sigs.k8s.io/kueue@v0.6.2/test/integration/controller/jobs/tfjob/tfjob_controller_test.go

/*
Copyright 2023 The Kubernetes Authors.

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 tfjob

import (
	kftraining "github.com/kubeflow/training-operator/pkg/apis/kubeflow.org/v1"
	"github.com/onsi/ginkgo/v2"
	"github.com/onsi/gomega"
	corev1 "k8s.io/api/core/v1"
	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"

	configapi "sigs.k8s.io/kueue/apis/config/v1beta1"
	kueue "sigs.k8s.io/kueue/apis/kueue/v1beta1"
	"sigs.k8s.io/kueue/pkg/controller/jobframework"
	workloadtfjob "sigs.k8s.io/kueue/pkg/controller/jobs/kubeflow/jobs/tfjob"
	"sigs.k8s.io/kueue/pkg/controller/jobs/kubeflow/kubeflowjob"
	"sigs.k8s.io/kueue/pkg/util/testing"
	testingtfjob "sigs.k8s.io/kueue/pkg/util/testingjobs/tfjob"
	kftesting "sigs.k8s.io/kueue/test/integration/controller/jobs/kubeflow"
	"sigs.k8s.io/kueue/test/integration/framework"
	"sigs.k8s.io/kueue/test/util"
)

const (
	jobName           = "test-job"
	instanceKey       = "cloud.provider.com/instance"
	priorityClassName = "test-priority-class"
	priorityValue     = 10
	jobQueueName      = "test-queue"
)

// +kubebuilder:docs-gen:collapse=Imports

var _ = ginkgo.Describe("Job controller", ginkgo.Ordered, ginkgo.ContinueOnFailure, func() {

	ginkgo.BeforeAll(func() {
		fwk = &framework.Framework{
			CRDPath:     crdPath,
			DepCRDPaths: []string{tensorflowCrdPath},
		}
		cfg = fwk.Init()
		ctx, k8sClient = fwk.RunManager(cfg, managerSetup(jobframework.WithManageJobsWithoutQueueName(true)))
	})
	ginkgo.AfterAll(func() {
		fwk.Teardown()
	})

	var (
		ns *corev1.Namespace
	)
	ginkgo.BeforeEach(func() {
		ns = &corev1.Namespace{
			ObjectMeta: metav1.ObjectMeta{
				GenerateName: "core-",
			},
		}
		gomega.Expect(k8sClient.Create(ctx, ns)).To(gomega.Succeed())
	})
	ginkgo.AfterEach(func() {
		gomega.Expect(util.DeleteNamespace(ctx, k8sClient, ns)).To(gomega.Succeed())
	})

	ginkgo.It("Should reconcile TFJobs", func() {
		kfJob := kubeflowjob.KubeflowJob{KFJobControl: (*workloadtfjob.JobControl)(testingtfjob.MakeTFJob(jobName, ns.Name).Obj())}
		createdJob := kubeflowjob.KubeflowJob{KFJobControl: (*workloadtfjob.JobControl)(&kftraining.TFJob{})}

		kftesting.ShouldReconcileJob(ctx, k8sClient, kfJob, createdJob, []kftesting.PodSetsResource{
			{
				RoleName:    kftraining.TFJobReplicaTypeChief,
				ResourceCPU: "on-demand",
			},
			{
				RoleName:    kftraining.TFJobReplicaTypePS,
				ResourceCPU: "spot",
			},
			{
				RoleName:    kftraining.TFJobReplicaTypeWorker,
				ResourceCPU: "spot",
			},
		})
	})
})

var _ = ginkgo.Describe("Job controller when waitForPodsReady enabled", ginkgo.Ordered, ginkgo.ContinueOnFailure, func() {
	var (
		ns            *corev1.Namespace
		defaultFlavor = testing.MakeResourceFlavor("default").Label(instanceKey, "default").Obj()
	)

	ginkgo.BeforeAll(func() {
		fwk = &framework.Framework{
			CRDPath:     crdPath,
			DepCRDPaths: []string{tensorflowCrdPath},
		}
		cfg := fwk.Init()
		ctx, k8sClient = fwk.RunManager(cfg, managerSetup(jobframework.WithWaitForPodsReady(&configapi.WaitForPodsReady{Enable: true})))

		ginkgo.By("Create a resource flavor")
		gomega.Expect(k8sClient.Create(ctx, defaultFlavor)).Should(gomega.Succeed())
	})
	ginkgo.AfterAll(func() {
		util.ExpectResourceFlavorToBeDeleted(ctx, k8sClient, defaultFlavor, true)
		fwk.Teardown()
	})

	ginkgo.BeforeEach(func() {
		ns = &corev1.Namespace{
			ObjectMeta: metav1.ObjectMeta{
				GenerateName: "core-",
			},
		}
		gomega.Expect(k8sClient.Create(ctx, ns)).To(gomega.Succeed())
	})
	ginkgo.AfterEach(func() {
		gomega.Expect(util.DeleteNamespace(ctx, k8sClient, ns)).To(gomega.Succeed())
	})

	ginkgo.DescribeTable("Single job at different stages of progress towards completion",
		func(podsReadyTestSpec kftesting.PodsReadyTestSpec) {
			kfJob := kubeflowjob.KubeflowJob{KFJobControl: (*workloadtfjob.JobControl)(testingtfjob.MakeTFJob(jobName, ns.Name).Parallelism(2, 2).Obj())}
			createdJob := kubeflowjob.KubeflowJob{KFJobControl: (*workloadtfjob.JobControl)(&kftraining.TFJob{})}

			kftesting.JobControllerWhenWaitForPodsReadyEnabled(ctx, k8sClient, kfJob, createdJob, podsReadyTestSpec, []kftesting.PodSetsResource{
				{
					RoleName:    kftraining.TFJobReplicaTypeChief,
					ResourceCPU: "default",
				},
				{
					RoleName:    kftraining.TFJobReplicaTypePS,
					ResourceCPU: "default",
				},
				{
					RoleName:    kftraining.TFJobReplicaTypeWorker,
					ResourceCPU: "default",
				},
			})
		},
		ginkgo.Entry("No progress", kftesting.PodsReadyTestSpec{
			WantCondition: &metav1.Condition{
				Type:    kueue.WorkloadPodsReady,
				Status:  metav1.ConditionFalse,
				Reason:  "PodsReady",
				Message: "Not all pods are ready or succeeded",
			},
		}),
		ginkgo.Entry("Running TFJob", kftesting.PodsReadyTestSpec{
			JobStatus: kftraining.JobStatus{
				Conditions: []kftraining.JobCondition{
					{
						Type:   kftraining.JobRunning,
						Status: corev1.ConditionTrue,
						Reason: "Running",
					},
				},
			},
			WantCondition: &metav1.Condition{
				Type:    kueue.WorkloadPodsReady,
				Status:  metav1.ConditionTrue,
				Reason:  "PodsReady",
				Message: "All pods were ready or succeeded since the workload admission",
			},
		}),
		ginkgo.Entry("Running TFJob; PodsReady=False before", kftesting.PodsReadyTestSpec{
			BeforeCondition: &metav1.Condition{
				Type:    kueue.WorkloadPodsReady,
				Status:  metav1.ConditionFalse,
				Reason:  "PodsReady",
				Message: "Not all pods are ready or succeeded",
			},
			JobStatus: kftraining.JobStatus{
				Conditions: []kftraining.JobCondition{
					{
						Type:   kftraining.JobRunning,
						Status: corev1.ConditionTrue,
						Reason: "Running",
					},
				},
			},
			WantCondition: &metav1.Condition{
				Type:    kueue.WorkloadPodsReady,
				Status:  metav1.ConditionTrue,
				Reason:  "PodsReady",
				Message: "All pods were ready or succeeded since the workload admission",
			},
		}),
		ginkgo.Entry("Job suspended; PodsReady=True before", kftesting.PodsReadyTestSpec{
			BeforeJobStatus: &kftraining.JobStatus{
				Conditions: []kftraining.JobCondition{
					{
						Type:   kftraining.JobRunning,
						Status: corev1.ConditionTrue,
						Reason: "Running",
					},
				},
			},
			BeforeCondition: &metav1.Condition{
				Type:    kueue.WorkloadPodsReady,
				Status:  metav1.ConditionTrue,
				Reason:  "PodsReady",
				Message: "All pods were ready or succeeded since the workload admission",
			},
			JobStatus: kftraining.JobStatus{
				Conditions: []kftraining.JobCondition{
					{
						Type:   kftraining.JobRunning,
						Status: corev1.ConditionFalse,
						Reason: "Suspended",
					},
				},
			},
			Suspended: true,
			WantCondition: &metav1.Condition{
				Type:    kueue.WorkloadPodsReady,
				Status:  metav1.ConditionFalse,
				Reason:  "PodsReady",
				Message: "Not all pods are ready or succeeded",
			},
		}),
	)
})

var _ = ginkgo.Describe("Job controller interacting with scheduler", ginkgo.Ordered, ginkgo.ContinueOnFailure, func() {
	var (
		ns                  *corev1.Namespace
		onDemandFlavor      *kueue.ResourceFlavor
		spotUntaintedFlavor *kueue.ResourceFlavor
		clusterQueue        *kueue.ClusterQueue
		localQueue          *kueue.LocalQueue
	)

	ginkgo.BeforeAll(func() {
		fwk = &framework.Framework{
			CRDPath:     crdPath,
			DepCRDPaths: []string{tensorflowCrdPath},
		}
		cfg := fwk.Init()
		ctx, k8sClient = fwk.RunManager(cfg, managerAndSchedulerSetup())
	})
	ginkgo.AfterAll(func() {
		fwk.Teardown()
	})

	ginkgo.BeforeEach(func() {
		ns = &corev1.Namespace{
			ObjectMeta: metav1.ObjectMeta{
				GenerateName: "core-",
			},
		}
		gomega.Expect(k8sClient.Create(ctx, ns)).To(gomega.Succeed())

		onDemandFlavor = testing.MakeResourceFlavor("on-demand").Label(instanceKey, "on-demand").Obj()
		gomega.Expect(k8sClient.Create(ctx, onDemandFlavor)).Should(gomega.Succeed())

		spotUntaintedFlavor = testing.MakeResourceFlavor("spot-untainted").Label(instanceKey, "spot-untainted").Obj()
		gomega.Expect(k8sClient.Create(ctx, spotUntaintedFlavor)).Should(gomega.Succeed())

		clusterQueue = testing.MakeClusterQueue("dev-clusterqueue").
			ResourceGroup(
				*testing.MakeFlavorQuotas("spot-untainted").Resource(corev1.ResourceCPU, "8").Obj(),
				*testing.MakeFlavorQuotas("on-demand").Resource(corev1.ResourceCPU, "5").Obj(),
			).Obj()
		gomega.Expect(k8sClient.Create(ctx, clusterQueue)).Should(gomega.Succeed())
	})
	ginkgo.AfterEach(func() {
		gomega.Expect(util.DeleteNamespace(ctx, k8sClient, ns)).To(gomega.Succeed())
		util.ExpectClusterQueueToBeDeleted(ctx, k8sClient, clusterQueue, true)
		util.ExpectResourceFlavorToBeDeleted(ctx, k8sClient, onDemandFlavor, true)
		gomega.Expect(util.DeleteResourceFlavor(ctx, k8sClient, spotUntaintedFlavor)).To(gomega.Succeed())
	})

	ginkgo.It("Should schedule jobs as they fit in their ClusterQueue", func() {
		ginkgo.By("creating localQueue")
		localQueue = testing.MakeLocalQueue("local-queue", ns.Name).ClusterQueue(clusterQueue.Name).Obj()
		gomega.Expect(k8sClient.Create(ctx, localQueue)).Should(gomega.Succeed())

		kfJob := kubeflowjob.KubeflowJob{KFJobControl: (*workloadtfjob.JobControl)(
			testingtfjob.MakeTFJob(jobName, ns.Name).Queue(localQueue.Name).
				Request(kftraining.TFJobReplicaTypeChief, corev1.ResourceCPU, "3").
				Request(kftraining.TFJobReplicaTypePS, corev1.ResourceCPU, "4").
				Request(kftraining.TFJobReplicaTypeWorker, corev1.ResourceCPU, "4").
				Obj(),
		)}
		createdJob := kubeflowjob.KubeflowJob{KFJobControl: (*workloadtfjob.JobControl)(&kftraining.TFJob{})}

		kftesting.ShouldScheduleJobsAsTheyFitInTheirClusterQueue(ctx, k8sClient, kfJob, createdJob, clusterQueue, []kftesting.PodSetsResource{
			{
				RoleName:    kftraining.TFJobReplicaTypeChief,
				ResourceCPU: kueue.ResourceFlavorReference(spotUntaintedFlavor.Name),
			},
			{
				RoleName:    kftraining.TFJobReplicaTypePS,
				ResourceCPU: kueue.ResourceFlavorReference(spotUntaintedFlavor.Name),
			},
			{
				RoleName:    kftraining.TFJobReplicaTypeWorker,
				ResourceCPU: kueue.ResourceFlavorReference(onDemandFlavor.Name),
			},
		})
	})
})