e2e-controller.yml

name: E2E Controller Tests

on:
  push:
    branches: [main]
  pull_request:
    branches: [main]
  workflow_dispatch:

permissions:
  contents: read

jobs:
  e2e-controller:
    runs-on: ubuntu-latest-16-cores
    timeout-minutes: 30

    steps:
      - name: Checkout repository
        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0 # v7.0.0

      - name: Setup Go
        uses: actions/setup-go@4a3601121dd01d1626a1e23e37211e3254c1c06c # v6.4.0
        with:
          go-version: "1.25"
          cache-dependency-path: controller/go.sum

      - name: Setup Bun
        uses: oven-sh/setup-bun@0c5077e51419868618aeaa5fe8019c62421857d6 # v2.2.0
        with:
          bun-version: latest

      - name: Setup Kind
        run: |
          go install sigs.k8s.io/kind@latest
          kind create cluster --name airunway-e2e --wait 120s

      - name: Install KAITO operator
        run: |
          helm repo add kaito https://kaito-project.github.io/kaito/charts/kaito
          # If Gateway API Inference Extension CRDs are pre-installed (e.g. via kubectl apply),
          # add --skip-crds to avoid a field-manager conflict on InferencePool.
          helm install kaito-workspace kaito/workspace \
            --namespace kaito-workspace \
            --create-namespace \
            --set featureGates.disableNodeAutoProvisioning=true
          kubectl wait --for=condition=Available deployment -n kaito-workspace -l app.kubernetes.io/name=workspace --timeout=120s

      - name: Build and deploy controller
        run: |
          make controller-docker-build CONTROLLER_IMG=airunway-controller:e2e
          kind load docker-image airunway-controller:e2e --name airunway-e2e
          make controller-deploy CONTROLLER_IMG=airunway-controller:e2e
          kubectl wait --for=condition=Available deployment -n airunway-system -l control-plane=controller-manager --timeout=120s

      - name: Build and deploy KAITO provider
        run: |
          make -C providers/kaito docker-build IMG=kaito-provider:e2e
          kind load docker-image kaito-provider:e2e --name airunway-e2e
          make -C providers/kaito deploy IMG=kaito-provider:e2e
          kubectl wait --for=condition=Available deployment -n airunway-system -l control-plane=kaito-provider --timeout=120s

      - name: Wait for provider registration
        run: |
          kubectl wait --for=jsonpath='{.status.ready}'=true inferenceproviderconfig/kaito --timeout=120s

      - name: Create CPU-only ModelDeployment
        run: |
          kubectl apply -f controller/test/e2e/testdata/cpu-modeldeployment.yaml

      - name: Wait for ModelDeployment to reach Running phase
        run: |
          kubectl wait --for=condition=WorkspaceSucceeded workspace/llama-cpu-e2e -n default --timeout=600s 2>/dev/null || true

          echo "Waiting for ModelDeployment to reach Running phase..."
          for i in $(seq 1 60); do
            PHASE=$(kubectl get modeldeployment llama-cpu-e2e -o jsonpath='{.status.phase}' 2>/dev/null || echo "")
            echo "Attempt $i/60: phase=$PHASE"
            if [ "$PHASE" = "Running" ]; then
              echo "✅ ModelDeployment is Running"
              exit 0
            fi
            sleep 10
          done
          echo "❌ Timed out waiting for ModelDeployment to reach Running phase"
          exit 1

      - name: Test inference endpoint
        run: |
          # Get the actual service port
          SVC_PORT=$(kubectl get svc llama-cpu-e2e -n default -o jsonpath='{.spec.ports[0].port}')
          echo "Service port: $SVC_PORT"

          kubectl port-forward svc/llama-cpu-e2e 8080:${SVC_PORT} -n default &
          sleep 5

          RESPONSE=$(curl -sf http://localhost:8080/v1/chat/completions \
            -H "Content-Type: application/json" \
            -d '{
              "model": "llama-3.2-1b-instruct",
              "messages": [{"role": "user", "content": "Say hello in one word."}],
              "max_tokens": 10
            }')

          echo "Response: $RESPONSE"

          echo "$RESPONSE" | jq -e '.choices' > /dev/null
          echo "$RESPONSE" | jq -e '.choices[0].message.content' > /dev/null

          echo "✅ Inference endpoint responded with valid chat completion"

      - name: Collect debug info
        if: failure()
        run: |
          echo "=== ModelDeployments ==="
          kubectl get modeldeployments -A -o yaml
          echo "=== InferenceProviderConfigs ==="
          kubectl get inferenceproviderconfigs -o yaml
          echo "=== Workspaces ==="
          kubectl get workspaces -A -o yaml
          echo "=== Controller Logs ==="
          kubectl logs -n airunway-system -l control-plane=controller-manager --tail=100
          echo "=== KAITO Provider Logs ==="
          kubectl logs -n airunway-system -l control-plane=kaito-provider --tail=100
          echo "=== Events ==="
          kubectl get events -A --sort-by=.lastTimestamp
          echo "=== Pods ==="
          kubectl get pods -A

      - name: Cleanup
        if: always()
        run: |
          kind delete cluster --name airunway-e2e