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Kubernetes Event-Driven Autoscaling; scales workloads on external triggers such as Kafka consumer-group lag and can scale to zero by managing an HPA around the workload. Used here via a ScaledObject with a kafka trigger.
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The bank pooled nearly 10,000 heterogeneous accelerator cards under Kubernetes and reports average utilization rising from 35% to more than 60%. That density supplies 1.71 of the 2.5x drop in cost per million tokens.
Reality
Replica count, pod size and node count each have one tool that can move them. A dev.to guide to HPA, VPA, KEDA and Karpenter puts the usual production autoscaling failures at the boundaries between those three levels.
Reality
The 40x is arithmetic on an upstream default of five goroutines. It only transfers if every HPA evaluation really costs about 100ms. The reasoning that holds regardless is why a shared API server could not be handed the same setting.
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Azure starts new subscriptions at zero GPU vCPUs and raises them by hand, which puts the one step you cannot rerun at the front of a walkthrough where everything after it is just a command you can repeat.
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A lab writeup on dev.to turns always-on Kafka sinks into on-demand workers. The interesting part is not the zero, it is the ceiling that the partition count puts on your spike response.
Reality