deploy-dashboard.yml

name: Deploy Bot Dashboard (Cloud Run)

on:
  push:
    branches: [main]
    paths:
      - 'dashboard/**'
      - 'scripts/agent_tracer.py'
      - '.github/workflows/deploy-dashboard.yml'
  workflow_dispatch:

concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: false

env:
  PROJECT_ID: coderd
  GAR_LOCATION: us-central1
  REPOSITORY: catalog
  SERVICE_NAME: bot-dashboard
  REGION: us-central1

jobs:
  build-and-deploy:
    name: Build and Deploy to Cloud Run
    runs-on: ubuntu-latest
    permissions:
      contents: read
      id-token: write

    steps:
      - name: Checkout code
        uses: actions/checkout@v6

      - name: Free up disk space
        run: |
          sudo rm -rf /usr/share/dotnet /opt/ghc /usr/local/share/boost "$AGENT_TOOLSDIRECTORY"
          docker system prune -af --volumes

      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v3

      - name: Authenticate to Google Cloud
        uses: google-github-actions/auth@v3
        with:
          workload_identity_provider: ${{ secrets.GCP_WORKLOAD_IDENTITY_PROVIDER }}
          service_account: ${{ secrets.GCP_SERVICE_ACCOUNT }}

      - name: Set up Cloud SDK
        uses: google-github-actions/setup-gcloud@v3

      - name: Configure Docker for Artifact Registry
        run: |
          gcloud auth configure-docker ${{ env.GAR_LOCATION }}-docker.pkg.dev --quiet

      - name: Create Artifact Registry repository
        run: |
          if ! gcloud artifacts repositories describe ${{ env.REPOSITORY }} \
            --location=${{ env.GAR_LOCATION }} \
            --format="get(name)" 2>/dev/null; then
            echo "Creating Artifact Registry repository"
            gcloud artifacts repositories create ${{ env.REPOSITORY }} \
              --repository-format=docker \
              --location=${{ env.GAR_LOCATION }} \
              --description="Docker repository for Catalog services"
            echo "✓ Repository created"
          else
            echo "✓ Repository exists"
          fi

      - name: Build and push Docker image
        run: |
          IMAGE_URL="${{ env.GAR_LOCATION }}-docker.pkg.dev/${{ env.PROJECT_ID }}/${{ env.REPOSITORY }}/${{ env.SERVICE_NAME }}:${{ github.sha }}"
          LATEST_URL="${{ env.GAR_LOCATION }}-docker.pkg.dev/${{ env.PROJECT_ID }}/${{ env.REPOSITORY }}/${{ env.SERVICE_NAME }}:latest"

          docker build \
            -t "$IMAGE_URL" \
            -t "$LATEST_URL" \
            --build-arg NEXT_PUBLIC_GOOGLE_CLIENT_ID="${{ secrets.GOOGLE_CLIENT_ID }}" \
            --build-arg NEXT_PUBLIC_APP_URL="https://catalog.vectorinstitute.ai" \
            --cache-from type=gha,scope=bot-dashboard \
            --cache-to type=gha,mode=max,scope=bot-dashboard \
            dashboard/

          docker push "$IMAGE_URL"
          docker push "$LATEST_URL"

          echo "✓ Image pushed: $IMAGE_URL"
          echo "image=$IMAGE_URL" >> $GITHUB_OUTPUT
        id: build

      - name: Deploy to Cloud Run
        id: deploy
        run: |
          gcloud run deploy ${{ env.SERVICE_NAME }} \
            --image ${{ steps.build.outputs.image }} \
            --region ${{ env.REGION }} \
            --platform managed \
            --allow-unauthenticated \
            --memory=1Gi \
            --cpu=1 \
            --timeout=300s \
            --max-instances=10 \
            --min-instances=0 \
            --concurrency=80 \
            --port=8080 \
            --set-env-vars="NODE_ENV=production,NEXT_PUBLIC_GOOGLE_CLIENT_ID=${{ secrets.GOOGLE_CLIENT_ID }},GOOGLE_CLIENT_SECRET=${{ secrets.GOOGLE_CLIENT_SECRET }},SESSION_SECRET=${{ secrets.SESSION_SECRET }},NEXT_PUBLIC_APP_URL=https://catalog.vectorinstitute.ai,REDIRECT_URI=https://catalog.vectorinstitute.ai/aieng-bot-maintain/api/auth/callback,ALLOWED_DOMAINS=vectorinstitute.ai" \
            --update-labels="deployed-by=github-actions,commit=${{ github.sha }},service=bot-dashboard" \
            --quiet

          SERVICE_URL=$(gcloud run services describe ${{ env.SERVICE_NAME }} \
            --region ${{ env.REGION }} \
            --format 'value(status.url)')

          echo "url=$SERVICE_URL" >> $GITHUB_OUTPUT
          echo "✓ Service deployed at $SERVICE_URL"

      - name: Verify deployment
        run: |
          SERVICE_URL="${{ steps.deploy.outputs.url }}"
          echo "Verifying deployment at $SERVICE_URL..."

          MAX_RETRIES=20
          for i in $(seq 1 $MAX_RETRIES); do
            if curl -sf --max-time 10 "${SERVICE_URL}/aieng-bot-maintain/login" > /dev/null 2>&1; then
              echo "✓ Service is responding"
              exit 0
            fi
            echo "Attempt $i/$MAX_RETRIES failed, waiting..."
            sleep 5
          done

          echo "✗ Deployment verification failed"
          exit 1

      - name: Output deployment summary
        run: |
          cat >> $GITHUB_STEP_SUMMARY << EOF
          ## 🚀 Bot Dashboard Deployed

          **Service URL:** ${{ steps.deploy.outputs.url }}
          **Commit:** \`${{ github.sha }}\`
          **Region:** ${{ env.REGION }}

          ### Next Steps
          Configure load balancer to route:
          - \`catalog.vectorinstitute.ai/aieng-bot-maintain/*\` → Cloud Run service

          **Cloud Run Service:** \`${{ env.SERVICE_NAME }}\`

          ### Manual Load Balancer Setup
          If not already configured, run:
          \`\`\`bash
          # Create network endpoint group
          gcloud compute network-endpoint-groups create bot-dashboard-neg \\
            --region=us-central1 \\
            --network-endpoint-type=serverless \\
            --cloud-run-service=bot-dashboard

          # Create backend service
          gcloud compute backend-services create bot-dashboard-backend \\
            --global \\
            --load-balancing-scheme=EXTERNAL_MANAGED

          gcloud compute backend-services add-backend bot-dashboard-backend \\
            --global \\
            --network-endpoint-group=bot-dashboard-neg \\
            --network-endpoint-group-region=us-central1

          # Add path rule to existing URL map (get name first)
          # Update path matcher to route /aieng-bot-maintain/* to bot-dashboard-backend
          \`\`\`
          EOF