skills/gke-app-onboarding/SKILL.md
Workflows for containerizing and deploying applications to GKE for the first time.
npx skillsauth add googlecloudplatform/gke-mcp gke-app-onboardingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill provides workflows for preparing applications that are not yet running on Kubernetes and deploying them to GKE for the first time.
Before containerizing, assess the application's requirements:
Create a container image suitable for the application:
Dockerfile in the project root.stdout and stderr for proper log collection.Build and store the container image:
Generate Kubernetes manifests for the application:
Namespace for the application to isolate resources.
pod-security.kubernetes.io/enforce: restricted and pod-security.kubernetes.io/enforce-version: latest).ServiceAccount for the application. Avoid using the default ServiceAccount to follow the principle of least privilege.Deployment manifest.
ServiceAccount using the serviceAccountName field.Apply the manifests and verify the deployment:
kubectl apply -f <manifest-file>.kubectl get pods and ensure the service is accessible.Once the application is running, use the gke-productionize skill to assess its readiness for production.
data-ai
Systematically diagnose GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads. Identifies preemption events, maintenance interruptions, bad host VMs, unhealthy pods, and coordinator worker failures.
development
Diagnose and prevent `vbar_control_agent` segfaults and OOMs caused by race conditions during TPU device resets and frequent metrics collection (e.g. every 3s). Use when TPU slice initialization fails or `vbar_control_agent` crashes on TPU v6e nodes.
development
Expert instructions for building high-quality GKE troubleshooting skills. Codifies Step 0 context rules, zero-hallucination signatures, and explicit LQL/PromQL query requirements.
tools
Assists in preparing applications and clusters on GKE for production.