intel-device-plugins-for-ku.../test/e2e/gpu/gpu.go
Dmitry Rozhkov 8fc187f4d8 move to k8s v1.18.2 release
Also fix the plugins and e2e tests
2020-04-17 12:40:18 +03:00

82 lines
3.2 KiB
Go

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