gke-app-onboarding

GKE App Onboarding

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

MCP Tools: get_k8s_resource, get_k8s_rollout_status, get_k8s_logs, describe_k8s_resource

A change goes out as a pull request to the GitOps repository, never as a write from here: Kubernetes objects as YAML through gke-manifest-generation, cluster settings and other Google Cloud resources as Config Connector YAML through gcp-config-connector, opened with submit-suggestion. Each profile's config offers only the gke MCP server's read tools, and the broker refuses kubectl and gcloud writes.

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 to automatically detect the language and build a container image:

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