Case Study: Flowcore achieves 50% AKS cost savings with CAST AI

Flowcore saved 50% on AKS costs with full visibility and control

Flowcore, a developer-first real-time data platform startup, needed better visibility and control as its platform scaled and data volumes rose. To keep Kubernetes costs from spiraling in a dynamic, high-traffic Azure AKS environment, the team evaluated tools like OpenCost and Kubecost before choosing CAST AI for cost visibility and automated optimization.

With CAST AI’s workload optimization, node autoscaling, node rebalancing, and database optimizer, Flowcore automated cluster rightsizing and reduced waste across both infrastructure and workloads. The results were significant: cloud costs were cut by about 50%, resource allocation became more efficient, and the team gained clear visibility into every cluster while also improving stability and performance.

Flowcore

Julius á Rógvi Biskopstø

Chief Technology Officer and Co-founder