Cloud cost optimization
Kubernetes FinOps: Build Cost Ownership Into Engineering
Learn how Kubernetes FinOps helps teams close the gap between infrastructure spend and actual resource…
Fractional GPUs and GPU Rightsizing: Stop Wasting Whole Cards
Learn how to reduce Kubernetes GPU waste when average utilization sits at just 5%. This…
GPU Scheduling and Bin-Packing in Kubernetes: Pack More AI onto Every GPU
Learn how Kubernetes GPU scheduling affects utilization, cost, and AI workload density. This guide covers…
Kubernetes Bin-Packing and Node Consolidation: How to Cut Idle Node Cost
69% of Kubernetes clusters over-provision CPU. The default scheduler is partly to blame. Here is…
Kubernetes GPU Autoscaling: Scale GPU Capacity to Real Demand
GPU autoscaling in Kubernetes matches GPU capacity to real AI workload demand. Learn to configure…
GKE Autopilot: How It Works, the Cost Model, and When It Saves
Learn how GKE Autopilot compares with Standard mode for Kubernetes cost optimization. This guide explains…
KEDA: How Event-Driven Autoscaling Cuts Kubernetes Cost
Learn how KEDA enables event-driven autoscaling in Kubernetes using external metrics such as Kafka, Prometheus,…
Kubernetes Cluster Autoscaler: How It Works and How to Tune Scale-Up and Scale-Down
Learn how the Kubernetes Cluster Autoscaler works, why it struggles with overprovisioned resource requests, and…
HPA vs VPA: When to Use Each, and Can You Use Both?
HPA scales the number of pod replicas; VPA scales the CPU and memory each pod…
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