Kubernetes使用Keda进行弹性伸缩，更合理利用资源

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1 简介

Kubernetes自带的HPA是只支持CPU/MEM的，很多时候我们并不根据这两项指标来进行伸缩资源。比如消费者不断处理MQ的消息，我们希望MQ如果堆积过多，就启动更多的消费者来处理任务。而Keda给了我们很多选择。

KEDA 是 Kubernetes 基于事件驱动的自动伸缩工具，通过 KEDA 我们可以根据需要处理的事件数量来驱动 Kubernetes 中任何容器的扩展。KEDA 可以直接部署到任何 Kubernetes 集群中和标准的组件一起工作。

Keda所支持的事件源非常丰富，本文我们以RabbitMQ为例进行演示。

2 安装Keda

安装的方法很多，我们直接通过yaml文件来安装，这样还可以修改镜像地址等。先从（ https://github.com/kedacore/keda/releases/download/v2.2.0/keda-2.2.0.yaml ）下载yaml文件，然后执行：

$ kubectl apply -f ~/Downloads/keda-2.2.0.yaml
namespace/keda created
customresourcedefinition.apiextensions.k8s.io/clustertriggerauthentications.keda.sh created
customresourcedefinition.apiextensions.k8s.io/scaledjobs.keda.sh created
customresourcedefinition.apiextensions.k8s.io/scaledobjects.keda.sh created
customresourcedefinition.apiextensions.k8s.io/triggerauthentications.keda.sh created
serviceaccount/keda-operator created
clusterrole.rbac.authorization.k8s.io/keda-external-metrics-reader created
clusterrole.rbac.authorization.k8s.io/keda-operator created
rolebinding.rbac.authorization.k8s.io/keda-auth-reader created
clusterrolebinding.rbac.authorization.k8s.io/keda-hpa-controller-external-metrics created
clusterrolebinding.rbac.authorization.k8s.io/keda-operator created
clusterrolebinding.rbac.authorization.k8s.io/keda:system:auth-delegator created
service/keda-metrics-apiserver created
deployment.apps/keda-metrics-apiserver created
deployment.apps/keda-operator created
apiservice.apiregistration.k8s.io/v1beta1.external.metrics.k8s.io created

检查一下是否都已经启动完成：

$ kubectl get all -n keda
NAME                                          READY   STATUS    RESTARTS   AGE
pod/keda-metrics-apiserver-55dc9f9498-smc2d   1/1     Running   0          2m41s
pod/keda-operator-59dcf989d6-pxcbb            1/1     Running   0          2m41s

NAME                             TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)          AGE
service/keda-metrics-apiserver   ClusterIP   10.104.255.44   <none>        443/TCP,80/TCP   2m41s

NAME                                     READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/keda-metrics-apiserver   1/1     1            1           2m42s
deployment.apps/keda-operator            1/1     1            1           2m42s

NAME                                                DESIRED   CURRENT   READY   AGE
replicaset.apps/keda-metrics-apiserver-55dc9f9498   1         1         1       2m42s
replicaset.apps/keda-operator-59dcf989d6            1         1         1       2m42s

也可以看到镜像多了：

$ docker images | grep keda
ghcr.io/kedacore/keda-metrics-apiserver                 2.2.0                                            a43d40453368        6 weeks ago         95.3MB
ghcr.io/kedacore/keda                                   2.2.0                                            42b88f042914        6 weeks ago         83MB

如果要卸载请执行：

$ kubectl delete -f ~/Downloads/keda-2.2.0.yaml

3 安装RabbitMQ

为了快速安装，也方便日后删除，我们通过Helm来安装RabbitMQ。

查看可用的chart：

$ helm search repo rabbit

执行安装：

$ helm install azure-rabbitmq azure/rabbitmq

检查一下：

$ helm list
NAME          	NAMESPACE	REVISION	UPDATED                             	STATUS  	CHART               	APP VERSION
azure-ingress 	default  	1       	2021-02-14 01:21:07.212107 +0800 CST	deployed	nginx-ingress-1.41.3	v0.34.1
azure-rabbitmq	default  	1       	2021-05-05 11:29:06.979437 +0800 CST	deployed	rabbitmq-6.18.2     	3.8.2

用户名为user，密码获取如下：

$ echo "Password      : $(kubectl get secret --namespace default azure-rabbitmq -o jsonpath="{.data.rabbitmq-password}" | base64 --decode)"
Password      : YNsEayx8w2

4 测试

部署消费者，注意这里有个MQ连接信息和加密，要根据自己情况修改。

$ kubectl apply -f src/main/kubernetes/deploy-consumer.yaml
secret/rabbitmq-consumer-secret created
deployment.apps/rabbitmq-consumer created
scaledobject.keda.sh/rabbitmq-consumer created
triggerauthentication.keda.sh/rabbitmq-consumer-trigger created

查看deployment，发现是没有Pod创建，因为还不需要处理，MQ现在的队列为0。

$ kubectl get deployments
NAME                                          READY   UP-TO-DATE   AVAILABLE   AGE
azure-ingress-nginx-ingress-controller        1/1     1            1           80d
azure-ingress-nginx-ingress-default-backend   1/1     1            1           80d
rabbitmq-consumer                             0/0     0            0           131m

部署生产者，往MQ发送消息：

$ kubectl apply -f src/main/kubernetes/deploy-publisher-job.yaml
job.batch/rabbitmq-publish created

可以看到，慢慢消费者就起来了，并且创建了越来越多的Pod来处理MQ：

$ kubectl get deployments rabbitmq-consumer
NAME                READY   UP-TO-DATE   AVAILABLE   AGE
rabbitmq-consumer   1/1     1            1           167m

$ kubectl get deployments rabbitmq-consumer
NAME                READY   UP-TO-DATE   AVAILABLE   AGE
rabbitmq-consumer   3/4     4            3           168m

$ kubectl get deployments rabbitmq-consumer
NAME                READY   UP-TO-DATE   AVAILABLE   AGE
rabbitmq-consumer   4/8     8            4           168m

$ kubectl get deployments rabbitmq-consumer
NAME                READY   UP-TO-DATE   AVAILABLE   AGE
rabbitmq-consumer   6/8     8            6           169m
$ kubectl get deployments rabbitmq-consumer
NAME                READY   UP-TO-DATE   AVAILABLE   AGE
rabbitmq-consumer   0/0     0            0           171m

查看Deployment的Event也可以看到结果：

Events:
  Type    Reason             Age                   From                   Message
  ----    ------             ----                  ----                   -------
  Normal  ScalingReplicaSet  5m55s (x2 over 172m)  deployment-controller  Scaled up replica set rabbitmq-consumer-7b477f78b4 to 1
  Normal  ScalingReplicaSet  5m6s                  deployment-controller  Scaled up replica set rabbitmq-consumer-7b477f78b4 to 4
  Normal  ScalingReplicaSet  4m6s                  deployment-controller  Scaled up replica set rabbitmq-consumer-7b477f78b4 to 8
  Normal  ScalingReplicaSet  3m5s                  deployment-controller  Scaled up replica set rabbitmq-consumer-7b477f78b4 to 16
  Normal  ScalingReplicaSet  3m3s (x2 over 172m)   deployment-controller  Scaled down replica set rabbitmq-consumer-7b477f78b4 to 0

处理完成后，又会回到0了。

总结

代码请查看：https://github.com/LarryDpk/pkslow-samples

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