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e2e_node: install gpu pod with PodClient

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Prior to this change, the pod was not getting scheduled on the node as
we don't have a running scheduler in e2e_node. PodClient solves this
problem by manually assigning the pod to the node.
This commit is contained in:
Danielle Lancashire 2021-08-26 14:22:22 +02:00
parent 0cc8af82a1
commit 7d7884c0e6
1 changed files with 4 additions and 7 deletions
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11
test/e2e_node/gpu_device_plugin_test.go
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@ -54,8 +54,7 @@ func NVIDIADevicePlugin() *v1.Pod {
framework.ExpectNoError(err)
p := &v1.Pod{
ObjectMeta: metav1.ObjectMeta{
Name: "device-plugin-nvidia-gpu-" + string(uuid.NewUUID()),
Namespace: metav1.NamespaceSystem,
Name: "device-plugin-nvidia-gpu-" + string(uuid.NewUUID()),
},
Spec: ds.Spec.Template.Spec,
}
@ -70,7 +69,6 @@ var _ = SIGDescribe("NVIDIA GPU Device Plugin [Feature:GPUDevicePlugin][NodeFeat
ginkgo.Context("DevicePlugin", func() {
var devicePluginPod *v1.Pod
var err error
ginkgo.BeforeEach(func() {
ginkgo.By("Ensuring that Nvidia GPUs exists on the node")
if !checkIfNvidiaGPUsExistOnNode() {
@ -81,14 +79,13 @@ var _ = SIGDescribe("NVIDIA GPU Device Plugin [Feature:GPUDevicePlugin][NodeFeat
ginkgo.Skip("Test works only with in-tree dockershim. Skipping test.")
}
ginkgo.By("Creating the Google Device Plugin pod for NVIDIA GPU in GKE")
devicePluginPod, err = f.ClientSet.CoreV1().Pods(metav1.NamespaceSystem).Create(context.TODO(), NVIDIADevicePlugin(), metav1.CreateOptions{})
framework.ExpectNoError(err)
ginkgo.By("Creating the Google Device Plugin pod for NVIDIA GPU")
devicePluginPod = f.PodClient().Create(NVIDIADevicePlugin())
ginkgo.By("Waiting for GPUs to become available on the local node")
gomega.Eventually(func() bool {
return numberOfNVIDIAGPUs(getLocalNode(f)) > 0
}, 5*time.Minute, framework.Poll).Should(gomega.BeTrue())
}, 5*time.Minute, framework.Poll).Should(gomega.BeTrue(), "GPUs never became available on the local node")
if numberOfNVIDIAGPUs(getLocalNode(f)) < 2 {
ginkgo.Skip("Not enough GPUs to execute this test (at least two needed)")