mirror of
https://github.com/intel/intel-device-plugins-for-kubernetes.git
synced 2025-06-03 03:59:37 +00:00
82 lines
3.2 KiB
Go
82 lines
3.2 KiB
Go
// Copyright 2020 Intel Corporation. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package gpu
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import (
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"context"
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"path/filepath"
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"time"
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"github.com/intel/intel-device-plugins-for-kubernetes/test/e2e/utils"
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"github.com/onsi/ginkgo"
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v1 "k8s.io/api/core/v1"
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"k8s.io/apimachinery/pkg/api/resource"
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metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
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"k8s.io/apimachinery/pkg/labels"
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"k8s.io/kubernetes/test/e2e/framework"
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"k8s.io/kubernetes/test/e2e/framework/kubectl"
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e2epod "k8s.io/kubernetes/test/e2e/framework/pod"
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imageutils "k8s.io/kubernetes/test/utils/image"
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)
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const (
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kustomizationYaml = "deployments/gpu_plugin/kustomization.yaml"
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)
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func init() {
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ginkgo.Describe("GPU plugin", describe)
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}
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func describe() {
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f := framework.NewDefaultFramework("gpuplugin")
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kustomizationPath, err := utils.LocateRepoFile(kustomizationYaml)
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if err != nil {
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framework.Failf("unable to locate %q: %v", kustomizationYaml, err)
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}
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ginkgo.It("checks availability of GPU resources", func() {
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ginkgo.By("deploying GPU plugin")
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framework.RunKubectlOrDie(f.Namespace.Name, "--namespace", f.Namespace.Name, "apply", "-k", filepath.Dir(kustomizationPath))
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ginkgo.By("waiting for GPU plugin's availability")
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if _, err := e2epod.WaitForPodsWithLabelRunningReady(f.ClientSet, f.Namespace.Name,
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labels.Set{"app": "intel-gpu-plugin"}.AsSelector(), 1 /* one replica */, 10*time.Second); err != nil {
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framework.DumpAllNamespaceInfo(f.ClientSet, f.Namespace.Name)
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kubectl.LogFailedContainers(f.ClientSet, f.Namespace.Name, framework.Logf)
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framework.Failf("unable to wait for all pods to be running and ready: %v", err)
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}
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ginkgo.By("checking the resource is allocatable")
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if err := utils.WaitForNodesWithResource(f.ClientSet, "gpu.intel.com/i915", 30*time.Second); err != nil {
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framework.Failf("unable to wait for nodes to have positive allocatable resource: %v", err)
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}
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ginkgo.By("submitting a pod requesting GPU resources")
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podSpec := f.NewTestPod("gpuplugin-tester",
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v1.ResourceList{"gpu.intel.com/i915": resource.MustParse("1")},
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v1.ResourceList{"gpu.intel.com/i915": resource.MustParse("1")})
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podSpec.Spec.RestartPolicy = v1.RestartPolicyNever
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podSpec.Spec.Containers[0].Image = imageutils.GetE2EImage(imageutils.BusyBox)
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podSpec.Spec.Containers[0].Command = []string{"/bin/sh"}
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podSpec.Spec.Containers[0].Args = []string{"-c", "echo hello world"}
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pod, err := f.ClientSet.CoreV1().Pods(f.Namespace.Name).Create(context.TODO(), podSpec, metav1.CreateOptions{})
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framework.ExpectNoError(err, "pod Create API error")
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ginkgo.By("waiting the pod to finnish successfully")
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f.PodClient().WaitForFinish(pod.ObjectMeta.Name, 30*time.Second)
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})
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}
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