Marin - CoreWeave GPU Canary Ferry #55
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| name: Marin - CoreWeave GPU Canary Ferry | |
| on: | |
| schedule: | |
| - cron: '0 10 * * *' # Daily at 10 AM UTC | |
| workflow_dispatch: | |
| inputs: | |
| keep_nodepool: | |
| description: 'Keep CW node pool alive after the run (for faster re-runs)' | |
| type: boolean | |
| default: false | |
| permissions: | |
| contents: read # actions/checkout | |
| packages: write # docker login ghcr.io for iris cluster start | |
| jobs: | |
| canary-ferry-cw: | |
| runs-on: ubuntu-latest | |
| timeout-minutes: 180 | |
| concurrency: | |
| group: canary-ferry-cw | |
| cancel-in-progress: true | |
| env: | |
| RUN_ID: canary-gpu-${{ github.run_id }}-${{ github.run_attempt }} | |
| WANDB_ENTITY: marin-community | |
| WANDB_PROJECT: marin | |
| steps: | |
| - name: Checkout code | |
| uses: actions/checkout@v3 | |
| - name: Set up Python 3.12 | |
| uses: actions/setup-python@v4 | |
| with: | |
| python-version: "3.12" | |
| - name: Install uv | |
| uses: astral-sh/setup-uv@v7 | |
| with: | |
| enable-cache: true | |
| - name: Install dependencies | |
| run: uv sync --all-packages --extra=cpu --no-default-groups | |
| - name: Write CoreWeave kubeconfig | |
| run: | | |
| mkdir -p ~/.kube | |
| echo "${{ secrets.CW_KUBECONFIG }}" > ~/.kube/coreweave-iris | |
| chmod 600 ~/.kube/coreweave-iris | |
| - name: Log in to GitHub Container Registry | |
| uses: docker/login-action@v3 | |
| with: | |
| registry: ghcr.io | |
| username: ${{ github.actor }} | |
| password: ${{ secrets.GITHUB_TOKEN }} | |
| - name: Start CoreWeave cluster | |
| run: .venv/bin/iris -v --config=lib/iris/examples/coreweave.yaml cluster start | |
| env: | |
| BUILDKIT_PROGRESS: plain | |
| R2_ACCESS_KEY_ID: ${{ secrets.R2_ACCESS_KEY_ID }} | |
| R2_SECRET_ACCESS_KEY: ${{ secrets.R2_SECRET_ACCESS_KEY }} | |
| - name: Submit canary ferry | |
| shell: bash -l {0} | |
| run: | | |
| .venv/bin/iris --config=lib/iris/examples/coreweave.yaml \ | |
| job run \ | |
| --memory=16G --disk=16G --cpu=1 --extra=cpu \ | |
| -e MARIN_PREFIX s3://marin-us-west-04a/marin/ \ | |
| -e RUN_ID "$RUN_ID" \ | |
| -e WANDB_ENTITY "$WANDB_ENTITY" \ | |
| -e WANDB_PROJECT "$WANDB_PROJECT" \ | |
| -e WANDB_API_KEY "$WANDB_API_KEY" \ | |
| -e HF_TOKEN "$HF_TOKEN" \ | |
| -- python -m experiments.ferries.canary_ferry_cw | |
| env: | |
| WANDB_API_KEY: ${{ secrets.WANDB_API_KEY }} | |
| HF_TOKEN: ${{ secrets.HF_TOKEN }} | |
| R2_ACCESS_KEY_ID: ${{ secrets.R2_ACCESS_KEY_ID }} | |
| R2_SECRET_ACCESS_KEY: ${{ secrets.R2_SECRET_ACCESS_KEY }} | |
| - name: Summarize GPU canary profile | |
| shell: bash -l {0} | |
| run: | | |
| .venv/bin/python -m marin.profiling.cli summarize \ | |
| --run-target "$RUN_ID" \ | |
| --entity "$WANDB_ENTITY" \ | |
| --project "$WANDB_PROJECT" | |
| env: | |
| WANDB_API_KEY: ${{ secrets.WANDB_API_KEY }} | |
| # `cluster stop` only deletes Pods; NodePools survive and rely on the | |
| # CW autoscaler to scale down. Delete them explicitly to avoid lingering | |
| # H100 costs. We attempt both even if one fails — cost protection matters | |
| # more than clean state. | |
| # TODO(#3277): Move NodePool teardown into Iris (e.g. `iris cluster stop | |
| # --delete-nodepools`) so CI doesn't leak the `iris-iris-managed` label. | |
| - name: Tear down CoreWeave cluster | |
| if: always() | |
| run: | | |
| .venv/bin/iris -v --config=lib/iris/examples/coreweave.yaml cluster stop || true | |
| if [ "${{ inputs.keep_nodepool }}" != "true" ]; then | |
| kubectl --kubeconfig ~/.kube/coreweave-iris \ | |
| delete nodepool -l iris-iris-managed=true | |
| else | |
| echo "Keeping node pool alive (keep_nodepool=true)" | |
| fi |