Add KFTO upgrade test for uninterrupted training

tests/kfto/upgrade/kfto_sft_upgrade_sleep_test.go

@@ -0,0 +1,114 @@
+/*
+Copyright 2024.
+
+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 kfto
+
+import (
+	"testing"
+
+	. "github.com/onsi/gomega"
+	kftocore "github.com/opendatahub-io/distributed-workloads/tests/kfto/core"
+	. "github.com/project-codeflare/codeflare-common/support"
+
+	corev1 "k8s.io/api/core/v1"
+	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
+
+	kftov1 "github.com/kubeflow/training-operator/pkg/apis/kubeflow.org/v1"
+)
+
+var (
+	sleepNamespaceName  = "test-kfto-upgrade-sleep"
+	sleepPyTorchJobName = "pytorch-upgrade-sleep"
+)
+
+func TestSetupSleepPytorchjob(t *testing.T) {
+	test := With(t)
+
+	// Create a namespace
+	namespace := &corev1.Namespace{
+		ObjectMeta: metav1.ObjectMeta{
+			Name: sleepNamespaceName,
+		},
+	}
+	_, err := test.Client().Core().CoreV1().Namespaces().Create(test.Ctx(), namespace, metav1.CreateOptions{})
+	test.Expect(err).NotTo(HaveOccurred())
+
+	// Create training PyTorch job
+	createSleepPyTorchJob(test, sleepNamespaceName)
+
+	// Make sure the PyTorch job is running, waiting for Training operator upgrade
+	test.Eventually(kftocore.PytorchJob(test, sleepNamespaceName, sleepPyTorchJobName), TestTimeoutShort).
+		Should(WithTransform(kftocore.PytorchJobConditionRunning, Equal(corev1.ConditionTrue)))
+}
+
+func TestVerifySleepPytorchjob(t *testing.T) {
+	test := With(t)
+	namespace := GetNamespaceWithName(test, sleepNamespaceName)
+
+	// Cleanup namespace in the end
+	defer DeleteTestNamespace(test, namespace)
+
+	// PyTorch job should be still running
+	test.Expect(kftocore.PytorchJob(test, sleepNamespaceName, sleepPyTorchJobName)(test)).
+		Should(WithTransform(kftocore.PytorchJobConditionRunning, Equal(corev1.ConditionTrue)))
+
+	// Pod job should be running without restart
+	test.Expect(GetPods(test, sleepNamespaceName, metav1.ListOptions{})).
+		Should(
+			And(
+				HaveLen(1),
+				ContainElement(WithTransform(sleepPodRestartCount, BeNumerically("==", 0))),
+			),
+		)
+}
+
+func createSleepPyTorchJob(test Test, namespace string) *kftov1.PyTorchJob {
+	tuningJob := &kftov1.PyTorchJob{
+		ObjectMeta: metav1.ObjectMeta{
+			Name: sleepPyTorchJobName,
+		},
+		Spec: kftov1.PyTorchJobSpec{
+			PyTorchReplicaSpecs: map[kftov1.ReplicaType]*kftov1.ReplicaSpec{
+				"Master": {
+					Replicas:      Ptr(int32(1)),
+					RestartPolicy: "OnFailure",
+					Template: corev1.PodTemplateSpec{
+						Spec: corev1.PodSpec{
+							Containers: []corev1.Container{
+								{
+									Name:            "pytorch",
+									Image:           "gcr.io/k8s-staging-perf-tests/sleep:v0.1.0",
+									ImagePullPolicy: corev1.PullIfNotPresent,
+									Args:            []string{"24h"},
+								},
+							},
+						},
+					},
+				},
+			},
+		},
+	}
+
+	tuningJob, err := test.Client().Kubeflow().KubeflowV1().PyTorchJobs(namespace).Create(test.Ctx(), tuningJob, metav1.CreateOptions{})
+	test.Expect(err).NotTo(HaveOccurred())
+	test.T().Logf("Created PytorchJob %s/%s successfully", tuningJob.Namespace, tuningJob.Name)
+
+	return tuningJob
+}
+
+func sleepPodRestartCount(pod corev1.Pod) int {
+	return int(pod.Status.ContainerStatuses[0].RestartCount)
+}