/gke-app-onboarding

name: gke-app-onboarding
description: >-
  Manages GKE application onboarding, covering containerization, deployment
  manifests, and migration. Use when onboarding or deploying an application to
  GKE for the first time, or containerizing an app for GKE. Don't use for
  general GKE cluster administration or upgrades (use gke-basics or
  gke-upgrades instead).
metadata:
  category: Containers

GKE App Onboarding

This reference provides workflows for containerizing and deploying applications to GKE for the first time.

> **MCP Tools:** `apply_k8s_manifest`, `get_k8s_resource`, > `get_k8s_rollout_status`, `get_k8s_logs`, `describe_k8s_resource`

Workflow

1. App Assessment

Before containerizing, assess the application:

• **Language & Framework**: Identify the tech stack
• **Dependencies**: List required libraries and external services
• **Configuration**: How is the app configured? (env vars, config files,

secrets)

• **Statefulness**: Does it need persistent storage? (databases, file storage)
• **Networking**: Port mapping and protocol (HTTP, gRPC, TCP)
• **Health endpoints**: Does the app expose health check endpoints?

2. Containerization

Create a container image:

**Dockerfile (recommended for most apps):**

# Multi-stage build for smaller, more secure images
FROM golang:1.22 AS builder
WORKDIR /app
COPY . .
RUN CGO_ENABLED=0 go build -o server .

FROM gcr.io/distroless/static:nonroot
COPY --from=builder /app/server /server
USER nonroot:nonroot
EXPOSE 8080
ENTRYPOINT ["/server"]

**Best practices:**

• Use multi-stage builds to keep production images small
• Use distroless or minimal base images to reduce attack surface
• Run as non-root user
• Log to `stdout` and `stderr` for Cloud Logging collection

For applications where writing a Dockerfile is not preferred, you can use [**Cloud Native Buildpacks**](https://buildpacks.io/) to automatically detect the language and build a container image:

pack build <image> --builder gcr.io/buildpacks/builder:latest

3. Image Management

Build and store the container image:

# Configure Docker for Artifact Registry
gcloud auth configure-docker <REGION>-docker.pkg.dev --quiet

# Build and push
docker build -t <REGION>-docker.pkg.dev/<PROJECT>/<REPO>/<IMAGE>:<TAG> .
docker push <REGION>-docker.pkg.dev/<PROJECT>/<REPO>/<IMAGE>:<TAG>

**Vulnerability scanning**: Enable automatic scanning in Artifact Registry to detect issues in base images and dependencies.

# Check scan results
gcloud artifacts docker images describe \
  <REGION>-docker.pkg.dev/<PROJECT>/<REPO>/<IMAGE>:<TAG> \
  --show-package-vulnerability \
  --quiet

4. Manifest Generation

Generate Kubernetes manifests for the application:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
  namespace: default
spec:
  replicas: 2
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      containers:
      - name: my-app
        image: <REGION>-docker.pkg.dev/<PROJECT>/<REPO>/<IMAGE>:<TAG>
        ports:
        - containerPort: 8080
        resources:
          requests:
            cpu: "250m"
            memory: "256Mi"
          limits:
            cpu: "500m"
            memory: "512Mi"
        livenessProbe:
          httpGet:
            path: /healthz
            port: 8080
          initialDelaySeconds: 10
        readinessProbe:
          httpGet:
            path: /readyz
            port: 8080
          initialDelaySeconds: 5
---
apiVersion: v1
kind: Service
metadata:
  name: my-app
spec:
  selector:
    app: my-app
  ports:
  - port: 80
    targetPort: 8080
  type: ClusterIP

**Checklist for manifests:**

• Resource requests and limits set
• Liveness and readiness probes configured
• At least 2 replicas for production
• Service type appropriate (ClusterIP for internal, use Gateway API for

external)

5. Deploy

# MCP (preferred)
apply_k8s_manifest(parent="projects/<PROJECT>/locations/<REGION>/clusters/<CLUSTER>", yamlManifest="<manifest>")

# Verify
get_k8s_rollout_status(parent="...", resourceType="deployment", name="my-app")
get_k8s_resource(parent="...", resourceType="pod", labelSelector="app=my-app")

**kubectl fallback:**

kubectl apply -f manifests/
kubectl rollout status deployment/my-app
kubectl get pods -l app=my-app

Next Steps

Once the application is running on GKE:

• Configure autoscaling — see the `gke-workload-scaling` skill
• Set up observability — see the `gke-observability` skill
• Harden security — see the `gke-workload-security` skill
• Configure reliability (PDBs, topology spread) — see the `gke-reliability`

skill