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1 简介
Kubernetes 自带的 HPA 是只反对 CPU/MEM 的，很多时候咱们并不依据这两项指标来进行伸缩资源。比方消费者一直解决 MQ 的音讯，咱们心愿 MQ 如果沉积过多，就启动更多的消费者来解决工作。而 Keda 给了咱们很多抉择。
KEDA 是 Kubernetes 基于事件驱动的主动伸缩工具，通过 KEDA 咱们能够依据须要解决的事件数量来驱动 Kubernetes 中任何容器的扩大。KEDA 能够间接部署到任何 Kubernetes 集群中和规范的组件一起工作。
Keda 所反对的事件源十分丰盛，本文咱们以 RabbitMQ 为例进行演示。
2 装置 Keda
装置的办法很多，咱们间接通过 yaml 文件来装置，这样还能够批改镜像地址等。先从（https://github.com/kedacore/k…）下载 yaml 文件，而后执行：
$ 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检查一下是否都曾经启动实现：
$ 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也能够看到镜像多了：
$ 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.yaml3 装置 RabbitMQ
为了疾速装置，也不便日后删除，咱们通过 Helm 来装置 RabbitMQ。
查看可用的 chart：
$ helm search repo rabbit执行装置：
$ 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，明码获取如下：
$ echo "Password : $(kubectl get secret --namespace default azure-rabbitmq -o jsonpath="{.data.rabbitmq-password}"| base64 --decode)"
Password : YNsEayx8w24 测试
部署消费者，留神这里有个 MQ 连贯信息和加密，要依据本人状况批改。
$ 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 创立，因为还不须要解决，MQ 当初的队列为 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 发送音讯：
$ kubectl apply -f src/main/kubernetes/deploy-publisher-job.yaml
job.batch/rabbitmq-publish created能够看到，缓缓消费者就起来了，并且创立了越来越多的 Pod 来解决 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 也能够看到后果：
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解决实现后，又会回到 0 了。
总结
代码请查看：https://github.com/LarryDpk/p…
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