gke-app-onboarding
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).
pinned to #092e210updated 2 days ago
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- #googlecloud
- #skills
About this skill
Pulled from SKILL.md at publish time.
This reference provides workflows for containerizing and deploying applications to GKE for the first time.
Evaluation report
WarningsAutomated checks the publisher passed at publish time — structure, docs, safety, and whether the artifact behaves as claimed.092e210· 2 days ago
Documentation
8 passed1 warningHomepage or repository declaredwarn
No homepage or repository declared.
Add a "homepage" or "repository" field to SKILL.md.
Description quality
43 words · 311 chars — "Manages GKE application onboarding, covering containerization, deployment manife…"
README is present and substantial
11,950 chars · 7 sections · 1 code block
Tags / topics declared
3 total — google, googlecloud, skills
README has usage / example sections
found: Installation
Homepage / docs URL declared
no homepage declared (registry will use the repo URL) — info-only, not blocking
Description is substantive
Description is 43 words.
Documentation present and substantive
Documentation present (SKILL.md, 541 words).
Documentation shows usage
Documentation includes 7 code examples.
Release history
1- releasecurrent092e210warn2 days ago
Contents
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
stdoutandstderrfor Cloud Logging collection
For applications where writing a Dockerfile is not preferred, you can use Cloud Native Buildpacks 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-scalingskill - Set up observability — see the
gke-observabilityskill - Harden security — see the
gke-workload-securityskill - Configure reliability (PDBs, topology spread) — see the
gke-reliabilityskill
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Verification Before Completion
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Writing Plans
Turn specs into phased implementation plans
Test-Driven Development
Red → green → refactor discipline for any feature or bugfix
mh install skills/gke-app-onboarding