A developer built a retrieval-augmented generation (RAG) indexing platform on Amazon EKS that combines asynchronous queue-based ingestion, KEDA backlog-driven pod autoscaling, and Karpenter just-in-ti…
Cast AI's Kubernetes automation makes decisions from observed usage signals — including error rate, p99 latency, OOMKill rate and PSI — and logs every action with a timestamp, operation name and initi…
AKS clusters average just 8% CPU utilization, 20% memory utilization, and 2% GPU utilization, the lowest of any major cloud provider, according to Cast AI's 2026 State of Kubernetes Optimization Repor…
Average CPU utilization across Amazon Elastic Kubernetes Service (EKS) clusters has fallen to 8% in 2026 from 10% in 2025, with 69% of provisioned CPU now completely unused, up from 40% year-over-year…
The average production Kubernetes cluster runs at just 8% CPU utilization, according to the Cast AI 2026 State of Kubernetes Optimization Report, even as 88% of organizations report year-over-year inc…
Cast AI creates low technical lock-in but moderate operational lock-in, according to a Cast AI analysis of its own Kubernetes node-provisioning product. The company states that Cast AI provisions stan…
CAST AI's guide to Karpenter best practices for production clusters on Amazon EKS details 10 configuration tips, including running the controller on dedicated nodes, using mutually exclusive NodePools…
AWS launched EKS Auto Mode at re:Invent 2024 (GA: December 1, 2024), a cluster configuration mode that runs Karpenter as a fully managed, off-cluster service, automating node provisioning, AMI patchin…
CAST AI's 2026 Kubernetes Efficiency Report found CPU overprovisioning jumped from 40% to 69% year over year, and Karpenter's disruption system—consolidation, drift, and expiration—can recover that wa…
Karpenter best practices from CAST AI recommend designing multiple focused NodePools with taints for workload isolation, enabling the SQS interruption queue for Spot, and setting CPU and memory limits…
According to the Cast AI 2025 Kubernetes Cost Benchmark, teams using Karpenter with partial spot configurations save an average of 59% on compute costs, while all-spot configurations save up to 77%. C…
According to the Cast AI 2026 State of Kubernetes Optimization report, which analyzed 23,000+ clusters, the median CPU utilization across autoscaled EKS clusters is 8%, with 69% of Kubernetes clusters…
A developer built a production-safe AI remediation firewall for Amazon EKS, demonstrating how to spread a service across simulated availability zones so that losing an entire zone drops zero requests.…
Karpenter v1.14.0 can autoscale GPU inference on Amazon EKS by provisioning spot GPU nodes on demand, bin-packing a vLLM v0.25.1 model server, and deleting nodes when traffic drops, eliminating static…
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…
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…
Red Hat OpenShift 4.22 is now generally available, focusing on cutting cloud infrastructure costs, simplifying operations of virtualized workloads, and securing sensitive data. The release introduces …
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…
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…
By 2026, AI workloads will consume roughly 40% of enterprise Kubernetes clusters, but the default scheduler is ill-suited for GPU-intensive tasks, leading to 30-45% GPU utilization rates and wasted co…