Every resilience pattern you know assumes the machine shows up. Accelerator scarcity breaks that assumption, and the pattern catalogs have not caught up. Here is the Compute Fallback Ladder—an ordered set of rungs your workload can run on, a selector that picks the highest obtainable one, and a promotion path back up when capacity returns.
Agent density is a lifecycle problem, not an isolation problem. Google's own GKE Agent Sandbox benchmark puts the sandbox at 44% and suspend and resume at up to 3.5x—the sandbox is the smaller half. And upstream Kubernetes 1.37 is quietly turning checkpoint and restore into a kubelet primitive. Here's why the economics live in the lifecycle, not the box.
I'm hiring a Senior Developer Relations Engineer for GKE and AI Infrastructure. Instead of describing the work, I built it: a small, playable cluster scheduler that teaches the real problem behind running AI at scale—gang scheduling, memory ceilings, spot preemption, and a TPU slice with actual topology.
