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Add labels to deployments and improve label coverage of resources #2130

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merged 11 commits into from
Jul 30, 2020
Merged

Add labels to deployments and improve label coverage of resources #2130

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44d8861
Add new component and endpoint labels to operator and remove old labels
Jul 14, 2020
efa110c
Merge remote-tracking branch 'upstream/master' into 1405-new-labels
Jul 14, 2020
059959e
Merge remote-tracking branch 'upstream/master' into 1405-new-labels
Jul 16, 2020
c1e0cc5
Merge remote-tracking branch 'upstream/master' into 1405-new-labels
Jul 17, 2020
cf55b71
Add container service keys and values back in
Jul 17, 2020
b221cea
Revert labels to bools
Jul 21, 2020
676471b
Add labels when creating components
Jul 22, 2020
48bb526
Remove explainer label from other pu types
Jul 22, 2020
b1987e2
Remove comment
Jul 22, 2020
d3f15e4
Add seldon.io prefix to labels
Jul 23, 2020
fcc4826
Return deployments and services when adding labels
Jul 24, 2020
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18 changes: 9 additions & 9 deletions operator/apis/machinelearning.seldon.io/v1/seldondeployment_types.go
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Original file line number Diff line number Diff line change
Expand Up @@ -34,15 +34,15 @@ const (
Label_svc_orch = "seldon-deployment-contains-svcorch"
Label_app = "app"
Label_fluentd = "fluentd"
Label_router = "router"
Label_combiner = "combiner"
Label_model = "model"
Label_transformer = "transformer"
Label_output_transformer = "output-transformer"
Label_default = "default"
Label_shadow = "shadow"
Label_canary = "canary"
Label_explainer = "explainer"
Label_router = "seldon.io/router"
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Nice one! Namespacing the labels under seldon.io/* seems like the right thing to do 👍

Label_combiner = "seldon.io/combiner"
Label_model = "seldon.io/model"
Label_transformer = "seldon.io/transformer"
Label_output_transformer = "seldon.io/output-transformer"
Label_default = "seldon.io/default"
Label_shadow = "seldon.io/shadow"
Label_canary = "seldon.io/canary"
Label_explainer = "seldon.io/explainer"
Label_managed_by = "app.kubernetes.io/managed-by"
Label_value_seldon = "seldon-core"

Expand Down
50 changes: 41 additions & 9 deletions operator/controllers/labels.go
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Original file line number Diff line number Diff line change
Expand Up @@ -6,8 +6,8 @@ import (
corev1 "k8s.io/api/core/v1"
)

func addLabelsToService(svc *corev1.Service, pu *machinelearningv1.PredictiveUnit, p machinelearningv1.PredictorSpec) {
if pu.Type != nil {
func addLabelsToService(svc *corev1.Service, pu *machinelearningv1.PredictiveUnit, p *machinelearningv1.PredictorSpec) *corev1.Service {
if pu != nil && pu.Type != nil {
switch *pu.Type {
case machinelearningv1.ROUTER:
svc.Labels[machinelearningv1.Label_router] = "true"
Expand All @@ -20,6 +20,8 @@ func addLabelsToService(svc *corev1.Service, pu *machinelearningv1.PredictiveUni
case machinelearningv1.OUTPUT_TRANSFORMER:
svc.Labels[machinelearningv1.Label_output_transformer] = "true"
}
} else if !isEmptyExplainer(p.Explainer) {
svc.Labels[machinelearningv1.Label_explainer] = "true"
}
if p.Shadow != true && (p.Traffic >= 50 || p.Traffic == 0) {
svc.Labels[machinelearningv1.Label_default] = "true"
Expand All @@ -30,16 +32,46 @@ func addLabelsToService(svc *corev1.Service, pu *machinelearningv1.PredictiveUni
if p.Traffic < 50 && p.Traffic > 0 {
svc.Labels[machinelearningv1.Label_canary] = "true"
}
if !isEmptyExplainer(p.Explainer) {
svc.Labels[machinelearningv1.Label_explainer] = "true"
}
svc.Labels[machinelearningv1.Label_managed_by] = machinelearningv1.Label_value_seldon
return svc
}

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
func addLabelsToDeployment(deploy *appsv1.Deployment, pu *machinelearningv1.PredictiveUnit, p *machinelearningv1.PredictorSpec) *appsv1.Deployment {
if pu != nil && pu.Type != nil {
switch *pu.Type {
case machinelearningv1.ROUTER:
deploy.Labels[machinelearningv1.Label_router] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_router] = "true"
case machinelearningv1.COMBINER:
deploy.Labels[machinelearningv1.Label_combiner] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_combiner] = "true"
case machinelearningv1.MODEL:
deploy.Labels[machinelearningv1.Label_model] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_model] = "true"
case machinelearningv1.TRANSFORMER:
deploy.Labels[machinelearningv1.Label_transformer] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_transformer] = "true"
case machinelearningv1.OUTPUT_TRANSFORMER:
deploy.Labels[machinelearningv1.Label_output_transformer] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_output_transformer] = "true"
}
} else if !isEmptyExplainer(p.Explainer) {
deploy.Labels[machinelearningv1.Label_explainer] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_explainer] = "true"
}
if p.Shadow != true && (p.Traffic >= 50 || p.Traffic == 0) {
deploy.Labels[machinelearningv1.Label_default] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_default] = "true"
}
if p.Shadow == true {
deploy.Labels[machinelearningv1.Label_shadow] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_shadow] = "true"
}
if p.Traffic < 50 && p.Traffic > 0 {
deploy.Labels[machinelearningv1.Label_canary] = "true"
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_canary] = "true"
}
deploy.ObjectMeta.Labels[machinelearningv1.Label_managed_by] = machinelearningv1.Label_value_seldon
deploy.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_managed_by] = machinelearningv1.Label_value_seldon
return deploy
}
165 changes: 137 additions & 28 deletions operator/controllers/labels_test.go
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Original file line number Diff line number Diff line change
@@ -1,8 +1,6 @@
package controllers

import (
"testing"

. "github.com/onsi/ginkgo"
. "github.com/onsi/ginkgo/extensions/table"
. "github.com/onsi/gomega"
Expand All @@ -12,37 +10,144 @@ import (
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{},
var _ = Describe("addLabelsToDeployment", func() {

var dep *appsv1.Deployment
var p *machinelearningv1.PredictorSpec
var pu *machinelearningv1.PredictiveUnit

BeforeEach(func() {
dep = &appsv1.Deployment{
ObjectMeta: metav1.ObjectMeta{
Labels: map[string]string{},
},
Template: corev1.PodTemplateSpec{
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"))
g.Expect(d.ObjectMeta.Labels[machinelearningv1.Label_managed_by]).To(Equal(machinelearningv1.Label_value_seldon))
g.Expect(d.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_managed_by]).To(Equal(machinelearningv1.Label_value_seldon))
}
p = &machinelearningv1.PredictorSpec{}
pu = &machinelearningv1.PredictiveUnit{}
})
}

DescribeTable(
"Adds correct label to Deployment from Predictive Unit Type",
func(puType machinelearningv1.PredictiveUnitType, result string) {
pu.Type = &puType
addLabelsToDeployment(dep, pu, p)

Expect(dep.Labels[result]).To(Equal("true"))
Expect(dep.Spec.Template.ObjectMeta.Labels[result]).To(Equal("true"))
Expect(dep.Labels[machinelearningv1.Label_managed_by]).To(Equal(machinelearningv1.Label_value_seldon))
Expect(dep.Spec.Template.ObjectMeta.Labels[machinelearningv1.Label_managed_by]).To(Equal(machinelearningv1.Label_value_seldon))
},
Entry("router", machinelearningv1.ROUTER, machinelearningv1.Label_router),
Entry("combiner", machinelearningv1.COMBINER, machinelearningv1.Label_combiner),
Entry("model", machinelearningv1.MODEL, machinelearningv1.Label_model),
Entry("transformer", machinelearningv1.TRANSFORMER, machinelearningv1.Label_transformer),
Entry("output transformer", machinelearningv1.OUTPUT_TRANSFORMER, machinelearningv1.Label_output_transformer),
)

DescribeTable(
"Adds correct label to Deployment from Predictor Spec",
func(shadow bool, explainer *machinelearningv1.Explainer, traffic int, result string, missing []string) {
p.Shadow = shadow
p.Explainer = explainer
p.Traffic = int32(traffic)

// Required until https://github.com/SeldonIO/seldon-core/pull/1600 is
// merged. We should remove afterwards.
if explainer != nil {
pu.Type = nil
} else {
puType := machinelearningv1.MODEL
pu.Type = &puType
}

addLabelsToDeployment(dep, pu, p)

Expect(dep.Labels[result]).To(Equal("true"))
for _, m := range missing {
Expect(dep.Labels).ToNot(HaveKey(m))
}
},
Entry(
"default",
false,
nil,
0,
machinelearningv1.Label_default,
[]string{machinelearningv1.Label_explainer},
),
Entry(
"default with 50%% traffic",
false,
nil,
50,
machinelearningv1.Label_default,
[]string{machinelearningv1.Label_explainer},
),
Entry(
"default with 75%% traffic",
false,
nil,
50,
machinelearningv1.Label_default,
[]string{machinelearningv1.Label_explainer},
),
Entry(
"default with empty explainer",
false,
&machinelearningv1.Explainer{},
0,
machinelearningv1.Label_default,
[]string{machinelearningv1.Label_explainer},
),
Entry(
"shadow",
true,
nil,
0,
machinelearningv1.Label_shadow,
[]string{
machinelearningv1.Label_explainer,
machinelearningv1.Label_default,
},
),
Entry(
"canary",
false,
nil,
48,
machinelearningv1.Label_canary,
[]string{
machinelearningv1.Label_explainer,
machinelearningv1.Label_default,
},
),
Entry(
"explainer",
false,
&machinelearningv1.Explainer{
Type: machinelearningv1.AlibiAnchorsImageExplainer,
},
0,
machinelearningv1.Label_explainer,
[]string{},
),
)
})

var _ = Describe("addLabelsToService", func() {

var svc *corev1.Service
var p machinelearningv1.PredictorSpec
var p *machinelearningv1.PredictorSpec
var pu *machinelearningv1.PredictiveUnit

BeforeEach(func() {
Expand All @@ -51,7 +156,7 @@ var _ = Describe("addLabelsToService", func() {
Labels: map[string]string{},
},
}
p = machinelearningv1.PredictorSpec{}
p = &machinelearningv1.PredictorSpec{}
pu = &machinelearningv1.PredictiveUnit{}
})

Expand Down Expand Up @@ -80,8 +185,12 @@ var _ = Describe("addLabelsToService", func() {

// Required until https://github.com/SeldonIO/seldon-core/pull/1600 is
// merged. We should remove afterwards.
puType := machinelearningv1.MODEL
pu.Type = &puType
if explainer != nil {
pu.Type = nil
} else {
puType := machinelearningv1.MODEL
pu.Type = &puType
}

addLabelsToService(svc, pu, p)

Expand Down
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