e2e: Add e2e for CronFederatedHPA
Signed-off-by: jwcesign <jiangwei115@huawei.com>
This commit is contained in:
jwcesign
jwcesign
parent
2a314eb46e
commit
7ac69c1864
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@ -231,6 +231,9 @@ util::wait_pod_ready "${HOST_CLUSTER_NAME}" "${KARMADA_AGGREGATION_APISERVER_LAB
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# deploy karmada-search on host cluster
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kubectl --context="${HOST_CLUSTER_NAME}" apply -f "${REPO_ROOT}/artifacts/deploy/karmada-search.yaml"
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util::wait_pod_ready "${HOST_CLUSTER_NAME}" "${KARMADA_SEARCH_LABEL}" "${KARMADA_SYSTEM_NAMESPACE}"
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# deploy karmada-metrics-adapter on host cluster
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kubectl --context="${HOST_CLUSTER_NAME}" apply -f "${REPO_ROOT}/artifacts/deploy/karmada-metrics-adapter.yaml"
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util::wait_pod_ready "${HOST_CLUSTER_NAME}" "${KARMADA_METRICS_ADAPTER_LABEL}" "${KARMADA_SYSTEM_NAMESPACE}"
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# install CRD APIs on karmada apiserver.
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if ! kubectl config get-contexts "karmada-apiserver" > /dev/null 2>&1;
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@ -260,6 +263,11 @@ kubectl --context="karmada-apiserver" apply -f "${REPO_ROOT}/artifacts/deploy/ka
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# make sure apiservice for v1alpha1.search.karmada.io is Available
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util::wait_apiservice_ready "karmada-apiserver" "${KARMADA_SEARCH_LABEL}"
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# deploy APIService on karmada apiserver for karmada-metrics-adapter
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kubectl --context="karmada-apiserver" apply -f "${REPO_ROOT}/artifacts/deploy/karmada-metrics-adapter-apiservice.yaml"
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# make sure apiservice for karmada metrics adapter is Available
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util::wait_apiservice_ready "karmada-apiserver" "${KARMADA_METRICS_ADAPTER_LABEL}"
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# deploy cluster proxy rbac for admin
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kubectl --context="karmada-apiserver" apply -f "${REPO_ROOT}/artifacts/deploy/cluster-proxy-admin-rbac.yaml"
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@ -135,6 +135,7 @@ kind load docker-image "${REGISTRY}/karmada-webhook:${VERSION}" --name="${HOST_C
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kind load docker-image "${REGISTRY}/karmada-scheduler-estimator:${VERSION}" --name="${HOST_CLUSTER_NAME}"
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kind load docker-image "${REGISTRY}/karmada-aggregated-apiserver:${VERSION}" --name="${HOST_CLUSTER_NAME}"
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kind load docker-image "${REGISTRY}/karmada-search:${VERSION}" --name="${HOST_CLUSTER_NAME}"
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kind load docker-image "${REGISTRY}/karmada-metrics-adapter:${VERSION}" --name="${HOST_CLUSTER_NAME}"
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#step5. install karmada control plane components
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"${REPO_ROOT}"/hack/deploy-karmada.sh "${MAIN_KUBECONFIG}" "${HOST_CLUSTER_NAME}"
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@ -169,12 +170,17 @@ kind load docker-image "${REGISTRY}/karmada-agent:${VERSION}" --name="${PULL_MOD
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#step7. deploy karmada agent in pull mode member clusters
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"${REPO_ROOT}"/hack/deploy-agent-and-estimator.sh "${MAIN_KUBECONFIG}" "${HOST_CLUSTER_NAME}" "${MAIN_KUBECONFIG}" "${KARMADA_APISERVER_CLUSTER_NAME}" "${PULL_MODE_CLUSTER_TMP_CONFIG}" "${PULL_MODE_CLUSTER_NAME}"
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#step8. deploy metrics adapter in member clusters
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"${REPO_ROOT}"/hack/deploy-k8s-metrics-server.sh "${MEMBER_CLUSTER_1_TMP_CONFIG}" "${MEMBER_CLUSTER_1_NAME}"
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"${REPO_ROOT}"/hack/deploy-k8s-metrics-server.sh "${MEMBER_CLUSTER_2_TMP_CONFIG}" "${MEMBER_CLUSTER_2_NAME}"
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"${REPO_ROOT}"/hack/deploy-k8s-metrics-server.sh "${PULL_MODE_CLUSTER_TMP_CONFIG}" "${PULL_MODE_CLUSTER_NAME}"
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# wait all of clusters member1, member2 and member3 status is ready
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util:wait_cluster_ready "${KARMADA_APISERVER_CLUSTER_NAME}" "${MEMBER_CLUSTER_1_NAME}"
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util:wait_cluster_ready "${KARMADA_APISERVER_CLUSTER_NAME}" "${MEMBER_CLUSTER_2_NAME}"
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util:wait_cluster_ready "${KARMADA_APISERVER_CLUSTER_NAME}" "${PULL_MODE_CLUSTER_NAME}"
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#step8. merge temporary kubeconfig of member clusters by kubectl
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#step9. merge temporary kubeconfig of member clusters by kubectl
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export KUBECONFIG=$(find ${KUBECONFIG_PATH} -maxdepth 1 -type f | grep ${MEMBER_TMP_CONFIG_PREFIX} | tr '\n' ':')
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kubectl config view --flatten > ${MEMBER_CLUSTER_KUBECONFIG}
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rm $(find ${KUBECONFIG_PATH} -maxdepth 1 -type f | grep ${MEMBER_TMP_CONFIG_PREFIX})
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@ -0,0 +1,199 @@
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/*
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Copyright 2023 The Karmada Authors.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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*/
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package e2e
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import (
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"time"
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"github.com/onsi/ginkgo/v2"
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appsv1 "k8s.io/api/apps/v1"
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"k8s.io/apimachinery/pkg/util/rand"
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"k8s.io/utils/pointer"
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autoscalingv1alpha1 "github.com/karmada-io/karmada/pkg/apis/autoscaling/v1alpha1"
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policyv1alpha1 "github.com/karmada-io/karmada/pkg/apis/policy/v1alpha1"
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"github.com/karmada-io/karmada/test/e2e/framework"
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"github.com/karmada-io/karmada/test/helper"
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)
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/*
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CronFederatedHPA focus on scaling FederatedHPA or other resource with scale subresource (e.g. Deployment, StatefulSet).
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Test Case Overview:
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case 1:
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Scale FederatedHPA.
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case 2:
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Scale deployment.
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case 3:
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Test suspend rule in CronFederatedHPA
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case 4:
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Test unsuspend rule then suspend it in CronFederatedHPA
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*/
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var _ = ginkgo.Describe("[CronFederatedHPA] CronFederatedHPA testing", func() {
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var cronFHPAName, fhpaName, policyName, deploymentName string
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var cronFHPA *autoscalingv1alpha1.CronFederatedHPA
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var fhpa *autoscalingv1alpha1.FederatedHPA
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var deployment *appsv1.Deployment
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var policy *policyv1alpha1.PropagationPolicy
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ginkgo.BeforeEach(func() {
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cronFHPAName = cronFedratedHPANamePrefix + rand.String(RandomStrLength)
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fhpaName = federatedHPANamePrefix + rand.String(RandomStrLength)
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policyName = deploymentNamePrefix + rand.String(RandomStrLength)
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deploymentName = policyName
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deployment = helper.NewDeployment(testNamespace, deploymentName)
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policy = helper.NewPropagationPolicy(testNamespace, policyName, []policyv1alpha1.ResourceSelector{
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{
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APIVersion: deployment.APIVersion,
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Kind: deployment.Kind,
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Name: deploymentName,
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},
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}, policyv1alpha1.Placement{
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ClusterAffinity: &policyv1alpha1.ClusterAffinity{
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ClusterNames: framework.ClusterNames(),
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},
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ReplicaScheduling: &policyv1alpha1.ReplicaSchedulingStrategy{
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ReplicaSchedulingType: policyv1alpha1.ReplicaSchedulingTypeDivided,
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ReplicaDivisionPreference: policyv1alpha1.ReplicaDivisionPreferenceAggregated,
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},
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})
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})
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ginkgo.JustBeforeEach(func() {
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framework.CreatePropagationPolicy(karmadaClient, policy)
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framework.CreateDeployment(kubeClient, deployment)
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ginkgo.DeferCleanup(func() {
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framework.RemoveDeployment(kubeClient, deployment.Namespace, deployment.Name)
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framework.RemovePropagationPolicy(karmadaClient, policy.Namespace, policy.Name)
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})
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})
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// case 1: Scale FederatedHPA.
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ginkgo.Context("Scale FederatedHPA", func() {
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targetMinReplicas := pointer.Int32(2)
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targetMaxReplicas := pointer.Int32(100)
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ginkgo.BeforeEach(func() {
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// */1 * * * * means the rule will be triggered every 1 minute
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rule := helper.NewCronFederatedHPARule("scale-up", "*/1 * * * *", false, nil, targetMinReplicas, targetMaxReplicas)
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fhpa = helper.NewFederatedHPA(testNamespace, fhpaName, deploymentName)
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cronFHPA = helper.NewCronFederatedHPAWithScalingFHPA(testNamespace, cronFHPAName, fhpaName, rule)
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framework.CreateFederatedHPA(karmadaClient, fhpa)
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})
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ginkgo.AfterEach(func() {
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framework.RemoveFederatedHPA(karmadaClient, testNamespace, fhpaName)
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framework.RemoveCronFederatedHPA(karmadaClient, testNamespace, cronFHPAName)
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})
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ginkgo.It("Scale FederatedHPA testing", func() {
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*fhpa.Spec.MinReplicas))
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// Create CronFederatedHPA to scale FederatedHPA
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framework.CreateCronFederatedHPA(karmadaClient, cronFHPA)
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// Wait CronFederatedHPA to scale FederatedHPA's minReplicas which will trigger scaling deployment's replicas to minReplicas
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*targetMinReplicas))
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})
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})
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// case 2. Scale deployment.
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ginkgo.Context("Scale Deployment", func() {
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targetReplicas := pointer.Int32(4)
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ginkgo.BeforeEach(func() {
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// */1 * * * * means the rule will be executed every 1 minute
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rule := helper.NewCronFederatedHPARule("scale-up", "*/1 * * * *", false, targetReplicas, nil, nil)
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cronFHPA = helper.NewCronFederatedHPAWithScalingDeployment(testNamespace, cronFHPAName, deploymentName, rule)
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})
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ginkgo.AfterEach(func() {
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framework.RemoveCronFederatedHPA(karmadaClient, testNamespace, cronFHPAName)
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})
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ginkgo.It("Scale Deployment testing", func() {
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*deployment.Spec.Replicas))
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// Create CronFederatedHPA to scale Deployment
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framework.CreateCronFederatedHPA(karmadaClient, cronFHPA)
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*targetReplicas))
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})
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})
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// case 3. Test suspend rule in CronFederatedHPA
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ginkgo.Context("Test suspend rule in CronFederatedHPA", func() {
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ginkgo.BeforeEach(func() {
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// */1 * * * * means the rule will be executed every 1 minute
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rule := helper.NewCronFederatedHPARule("scale-up", "*/1 * * * *", true, pointer.Int32(30), nil, nil)
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cronFHPA = helper.NewCronFederatedHPAWithScalingDeployment(testNamespace, cronFHPAName, deploymentName, rule)
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})
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ginkgo.AfterEach(func() {
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framework.RemoveCronFederatedHPA(karmadaClient, testNamespace, cronFHPAName)
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})
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ginkgo.It("Test suspend rule with CronFederatedHPA", func() {
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*deployment.Spec.Replicas))
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// Create CronFederatedHPA to scale Deployment
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framework.CreateCronFederatedHPA(karmadaClient, cronFHPA)
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// */1 * * * * means the rule will be triggered every 1 minute
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// So wait for 1m30s and check whether the replicas changed and whether the suspend field works
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time.Sleep(time.Minute*1 + time.Second*30)
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*deployment.Spec.Replicas))
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})
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})
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// case 4. Test unsuspend rule then suspend it in CronFederatedHPA
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ginkgo.Context("Test unsuspend rule then suspend it in CronFederatedHPA", func() {
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rule := autoscalingv1alpha1.CronFederatedHPARule{}
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targetReplicas := pointer.Int32(4)
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ginkgo.BeforeEach(func() {
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// */1 * * * * means the rule will be executed every 1 minute
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rule = helper.NewCronFederatedHPARule("scale-up", "*/1 * * * *", false, targetReplicas, nil, nil)
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cronFHPA = helper.NewCronFederatedHPAWithScalingDeployment(testNamespace, cronFHPAName, deploymentName, rule)
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})
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ginkgo.AfterEach(func() {
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framework.RemoveCronFederatedHPA(karmadaClient, testNamespace, cronFHPAName)
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})
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ginkgo.It("Test unsuspend rule then suspend it in CronFederatedHPA", func() {
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// Step 1.Check the init replicas, which should be 3(deployment.Spec.Replicas)
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*deployment.Spec.Replicas))
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// Step 2.Create CronFederatedHPA to scale Deployment
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framework.CreateCronFederatedHPA(karmadaClient, cronFHPA)
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*targetReplicas))
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// Step 3.Update replicas to 3(deployment.Spec.Replicas)
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framework.UpdateDeploymentReplicas(kubeClient, deployment, *deployment.Spec.Replicas)
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// Step 4. Suspend rule
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rule.Suspend = pointer.Bool(true)
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framework.UpdateCronFederatedHPAWithRule(karmadaClient, testNamespace, cronFHPAName, []autoscalingv1alpha1.CronFederatedHPARule{rule})
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// Step 5. Check the replicas, which should not be changed
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// */1 * * * * means the rule will be triggered every 1 minute
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// So wait for 1m30s and check whether the replicas changed and whether the suspend field works
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time.Sleep(time.Minute*1 + time.Second*30)
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framework.WaitDeploymentReplicasFitWith(framework.ClusterNames(), testNamespace, deploymentName, int(*deployment.Spec.Replicas))
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})
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})
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})
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@ -0,0 +1,54 @@
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/*
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Copyright 2023 The Karmada Authors.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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*/
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package framework
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import (
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"context"
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"fmt"
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"github.com/onsi/ginkgo/v2"
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"github.com/onsi/gomega"
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metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
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autoscalingv1alpha1 "github.com/karmada-io/karmada/pkg/apis/autoscaling/v1alpha1"
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karmada "github.com/karmada-io/karmada/pkg/generated/clientset/versioned"
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)
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// CreateCronFederatedHPA create CronFederatedHPA with karmada client.
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func CreateCronFederatedHPA(client karmada.Interface, fhpa *autoscalingv1alpha1.CronFederatedHPA) {
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ginkgo.By(fmt.Sprintf("Create FederatedHPA(%s/%s)", fhpa.Namespace, fhpa.Name), func() {
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_, err := client.AutoscalingV1alpha1().CronFederatedHPAs(fhpa.Namespace).Create(context.TODO(), fhpa, metav1.CreateOptions{})
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gomega.Expect(err).ShouldNot(gomega.HaveOccurred())
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})
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}
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// RemoveCronFederatedHPA delete CronFederatedHPA with karmada client.
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func RemoveCronFederatedHPA(client karmada.Interface, namespace, name string) {
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ginkgo.By(fmt.Sprintf("Remove FederatedHPA(%s/%s)", namespace, name), func() {
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err := client.AutoscalingV1alpha1().CronFederatedHPAs(namespace).Delete(context.TODO(), name, metav1.DeleteOptions{})
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gomega.Expect(err).ShouldNot(gomega.HaveOccurred())
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})
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}
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// UpdateCronFederatedHPAWithRule update CronFederatedHPA with karmada client.
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func UpdateCronFederatedHPAWithRule(client karmada.Interface, namespace, name string, rule []autoscalingv1alpha1.CronFederatedHPARule) {
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ginkgo.By(fmt.Sprintf("Updating CronFederatedHPA(%s/%s)", namespace, name), func() {
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newCronFederatedHPA, err := client.AutoscalingV1alpha1().CronFederatedHPAs(namespace).Get(context.TODO(), name, metav1.GetOptions{})
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gomega.Expect(err).ShouldNot(gomega.HaveOccurred())
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newCronFederatedHPA.Spec.Rules = rule
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_, err = client.AutoscalingV1alpha1().CronFederatedHPAs(namespace).Update(context.TODO(), newCronFederatedHPA, metav1.UpdateOptions{})
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gomega.Expect(err).ShouldNot(gomega.HaveOccurred())
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})
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}
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@ -223,3 +223,25 @@ func WaitDeploymentGetByClientFitWith(client kubernetes.Interface, namespace, na
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}, pollTimeout, pollInterval).Should(gomega.Equal(true))
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})
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}
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func WaitDeploymentReplicasFitWith(clusters []string, namespace, name string, expectReplicas int) {
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ginkgo.By(fmt.Sprintf("Check deployment(%s/%s) replicas fit with expecting", namespace, name), func() {
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gomega.Eventually(func() bool {
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totalReplicas := 0
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for _, cluster := range clusters {
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clusterClient := GetClusterClient(cluster)
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if clusterClient == nil {
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continue
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}
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dep, err := clusterClient.AppsV1().Deployments(namespace).Get(context.TODO(), name, metav1.GetOptions{})
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if err != nil {
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continue
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}
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totalReplicas += int(*dep.Spec.Replicas)
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}
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klog.Infof("The total replicas of deployment(%s/%s) is %d", namespace, name, totalReplicas)
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return totalReplicas == expectReplicas
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}, pollTimeout, pollInterval).Should(gomega.Equal(true))
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})
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}
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@ -0,0 +1,42 @@
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/*
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Copyright 2023 The Karmada Authors.
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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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http://www.apache.org/licenses/LICENSE-2.0
|
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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,
|
||||
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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*/
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package framework
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import (
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"context"
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"fmt"
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"github.com/onsi/ginkgo/v2"
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"github.com/onsi/gomega"
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metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
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autoscalingv1alpha1 "github.com/karmada-io/karmada/pkg/apis/autoscaling/v1alpha1"
|
||||
karmada "github.com/karmada-io/karmada/pkg/generated/clientset/versioned"
|
||||
)
|
||||
|
||||
// CreateFederatedHPA create FederatedHPA with karmada client.
|
||||
func CreateFederatedHPA(client karmada.Interface, fhpa *autoscalingv1alpha1.FederatedHPA) {
|
||||
ginkgo.By(fmt.Sprintf("Create FederatedHPA(%s/%s)", fhpa.Namespace, fhpa.Name), func() {
|
||||
_, err := client.AutoscalingV1alpha1().FederatedHPAs(fhpa.Namespace).Create(context.TODO(), fhpa, metav1.CreateOptions{})
|
||||
gomega.Expect(err).ShouldNot(gomega.HaveOccurred())
|
||||
})
|
||||
}
|
||||
|
||||
// RemoveFederatedHPA delete FederatedHPA with karmada client.
|
||||
func RemoveFederatedHPA(client karmada.Interface, namespace, name string) {
|
||||
ginkgo.By(fmt.Sprintf("Remove FederatedHPA(%s/%s)", namespace, name), func() {
|
||||
err := client.AutoscalingV1alpha1().FederatedHPAs(namespace).Delete(context.TODO(), name, metav1.DeleteOptions{})
|
||||
gomega.Expect(err).ShouldNot(gomega.HaveOccurred())
|
||||
})
|
||||
}
|
||||
|
|
@ -56,6 +56,8 @@ const (
|
|||
roleBindingNamePrefix = "rolebinding-"
|
||||
clusterRoleBindingNamePrefix = "clusterrolebinding-"
|
||||
podDisruptionBudgetNamePrefix = "poddisruptionbudget-"
|
||||
federatedHPANamePrefix = "fhpa-"
|
||||
cronFedratedHPANamePrefix = "cronfhpa-"
|
||||
|
||||
updateDeploymentReplicas = 2
|
||||
updateStatefulSetReplicas = 2
|
||||
|
|
|
|||
|
|
@ -4,6 +4,7 @@ import (
|
|||
"fmt"
|
||||
|
||||
appsv1 "k8s.io/api/apps/v1"
|
||||
autoscalingv2 "k8s.io/api/autoscaling/v2"
|
||||
batchv1 "k8s.io/api/batch/v1"
|
||||
corev1 "k8s.io/api/core/v1"
|
||||
networkingv1 "k8s.io/api/networking/v1"
|
||||
|
|
@ -18,6 +19,7 @@ import (
|
|||
"k8s.io/utils/pointer"
|
||||
|
||||
workloadv1alpha1 "github.com/karmada-io/karmada/examples/customresourceinterpreter/apis/workload/v1alpha1"
|
||||
autoscalingv1alpha1 "github.com/karmada-io/karmada/pkg/apis/autoscaling/v1alpha1"
|
||||
clusterv1alpha1 "github.com/karmada-io/karmada/pkg/apis/cluster/v1alpha1"
|
||||
)
|
||||
|
||||
|
|
@ -31,6 +33,104 @@ const (
|
|||
ResourceUnitGPU int64 = 1
|
||||
)
|
||||
|
||||
// NewCronFederatedHPAWithScalingDeployment will build a CronFederatedHPA object with scaling deployment.
|
||||
func NewCronFederatedHPAWithScalingDeployment(namespace, name, deploymentName string,
|
||||
rule autoscalingv1alpha1.CronFederatedHPARule) *autoscalingv1alpha1.CronFederatedHPA {
|
||||
return &autoscalingv1alpha1.CronFederatedHPA{
|
||||
TypeMeta: metav1.TypeMeta{
|
||||
APIVersion: "autoscaling.karmada.io/v1alpha1",
|
||||
Kind: "CronFederatedHPA",
|
||||
},
|
||||
ObjectMeta: metav1.ObjectMeta{
|
||||
Namespace: namespace,
|
||||
Name: name,
|
||||
},
|
||||
Spec: autoscalingv1alpha1.CronFederatedHPASpec{
|
||||
ScaleTargetRef: autoscalingv2.CrossVersionObjectReference{
|
||||
APIVersion: "apps/v1",
|
||||
Kind: "Deployment",
|
||||
Name: deploymentName,
|
||||
},
|
||||
Rules: []autoscalingv1alpha1.CronFederatedHPARule{rule},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
// NewCronFederatedHPAWithScalingFHPA will build a CronFederatedHPA object with scaling FederatedHPA.
|
||||
func NewCronFederatedHPAWithScalingFHPA(namespace, name, fhpaName string,
|
||||
rule autoscalingv1alpha1.CronFederatedHPARule) *autoscalingv1alpha1.CronFederatedHPA {
|
||||
return &autoscalingv1alpha1.CronFederatedHPA{
|
||||
TypeMeta: metav1.TypeMeta{
|
||||
APIVersion: "autoscaling.karmada.io/v1alpha1",
|
||||
Kind: "CronFederatedHPA",
|
||||
},
|
||||
ObjectMeta: metav1.ObjectMeta{
|
||||
Namespace: namespace,
|
||||
Name: name,
|
||||
},
|
||||
Spec: autoscalingv1alpha1.CronFederatedHPASpec{
|
||||
ScaleTargetRef: autoscalingv2.CrossVersionObjectReference{
|
||||
APIVersion: "autoscaling.karmada.io/v1alpha1",
|
||||
Kind: "FederatedHPA",
|
||||
Name: fhpaName,
|
||||
},
|
||||
Rules: []autoscalingv1alpha1.CronFederatedHPARule{rule},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
// NewCronFederatedHPARule will build a CronFederatedHPARule object.
|
||||
func NewCronFederatedHPARule(name, cron string, suspend bool, targetReplicas, targetMinReplicas, targetMaxReplicas *int32) autoscalingv1alpha1.CronFederatedHPARule {
|
||||
return autoscalingv1alpha1.CronFederatedHPARule{
|
||||
Name: name,
|
||||
Schedule: cron,
|
||||
TargetReplicas: targetReplicas,
|
||||
TargetMinReplicas: targetMinReplicas,
|
||||
TargetMaxReplicas: targetMaxReplicas,
|
||||
Suspend: pointer.Bool(suspend),
|
||||
}
|
||||
}
|
||||
|
||||
// NewFederatedHPA will build a FederatedHPA object.
|
||||
func NewFederatedHPA(namespace, name, scaleTargetDeployment string) *autoscalingv1alpha1.FederatedHPA {
|
||||
return &autoscalingv1alpha1.FederatedHPA{
|
||||
TypeMeta: metav1.TypeMeta{
|
||||
APIVersion: "autoscaling.karmada.io/v1alpha1",
|
||||
Kind: "FederatedHPA",
|
||||
},
|
||||
ObjectMeta: metav1.ObjectMeta{
|
||||
Namespace: namespace,
|
||||
Name: name,
|
||||
},
|
||||
Spec: autoscalingv1alpha1.FederatedHPASpec{
|
||||
ScaleTargetRef: autoscalingv2.CrossVersionObjectReference{
|
||||
APIVersion: "apps/v1",
|
||||
Kind: "Deployment",
|
||||
Name: scaleTargetDeployment,
|
||||
},
|
||||
Behavior: &autoscalingv2.HorizontalPodAutoscalerBehavior{
|
||||
ScaleDown: &autoscalingv2.HPAScalingRules{
|
||||
StabilizationWindowSeconds: pointer.Int32(10),
|
||||
},
|
||||
},
|
||||
MinReplicas: pointer.Int32(1),
|
||||
MaxReplicas: 1,
|
||||
Metrics: []autoscalingv2.MetricSpec{
|
||||
{
|
||||
Type: autoscalingv2.ResourceMetricSourceType,
|
||||
Resource: &autoscalingv2.ResourceMetricSource{
|
||||
Name: corev1.ResourceCPU,
|
||||
Target: autoscalingv2.MetricTarget{
|
||||
Type: autoscalingv2.UtilizationMetricType,
|
||||
AverageUtilization: pointer.Int32(80),
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
// NewDeployment will build a deployment object.
|
||||
func NewDeployment(namespace string, name string) *appsv1.Deployment {
|
||||
podLabels := map[string]string{"app": "nginx"}
|
||||
|
|
@ -58,6 +158,9 @@ func NewDeployment(namespace string, name string) *appsv1.Deployment {
|
|||
Name: "nginx",
|
||||
Image: "nginx:1.19.0",
|
||||
Resources: corev1.ResourceRequirements{
|
||||
Requests: map[corev1.ResourceName]resource.Quantity{
|
||||
corev1.ResourceCPU: resource.MustParse("10m"),
|
||||
},
|
||||
Limits: map[corev1.ResourceName]resource.Quantity{
|
||||
corev1.ResourceCPU: resource.MustParse("100m"),
|
||||
},
|
||||
|
|
|
|||
Loading…
Reference in New Issue