How to schedule and scale GPU-backed LLM inference on Kubernetes today with device plugins, vLLM and sensible autoscaling, and what Dynamic Resource Allocation, now GA, changes for AI workloads across EKS, GKE and AKS.
Scale pods on queue depth with KEDA and scale nodes on pending pods with Karpenter on EKS, plus the GKE equivalents, with the NodePool, ScaledObject and disruption settings that keep it cheap and stable.
A practical migration playbook from Grafana Agent to Grafana Alloy on Kubernetes, with the conversion tool, a DaemonSet plus clustered StatefulSet layout, and the dashboards that tell you the pipeline is healthy.