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认识Kubernetes Descheduler

kube-scheduler 是 Kubernetes 中负责调度的组件，它本身的调度功能已经很强大了。但由于 Kubernetes 集群非常活跃，它的状态会随时间而改变，由于各种原因，你可能需要将已经运行的 Pod 移动到其他节点：

某些节点负载过高
某些资源对象被添加了 node 亲和性或 pod （反）亲和性
集群中加入了新节点

一旦 Pod 启动之后 kube-scheduler 便不会再尝试重新调度它。根据环境的不同，你可能会有很多需要手动调整 Pod 的分布，例如：如果集群中新加入了一个节点，那么已经运行的 Pod 并不会被分摊到这台节点上，这台节点可能只运行了少量的几个 Pod，这并不理想，对吧？

Descheduler 如何工作？

Descheduler 会检查 Pod 的状态，并根据自定义的策略将不满足要求的 Pod 从该节点上驱逐出去。Descheduler 并不是 kube-scheduler 的替代品，而是要依赖于它。该项目目前放在 Kubernetes 的孵化项目中，还没准备投入生产，但经过我实验发现它的运行效果很好，而且非常稳定。那么该如何安装呢？

部署方法

你可以通过 Job 或 CronJob 来运行 descheduler。我已经创建了一个镜像 komljen/descheduler:v0.5.0-4-ga7ceb671（包含在下面的 yaml 文件中），但由于这个项目的更新速度很快，你可以通过以下的命令创建你自己的镜像：

1 2	⚡ git clone https://github.com/kubernetes-incubator/descheduler ⚡ cd descheduler && make image

然后打好标签 push 到自己的镜像仓库中。

通过我创建的 chart 模板，你可以用 Helm 来部署 descheduler，该模板支持 RBAC 并且已经在 Kubernetes v1.9 上测试通过。

添加我的 helm 私有仓库，然后部署 descheduler：

⚡ helm repo add akomljen-charts 
    https://raw.githubusercontent.com/komljen/helm-charts/master/charts/

⚡ helm install --name ds 
    --namespace kube-system 
    akomljen-charts/descheduler

你也可以不使用 helm，通过手动部署。首先创建 serviceaccount 和 clusterrolebinding：

# Create a cluster role
⚡ cat << EOF| kubectl create -n kube-system -f -
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRole
metadata:
  name: descheduler
rules:
- apiGroups: [""]
  resources: ["nodes"]
  verbs: ["get", "watch", "list"]
- apiGroups: [""]
  resources: ["pods"]
  verbs: ["get", "watch", "list", "delete"]
- apiGroups: [""]
  resources: ["pods/eviction"]
  verbs: ["create"]
EOF

# Create a service account
⚡ kubectl create sa descheduler -n kube-system

# Bind the cluster role to the service account
⚡ kubectl create clusterrolebinding descheduler 
    -n kube-system 
    --clusterrole=descheduler 
    --serviceaccount=kube-system:descheduler

然后通过 configmap 创建 descheduler 策略。目前只支持四种策略：

RemoveDuplicates
RS、deployment 中的 pod 不能同时出现在一台机器上
LowNodeUtilization
找到资源使用率比较低的 node，然后驱逐其他资源使用率比较高节点上的 pod，期望调度器能够重新调度让资源更均衡
RemovePodsViolatingInterPodAntiAffinity
找到已经违反 Pod Anti Affinity 规则的 pods 进行驱逐，可能是因为反亲和是后面加上去的
RemovePodsViolatingNodeAffinity
找到违反 Node Affinity 规则的 pods 进行驱逐，可能是因为 node 后面修改了 label

默认这四种策略全部开启，你可以根据需要关闭它们。下面在 kube-system 命名空间中创建一个 configmap：

⚡ cat << EOF| kubectl create -n kube-system -f -
apiVersion: v1
kind: ConfigMap
metadata:
  name: descheduler
data:
  policy.yaml: |-  
    apiVersion: descheduler/v1alpha1
    kind: DeschedulerPolicy
    strategies:
      RemoveDuplicates:
         enabled: false
      LowNodeUtilization:
         enabled: true
         params:
           nodeResourceUtilizationThresholds:
             thresholds:
               cpu: 20
               memory: 20
               pods: 20
             targetThresholds:
               cpu: 50
               memory: 50
               pods: 50
      RemovePodsViolatingInterPodAntiAffinity:
        enabled: true
      RemovePodsViolatingNodeAffinity:
        enabled: true
        params:
          nodeAffinityType:
          - requiredDuringSchedulingIgnoredDuringExecution
EOF

在 kube-system 命名空间中创建一个 CronJob，该 CroJob 每 30 分钟运行一次：

⚡ cat << EOF| kubectl create -n kube-system -f -
apiVersion: batch/v1beta1
kind: CronJob
metadata:
  name: descheduler
spec:
  schedule: "*/30 * * * *"
  jobTemplate:
    metadata:
      name: descheduler
      annotations:
        scheduler.alpha.kubernetes.io/critical-pod: "true"
    spec:
      template:
        spec:
          serviceAccountName: descheduler
          containers:
          - name: descheduler
            image: komljen/descheduler:v0.6.0
            volumeMounts:
            - mountPath: /policy-dir
              name: policy-volume
            command:
            - /bin/descheduler
            - --v=4
            - --max-pods-to-evict-per-node=10
            - --policy-config-file=/policy-dir/policy.yaml
          restartPolicy: "OnFailure"
          volumes:
          - name: policy-volume
            configMap:
              name: descheduler
EOF

⚡ kubectl get cronjobs -n kube-system
NAME             SCHEDULE       SUSPEND   ACTIVE    LAST SCHEDULE   AGE
descheduler      */30 * * * *   False     0         2m              32m

当 CronJob 开始工作后，可以通过以下命令查看已经成功结束的 Pod：

⚡ kubectl get pods -n kube-system -a | grep Completed
descheduler-1525520700-297pq          0/1       Completed   0          1h
descheduler-1525521000-tz2ch          0/1       Completed   0          32m
descheduler-1525521300-mrw4t          0/1       Completed   0          2m

也可以查看这些 Pod 的日志，然后根据需要调整 descheduler 策略：

⚡ kubectl logs descheduler-1525521300-mrw4t -n kube-system
I0505 11:55:07.554195       1 reflector.go:202] Starting reflector *v1.Node (1h0m0s) from github.com/kubernetes-incubator/descheduler/pkg/descheduler/node/node.go:84
I0505 11:55:07.554255       1 reflector.go:240] Listing and watching *v1.Node from github.com/kubernetes-incubator/descheduler/pkg/descheduler/node/node.go:84
I0505 11:55:07.767903       1 lownodeutilization.go:147] Node "ip-10-4-63-172.eu-west-1.compute.internal" is appropriately utilized with usage: api.ResourceThresholds{"cpu":41.5, "memory":1.3635487207675927, "pods":8.181818181818182}
I0505 11:55:07.767942       1 lownodeutilization.go:149] allPods:9, nonRemovablePods:9, bePods:0, bPods:0, gPods:0
I0505 11:55:07.768141       1 lownodeutilization.go:144] Node "ip-10-4-36-223.eu-west-1.compute.internal" is over utilized with usage: api.ResourceThresholds{"cpu":48.75, "memory":61.05259502942694, "pods":30}
I0505 11:55:07.768156       1 lownodeutilization.go:149] allPods:33, nonRemovablePods:12, bePods:1, bPods:19, gPods:1
I0505 11:55:07.768376       1 lownodeutilization.go:144] Node "ip-10-4-41-14.eu-west-1.compute.internal" is over utilized with usage: api.ResourceThresholds{"cpu":39.125, "memory":98.19259268881142, "pods":33.63636363636363}
I0505 11:55:07.768390       1 lownodeutilization.go:149] allPods:37, nonRemovablePods:8, bePods:0, bPods:29, gPods:0
I0505 11:55:07.768538       1 lownodeutilization.go:147] Node "ip-10-4-34-29.eu-west-1.compute.internal" is appropriately utilized with usage: api.ResourceThresholds{"memory":43.19826999287199, "pods":30.90909090909091, "cpu":35.25}
I0505 11:55:07.768552       1 lownodeutilization.go:149] allPods:34, nonRemovablePods:11, bePods:8, bPods:15, gPods:0
I0505 11:55:07.768556       1 lownodeutilization.go:65] Criteria for a node under utilization: CPU: 20, Mem: 20, Pods: 20
I0505 11:55:07.768571       1 lownodeutilization.go:69] No node is underutilized, nothing to do here, you might tune your thersholds further
I0505 11:55:07.768576       1 pod_antiaffinity.go:45] Processing node: "ip-10-4-63-172.eu-west-1.compute.internal"
I0505 11:55:07.779313       1 pod_antiaffinity.go:45] Processing node: "ip-10-4-36-223.eu-west-1.compute.internal"
I0505 11:55:07.796766       1 pod_antiaffinity.go:45] Processing node: "ip-10-4-41-14.eu-west-1.compute.internal"
I0505 11:55:07.813303       1 pod_antiaffinity.go:45] Processing node: "ip-10-4-34-29.eu-west-1.compute.internal"
I0505 11:55:07.829109       1 node_affinity.go:40] Executing for nodeAffinityType: requiredDuringSchedulingIgnoredDuringExecution
I0505 11:55:07.829133       1 node_affinity.go:45] Processing node: "ip-10-4-63-172.eu-west-1.compute.internal"
I0505 11:55:07.840416       1 node_affinity.go:45] Processing node: "ip-10-4-36-223.eu-west-1.compute.internal"
I0505 11:55:07.856735       1 node_affinity.go:45] Processing node: "ip-10-4-41-14.eu-west-1.compute.internal"
I0505 11:55:07.945566       1 request.go:480] Throttling request took 88.738917ms, request: GET:https://100.64.0.1:443/api/v1/pods?fieldSelector=spec.nodeName%3Dip-10-4-41-14.eu-west-1.compute.internal%2Cstatus.phase%21%3DFailed%2Cstatus.phase%21%3DSucceeded
I0505 11:55:07.972702       1 node_affinity.go:45] Processing node: "ip-10-4-34-29.eu-west-1.compute.internal"
I0505 11:55:08.145559       1 request.go:480] Throttling request took 172.751657ms, request: GET:https://100.64.0.1:443/api/v1/pods?fieldSelector=spec.nodeName%3Dip-10-4-34-29.eu-west-1.compute.internal%2Cstatus.phase%21%3DFailed%2Cstatus.phase%21%3DSucceeded
I0505 11:55:08.160964       1 node_affinity.go:72] Evicted 0 pods

哇哦，现在你的集群中已经运行了一个 descheduler！

总结

Kubernetes 的默认调度器已经做的很好，但由于集群处于不断变化的状态中，某些 Pod 可能运行在错误的节点上，或者你想要均衡集群资源的分配，这时候就需要 descheduler 来帮助你将某些节点上的 Pod 驱逐到正确的节点上去。我很期待正式版的发布！

参考文档:

Meet a Kubernetes Descheduler

查看全文

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原文地址：https://www.cnblogs.com/evenchen/p/12107248.html