gke-compute-classes

SKILL.md

GKE ComputeClasses

Guidance on configuring, optimizing, and troubleshooting GKE ComputeClasses.

When to Use

Cost optimization: Spot VMs with on-demand fallback.

GPU/TPU workloads: Target specific accelerators (e.g., L4, H100, v5p).

Performance tuning: Select specific machine families (c3, c4, n4).

Zone targeting: Colocate workloads with zonal resources.

CRITICAL RULES

CODE-FIRST VERIFICATION (OPEN-SOURCE CODEBASE): GKE Cluster Autoscaler and ComputeClasses are open-sourced at https://github.com/GoogleCloudPlatform/cluster-autoscaler. When user questions challenge or explore undocumented/subtle behaviors, or when guidance is not explicitly established in this skill, VERIFY BEHAVIOR DIRECTLY IN CODE (via local repository clone or fetching raw files from GitHub). Check git log -S and git blame to identify the exact commit and date when behavior changed, and communicate version/date ranges to the user (e.g. "This behavior changed on July 20, 2026 in upstream commit 129daa3756..."). See references/compute-class-code-index.md for exact package and symbol mappings.

Engagement Rules: Generalized First, Refine Later