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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).
npx skills add google/skills --skill gke-app-onboardingInstalls from the source repository, including any supporting files.
Downloads contain the instructions shown here. Use the install command for the complete skill.
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
MUST READ: Before executing any gcloud, REST API, or MCP command, you
MUST read Usage Attribution. For commands executed
directly in the terminal (never in generated scripts, Terraform, or user code),
prefix gcloud with
CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:gke-app-onboarding)"
and append agent-skills/1.0 (skill:gke-app-onboarding) to User-Agent headers.
Before containerizing, assess the application:
Create a container image. A Dockerfile with a multi-stage build is recommended
for most apps — see the Go Dockerfile in
references/go-example.md for a worked example.
Best practices:
stdout and stderr for Cloud Logging collectionA complete worked Node.js example is provided in assets/:
(non-root user),
(implements distinct and
endpoints), , and
(hardened Deployment plus
ClusterIP Service, probes wired to and ).
Dockerfilenode/healthz/readyz/healthz/readyzFor 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
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
Generate Kubernetes manifests for the application. A baseline Deployment +
ClusterIP Service manifest (probes, resource requests/limits, 2 replicas) is in
references/go-example.md.
Checklist for manifests:
See assets/deployment.yaml for a hardened worked
example. A production-hardened pod spec must include ALL of: runAsNonRoot: true, readOnlyRootFilesystem: true, allowPrivilegeEscalation: false,
capabilities.drop: ["ALL"], seccompProfile: {type: RuntimeDefault},
automountServiceAccountToken: false (unless the pod needs the token — then say
why), resource requests, digest-pinned image, and a ClusterIP Service.
That checklist is the baseline for any pod spec produced here. For manifest work
beyond it — Gateway API routes, GCS FUSE and secret volume mounting, subPath
overlays, Spot VM targeting, or AI/inference serving specs — see
gke-manifest-generation.
# 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
For every production application onboarding to GKE:
runAsNonRoot: true), lockfile
install, minimal/distroless base image.livenessProbe) and readiness
(readinessProbe) probes configured.PodDisruptionBudget (minAvailable: 1 or 2).iam.gke.io/gcp-service-account) instead of static service account keys.Once the application is running on GKE:
gke-workload-scaling skillgke-observability skillgke-workload-security skillgke-reliability
skill---
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:
version: "1.0.1"
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`
## Attribution
**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you
MUST read [Usage Attribution](references/attribution.md). For commands executed
directly in the terminal (never in generated scripts, Terraform, or user code),
prefix `gcloud` with
`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:gke-app-onboarding)"`
and append `agent-skills/1.0 (skill:gke-app-onboarding)` to `User-Agent` headers.
## 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. A Dockerfile with a multi-stage build is recommended
for most apps — see the Go Dockerfile in
[`references/go-example.md`](./references/go-example.md) for a worked example.
**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
A complete worked Node.js example is provided in [`assets/`](./assets/):
[`Dockerfile`](./assets/Dockerfile) (non-root `node` user),
[`index.js`](./assets/index.js) (implements distinct `/healthz` and `/readyz`
endpoints), [`package.json`](./assets/package.json), and
[`deployment.yaml`](./assets/deployment.yaml) (hardened Deployment plus
ClusterIP Service, probes wired to `/healthz` and `/readyz`).
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:
```bash
pack build <image> --builder gcr.io/buildpacks/builder:latest
```
### 3. Image Management
Build and store the container image:
```bash
# 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.
```bash
# 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. A baseline Deployment +
ClusterIP Service manifest (probes, resource requests/limits, 2 replicas) is in
[`references/go-example.md`](./references/go-example.md).
**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)
See [`assets/deployment.yaml`](./assets/deployment.yaml) for a hardened worked
example. A production-hardened pod spec must include ALL of: `runAsNonRoot:
true`, `readOnlyRootFilesystem: true`, `allowPrivilegeEscalation: false`,
`capabilities.drop: ["ALL"]`, `seccompProfile: {type: RuntimeDefault}`,
`automountServiceAccountToken: false` (unless the pod needs the token — then say
why), resource requests, digest-pinned image, and a ClusterIP Service.
That checklist is the baseline for any pod spec produced here. For manifest work
beyond it — Gateway API routes, GCS FUSE and secret volume mounting, `subPath`
overlays, Spot VM targeting, or AI/inference serving specs — see
`gke-manifest-generation`.
### 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:**
```bash
kubectl apply -f manifests/
kubectl rollout status deployment/my-app
kubectl get pods -l app=my-app
```
## Golden Path Onboarding Checklist
For every production application onboarding to GKE:
1. **Container Security**: Non-root user (`runAsNonRoot: true`), lockfile
install, minimal/distroless base image.
2. **Resource Requests**: Explicit CPU and memory requests (mandatory for GKE
Autopilot).
3. **Health Probes**: Both liveness (`livenessProbe`) and readiness
(`readinessProbe`) probes configured.
4. **Reliability & Availability**: At least 2 replicas and a
`PodDisruptionBudget` (`minAvailable: 1` or `2`).
5. **IAM & Workload Identity**: Workload Identity
(`iam.gke.io/gcp-service-account`) instead of static service account keys.
## 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