* Update localization guidelines for language labels
Continuing work
Continuing work
Continuing work
More work in progress
Add local OWNERS folders
Add an OWNERS file to Chinese
Remove shortcode for repos
Add Japanese
Alphabetize languages, change weights accordingly
More updates
Add Korean in Korean
Add English to languageName
Feedback from gochist
Move Chinese content from cn/ to zh/
Move OWNERS from cn/ to zh/
Resolve merge conflicts by updating from master
Add files back in to prep for resolution
After rebase on upstream/master, remove files
Review and update localization guidelines
Feedback from gochist, tnir, cstoku
Add a trailing newline to content/ja/OWNERS
Add a trailing newline to content/zh/OWNERS
Drop requirement for GH repo project
Clarify language about forks/branches
Edits and typos
Remove a shortcode specific to a multi-repo language setup
Update aliases and owners
Add explicit OWNERS for content/en
Migrate content from Chinese repo, update regex in config.toml
Remove untranslated strings
Add trailing newline to content/en/OWNERS
Add trailing newlines to OWNERS files
add Jaguar project description (#10433)
* add Jaguar project description
[Jaguar](https://gitlab.com/sdnlab/jaguar) is an open source solution for Kubernetes's network based on OpenDaylight.
Jaguar provides overlay network using vxlan and Jaguar CNIPlugin provides one IP address per pod.
* Minor newline tweak
blog post for azure vmss (#10538)
Add microk8s to pick-right-solution.md (#10542)
* Add microk8s to pick-right-solution.md
Microk8s is a single-command installation of upstream Kubernetes on any Linux and should be included in the list of local-machine solutions.
* capitalized Istio
Add microk8s to foundational.md (#10543)
* Add microk8s to foundational.md
Adding microk8s as credible and stable alternative to get started with Kubernetes on a local machine. This is especially attractive for those not wanting to incur the overhead of running a VM for a local cluster.
* Update foundational.md
Thank you for your suggestions! LMK if this works now?
* Rewrote first paragraph
And included a bullet list of features of microk8s
* Copyedit
fix typo (#10545)
Fix the kubectl subcommands links. (#10550)
Signed-off-by: William Zhang <warmchang@outlook.com>
Fix command issue (#10515)
Signed-off-by: mooncake <xcoder@tenxcloud.com>
remove imported community files per issue 10184 (#10501)
networking.md: Markdown fix (#10498)
Fix front matter, federation command-line tools (#10500)
Clean up glossary entry (#10399)
update slack link (#10536)
typo in StatefulSet docs (#10558)
fix discription about horizontal pod autoscale (#10557)
Remove redundant symbols (#10556)
Fix issue #10520 (#10554)
Signed-off-by: William Zhang <warmchang@outlook.com>
Update api-concepts.md (#10534)
Revert "Fix command issue (#10515)"
This reverts commit c02a7fb9f9.
Update memory-constraint-namespace.md (#10530)
update memory request to 100MiB corresponding the yaml content
Blog: Introducing Volume Snapshot Alpha for Kubernetes (#10562)
* blog post for azure vmss
* snapshot blog post
Resolve merge conflicts in OWNERS*
Minor typo fix (#10567)
Not sure what's supposed to be here, proposing removing it.
* Feedback from gochist
Tweaks to feedback
* Feedback from ClaudiaJKang
14 KiB
approvers, title, redirect_from, content_template
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应用资源配额和限额 |
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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, ResourceQuota 和 LimitRange。
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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 cpu 和 memory 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 cpu 和 memory 指定 requests 或 limits。
因此,我们来为 pod 指定它可以使用的 cpu 和 memory 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 limits,best-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。
除 BestEffort 和 NotBestEffort 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.activeDeadlineSeconds 为 nil 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。
{{% /capture %}}
{{% capture discussion %}}
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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