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Add ai-ml/gke-ray/tpu/get-started: Ray on TPU end-to-end example (#2122) #2

Add ai-ml/gke-ray/tpu/get-started: Ray on TPU end-to-end example (#2122)

Add ai-ml/gke-ray/tpu/get-started: Ray on TPU end-to-end example (#2122) #2

# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
name: ai-ml-gke-ray-tpu-get-started-ci
on:
push:
branches:
- main
paths:
- '.github/workflows/ai-ml-gke-ray-tpu-get-started-ci.yml'
- 'ai-ml/gke-ray/tpu/get-started/**'
pull_request:
paths:
- '.github/workflows/ai-ml-gke-ray-tpu-get-started-ci.yml'
- 'ai-ml/gke-ray/tpu/get-started/**'
jobs:
job:
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- name: Validate cluster Terraform
run: |
cd ai-ml/gke-ray/tpu/get-started/cluster
terraform init -backend=false
terraform validate
# The serve and train images build on the large vllm-tpu nightly base, so
# free the runner disk before building to avoid running out of space.
- name: Free up disk space
run: |
sudo rm -rf /usr/share/dotnet /opt/ghc /usr/local/lib/android /usr/local/.ghcup
df -h /
- name: Build serve container image
run: |
cd ai-ml/gke-ray/tpu/get-started/serve
docker build --tag qwen3-serve-tpu .
- name: Build train container image
run: |
cd ai-ml/gke-ray/tpu/get-started/train
docker build --tag qwen3-train-tpu .