we achieved approximately 40% cost savings while maintaining optimal performance and reliability across the EKS clusters. Thanks to Velotio's engineering team, we achieved overall operational excellence.

Product Manager, FinTech Company

How We Made It Happen

To address the client's challenges comprehensively and optimize costs effectively across their Amazon EKS clusters, we implemented a multifaceted approach leveraging a combination of tools, strategies, and best practices in Kubernetes cost optimisation. 

Here’s the approach we took to strategically optimize cost for the client. 

  • Multi-Cluster Cost Analysis with Kubecost and Prometheus:

We conducted a detailed cost analysis to understand the client's cost structure and identify optimisation opportunities. Utilising Kubecost with a remote Prometheus server, we gained granular insights into resource utilisation and cost breakdowns across multiple EKS clusters. Additionally, AWS Cost Explorer provided further insights into usage trends and optimisation potential. By leveraging AWS Managed Prometheus or self-managed Prometheus, we achieved comprehensive cost visibility and analysis across all clusters, facilitating informed decision-making and optimisation strategies.

  • Resource Right-Sizing:

Leveraging tools like Vertical Pod Autoscaler (VPA) and Goldilocks, we optimised resource allocation by dynamically adjusting CPU and memory requests based on actual usage patterns. This proactive approach minimised resource wastage and maximised cost efficiency without compromising performance.

  • Compute Right-Sizing:

To optimize EKS compute resources, we used Mixed Instance Auto Scaling groups, tailored Node Groups, and Graviton Instances to match workload demands. This mix of Spot and On-Demand Instances ensured cost-effectiveness and reliability. Customising Node Groups by application needs enhanced performance, while Graviton Instances offered up to 40% cost savings and improved performance. These strategies maximised cost efficiency and maintained peak performance.

  • Cluster Scaling and Elasticity:

Implementing Kubernetes' native auto-scaling capabilities HPA and Cluster Autoscaler, we ensured optimal resource utilisation across the client's EKS clusters. By dynamically adjusting the cluster size based on workload demand, we minimised unnecessary overhead costs while maintaining performance and reliability.

  • Continuous Optimisation and Monitoring:

We established robust monitoring and alerting mechanisms using Prometheus, Grafana, and custom dashboards to track resource utilisation and cost metrics in real time. By actively monitoring cost and performance metrics, we identified optimisation opportunities and implemented corrective actions to ensure ongoing cost efficiency and operational excellence.

Through these strategic interventions and comprehensive optimisation strategies, Velotio empowered the client to achieve significant cost savings while maintaining optimal performance and reliability across their EKS clusters. Our strategic approach to cost optimisation, coupled with continuous monitoring and fine-tuning, ensured sustainable cost management and operational excellence, enabling the client to focus on driving business innovation and growth effectively.

How Velotio Made a Difference

By implementing cost optimization strategies and leveraging cutting-edge tools, we achieved ~40% cost savings while maintaining optimal performance and reliability across the client's EKS clusters.

By optimizing resource utilization, implementing auto-scaling mechanisms, and leveraging purchasing options such as Spot Instances and Reserved Instances, we maximized cost efficiency without compromising on performance.

By empowering the client with robust cost management capabilities and actionable insights, Velotio facilitated sustainable cost optimization across their EKS clusters, enabling them to focus on driving business innovation and growth in the dynamic financial technology landscape.

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