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…
Karpenter, an open-source node provisioner, directly provisions cloud instances without node groups, while Cluster Autoscaler scales pre-defined node groups. Karpenter is faster, cheaper, and more fle…
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…
A 2026 GPU price report reveals that cloud GPU availability and pricing remain chaotic, with H100 and A100 instances often pre-sold via multi-year reserved instances, undermining cloud elasticity. The…
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…
Kubernetes exit codes 137, 139, and 143 indicate container crashes caused by OOM kills, segmentation faults, and SIGTERM signals respectively. The article explains how to diagnose these codes using ku…
Google's TPU v5p and upcoming Ironwood TPU7x offer higher raw matrix throughput and simpler interconnects than NVIDIA H100 GPUs for large-scale AI training, but GPUs remain superior for inference with…