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* Add new labels in pod creation Signed-off-by: glindsell <[email protected]> * Remove test pod labels and add service labels Signed-off-by: glindsell <[email protected]> * Replace default bool with canary bool Signed-off-by: glindsell <[email protected]> * Remove canary field in CRD and update Canary logic Signed-off-by: glindsell <[email protected]> * Move labels logic and add tests Signed-off-by: glindsell <[email protected]>
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Mar 24, 2020
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,40 @@ | ||
| package controllers | ||
|
|
||
| import ( | ||
| machinelearningv1 "github.com/seldonio/seldon-core/operator/apis/machinelearning/v1" | ||
| appsv1 "k8s.io/api/apps/v1" | ||
| corev1 "k8s.io/api/core/v1" | ||
| ) | ||
|
|
||
| func addLabelsToService(svc *corev1.Service, pu *machinelearningv1.PredictiveUnit, p machinelearningv1.PredictorSpec) { | ||
| switch *pu.Type { | ||
| case machinelearningv1.ROUTER: | ||
| svc.Labels[machinelearningv1.Label_router] = "true" | ||
| case machinelearningv1.COMBINER: | ||
| svc.Labels[machinelearningv1.Label_combiner] = "true" | ||
| case machinelearningv1.MODEL: | ||
| svc.Labels[machinelearningv1.Label_model] = "true" | ||
| case machinelearningv1.TRANSFORMER: | ||
| svc.Labels[machinelearningv1.Label_transformer] = "true" | ||
| case machinelearningv1.OUTPUT_TRANSFORMER: | ||
| svc.Labels[machinelearningv1.Label_output_transformer] = "true" | ||
| } | ||
| if p.Shadow != true && (p.Traffic >= 50 || p.Traffic == 0) { | ||
| svc.Labels[machinelearningv1.Label_default] = "true" | ||
| } | ||
| if p.Shadow == true { | ||
| svc.Labels[machinelearningv1.Label_shadow] = "true" | ||
| } | ||
| if p.Traffic < 50 && p.Traffic > 0 { | ||
| svc.Labels[machinelearningv1.Label_canary] = "true" | ||
| } | ||
| if p.Explainer != nil { | ||
| svc.Labels[machinelearningv1.Label_explainer] = "true" | ||
| } | ||
| } | ||
|
|
||
| func addLabelsToDeployment(deploy *appsv1.Deployment, containerServiceKey, containerServiceValue string) { | ||
| deploy.ObjectMeta.Labels[containerServiceKey] = containerServiceValue | ||
| deploy.Spec.Selector.MatchLabels[containerServiceKey] = containerServiceValue | ||
| deploy.Spec.Template.ObjectMeta.Labels[containerServiceKey] = containerServiceValue | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,132 @@ | ||
| package controllers | ||
|
|
||
| import ( | ||
| "testing" | ||
|
|
||
| . "github.com/onsi/gomega" | ||
| machinelearningv1 "github.com/seldonio/seldon-core/operator/apis/machinelearning/v1" | ||
| appsv1 "k8s.io/api/apps/v1" | ||
| corev1 "k8s.io/api/core/v1" | ||
|
|
||
| metav1 "k8s.io/apimachinery/pkg/apis/meta/v1" | ||
| ) | ||
|
|
||
| func TestAddLabelsToDeployment(t *testing.T) { | ||
| g := NewGomegaWithT(t) | ||
| d := &appsv1.Deployment{ | ||
| ObjectMeta: metav1.ObjectMeta{ | ||
| Labels: map[string]string{}, | ||
| }, | ||
| Spec: appsv1.DeploymentSpec{ | ||
| Selector: &metav1.LabelSelector{ | ||
| MatchLabels: map[string]string{}, | ||
| }, | ||
| Template: corev1.PodTemplateSpec{ | ||
| ObjectMeta: metav1.ObjectMeta{ | ||
| Labels: map[string]string{}, | ||
| }, | ||
| }, | ||
| }, | ||
| } | ||
| t.Run("adds correct label to Deployment", func(t *testing.T) { | ||
| addLabelsToDeployment(d, "TestKey", "TestValue") | ||
| g.Expect(d.ObjectMeta.Labels["TestKey"]).To(Equal("TestValue")) | ||
| g.Expect(d.Spec.Selector.MatchLabels["TestKey"]).To(Equal("TestValue")) | ||
| g.Expect(d.Spec.Template.ObjectMeta.Labels["TestKey"]).To(Equal("TestValue")) | ||
| }) | ||
| } | ||
|
|
||
| func TestAddLabelsToService(t *testing.T) { | ||
| g := NewGomegaWithT(t) | ||
| cases1 := []struct { | ||
| puType machinelearningv1.PredictiveUnitType | ||
| result string | ||
| }{ | ||
| { | ||
| puType: machinelearningv1.ROUTER, | ||
| result: machinelearningv1.Label_router, | ||
| }, | ||
| { | ||
| puType: machinelearningv1.COMBINER, | ||
| result: machinelearningv1.Label_combiner, | ||
| }, | ||
| { | ||
| puType: machinelearningv1.MODEL, | ||
| result: machinelearningv1.Label_model, | ||
| }, | ||
| { | ||
| puType: machinelearningv1.TRANSFORMER, | ||
| result: machinelearningv1.Label_transformer, | ||
| }, | ||
| { | ||
| puType: machinelearningv1.OUTPUT_TRANSFORMER, | ||
| result: machinelearningv1.Label_output_transformer, | ||
| }, | ||
| } | ||
| cases2 := []struct { | ||
| shadow bool | ||
| explainer *machinelearningv1.Explainer | ||
| traffic int32 | ||
| result string | ||
| }{ | ||
| { | ||
| shadow: false, | ||
| explainer: nil, | ||
| traffic: 0, | ||
| result: machinelearningv1.Label_default, | ||
| }, | ||
| { | ||
| shadow: false, | ||
| explainer: nil, | ||
| traffic: 50, | ||
| result: machinelearningv1.Label_default, | ||
| }, | ||
| { | ||
| shadow: false, | ||
| explainer: nil, | ||
| traffic: 75, | ||
| result: machinelearningv1.Label_default, | ||
| }, | ||
| { | ||
| shadow: true, | ||
| explainer: nil, | ||
| traffic: 0, | ||
| result: machinelearningv1.Label_shadow, | ||
| }, | ||
| { | ||
| shadow: false, | ||
| explainer: nil, | ||
| traffic: 49, | ||
| result: machinelearningv1.Label_canary, | ||
| }, | ||
| { | ||
| shadow: false, | ||
| explainer: &machinelearningv1.Explainer{}, | ||
| traffic: 0, | ||
| result: machinelearningv1.Label_explainer, | ||
| }, | ||
| } | ||
| svc := &corev1.Service{ | ||
| ObjectMeta: metav1.ObjectMeta{ | ||
| Labels: map[string]string{}, | ||
| }, | ||
| } | ||
| p := machinelearningv1.PredictorSpec{} | ||
| pu := &machinelearningv1.PredictiveUnit{} | ||
| t.Run("adds correct label to Service from Predictive Unit Type", func(t *testing.T) { | ||
| for _, c := range cases1 { | ||
| pu.Type = &c.puType | ||
| addLabelsToService(svc, pu, p) | ||
| g.Expect(svc.Labels[c.result]).To(Equal("true")) | ||
| } | ||
| }) | ||
| t.Run("adds correct label to Service for Default, Shadow, Canary & Explainer from Predictor Spec", func(t *testing.T) { | ||
| for _, c := range cases2 { | ||
| p.Shadow = c.shadow | ||
| p.Explainer = c.explainer | ||
| p.Traffic = c.traffic | ||
| addLabelsToService(svc, pu, p) | ||
| g.Expect(svc.Labels[c.result]).To(Equal("true")) | ||
| } | ||
| }) | ||
| } |
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