The average Kubernetes cluster uses just 8% of the CPU it pays for, according to the Cast AI 2026 State of Kubernetes Optimization Report, highlighting the need for Kubernetes FinOps to close the gap …
Average GPU utilization in production Kubernetes clusters is just 5%, according to the Cast AI 2026 State of Kubernetes Optimization Report, meaning 95 cents of every GPU dollar goes to idle silicon. …
Average GPU utilization across tens of thousands of production Kubernetes clusters is just 5%, according to the Cast AI 2026 State of Kubernetes Optimization Report. Default Kubernetes scheduling uses…
GPU utilization averages just 5% across production Kubernetes clusters, according to the Cast AI 2026 State of Kubernetes Optimization Report, meaning 95% of provisioned GPU capacity is idle at any mo…
KEDA, a CNCF Graduated open-source project created by Microsoft and Red Hat, cuts Kubernetes costs by scaling workloads to zero replicas when no events are pending, a capability standard Horizontal Po…
The Kubernetes Cluster Autoscaler adds nodes reactively when pods are pending and removes them after a sustained underutilization window, with a default scale-down delay of 10 minutes and provisioning…
Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) solve different autoscaling problems in Kubernetes: HPA adds or removes pod replicas based on load, best for stateless workloads like …
A new Kubernetes cost optimization checklist reveals that average CPU utilization across production clusters is only 8% in 2026, down from 10% the prior year, with 69% of clusters over-provisioning CP…
A new guide compares four leading pod rightsizing tools for Kubernetes, revealing that average CPU utilization across production clusters is only 8% in 2026, with 79% of clusters overprovisioning memo…
A Kubernetes cost dashboard provides per-namespace and per-workload cost visibility that cloud billing lacks, enabling platform teams to identify waste and reduce spending. Key metrics include cost pe…
Cast AI and Kubecost serve different Kubernetes cost management needs: Kubecost provides cost visibility and allocation, while Cast AI automates optimization actions like rightsizing and bin-packing. …
Kubecost, a Kubernetes cost monitoring platform built on OpenCost, tracks costs by namespace, pod, deployment, and label, including compute, network, storage, idle capacity, and GPU costs. It surfaces…
Cast AI's 2026 analysis of tens of thousands of production clusters on AWS, GCP, and Azure found average CPU utilization at 8% fleet-wide, down from 10% the prior year. The company identified seven ke…
Kubernetes cost optimization removes waste through technical actions like rightsizing pods and adopting Spot instances, while cost management provides ongoing visibility, allocation, and governance. A…
Kubernetes Horizontal Pod Autoscaler (HPA) automatically adjusts pod replica counts based on real-time demand, addressing the industry-wide issue of average CPU utilization of just 8% across productio…
Kubernetes rightsizing matches pod resource requests to actual usage, closing an overprovisioning gap where 69% of requested CPU goes unused, according to the 2026 Cast AI report. A five-step workflow…
GPU utilization in production Kubernetes clusters averages just 5%, according to Cast AI's 2026 State of Kubernetes Optimization Report, while hardware costs continue to rise. The GPU Cost Optimizatio…
Kubernetes cost optimization tools are divided between visibility platforms that report spending and autonomous platforms that automatically reduce waste, with average CPU utilization at 8% and GPU ut…
CrashLoopBackOff in Kubernetes is a pod status indicating a container repeatedly crashes and restarts with exponential backoff, caused by application errors, OOM kills, failing probes, bad images, mis…
PEAK:AIO and Los Alamos National Laboratory have released PNFS-Lattice, an open-source metadata server for parallel NFS that scales to 1,000 servers and accelerates AI data feeds. The software separat…