I'm trying to right-size resource settings for several Kubernetes services and keep them accurate over time. My current CPU requests are around 200–500m, but steady-state usage is closer…
For months, I assumed our Kubernetes cost problem required better tooling. Then we discovered that cluster CPU utilization was only around 25% because teams had heavily padded their…
The common advice is to avoid CPU limits, set requests, and let workloads burst when spare capacity is available. I understand the concern that CFS throttling can create…
I'm currently managing a cluster that primarily runs stateless, HPA-driven workloads. Recently, we significantly lowered our CPU requests, which improved our utilization rates—some pods even dropped below 10%…
I've been working with workloads in Google Kubernetes Engine (GKE) where the resource utilization is somewhat optimized, particularly using the Vertical Pod Autoscaler (VPA) and Pod Disruption Budgets…