Optimizing Cloud Compute Spend with Dynamic Kubernetes Scaling

Over-provisioning is the easiest way to ensure uptime, but it burns runway. We deeply audited our containerized environments to ensure our pods scale exactly parallel to traffic graphs.

Predictive Scaling

Rather than waiting for CPU thresholds to hit 80%, we implemented predictive ML models that scale our Kubernetes clusters ahead of anticipated traffic spikes based on historical weekly patterns, saving thousands in idle compute costs.