| name | gke-compute-class-creator |
| description | Guide for creating GKE ComputeClass resources. Use this skill when users want to define custom node configurations, autoscaling priorities, or hardware requirements (e.g., Spot VMs, GPUs, specific machine families) for their GKE workloads. |
Creating GKE ComputeClasses
This skill helps you construct ComputeClass resources for Google Kubernetes Engine (GKE). ComputeClasses allow for declarative node configuration and sophisticated autoscaling behaviors like fallback priorities and active migration.
Workflow
- Analyze Requirements: Determine the user's goals (Cost optimization? Specific hardware? High availability?).
- Select Strategy:
- Cost Optimization: Use
spot: true as a high priority, with spot: false as a fallback.
- Performance: Select specific
machineFamily (e.g., c3, c4) or machineType.
- AI/ML: Configure
gpu or tpu fields.
- Construct YAML: Use the references below to build the
ComputeClass manifest.
- Validate: Ensure all fields comply with the specification.
- Apply: Provide the user with the
kubectl apply -f <filename>.yaml command.
References
- Specification: Detailed breakdown of the
ComputeClass CRD fields (priorities, machineFamily, gpu, etc.).
- Examples: Copy-pasteable YAML patterns for common scenarios (Spot fallback, GPU, Zonal).
Usage Tips