Case Study: a major tech company cuts Kubernetes costs by 25% with Sedai

Major Tech Company Reduces Dev/Test Kubernetes Costs by 25%

Sedai worked with a major tech company that was struggling to manage a large and fast-growing Kubernetes environment across Dev/Test workloads on Google Kubernetes Engine (GKE). With 1,400 services and many small individual cost centers, the engineering team found manual optimization inefficient, costly, and difficult to sustain.

Using Sedai’s autonomous optimization platform, the company rightsized CPU, memory, pod counts, and cluster configurations while maintaining performance. Sedai helped deliver $500,000 in annual run-rate savings and a 25% reduction in cloud costs in less than 60 days, showing measurable impact from AI-driven Kubernetes cost optimization.