Migrate AI Workloads to GKE Inference

This skill guides agents through the end-to-end process of migrating existing AI inference workloads (e.g., from Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted inference on Google Kubernetes Engine (GKE). The agent will act as an interactive architect, using a structured 4-phase workflow to discover requirements, design a Google Cloud-native solution, execute the implementation using gcloud and kubectl, and validate the deployment.

Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read and follow the instructions in Usage Attribution.

Gemini Cloud Assist MCP off-ramp

This skill covers manual, architect-guided migration only. Automated migration is the job of the Gemini Cloud Assist MCP server. Route between them as follows:

• The user asks to USE Gemini Cloud Assist or MCP automation for this migration (e.g., "use the Cloud Assist MCP server to do this"): stop the manual workflow and respond with the 4 required points below.
• The user mentions MCP only in passing, or explicitly declines it (e.g., "no MCP, let's do this manually"): proceed with the manual workflow. Do not stop and do not ask about MCP.
• The user does not mention MCP at all: proceed directly to the active phase. In your first discovery response only, add one sentence noting that an automated alternative exists via the Gemini Cloud Assist MCP server and the user can switch to it at any time. Do not wait for an answer before beginning discovery.

When stopping for an MCP request, your response MUST include these 4 points: