coreweave-ci-integration

# CoreWeave CI Integration ## Overview Set up CI/CD for CoreWeave GPU cloud workloads: run unit tests with mocked Kubernetes clients on every PR, deploy inference containers to CoreWeave namespaces on merge to main, and validate GPU resource requests against quota. CoreWeave uses standard Kubernetes APIs with GPU-specific scheduling, so CI pipelines authenticate via kubeconfig and manage deployments through `kubectl`. ## GitHub Actions Workflow ```yaml # .github/workflows/coreweave-ci.yml name: CoreWeave CI on: pull_request: paths: ['src/**', 'k8s/**', 'Dockerfile'] push: branches: [main] jobs: unit-tests: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-node@v4 with: { node-version: '20' } - run: npm ci - run: npm test -- --reporter=verbose deploy: if: github.ref == 'refs/heads/main' needs: unit-tests runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Build and push container run: | echo "${{ secrets.GHCR_TOKEN }}" | docker login ghcr.io -u ${{ github.actor }} --password-stdin docker build -t ghcr.io/${{ github.repository }}/inference:${{ github.sha }} . docker push ghcr.io/${{ github.repository }}/inference:${{ github.sha }} - name: Deploy to CoreWeave env: KUBECONFIG_DATA: ${{ secrets.COREWEAVE_KUBECONFIG }} run: | echo "$KUBECONFIG_DATA" | base64 -d > /tmp/kub...