Merge pull request #1970 from chengchengpei/cpei/fix_noEngine

fixed noEngine
SeldonIO · Jul 15, 2020 · 3730769 · 3730769
2 parents cbd86d5 + 4558aa3
commit 3730769
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Showing 2 changed files with 146 additions and 3 deletions.
diff --git a/operator/controllers/noengine_test.go b/operator/controllers/noengine_test.go
@@ -86,3 +86,146 @@ var _ = Describe("Create a Seldon Deployment without engine", func() {
 	})
 
 })
+
+var _ = Describe("Create a Seldon Deployment with engine", func() {
+	const timeout = time.Second * 30
+	const interval = time.Second * 1
+	By("Creating a resource")
+	It("should create a resource with defaults", func() {
+		Expect(k8sClient).NotTo(BeNil())
+		var modelType = machinelearningv1.MODEL
+		key := types.NamespacedName{
+			Name:      "dep2-1",
+			Namespace: "default",
+		}
+		instance := &machinelearningv1.SeldonDeployment{
+			ObjectMeta: metav1.ObjectMeta{
+				Name:      key.Name,
+				Namespace: key.Namespace,
+			},
+			Spec: machinelearningv1.SeldonDeploymentSpec{
+				Name: "mydep2-1",
+				Predictors: []machinelearningv1.PredictorSpec{
+					{
+						Annotations: map[string]string{
+							"seldon.io/no-engine": "false",
+						},
+						Name: "p1",
+						ComponentSpecs: []*machinelearningv1.SeldonPodSpec{
+							{
+								Spec: v1.PodSpec{
+									Containers: []v1.Container{
+										{
+											Image: "seldonio/mock_classifier:1.0",
+											Name:  "classifier",
+										},
+									},
+								},
+							},
+						},
+						Graph: machinelearningv1.PredictiveUnit{
+							Name: "classifier",
+							Type: &modelType,
+						},
+					},
+				},
+			},
+		}
+
+		// Run Defaulter
+		instance.Default()
+
+		Expect(k8sClient.Create(context.Background(), instance)).Should(Succeed())
+		//time.Sleep(time.Second * 5)
+
+		fetched := &machinelearningv1.SeldonDeployment{}
+		Eventually(func() error {
+			err := k8sClient.Get(context.Background(), key, fetched)
+			return err
+		}, timeout, interval).Should(BeNil())
+		Expect(fetched.Name).Should(Equal("dep2-1"))
+
+		depKey := types.NamespacedName{
+			Name:      machinelearningv1.GetDeploymentName(instance, instance.Spec.Predictors[0], instance.Spec.Predictors[0].ComponentSpecs[0], 0),
+			Namespace: "default",
+		}
+		depFetched := &appsv1.Deployment{}
+		Eventually(func() error {
+			err := k8sClient.Get(context.Background(), depKey, depFetched)
+			return err
+		}, timeout, interval).Should(BeNil())
+		Expect(len(depFetched.Spec.Template.Spec.Containers)).Should(Equal(2))
+
+		Expect(k8sClient.Delete(context.Background(), instance)).Should(Succeed())
+	})
+})
+
+var _ = Describe("Create a Seldon Deployment without seldon.io/no-engine annotation", func() {
+	const timeout = time.Second * 30
+	const interval = time.Second * 1
+	By("Creating a resource")
+	It("should create a resource with defaults", func() {
+		Expect(k8sClient).NotTo(BeNil())
+		var modelType = machinelearningv1.MODEL
+		key := types.NamespacedName{
+			Name:      "dep2-2",
+			Namespace: "default",
+		}
+		instance := &machinelearningv1.SeldonDeployment{
+			ObjectMeta: metav1.ObjectMeta{
+				Name:      key.Name,
+				Namespace: key.Namespace,
+			},
+			Spec: machinelearningv1.SeldonDeploymentSpec{
+				Name: "mydep2-2",
+				Predictors: []machinelearningv1.PredictorSpec{
+					{
+						Name: "p1",
+						ComponentSpecs: []*machinelearningv1.SeldonPodSpec{
+							{
+								Spec: v1.PodSpec{
+									Containers: []v1.Container{
+										{
+											Image: "seldonio/mock_classifier:1.0",
+											Name:  "classifier",
+										},
+									},
+								},
+							},
+						},
+						Graph: machinelearningv1.PredictiveUnit{
+							Name: "classifier",
+							Type: &modelType,
+						},
+					},
+				},
+			},
+		}
+
+		// Run Defaulter
+		instance.Default()
+
+		Expect(k8sClient.Create(context.Background(), instance)).Should(Succeed())
+		//time.Sleep(time.Second * 5)
+
+		fetched := &machinelearningv1.SeldonDeployment{}
+		Eventually(func() error {
+			err := k8sClient.Get(context.Background(), key, fetched)
+			return err
+		}, timeout, interval).Should(BeNil())
+		Expect(fetched.Name).Should(Equal("dep2-2"))
+
+		depKey := types.NamespacedName{
+			Name:      machinelearningv1.GetDeploymentName(instance, instance.Spec.Predictors[0], instance.Spec.Predictors[0].ComponentSpecs[0], 0),
+			Namespace: "default",
+		}
+		depFetched := &appsv1.Deployment{}
+		Eventually(func() error {
+			err := k8sClient.Get(context.Background(), depKey, depFetched)
+			return err
+		}, timeout, interval).Should(BeNil())
+		Expect(len(depFetched.Spec.Template.Spec.Containers)).Should(Equal(2))
+
+		Expect(k8sClient.Delete(context.Background(), instance)).Should(Succeed())
+	})
+})
diff --git a/operator/controllers/seldondeployment_controller.go b/operator/controllers/seldondeployment_controller.go
@@ -377,7 +377,7 @@ func (r *SeldonDeploymentReconciler) createComponents(mlDep *machinelearningv1.S
 	// Attempt to set httpAllowed and grpcAllowed to false if we have an noEngine predictor
 	for i := 0; i < len(mlDep.Spec.Predictors); i++ {
 		p := mlDep.Spec.Predictors[i]
-		_, noEngine := p.Annotations[machinelearningv1.ANNOTATION_NO_ENGINE]
+		noEngine := strings.ToLower(p.Annotations[machinelearningv1.ANNOTATION_NO_ENGINE]) == "true"
 		if noEngine && len(p.ComponentSpecs) > 0 && len(p.ComponentSpecs[0].Spec.Containers) > 0 {
 			pu := machinelearningv1.GetPredictiveUnit(&p.Graph, p.ComponentSpecs[0].Spec.Containers[0].Name)
 			if pu != nil {
@@ -393,11 +393,11 @@ func (r *SeldonDeploymentReconciler) createComponents(mlDep *machinelearningv1.S
 
 	for i := 0; i < len(mlDep.Spec.Predictors); i++ {
 		p := mlDep.Spec.Predictors[i]
-		_, noEngine := p.Annotations[machinelearningv1.ANNOTATION_NO_ENGINE]
+		noEngine := strings.ToLower(p.Annotations[machinelearningv1.ANNOTATION_NO_ENGINE]) == "true"
 		pSvcName := machinelearningv1.GetPredictorKey(mlDep, &p)
 		log.Info("pSvcName", "val", pSvcName)
 		// Add engine deployment if separate
-		_, hasSeparateEnginePod := mlDep.Spec.Annotations[machinelearningv1.ANNOTATION_SEPARATE_ENGINE]
+		hasSeparateEnginePod := strings.ToLower(mlDep.Spec.Annotations[machinelearningv1.ANNOTATION_SEPARATE_ENGINE]) == "true"
 		if hasSeparateEnginePod && !noEngine {
 			deploy, err := createEngineDeployment(mlDep, &p, pSvcName, engine_http_port, engine_grpc_port)
 			if err != nil {