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:
$ 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
- LowNodeUtilization
- RemovePodsViolatingInterPodAntiAffinity
- RemovePodsViolatingNodeAffinity
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-suystem
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:
$ 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:v0.5.0-4-ga7ceb671
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
该 CroJob 每 30 分钟运行一次,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!