What about clusters that are used for lumpy work loads? Like data science pipelines? For example, our org has a few dozen clusters being used like that.
Each pipeline gets its own cluster instance as a way to enforce rough and ready isolation. Most of the times the clusters sit unused. To keep them alive we keep a small, cheap, preemptive node alive on the idle cluster. When a new batch of data comes in, we fire up kube jobs which then triggers GKE autoscaling that processes the workload.
This pricing change means we're looking at thousands of dollar more in billing per month. Without any tangible improvement in service. (The keepalive node hack only costs $5 a month per cluster.) We could consolidate the segmented cluster instances into a single cluster with separate namespaces, but that would also cost thousands in valuable developer time.
I don't know how common our use pattern is, but I think we would be a lot better served by a discounted management fee when the cluster is just being kept alive and not actually using any resources. At $0.01, maybe even $0.02, per hour we could justify it. But paying $0.10 to keep empty clusters alive is just egregious.