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应用资源配额和限额
/docs/admin/resourcequota/walkthrough/
/docs/admin/resourcequota/walkthrough.html
/docs/tasks/configure-pod-container/apply-resource-quota-limit/
/docs/tasks/configure-pod-container/apply-resource-quota-limit.html
templates/task

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本示例展示了在一个 namespace 中控制资源用量的典型设置。

本文展示了以下资源的使用: Namespace, ResourceQuotaLimitRange

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  • {{< include "task-tutorial-prereqs.md" >}} {{< version-check >}}

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场景

集群管理员正在操作一个代表用户群体的集群,他希望控制一个特定 namespace 中可以被使用的资源总量,以达到促进对集群的公平共享及控制成本的目的。

集群管理员有以下目标:

  • 限制运行中 pods 使用的计算资源数量
  • 限制 persistent volume claims 数量以控制对存储的访问
  • 限制 load balancers 数量以控制成本
  • 防止使用 node ports 以保留稀缺资源
  • 提供默认计算资源请求以实现更好的调度决策

创建 namespace

本示例将在一个自定义的 namespace 中运行,以展示相关概念。

让我们创建一个叫做 quota-example 的新 namespace

$ kubectl create namespace quota-example
namespace "quota-example" created
$ kubectl get namespaces
NAME            STATUS    AGE
default         Active    2m
kube-system     Active    2m
quota-example   Active    39s

应用 object-count 配额到 namespace

集群管理员想要控制下列资源:

  • persistent volume claims
  • load balancers
  • node ports

我们来创建一个简单的配额,用于控制这个 namespace 中那些资源类型的对象数量。

$ kubectl create -f https://k8s.io/docs/tasks/configure-pod-container/rq-object-counts.yaml --namespace=quota-example
resourcequota "object-counts" created

配额系统将察觉到有一个配额被创建,并且会计算 namespace 中的资源消耗量作为响应。这应该会很快发生。

让我们显示一下配额来观察这个 namespace 中当前被消耗的资源:

$ kubectl describe quota object-counts --namespace=quota-example
Name:                  object-counts
Namespace:             quota-example
Resource               Used    Hard
--------               ----    ----
persistentvolumeclaims 0    2
services.loadbalancers 0    2
services.nodeports     0    0

配额系统现在将阻止用户创建比各个资源指定数量更多的资源。

应用计算资源配额到 namespace

为了限制这个 namespace 可以被使用的计算资源数量,让我们创建一个跟踪计算资源的配额。

$ kubectl create -f https://k8s.io/docs/tasks/configure-pod-container/rq-compute-resources.yaml --namespace=quota-example
resourcequota "compute-resources" created

让我们显示一下配额来观察这个 namespace 中当前被消耗的资源:

$ kubectl describe quota compute-resources --namespace=quota-example
Name:                  compute-resources
Namespace:             quota-example
Resource               Used Hard
--------               ---- ----
limits.cpu             0    2
limits.memory          0    2Gi
pods                   0    4
requests.cpu           0    1
requests.memory        0    1Gi

配额系统现在会防止 namespace 拥有超过 4 个没有终止的 pods。此外它还将强制 pod 中的每个容器配置一个 request 并为 cpumemory 定义 limit

应用默认资源请求和限制

Pod 的作者很少为它们的 pods 指定资源请求和限制。

既然我们对项目应用了配额,我们来看一下当终端用户通过创建一个没有 cpu 和 内存限制的 pod 时会发生什么。这通过在 pod 里创建一个 nginx 容器实现。

作为演示,让我们来创建一个运行 nginx 的 deployment

$ kubectl run nginx --image=nginx --replicas=1 --namespace=quota-example
deployment "nginx" created

现在我们来看一下创建的 pods。

$ kubectl get pods --namespace=quota-example

发生了什么?我一个 pods 都没有!让我们 describe 这个 deployment 来看看发生了什么。

$ kubectl describe deployment nginx --namespace=quota-example
Name:                   nginx
Namespace:              quota-example
CreationTimestamp:      Mon, 06 Jun 2016 16:11:37 -0400
Labels:                 run=nginx
Selector:               run=nginx
Replicas:               0 updated | 1 total | 0 available | 1 unavailable
StrategyType:           RollingUpdate
MinReadySeconds:        0
RollingUpdateStrategy:  1 max unavailable, 1 max surge
OldReplicaSets:         <none>
NewReplicaSet:          nginx-3137573019 (0/1 replicas created)
...

Deployment 创建了一个对应的 replica set 并尝试按照大小来创建一个 pod。

让我们看看 replica set 的更多细节。

$ kubectl describe rs nginx-3137573019 --namespace=quota-example
Name:                   nginx-3137573019
Namespace:              quota-example
Image(s):               nginx
Selector:               pod-template-hash=3137573019,run=nginx
Labels:                 pod-template-hash=3137573019
                        run=nginx
Replicas:               0 current / 1 desired
Pods Status:            0 Running / 0 Waiting / 0 Succeeded / 0 Failed
No volumes.
Events:
  FirstSeen    LastSeen    Count From                    SubobjectPath Type      Reason        Message
  ---------    --------  ----- ----                    -------------    --------  ------        -------
  4m        7s        11    {replicaset-controller }              Warning   FailedCreate  Error creating: pods "nginx-3137573019-" is forbidden: Failed quota: compute-resources: must specify limits.cpu,limits.memory,requests.cpu,requests.memory

Kubernetes API server 拒绝了 replica set 创建一个 pod 的请求,因为我们的 pods 没有为 cpumemory 指定 requestslimits

因此,我们来为 pod 指定它可以使用的 cpumemory 默认数量。

$ kubectl create -f https://k8s.io/docs/tasks/configure-pod-container/rq-limits.yaml --namespace=quota-example
limitrange "limits" created
$ kubectl describe limits limits --namespace=quota-example
Name:           limits
Namespace:      quota-example
Type      Resource  Min  Max  Default Request   Default Limit   Max Limit/Request Ratio
----      --------  ---  ---  ---------------   -------------   -----------------------
Container memory    -    -    256Mi             512Mi           -
Container cpu       -    -    100m              200m            -

如果 Kubernetes API server 发现一个 namespace 中有一个创建 pod 的请求,并且 pod 中的容器没有设置任何计算资源请求时,作为准入控制的一部分,一个默认的 request 和 limit 将会被应用。

在本例中,创建的每个 pod 都将拥有如下的计算资源限制:

$ kubectl run nginx \
  --image=nginx \
  --replicas=1 \
  --requests=cpu=100m,memory=256Mi \
  --limits=cpu=200m,memory=512Mi \
  --namespace=quota-example

由于已经为我们的 namespace 申请了默认的计算资源,我们的 replica set 应该能够创建它的 pods 了。

$ kubectl get pods --namespace=quota-example
NAME                     READY     STATUS    RESTARTS   AGE
nginx-3137573019-fvrig   1/1       Running   0          6m

而且如果打印出我们在这个 namespace 中的配额使用情况:

$ kubectl describe quota --namespace=quota-example
Name:           compute-resources
Namespace:      quota-example
Resource        Used    Hard
--------        ----    ----
limits.cpu      200m    2
limits.memory   512Mi   2Gi
pods            1       4
requests.cpu    100m    1
requests.memory 256Mi   1Gi


Name:                 object-counts
Namespace:            quota-example
Resource              Used    Hard
--------              ----    ----
persistentvolumeclaims 0      2
services.loadbalancers 0      2
services.nodeports     0      0

就像你看到的,创建的 pod 消耗了明确的计算资源量,并且正被 Kubernetes 正确的追踪着。

高级配额 scopes

让我们想象一下如果你不希望为你的 namespace 指定默认计算资源使用量。

作为替换,你希望用户在它们的 namespace 中运行指定数量的 BestEffort pods,以从宽松的计算资源中获得好处。然后要求用户为需要更高质量服务的 pods 配置一个显式的资源请求。

让我们新建一个拥有两个配额的 namespace 来演示这种行为:

$ kubectl create namespace quota-scopes
namespace "quota-scopes" created
$ kubectl create -f https://k8s.io/docs/tasks/configure-pod-container/rq-best-effort.yaml --namespace=quota-scopes
resourcequota "best-effort" created
$ kubectl create -f https://k8s.io/docs/tasks/configure-pod-container/rq-not-best-effort.yaml --namespace=quota-scopes
resourcequota "not-best-effort" created
$ kubectl describe quota --namespace=quota-scopes
Name:       best-effort
Namespace:  quota-scopes
Scopes:     BestEffort
 * Matches all pods that have best effort quality of service.
Resource    Used    Hard
--------    ----  ----
pods        0     10


Name:             not-best-effort
Namespace:        quota-scopes
Scopes:           NotBestEffort
 * Matches all pods that do not have best effort quality of service.
Resource          Used  Hard
--------          ----  ----
limits.cpu        0     2
limits.memory     0     2Gi
pods              0     4
requests.cpu      0     1
requests.memory   0     1Gi

在这种场景下,一个没有配置计算资源请求的 pod 将会被 best-effort 配额跟踪。

而配置了计算资源请求的则会被 not-best-effort 配额追踪。

让我们创建两个 deployments 作为演示:

$ kubectl run best-effort-nginx --image=nginx --replicas=8 --namespace=quota-scopes
deployment "best-effort-nginx" created
$ kubectl run not-best-effort-nginx \
  --image=nginx \
  --replicas=2 \
  --requests=cpu=100m,memory=256Mi \
  --limits=cpu=200m,memory=512Mi \
  --namespace=quota-scopes
deployment "not-best-effort-nginx" created

虽然没有指定默认的 limitsbest-effort-nginx deployment 还是会创建 8 个 pods。这是由于它被 best-effort 配额追踪,而 not-best-effort 配额将忽略它。not-best-effort 配额将追踪 not-best-effort-nginx deployment,因为它创建的 pods 具有 Burstable 服务质量。

让我们列出 namespace 中的 pods

$ kubectl get pods --namespace=quota-scopes
NAME                                     READY     STATUS    RESTARTS   AGE
best-effort-nginx-3488455095-2qb41       1/1       Running   0          51s
best-effort-nginx-3488455095-3go7n       1/1       Running   0          51s
best-effort-nginx-3488455095-9o2xg       1/1       Running   0          51s
best-effort-nginx-3488455095-eyg40       1/1       Running   0          51s
best-effort-nginx-3488455095-gcs3v       1/1       Running   0          51s
best-effort-nginx-3488455095-rq8p1       1/1       Running   0          51s
best-effort-nginx-3488455095-udhhd       1/1       Running   0          51s
best-effort-nginx-3488455095-zmk12       1/1       Running   0          51s
not-best-effort-nginx-2204666826-7sl61   1/1       Running   0          23s
not-best-effort-nginx-2204666826-ke746   1/1       Running   0          23s

如你看到的,所有 10 个 pods 都已经被准许创建。

让我们 describe 这个 namespace 当前的配额使用情况:

$ kubectl describe quota --namespace=quota-scopes
Name:            best-effort
Namespace:       quota-scopes
Scopes:          BestEffort
 * Matches all pods that have best effort quality of service.
Resource         Used  Hard
--------         ----  ----
pods             8     10


Name:               not-best-effort
Namespace:          quota-scopes
Scopes:             NotBestEffort
 * Matches all pods that do not have best effort quality of service.
Resource            Used  Hard
--------            ----  ----
limits.cpu          400m  2
limits.memory       1Gi   2Gi
pods                2     4
requests.cpu        200m  1
requests.memory     512Mi 1Gi

如你看到的,best-effort 配额追踪了我们在 best-effort-nginx deployment 中创建的 8 个 pods 的资源用量,而 not-best-effort 配额追踪了我们在 not-best-effort-nginx deployment 中创的两个 pods 的用量。

Scopes 提供了一种来对任何配额文档追踪的资源集合进行细分的机制,给操作人员部署和追踪资源消耗带来更大的灵活性。

BestEffortNotBestEffort scopes 之外,还有用于限制长时间运行和有时限 pods 的scopes。Terminating scope 将匹配任何 spec.activeDeadlineSeconds 不为 nil 的 pod。NotTerminating scope 将匹配任何 spec.activeDeadlineSecondsnil 的 pod。这些 scopes 允许你基于 pods 在你集群中 node 上的预期持久程度来为它们指定配额。

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总结

消耗节点 cpu 和 memory 资源的动作受到 namespace 配额定义的硬性配额限制的管制。

任意消耗那些资源的动作能够被调整,或者获得一个 namespace 级别的默认值以符合你最终的目标。

可以基于服务质量或者在你集群中节点上的预期持久程度来分配配额。

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