fix: go lint + test with wrong poolName

- if e2e is only tested on kind with specific guide gaie-sim then make
  it clear and fix the label value
- llm-d.ai/guide:simlulated-accelerators
- llm-d.ai/model:random

Signed-off-by: Wen Zhou <wenzhou@redhat.com>

Author: zdtsw

docs/developer-guide/testing.md

@@ -8,7 +8,7 @@ WVA has a multi-layered testing strategy:
 
 1. **Unit Tests** - Fast, isolated tests for individual packages and functions
 2. **Integration Tests** - Tests for component interactions within the controller
-3. **E2E Tests** - Environment-agnostic end-to-end tests (Kind emulated or OpenShift), with smoke and full tiers
+3. **E2E Tests** - End-to-end tests on Kind clusters with emulated GPUs, with smoke and full tiers
 
 ## Unit Tests
 
@@ -134,10 +134,12 @@ var _ = AfterSuite(func() {
 
 ## End-to-End Tests
 
-WVA provides a **single consolidated E2E suite** that runs on multiple environments (Kind with emulated GPUs, or OpenShift/kubernetes with real infrastructure). Tests are environment-agnostic and parameterized via environment variables; they create VA, HPA, and model services dynamically as part of the test workflow.
+WVA provides a **single consolidated E2E suite** that runs on Kind clusters with emulated GPUs. Tests create VA, HPA, and model services dynamically as part of the test workflow.
+
+> **Note**: E2E tests are only supported on Kind clusters (`ENVIRONMENT=kind-emulator`). The test fixtures and labels are configured specifically for the Kind emulator deployment which uses the `simulated-accelerators` guide from llm-d. Running E2E tests on other environments (OpenShift, generic Kubernetes) is not supported for now.
 
 - **Location**: `test/e2e/`
-- **Environments**: Kind (emulated), OpenShift, or generic Kubernetes
+- **Supported Environment**: Kind (emulated GPUs only)
 - **Tiers**: Smoke (~5–10 min) for PRs; full suite (~15–25 min) for comprehensive validation
 
 ### Infra-Only Setup (Required Before Running Tests)

internal/controller/configmap_bootstrap.go

@@ -63,7 +63,7 @@ func (r *ConfigMapReconciler) BootstrapInitialConfigMaps(ctx context.Context) er
 							continue // Skip excluded namespaces. Only for all-namespaces mode.
 						}
 					}
-					
+
 				}
 				if ns.Labels != nil {
 					if value, ok := ns.Labels[constants.NamespaceConfigEnabledLabelKey]; ok {

test/e2e/fixtures/infra_builder.go

@@ -60,14 +60,14 @@ func buildService(namespace, name, appLabel string, port int) *corev1.Service {
 			Name:      serviceName,
 			Namespace: namespace,
 			Labels: map[string]string{
-				"app":                       appLabel,
+				"app":                        appLabel,
 				"llm-d.ai/inference-serving": "true",
-				"test-resource":             "true",
+				"test-resource":              "true",
 			},
 		},
 		Spec: corev1.ServiceSpec{
 			Selector: map[string]string{
-				"app":                       appLabel,
+				"app":                        appLabel,
 				"llm-d.ai/inference-serving": "true",
 			},
 			Ports: []corev1.ServicePort{

test/e2e/fixtures/model_service_builder.go

@@ -86,12 +86,20 @@ func buildModelServiceDeployment(namespace, name, poolName, modelID string, useS
 		image = "ghcr.io/llm-d/llm-d-cuda-dev:latest"
 	}
 	args := buildModelServerArgs(modelID, useSimulator, maxNumSeqs)
+	// Labels must include all labels from the infrastructure InferencePool's selector.
+	// For kind-emulator (gaie-sim), the selector uses:
+	// - llm-d.ai/inference-serving: "true"
+	// - llm-d.ai/guide: "simulated-accelerators"
+	// - llm-d.ai/accelerator-variant: "cpu"
+	// - llm-d.ai/model: "random"
 	labels := map[string]string{
-		"app":                         appLabel,
-		"llm-d.ai/inference-serving": "true",
-		"llm-d.ai/model":              "ms-sim-llm-d-modelservice",
-		"llm-d.ai/model-pool":         poolName,
-		"test-resource":               "true",
+		"app":                          appLabel,
+		"llm-d.ai/inference-serving":   "true",
+		"llm-d.ai/guide":               poolName,
+		"llm-d.ai/accelerator-variant": "cpu",
+		"llm-d.ai/model":               "random",
+		"llm-d.ai/model-pool":          poolName,
+		"test-resource":                "true",
 	}
 
 	envVars := []corev1.EnvVar{
@@ -135,10 +143,11 @@ func buildModelServiceDeployment(namespace, name, poolName, modelID string, useS
 			Replicas: ptr.To(int32(1)),
 			Selector: &metav1.LabelSelector{
 				MatchLabels: map[string]string{
-					"app":                       appLabel,
-					"llm-d.ai/inference-serving": "true",
-					"llm-d.ai/model":            "ms-sim-llm-d-modelservice",
-					"llm-d.ai/model-pool":       poolName,
+					"app":                          appLabel,
+					"llm-d.ai/inference-serving":   "true",
+					"llm-d.ai/guide":               poolName,
+					"llm-d.ai/accelerator-variant": "cpu",
+					"llm-d.ai/model":               "random", // to match simulator model
 				},
 			},
 			Template: corev1.PodTemplateSpec{

test/e2e/scale_from_zero_test.go

@@ -28,7 +28,9 @@ import (
 // Uses KEDA ScaledObject when standard HPA rejects minReplicas=0 (e.g. OpenShift).
 var _ = Describe("Scale-From-Zero Feature", Label("smoke", "full"), Ordered, func() {
 	var (
-		poolName         = "scale-from-zero-pool"
+		// poolName must match the infrastructure InferencePool's selector label (llm-d.ai/guide).
+		// E2E tests only run on kind-emulator which uses "simulated-accelerators" (WELL_LIT_PATH_NAME).
+		poolName         = "simulated-accelerators"
 		modelServiceName = "scale-from-zero-ms"
 		vaName           = "scale-from-zero-va"
 		hpaName          = "scale-from-zero-hpa"

test/utils/resources/llmdsim.go

@@ -23,17 +23,17 @@ func CreateLlmdSimDeployment(namespace, deployName, modelName, appLabel, port st
 			Replicas: ptr.To(replicas),
 			Selector: &metav1.LabelSelector{
 				MatchLabels: map[string]string{
-					"app":                       appLabel,
+					"app":                        appLabel,
 					"llm-d.ai/inference-serving": "true",
-					"llm-d.ai/model":            "ms-sim-llm-d-modelservice",
+					"llm-d.ai/model":             "ms-sim-llm-d-modelservice",
 				},
 			},
 			Template: corev1.PodTemplateSpec{
 				ObjectMeta: metav1.ObjectMeta{
 					Labels: map[string]string{
-						"app":                       appLabel,
+						"app":                        appLabel,
 						"llm-d.ai/inference-serving": "true",
-						"llm-d.ai/model":            "ms-sim-llm-d-modelservice",
+						"llm-d.ai/model":             "ms-sim-llm-d-modelservice",
 					},
 				},
 				Spec: corev1.PodSpec{
@@ -161,17 +161,17 @@ func CreateLlmdSimDeploymentWithGPU(namespace, deployName, modelName, appLabel,
 			Replicas: ptr.To(replicas),
 			Selector: &metav1.LabelSelector{
 				MatchLabels: map[string]string{
-					"app":                       appLabel,
+					"app":                        appLabel,
 					"llm-d.ai/inference-serving": "true",
-					"llm-d.ai/model":            "ms-sim-llm-d-modelservice",
+					"llm-d.ai/model":             "ms-sim-llm-d-modelservice",
 				},
 			},
 			Template: corev1.PodTemplateSpec{
 				ObjectMeta: metav1.ObjectMeta{
 					Labels: map[string]string{
-						"app":                       appLabel,
+						"app":                        appLabel,
 						"llm-d.ai/inference-serving": "true",
-						"llm-d.ai/model":            "ms-sim-llm-d-modelservice",
+						"llm-d.ai/model":             "ms-sim-llm-d-modelservice",
 					},
 				},
 				Spec: corev1.PodSpec{
@@ -251,13 +251,13 @@ func CreateLlmdSimService(namespace, serviceName, appLabel string, nodePort, por
 			Name:      serviceName,
 			Namespace: namespace,
 			Labels: map[string]string{
-				"app":                       appLabel,
+				"app":                        appLabel,
 				"llm-d.ai/inference-serving": "true",
 			},
 		},
 		Spec: corev1.ServiceSpec{
 			Selector: map[string]string{
-				"app":                       appLabel,
+				"app":                        appLabel,
 				"llm-d.ai/inference-serving": "true",
 			},
 			Ports: []corev1.ServicePort{