[zh] sync horizontal-pod-autoscale-walkthrough.md
0xff-dev
parent
fea06301e4
commit
ad638a8092
|
|
@ -1,7 +1,8 @@
|
|||
---
|
||||
title: Horizontal Pod Autoscaler 演练
|
||||
title: HorizontalPodAutoscaler 演练
|
||||
content_type: task
|
||||
weight: 100
|
||||
min-kubernetes-server-version: 1.23
|
||||
---
|
||||
|
||||
<!--
|
||||
|
|
@ -18,84 +19,106 @@ weight: 100
|
|||
<!-- overview -->
|
||||
|
||||
<!--
|
||||
Horizontal Pod Autoscaler automatically scales the number of pods
|
||||
in a replication controller, deployment or replica set or statefulset based on observed CPU utilization
|
||||
(or, with beta support, on some other, application-provided metrics).
|
||||
A [HorizontalPodAutoscaler](/docs/tasks/run-application/horizontal-pod-autoscale/)
|
||||
(HPA for short)
|
||||
automatically updates a workload resource (such as
|
||||
a {{< glossary_tooltip text="Deployment" term_id="deployment" >}} or
|
||||
{{< glossary_tooltip text="StatefulSet" term_id="statefulset" >}}), with the
|
||||
aim of automatically scaling the workload to match demand.
|
||||
|
||||
Horizontal scaling means that the response to increased load is to deploy more
|
||||
{{< glossary_tooltip text="Pods" term_id="pod" >}}.
|
||||
This is different from _vertical_ scaling, which for Kubernetes would mean
|
||||
assigning more resources (for example: memory or CPU) to the Pods that are already
|
||||
running for the workload.
|
||||
-->
|
||||
Horizontal Pod Autoscaler 可以根据 CPU 利用率自动扩缩 ReplicationController、
|
||||
Deployment、ReplicaSet 或 StatefulSet 中的 Pod 数量
|
||||
（也可以基于其他应用程序提供的度量指标，目前这一功能处于 beta 版本）。
|
||||
[HorizontalPodAutoscaler](/zh/docs/tasks/run-application/horizontal-pod-autoscale/) （简称 HPA ）
|
||||
自动更新工作负载资源（例如 {{< glossary_tooltip text="Deployment" term_id="deployment" >}} 或者
|
||||
{{< glossary_tooltip text="StatefulSet" term_id="statefulset" >}}），
|
||||
目的是自动扩缩工作负载以满足需求。
|
||||
|
||||
水平扩缩意味着对增加的负载的响应是部署更多的 {{< glossary_tooltip text="Pods" term_id="pod" >}}。
|
||||
这与 “垂直（Vertical）” 扩缩不同，对于 Kubernetes，
|
||||
垂直扩缩意味着将更多资源（例如：内存或 CPU）分配给已经为工作负载运行的 Pod。
|
||||
|
||||
<!--
|
||||
This document walks you through an example of enabling Horizontal Pod Autoscaler for the php-apache server.
|
||||
For more information on how Horizontal Pod Autoscaler behaves, see the
|
||||
[Horizontal Pod Autoscaler user guide](/docs/tasks/run-application/horizontal-pod-autoscale/).
|
||||
If the load decreases, and the number of Pods is above the configured minimum,
|
||||
the HorizontalPodAutoscaler instructs the workload resource (the Deployment, StatefulSet,
|
||||
or other similar resource) to scale back down.
|
||||
|
||||
This document walks you through an example of enabling HorizontalPodAutoscaler to
|
||||
automatically manage scale for an example web app. This example workload is Apache
|
||||
httpd running some PHP code.
|
||||
-->
|
||||
本文将引领你了解如何为 php-apache 服务器配置和使用 Horizontal Pod Autoscaler。
|
||||
与 Horizontal Pod Autoscaler 相关的更多信息请参阅
|
||||
[Horizontal Pod Autoscaler 用户指南](/zh/docs/tasks/run-application/horizontal-pod-autoscale/)。
|
||||
如果负载减少，并且 Pod 的数量高于配置的最小值，
|
||||
HorizontalPodAutoscaler 会指示工作负载资源（ Deployment、StatefulSet 或其他类似资源）缩减。
|
||||
|
||||
本文档将引导你完成启用 HorizontalPodAutoscaler 以自动管理示例 Web 应用程序的扩缩的示例。
|
||||
此示例工作负载是运行一些 PHP 代码的 Apache httpd。
|
||||
|
||||
## {{% heading "prerequisites" %}}
|
||||
|
||||
<!--
|
||||
This example requires a running Kubernetes cluster and kubectl, version 1.2 or later.
|
||||
[metrics-server](https://github.com/kubernetes-incubator/metrics-server/) monitoring needs to be deployed
|
||||
in the cluster to provide metrics through the [Metrics API](https://github.com/kubernetes/metrics).
|
||||
Horizontal Pod Autoscaler uses this API to collect metrics. To learn how to deploy the metrics-server,
|
||||
see the [metrics-server documentation](https://github.com/kubernetes-sigs/metrics-server#deployment).
|
||||
-->
|
||||
本文示例需要一个运行中的 Kubernetes 集群以及 kubectl，版本为 1.2 或更高。
|
||||
[Metrics 服务器](https://github.com/kubernetes-incubator/metrics-server/)
|
||||
需要被部署到集群中，以便通过 [Metrics API](https://github.com/kubernetes/metrics)
|
||||
提供度量数据。
|
||||
Horizontal Pod Autoscaler 根据此 API 来获取度量数据。
|
||||
要了解如何部署 metrics-server，请参考
|
||||
[metrics-server 文档](https://github.com/kubernetes-incubator/metrics-server/) 。
|
||||
{{< include "task-tutorial-prereqs.md" >}} {{< version-check >}}
|
||||
|
||||
<!--
|
||||
To specify multiple resource metrics for a Horizontal Pod Autoscaler, you must have a
|
||||
Kubernetes cluster and kubectl at version 1.6 or later. To make use of custom metrics, your cluster
|
||||
must be able to communicate with the API server providing the custom metrics API.
|
||||
Finally, to use metrics not related to any Kubernetes object you must have a
|
||||
Kubernetes cluster at version 1.10 or later, and you must be able to communicate with
|
||||
the API server that provides the external metrics API.
|
||||
See the [Horizontal Pod Autoscaler user guide](/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-custom-metrics) for more details.
|
||||
If you're running an older
|
||||
release of Kubernetes, refer to the version of the documentation for that release (see
|
||||
[available documentation versions](/docs/home/supported-doc-versions/)).
|
||||
-->
|
||||
如果需要为 Horizontal Pod Autoscaler 指定多种资源度量指标，你的 Kubernetes
|
||||
集群以及 kubectl 至少需要达到 1.6 版本。
|
||||
此外，如果要使用自定义度量指标，你的 Kubernetes 集群还必须能够与提供这些自定义指标
|
||||
的 API 服务器通信。
|
||||
最后，如果要使用与 Kubernetes 对象无关的度量指标，则 Kubernetes 集群版本至少需要
|
||||
达到 1.10 版本，同样，需要保证集群能够与提供这些外部指标的 API 服务器通信。
|
||||
更多详细信息，请参阅
|
||||
[Horizontal Pod Autoscaler 用户指南](/zh/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-custom-metrics)。
|
||||
如果你运行的是旧版本的 Kubernetes，请参阅该版本的文档版本
|
||||
（[可用的文档版本](/zh/docs/home/supported-doc-versions/)）。
|
||||
|
||||
<!--
|
||||
To follow this walkthrough, you also need to use a cluster that has a
|
||||
[Metrics Server](https://github.com/kubernetes-sigs/metrics-server#readme) deployed and configured.
|
||||
The Kubernetes Metrics Server collects resource metrics from
|
||||
the {{<glossary_tooltip term_id="kubelet" text="kubelets">}} in your cluster, and exposes those metrics
|
||||
through the [Kubernetes API](/docs/concepts/overview/kubernetes-api/),
|
||||
using an [APIService](/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/) to add
|
||||
new kinds of resource that represent metric readings.
|
||||
|
||||
To learn how to deploy the Metrics Server, see the
|
||||
[metrics-server documentation](https://github.com/kubernetes-sigs/metrics-server#deployment).
|
||||
-->
|
||||
按照本演练进行操作，你需要一个部署并配置了
|
||||
[Metrics Server](https://github.com/kubernetes-sigs/metrics-server#readme) 的集群。
|
||||
Kubernetes Metrics Server 从集群中的 {{<glossary_tooltip term_id="kubelet" text="kubelets">}} 收集资源指标，
|
||||
并通过 [Kubernetes API](/zh/docs/concepts/overview/kubernetes-api/) 公开这些指标，
|
||||
使用 [APIService](/zh/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/) 添加代表指标读数的新资源。
|
||||
|
||||
要了解如何部署 Metrics Server，请参阅
|
||||
[metrics-server 文档](https://github.com/kubernetes-sigs/metrics-server#deployment)。
|
||||
|
||||
<!-- steps -->
|
||||
|
||||
<!--
|
||||
## Run & expose php-apache server
|
||||
## Run and expose php-apache server
|
||||
-->
|
||||
## 运行 php-apache 服务器并暴露服务
|
||||
## 运行 php-apache 服务器并暴露服务 {#run-and-expose-php-apache-server}
|
||||
|
||||
<!--
|
||||
To demonstrate Horizontal Pod Autoscaler we will use a custom docker image based on the php-apache image.
|
||||
The Dockerfile has the following content:
|
||||
To demonstrate a HorizontalPodAutoscaler, you will first make a custom container image that uses
|
||||
the `php-apache` image from Docker Hub as its starting point. The `Dockerfile` is ready-made for you,
|
||||
and has the following content:
|
||||
-->
|
||||
为了演示 Horizontal Pod Autoscaler，我们将使用一个基于 php-apache 镜像的
|
||||
定制 Docker 镜像。Dockerfile 内容如下：
|
||||
为了演示 HorizontalPodAutoscaler，你将首先制作一个自定义容器镜像，
|
||||
该镜像使用来自 Docker Hub 的 `php-apache` 镜像作为其起点。
|
||||
`Dockerfile` 已经为你准备好了，内容如下：
|
||||
|
||||
```
|
||||
```dockerfile
|
||||
FROM php:5-apache
|
||||
COPY index.php /var/www/html/index.php
|
||||
RUN chmod a+rx index.php
|
||||
```
|
||||
|
||||
<!--
|
||||
It defines an index.php page which performs some CPU intensive computations:
|
||||
This code defines a simple `index.php` page that performs some CPU intensive computations,
|
||||
in order to simulate load in your cluster.
|
||||
-->
|
||||
该文件定义了一个 index.php 页面来执行一些 CPU 密集型计算：
|
||||
代码定义了一个简单的 `index.php` 页面，该页面执行一些 CPU 密集型计算，
|
||||
以模拟集群中的负载。
|
||||
|
||||
```
|
||||
```php
|
||||
<?php
|
||||
$x = 0.0001;
|
||||
for ($i = 0; $i <= 1000000; $i++) {
|
||||
|
|
@ -106,17 +129,19 @@ It defines an index.php page which performs some CPU intensive computations:
|
|||
```
|
||||
|
||||
<!--
|
||||
First, we will start a deployment running the image and expose it as a service
|
||||
using the following configuration:
|
||||
Once you have made that container image, start a Deployment that runs a container using the
|
||||
image you made, and expose it as a {{< glossary_tooltip term_id="service">}}
|
||||
using the following manifest:
|
||||
-->
|
||||
首先，我们使用下面的配置启动一个 Deployment 来运行这个镜像并暴露一个服务：
|
||||
制作完该容器镜像后，使用你制作的镜像启动运行一个容器的 Deployment，
|
||||
并使用以下清单将其公开为{{< glossary_tooltip term_id="service" text="服务" >}}：
|
||||
|
||||
{{< codenew file="application/php-apache.yaml" >}}
|
||||
|
||||
<!--
|
||||
Run the following command:
|
||||
To do so, run the following command:
|
||||
-->
|
||||
运行下面的命令：
|
||||
为此，运行下面的命令：
|
||||
|
||||
```shell
|
||||
kubectl apply -f https://k8s.io/examples/application/php-apache.yaml
|
||||
|
|
@ -128,28 +153,46 @@ service/php-apache created
|
|||
```
|
||||
|
||||
<!--
|
||||
## Create Horizontal Pod Autoscaler
|
||||
## Create the HorizontalPodAutoscaler {#create-horizontal-pod-autoscaler}
|
||||
|
||||
Now that the server is running, create the autoscaler using `kubectl`. There is
|
||||
[`kubectl autoscale`](/docs/reference/generated/kubectl/kubectl-commands#autoscale) subcommand,
|
||||
part of `kubectl`, that helps you do this.
|
||||
|
||||
You will shortly run a command that creates a HorizontalPodAutoscaler that maintains
|
||||
between 1 and 10 replicas of the Pods controlled by the php-apache Deployment that
|
||||
you created in the first step of these instructions.
|
||||
|
||||
Roughly speaking, the HPA {{<glossary_tooltip text="controller" term_id="controller">}} will increase and decrease
|
||||
the number of replicas (by updating the Deployment) to maintain an average CPU utilization across all Pods of 50%.
|
||||
The Deployment then updates the ReplicaSet - this is part of how all Deployments work in Kubernetes -
|
||||
and then the ReplicaSet either adds or removes Pods based on the change to its `.spec`.
|
||||
|
||||
Now that the server is running, we will create the autoscaler using
|
||||
[kubectl autoscale](/docs/reference/generated/kubectl/kubectl-commands#autoscale).
|
||||
The following command will create a Horizontal Pod Autoscaler that maintains between 1 and 10 replicas of the Pods
|
||||
controlled by the php-apache deployment we created in the first step of these instructions.
|
||||
Roughly speaking, HPA will increase and decrease the number of replicas
|
||||
(via the deployment) to maintain an average CPU utilization across all Pods of 50%.
|
||||
Since each pod requests 200 milli-cores by `kubectl run`, this means an average CPU usage of 100 milli-cores.
|
||||
See [here](/docs/tasks/run-application/horizontal-pod-autoscale/#algorithm-details) for more details on the algorithm.
|
||||
See [Algorithm details](/docs/tasks/run-application/horizontal-pod-autoscale/#algorithm-details) for more details
|
||||
on the algorithm.
|
||||
-->
|
||||
## 创建 Horizontal Pod Autoscaler {#create-horizontal-pod-autoscaler}
|
||||
## 创建 HorizontalPodAutoscaler {#create-horizontal-pod-autoscaler}
|
||||
|
||||
现在，php-apache 服务器已经运行，我们将通过
|
||||
[kubectl autoscale](/docs/reference/generated/kubectl/kubectl-commands#autoscale)
|
||||
命令创建 Horizontal Pod Autoscaler。
|
||||
以下命令将创建一个 Horizontal Pod Autoscaler 用于控制我们上一步骤中创建的
|
||||
Deployment，使 Pod 的副本数量维持在 1 到 10 之间。
|
||||
大致来说，HPA 将（通过 Deployment）增加或者减少 Pod 副本的数量以保持所有 Pod
|
||||
的平均 CPU 利用率在 50% 左右。由于每个 Pod 请求 200 毫核的 CPU，这意味着平均
|
||||
CPU 用量为 100 毫核。
|
||||
算法的详情请参阅[相关文档](/zh/docs/tasks/run-application/horizontal-pod-autoscale/#algorithm-details)。
|
||||
现在服务器正在运行，使用 `kubectl` 创建自动扩缩器。
|
||||
[`kubectl autoscale`](/zh/docs/reference/generated/kubectl/kubectl-commands#autoscale) 子命令是 `kubectl` 的一部分，
|
||||
可以帮助你执行此操作。
|
||||
|
||||
你将很快运行一个创建 HorizontalPodAutoscaler 的命令，
|
||||
该 HorizontalPodAutoscaler 维护由你在这些说明的第一步中创建的 php-apache Deployment 控制的 Pod 存在 1 到 10 个副本。
|
||||
|
||||
粗略地说，HPA {{<glossary_tooltip text="控制器" term_id="controller">}}将增加和减少副本的数量
|
||||
（通过更新 Deployment）以保持所有 Pod 的平均 CPU 利用率为 50%。
|
||||
Deployment 然后更新 ReplicaSet —— 这是所有 Deployment 在 Kubernetes 中工作方式的一部分 ——
|
||||
然后 ReplicaSet 根据其 `.spec` 的更改添加或删除 Pod。
|
||||
|
||||
由于每个 Pod 通过 `kubectl run` 请求 200 milli-cores，这意味着平均 CPU 使用率为 100 milli-cores。
|
||||
有关算法的更多详细信息，
|
||||
请参阅[算法详细信息](/zh/docs/tasks/run-application/horizontal-pod-autoscale/#algorithm-details)。
|
||||
|
||||
|
||||
<!-- Create the HorizontalPodAutoscaler: -->
|
||||
创建 HorizontalPodAutoscaler：
|
||||
|
||||
```shell
|
||||
kubectl autoscale deployment php-apache --cpu-percent=50 --min=1 --max=10
|
||||
|
|
@ -160,14 +203,19 @@ horizontalpodautoscaler.autoscaling/php-apache autoscaled
|
|||
```
|
||||
|
||||
<!--
|
||||
We may check the current status of autoscaler by running:
|
||||
You can check the current status of the newly-made HorizontalPodAutoscaler, by running:
|
||||
-->
|
||||
我们可以通过以下命令查看 Autoscaler 的状态：
|
||||
你可以通过运行以下命令检查新制作的 HorizontalPodAutoscaler 的当前状态：
|
||||
|
||||
<!--# You can use "hpa" or "horizontalpodautoscaler"; either name works OK. -->
|
||||
```shell
|
||||
# 你可以使用 “hap” 或 “horizontalpodautoscaler”；任何一个名字都可以。
|
||||
kubectl get hpa
|
||||
```
|
||||
|
||||
<!-- The output is similar to: -->
|
||||
输出类似于：
|
||||
|
||||
```
|
||||
NAME REFERENCE TARGET MINPODS MAXPODS REPLICAS AGE
|
||||
php-apache Deployment/php-apache/scale 0% / 50% 1 10 1 18s
|
||||
|
|
@ -175,42 +223,71 @@ php-apache Deployment/php-apache/scale 0% / 50% 1 10 1
|
|||
```
|
||||
|
||||
<!--
|
||||
Please note that the current CPU consumption is 0% as we are not sending any requests to the server
|
||||
(the ``CURRENT`` column shows the average across all the pods controlled by the corresponding deployment).
|
||||
(if you see other HorizontalPodAutoscalers with different names, that means they already existed,
|
||||
and isn't usually a problem).
|
||||
-->
|
||||
请注意当前的 CPU 利用率是 0%，这是由于我们尚未发送任何请求到服务器
|
||||
（``CURRENT`` 列显示了相应 Deployment 所控制的所有 Pod 的平均 CPU 利用率）。
|
||||
（如果你看到其他具有不同名称的 HorizontalPodAutoscalers，这意味着它们已经存在，这通常不是问题）。
|
||||
|
||||
<!--
|
||||
## Increase load
|
||||
Please note that the current CPU consumption is 0% as there are no clients sending requests to the server
|
||||
(the ``TARGET`` column shows the average across all the Pods controlled by the corresponding deployment).
|
||||
-->
|
||||
请注意当前的 CPU 利用率是 0%，这是由于我们尚未发送任何请求到服务器
|
||||
（``TARGET`` 列显示了相应 Deployment 所控制的所有 Pod 的平均 CPU 利用率）。
|
||||
|
||||
Now, we will see how the autoscaler reacts to increased load.
|
||||
We will start a container, and send an infinite loop of queries to the php-apache service (please run it in a different terminal):
|
||||
<!--
|
||||
## Increase the load {#increase-load}
|
||||
|
||||
Next, see how the autoscaler reacts to increased load.
|
||||
To do this, you'll start a different Pod to act as a client. The container within the client Pod
|
||||
runs in an infinite loop, sending queries to the php-apache service.
|
||||
-->
|
||||
## 增加负载 {#increase-load}
|
||||
|
||||
现在，我们将看到 Autoscaler 如何对增加负载作出反应。
|
||||
我们将启动一个容器，并通过一个循环向 php-apache 服务器发送无限的查询请求
|
||||
（请在另一个终端中运行以下命令）：
|
||||
接下来，看看自动扩缩器如何对增加的负载做出反应。
|
||||
为此，你将启动一个不同的 Pod 作为客户端。
|
||||
客户端 Pod 中的容器在无限循环中运行，向 php-apache 服务发送查询。
|
||||
|
||||
<!--
|
||||
# Run this in a separate terminal
|
||||
# so that the load generation continues and you can carry on with the rest of the steps
|
||||
-->
|
||||
```shell
|
||||
kubectl run -i --tty load-generator --rm --image=busybox --restart=Never -- /bin/sh -c "while sleep 0.01; do wget -q -O- http://php-apache; done"
|
||||
# 在单独的终端中运行它
|
||||
# 以便负载生成继续，你可以继续执行其余步骤
|
||||
kubectl run -i --tty load-generator --rm --image=busybox:1.28 --restart=Never -- /bin/sh -c "while sleep 0.01; do wget -q -O- http://php-apache; done"
|
||||
```
|
||||
|
||||
<!--
|
||||
Within a minute or so, we should see the higher CPU load by executing:
|
||||
-->
|
||||
一分钟时间左右之后，通过以下命令，我们可以看到 CPU 负载升高了：
|
||||
Now run:
|
||||
|
||||
Within a minute or so, you should see the higher CPU load; for example:
|
||||
-->
|
||||
现在执行：
|
||||
|
||||
<!-- # type Ctrl+C to end the watch when you're ready -->
|
||||
```shell
|
||||
kubectl get hpa
|
||||
# 准备好后按 Ctrl+C 结束观察
|
||||
kubectl get hpa php-apache --watch
|
||||
```
|
||||
|
||||
一分钟时间左右之后，通过以下命令，我们可以看到 CPU 负载升高了；例如：
|
||||
|
||||
```
|
||||
NAME REFERENCE TARGET MINPODS MAXPODS REPLICAS AGE
|
||||
php-apache Deployment/php-apache/scale 305% / 50% 1 10 1 3m
|
||||
```
|
||||
|
||||
<!--
|
||||
and then, more replicas. For example:
|
||||
-->
|
||||
然后，更多的副本被创建。例如：
|
||||
|
||||
```
|
||||
NAME REFERENCE TARGET MINPODS MAXPODS REPLICAS AGE
|
||||
php-apache Deployment/php-apache/scale 305% / 50% 1 10 7 3m
|
||||
```
|
||||
|
||||
<!--
|
||||
Here, CPU consumption has increased to 305% of the request.
|
||||
As a result, the deployment was resized to 7 replicas:
|
||||
|
|
@ -222,6 +299,11 @@ As a result, the deployment was resized to 7 replicas:
|
|||
kubectl get deployment php-apache
|
||||
```
|
||||
|
||||
<!--
|
||||
You should see the replica count matching the figure from the HorizontalPodAutoscaler
|
||||
-->
|
||||
你应该会看到与 HorizontalPodAutoscaler 中的数字与副本数匹配
|
||||
|
||||
```
|
||||
NAME READY UP-TO-DATE AVAILABLE AGE
|
||||
php-apache 7/7 7 7 19m
|
||||
|
|
@ -238,32 +320,40 @@ will differ from this example.
|
|||
{{< /note >}}
|
||||
|
||||
<!--
|
||||
## Stop load
|
||||
## Stop generating load {#stop-load}
|
||||
|
||||
We will finish our example by stopping the user load.
|
||||
To finish the example, stop sending the load.
|
||||
|
||||
In the terminal where we created the container with `busybox` image, terminate
|
||||
In the terminal where you created the Pod that runs a `busybox` image, terminate
|
||||
the load generation by typing `<Ctrl> + C`.
|
||||
|
||||
Then we will verify the result state (after a minute or so):
|
||||
Then verify the result state (after a minute or so):
|
||||
-->
|
||||
## 停止负载
|
||||
## 停止产生负载 {#stop-load}
|
||||
|
||||
我们将通过停止负载来结束我们的示例。
|
||||
要完成该示例，请停止发送负载。
|
||||
|
||||
在我们创建 busybox 容器的终端中，输入`<Ctrl> + C` 来终止负载的产生。
|
||||
在我们创建 `busybox` 容器的终端中，输入 `<Ctrl> + C` 来终止负载的产生。
|
||||
|
||||
然后我们可以再次检查负载状态（等待几分钟时间）：
|
||||
然后验证结果状态（大约一分钟后）：
|
||||
|
||||
<!-- # type Ctrl+C to end the watch when you're ready -->
|
||||
```shell
|
||||
kubectl get hpa
|
||||
# 准备好后按 Ctrl+C 结束观察
|
||||
kubectl get hpa php-apache --watch
|
||||
```
|
||||
|
||||
<!-- The output is similar to: -->
|
||||
输出类似于：
|
||||
|
||||
```
|
||||
NAME REFERENCE TARGET MINPODS MAXPODS REPLICAS AGE
|
||||
php-apache Deployment/php-apache/scale 0% / 50% 1 10 1 11m
|
||||
```
|
||||
|
||||
<!-- and the Deployment also shows that it has scaled down: -->
|
||||
Deployment 也显示它已经缩小了：
|
||||
|
||||
```shell
|
||||
kubectl get deployment php-apache
|
||||
```
|
||||
|
|
@ -274,16 +364,14 @@ php-apache 1/1 1 1 27m
|
|||
```
|
||||
|
||||
<!--
|
||||
Here CPU utilization dropped to 0, and so HPA autoscaled the number of replicas back down to 1.
|
||||
Once CPU utilization dropped to 0, the HPA automatically scaled the number of replicas back down to 1.
|
||||
-->
|
||||
这时，CPU 利用率已经降到 0，所以 HPA 将自动缩减副本数量至 1。
|
||||
一旦 CPU 利用率降至 0，HPA 会自动将副本数缩减为 1。
|
||||
|
||||
<!--
|
||||
Autoscaling the replicas may take a few minutes.
|
||||
-->
|
||||
{{< note >}}
|
||||
自动扩缩完成副本数量的改变可能需要几分钟的时间。
|
||||
{{< /note >}}
|
||||
|
||||
<!-- discussion -->
|
||||
|
||||
|
|
@ -291,17 +379,17 @@ Autoscaling the replicas may take a few minutes.
|
|||
## Autoscaling on multiple metrics and custom metrics
|
||||
|
||||
You can introduce additional metrics to use when autoscaling the `php-apache` Deployment
|
||||
by making use of the `autoscaling/v2beta2` API version.
|
||||
by making use of the `autoscaling/v2` API version.
|
||||
-->
|
||||
## 基于多项度量指标和自定义度量指标自动扩缩 {#autoscaling-on-multiple-metrics-and-custom-metrics}
|
||||
|
||||
利用 `autoscaling/v2beta2` API 版本，你可以在自动扩缩 php-apache 这个
|
||||
利用 `autoscaling/v2` API 版本，你可以在自动扩缩 php-apache 这个
|
||||
Deployment 时使用其他度量指标。
|
||||
|
||||
<!--
|
||||
First, get the YAML of your HorizontalPodAutoscaler in the `autoscaling/v2beta2` form:
|
||||
First, get the YAML of your HorizontalPodAutoscaler in the `autoscaling/v2` form:
|
||||
-->
|
||||
首先，将 HorizontalPodAutoscaler 的 YAML 文件改为 `autoscaling/v2beta2` 格式：
|
||||
首先，将 HorizontalPodAutoscaler 的 YAML 文件改为 `autoscaling/v2` 格式：
|
||||
|
||||
```shell
|
||||
kubectl get hpa php-apache -o yaml > /tmp/hpa-v2.yaml
|
||||
|
|
@ -313,7 +401,7 @@ Open the `/tmp/hpa-v2.yaml` file in an editor, and you should see YAML which loo
|
|||
在编辑器中打开 `/tmp/hpa-v2.yaml`：
|
||||
|
||||
```yaml
|
||||
apiVersion: autoscaling/v2beta2
|
||||
apiVersion: autoscaling/v2
|
||||
kind: HorizontalPodAutoscaler
|
||||
metadata:
|
||||
name: php-apache
|
||||
|
|
@ -376,13 +464,13 @@ advanced cluster monitoring setup.
|
|||
这些度量指标可能具有特定于集群的名称，并且需要更高级的集群监控设置。
|
||||
|
||||
<!--
|
||||
The first of these alternative metric types is *pod metrics*. These metrics describe pods, and
|
||||
are averaged together across pods and compared with a target value to determine the replica count.
|
||||
The first of these alternative metric types is *pod metrics*. These metrics describe Pods, and
|
||||
are averaged together across Pods and compared with a target value to determine the replica count.
|
||||
They work much like resource metrics, except that they *only* support a `target` type of `AverageValue`.
|
||||
-->
|
||||
第一种可选的度量指标类型是 Pod 度量指标。这些指标从某一方面描述了 Pod，
|
||||
第一种可选的度量指标类型是 **Pod 度量指标**。这些指标从某一方面描述了 Pod，
|
||||
在不同 Pod 之间进行平均，并通过与一个目标值比对来确定副本的数量。
|
||||
它们的工作方式与资源度量指标非常相像，只是它们仅支持 `target` 类型为 `AverageValue`。
|
||||
它们的工作方式与资源度量指标非常相像，只是它们 **仅** 支持 `target` 类型为 `AverageValue`。
|
||||
|
||||
<!--
|
||||
Pod metrics are specified using a metric block like this:
|
||||
|
|
@ -401,14 +489,14 @@ pods:
|
|||
|
||||
<!--
|
||||
The second alternative metric type is *object metrics*. These metrics describe a different
|
||||
object in the same namespace, instead of describing pods. The metrics are not necessarily
|
||||
object in the same namespace, instead of describing Pods. The metrics are not necessarily
|
||||
fetched from the object; they only describe it. Object metrics support `target` types of
|
||||
both `Value` and `AverageValue`. With `Value`, the target is compared directly to the returned
|
||||
metric from the API. With `AverageValue`, the value returned from the custom metrics API is divided
|
||||
by the number of pods before being compared to the target. The following example is the YAML
|
||||
by the number of Pods before being compared to the target. The following example is the YAML
|
||||
representation of the `requests-per-second` metric.
|
||||
-->
|
||||
第二种可选的度量指标类型是对象（Object）度量指标。这些度量指标用于描述
|
||||
第二种可选的度量指标类型是对象 **（Object）度量指标**。这些度量指标用于描述
|
||||
在相同名字空间中的别的对象，而非 Pods。
|
||||
请注意这些度量指标不一定来自某对象，它们仅用于描述这些对象。
|
||||
对象度量指标支持的 `target` 类型包括 `Value` 和 `AverageValue`。
|
||||
|
|
@ -447,7 +535,7 @@ you could update the definition above using `kubectl edit` to look like this:
|
|||
将上述 Horizontal Pod Autoscaler 的定义更改为：
|
||||
|
||||
```yaml
|
||||
apiVersion: autoscaling/v2beta1
|
||||
apiVersion: autoscaling/v2
|
||||
kind: HorizontalPodAutoscaler
|
||||
metadata:
|
||||
name: php-apache
|
||||
|
|
@ -463,7 +551,7 @@ spec:
|
|||
resource:
|
||||
name: cpu
|
||||
target:
|
||||
type: AverageUtilization
|
||||
type: Utilization
|
||||
averageUtilization: 50
|
||||
- type: Pods
|
||||
pods:
|
||||
|
|
@ -477,11 +565,11 @@ spec:
|
|||
metric:
|
||||
name: requests-per-second
|
||||
describedObject:
|
||||
apiVersion: networking.k8s.io/v1beta1
|
||||
apiVersion: networking.k8s.io/v1
|
||||
kind: Ingress
|
||||
name: main-route
|
||||
target:
|
||||
kind: Value
|
||||
type: Value
|
||||
value: 10k
|
||||
status:
|
||||
observedGeneration: 1
|
||||
|
|
@ -500,7 +588,7 @@ status:
|
|||
metric:
|
||||
name: requests-per-second
|
||||
describedObject:
|
||||
apiVersion: networking.k8s.io/v1beta1
|
||||
apiVersion: networking.k8s.io/v1
|
||||
kind: Ingress
|
||||
name: main-route
|
||||
current:
|
||||
|
|
@ -537,8 +625,8 @@ GET 请求执行：
|
|||
type: Object
|
||||
object:
|
||||
metric:
|
||||
name: `http_requests`
|
||||
selector: `verb=GET`
|
||||
name: http_requests
|
||||
selector: {matchLabels: {verb: GET}}
|
||||
```
|
||||
|
||||
<!--
|
||||
|
|
@ -617,14 +705,14 @@ access to any metric, so cluster administrators should take care when exposing i
|
|||
<!--
|
||||
## Appendix: Horizontal Pod Autoscaler Status Conditions
|
||||
|
||||
When using the `autoscaling/v2beta2` form of the HorizontalPodAutoscaler, you will be able to see
|
||||
When using the `autoscaling/v2` form of the HorizontalPodAutoscaler, you will be able to see
|
||||
*status conditions* set by Kubernetes on the HorizontalPodAutoscaler. These status conditions indicate
|
||||
whether or not the HorizontalPodAutoscaler is able to scale, and whether or not it is currently restricted
|
||||
in any way.
|
||||
-->
|
||||
## 附录：Horizontal Pod Autoscaler 状态条件
|
||||
|
||||
使用 `autoscaling/v2beta2` 格式的 HorizontalPodAutoscaler 时，你将可以看到
|
||||
使用 `autoscaling/v2` 格式的 HorizontalPodAutoscaler 时，你将可以看到
|
||||
Kubernetes 为 HorizongtalPodAutoscaler 设置的状态条件（Status Conditions）。
|
||||
这些状态条件可以显示当前 HorizontalPodAutoscaler 是否能够执行扩缩以及是否受到一定的限制。
|
||||
|
||||
|
|
@ -662,7 +750,7 @@ Events:
|
|||
```
|
||||
|
||||
<!--
|
||||
For this HorizontalPodAutoscaler, we can see several conditions in a healthy state. The first,
|
||||
For this HorizontalPodAutoscaler, you can see several conditions in a healthy state. The first,
|
||||
`AbleToScale`, indicates whether or not the HPA is able to fetch and update scales, as well as
|
||||
whether or not any backoff-related conditions would prevent scaling. The second, `ScalingActive`,
|
||||
indicates whether or not the HPA is enabled (i.e. the replica count of the target is not zero) and
|
||||
|
|
@ -681,7 +769,7 @@ HorizontalPodAutoscaler.
|
|||
这通常表明你可能需要调整 HorizontalPodAutoscaler 所定义的最大或者最小副本数量的限制了。
|
||||
|
||||
<!--
|
||||
## Appendix: Quantities
|
||||
## Quantities
|
||||
|
||||
All metrics in the HorizontalPodAutoscaler and metrics APIs are specified using
|
||||
a special whole-number notation known in Kubernetes as a
|
||||
|
|
@ -691,7 +779,7 @@ will return whole numbers without a suffix when possible, and will generally ret
|
|||
quantities in milli-units otherwise. This means you might see your metric value fluctuate
|
||||
between `1` and `1500m`, or `1` and `1.5` when written in decimal notation.
|
||||
-->
|
||||
## 附录：量纲 {#appendix-quantities}
|
||||
## 量纲 {#quantities}
|
||||
|
||||
HorizontalPodAutoscaler 和 度量指标 API 中的所有的度量指标使用 Kubernetes 中称为
|
||||
{{< glossary_tooltip term_id="quantity" text="量纲（Quantity）">}}
|
||||
|
|
@ -701,24 +789,24 @@ HorizontalPodAutoscaler 和 度量指标 API 中的所有的度量指标使用 K
|
|||
这意味着你可能会看到你的度量指标在 `1` 和 `1500m` （也就是在十进制记数法中的 `1` 和 `1.5`）之间波动。
|
||||
|
||||
<!--
|
||||
## Appendix: Other possible scenarios
|
||||
## Other possible scenarios
|
||||
|
||||
### Creating the autoscaler declaratively
|
||||
-->
|
||||
## 附录：其他可能的情况 {#appendix-other-possible-scenarios}
|
||||
## 其他可能的情况 {#other-possible-scenarios}
|
||||
|
||||
### 以声明式方式创建 Autoscaler {#creating-the-autoscaler-declaratively}
|
||||
|
||||
<!--
|
||||
Instead of using `kubectl autoscale` command to create a HorizontalPodAutoscaler imperatively we
|
||||
can use the following file to create it declaratively:
|
||||
can use the following manifest to create it declaratively:
|
||||
-->
|
||||
除了使用 `kubectl autoscale` 命令，也可以文件创建 HorizontalPodAutoscaler：
|
||||
除了使用 `kubectl autoscale` 命令，也可以使用以下清单以声明方式创建 HorizontalPodAutoscaler：
|
||||
|
||||
{{< codenew file="application/hpa/php-apache.yaml" >}}
|
||||
|
||||
<!--
|
||||
We will create the autoscaler by executing the following command:
|
||||
Then, create the autoscaler by executing the following command:
|
||||
-->
|
||||
使用如下命令创建 autoscaler：
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue