来自AI助手的总结
介绍KEDA在Kubernetes中的在线与离线安装配置方法
一、KEDA安装和使用
官方资料：https://keda.sh/docs/2.16/deploy/
注意事项：KEDA 需要 Kubernetes 集群版本 1.27 及更高版本
1.1 KEDA安装
1.1.1 Helm在线安装
1、添加KEDA的Helm源
#添加helm源
[root@k8s-master01 ~]# helm repo add kedacore https://kedacore.github.io/charts
#更新helm源
[root@k8s-master01 ~]# helm repo update
Hang tight while we grab the latest from your chart repositories...
...Successfully got an update from the "ot-helm" chart repository
...Successfully got an update from the "kedacore" chart repository
Update Complete. ⎈Happy Helming!⎈
2、安装KEDA
[root@k8s-master01 ~]# helm install keda kedacore/keda --namespace keda --create-namespace
...
...
Learn more about KEDA:
- Documentation: https://keda.sh/
- Support: https://keda.sh/support/
- File an issue: https://github.com/kedacore/keda/issues/new/choose
3、查看服务状态
[root@k8s-master01 ~]# kgp -n keda
1.1.2 Helm离线安装
1、添加KEDA的Helm源
#添加helm源
[root@k8s-master01 ~]# helm repo add kedacore https://kedacore.github.io/charts
#更新helm源
[root@k8s-master01 ~]# helm repo update
Hang tight while we grab the latest from your chart repositories...
...Successfully got an update from the "ot-helm" chart repository
...Successfully got an update from the "kedacore" chart repository
Update Complete. ⎈Happy Helming!⎈
2、下载并解压keda包
#下载keda包
[root@k8s-master01 ~]# helm pull kedacore/keda --version 2.16.1
#解压keda包
[root@k8s-master01 ~]# tar xf keda-2.16.1.tgz
3、创建ns
[root@k8s-master01 ~]# kubectl create ns keda
4、修改values.yaml文件
[root@k8s-master01 ~]# vim /root/keda/values.yaml
...
...
#修改第13行内容
13 registry: registry.cn-hangzhou.aliyuncs.com
#修改第15行内容
15 repository: github_images1024/keda
#修改第17行内容
17 tag: "2.16.1"
#修改第20行内容
20 registry: registry.cn-hangzhou.aliyuncs.com
#修改第22行内容
22 repository: github_images1024/keda-metrics-apiserver
#修改第24行内容
24 tag: "2.16.1"
#修改第27行内容
27 registry: registry.cn-hangzhou.aliyuncs.com
#修改第29行内容
29 repository: github_images1024/keda-admission-webhooks
#修改第31行内容
31 tag: "2.16.1"
完整values.yaml文件
[root@k8s-master01 ~]# egrep -v "^#|^$|#" /root/keda/values.yaml
global:
image:
registry: null
image:
keda:
registry: registry.cn-hangzhou.aliyuncs.com
repository: github_images1024/keda
tag: "2.16.1"
metricsApiServer:
registry: registry.cn-hangzhou.aliyuncs.com
repository: github_images1024/keda-metrics-apiserver
tag: "2.16.1"
webhooks:
registry: registry.cn-hangzhou.aliyuncs.com
repository: github_images1024/keda-admission-webhooks
tag: "2.16.1"
pullPolicy: Always
clusterName: kubernetes-default
clusterDomain: cluster.local
crds:
install: true
additionalAnnotations:
{}
watchNamespace: ""
imagePullSecrets: []
networkPolicy:
enabled: false
flavor: "cilium"
cilium:
operator:
extraEgressRules: []
operator:
name: keda-operator
revisionHistoryLimit: 10
replicaCount: 1
disableCompression: true
affinity: {}
extraContainers: []
extraInitContainers: []
livenessProbe:
initialDelaySeconds: 25
periodSeconds: 10
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
readinessProbe:
initialDelaySeconds: 20
periodSeconds: 3
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
metricsServer:
revisionHistoryLimit: 10
replicaCount: 1
disableCompression: true
dnsPolicy: ClusterFirst
useHostNetwork: false
affinity: {}
livenessProbe:
initialDelaySeconds: 5
periodSeconds: 10
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
readinessProbe:
initialDelaySeconds: 5
periodSeconds: 3
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
webhooks:
enabled: true
port: ""
healthProbePort: 8081
livenessProbe:
initialDelaySeconds: 25
periodSeconds: 10
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
readinessProbe:
initialDelaySeconds: 20
periodSeconds: 3
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
useHostNetwork: false
name: keda-admission-webhooks
revisionHistoryLimit: 10
replicaCount: 1
affinity: {}
failurePolicy: Ignore
upgradeStrategy:
operator: {}
metricsApiServer: {}
webhooks: {}
podDisruptionBudget:
operator: {}
metricServer: {}
webhooks: {}
additionalLabels:
{}
additionalAnnotations:
{}
podAnnotations:
keda: {}
metricsAdapter: {}
webhooks: {}
podLabels:
keda: {}
metricsAdapter: {}
webhooks: {}
rbac:
create: true
aggregateToDefaultRoles: false
enabledCustomScaledRefKinds: true
controlPlaneServiceAccountsNamespace: kube-system
scaledRefKinds:
- apiGroup: "*"
kind: "*"
serviceAccount:
operator:
create: true
name: keda-operator
automountServiceAccountToken: true
annotations: {}
metricServer:
create: true
name: keda-metrics-server
automountServiceAccountToken: true
annotations: {}
webhooks:
create: true
name: keda-webhook
automountServiceAccountToken: true
annotations: {}
podIdentity:
azureWorkload:
enabled: false
clientId: ""
tenantId: ""
tokenExpiration: 3600
aws:
irsa:
enabled: false
audience: "sts.amazonaws.com"
roleArn: ""
stsRegionalEndpoints: "true"
tokenExpiration: 86400
gcp:
enabled: false
gcpIAMServiceAccount: ""
grpcTLSCertsSecret: ""
hashiCorpVaultTLS: ""
logging:
operator:
level: info
format: console
timeEncoding: rfc3339
stackTracesEnabled: false
metricServer:
level: 0
stderrthreshold: ERROR
webhooks:
level: info
format: console
timeEncoding: rfc3339
securityContext:
operator:
capabilities:
drop:
- ALL
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
seccompProfile:
type: RuntimeDefault
metricServer:
capabilities:
drop:
- ALL
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
seccompProfile:
type: RuntimeDefault
webhooks:
capabilities:
drop:
- ALL
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
seccompProfile:
type: RuntimeDefault
podSecurityContext:
operator:
runAsNonRoot: true
metricServer:
runAsNonRoot: true
webhooks:
runAsNonRoot: true
service:
type: ClusterIP
portHttps: 443
portHttpsTarget: 6443
annotations: {}
resources:
operator:
limits:
cpu: 1
memory: 1000Mi
requests:
cpu: 100m
memory: 100Mi
metricServer:
limits:
cpu: 1
memory: 1000Mi
requests:
cpu: 100m
memory: 100Mi
webhooks:
limits:
cpu: 1
memory: 1000Mi
requests:
cpu: 100m
memory: 100Mi
nodeSelector: {}
tolerations: []
topologySpreadConstraints:
operator: []
metricsServer: []
webhooks: []
affinity: {}
priorityClassName: ""
http:
timeout: 3000
keepAlive:
enabled: true
minTlsVersion: TLS12
profiling:
operator:
enabled: false
port: 8082
metricsServer:
enabled: false
port: 8083
webhooks:
enabled: false
port: 8084
extraArgs:
keda: {}
metricsAdapter: {}
env: []
volumes:
keda:
extraVolumes: []
extraVolumeMounts: []
metricsApiServer:
extraVolumes: []
extraVolumeMounts: []
webhooks:
extraVolumes: []
extraVolumeMounts: []
prometheus:
metricServer:
enabled: false
port: 8080
portName: metrics
serviceMonitor:
enabled: false
jobLabel: ""
targetLabels: []
podTargetLabels: []
port: metrics
targetPort: ""
interval: ""
scrapeTimeout: ""
relabellings: []
relabelings: []
metricRelabelings: []
additionalLabels: {}
scheme: http
tlsConfig: {}
podMonitor:
enabled: false
interval: ""
scrapeTimeout: ""
namespace: ""
additionalLabels: {}
relabelings: []
metricRelabelings: []
operator:
enabled: false
port: 8080
serviceMonitor:
enabled: false
jobLabel: ""
targetLabels: []
podTargetLabels: []
port: metrics
targetPort: ""
interval: ""
scrapeTimeout: ""
relabellings: []
relabelings: []
metricRelabelings: []
additionalLabels: {}
scheme: http
tlsConfig: {}
podMonitor:
enabled: false
interval: ""
scrapeTimeout: ""
namespace: ""
additionalLabels: {}
relabelings: []
metricRelabelings: []
prometheusRules:
enabled: false
namespace: ""
additionalLabels: {}
alerts:
[]
webhooks:
enabled: false
port: 8080
serviceMonitor:
enabled: false
jobLabel: ""
targetLabels: []
podTargetLabels: []
port: metrics
targetPort: ""
interval: ""
scrapeTimeout: ""
relabellings: []
relabelings: []
metricRelabelings: []
additionalLabels: {}
scheme: http
tlsConfig: {}
prometheusRules:
enabled: false
namespace: ""
additionalLabels: {}
alerts: []
opentelemetry:
collector:
uri: ""
operator:
enabled: false
certificates:
autoGenerated: true
secretName: kedaorg-certs
mountPath: /certs
certManager:
enabled: false
generateCA: true
caSecretName: "kedaorg-ca"
secretTemplate: {}
issuer:
generate: true
name: foo-org-ca
kind: ClusterIssuer
group: cert-manager.io
operator:
permissions:
metricServer:
restrict:
secret: false
operator:
restrict:
secret: false
namesAllowList: []
extraObjects: []
asciiArt: true
customManagedBy: ""
5、安装keda
[root@k8s-master01 keda]# helm install keda . -n keda
查看资源
#查看pod
[root@k8s-master01 keda]# kgp -n keda
NAME READY STATUS RESTARTS AGE
keda-admission-webhooks-9664c747b-rxk88 1/1 Running 0 46s
keda-operator-848cf7589c-swfzd 1/1 Running 1 (42s ago) 46s
keda-operator-metrics-apiserver-7bc7d5755b-zdkbm 1/1 Running 0 46s
#查看crd
[root@k8s-master01 ~]# kg crd | grep keda
cloudeventsources.eventing.keda.sh 2025-04-03T03:49:23Z
clustercloudeventsources.eventing.keda.sh 2025-04-03T03:49:23Z
clustertriggerauthentications.keda.sh 2025-04-03T03:49:23Z
scaledjobs.keda.sh 2025-04-03T03:49:23Z
scaledobjects.keda.sh 2025-04-03T03:49:23Z
triggerauthentications.keda.sh 2025-04-03T03:49:23Z
#查看api-resources
[root@k8s-master01 ~]# kubectl api-resources | grep keda
cloudeventsources eventing.keda.sh/v1alpha1 true CloudEventSource
clustercloudeventsources eventing.keda.sh/v1alpha1 false ClusterCloudEventSource
clustertriggerauthentications cta,clustertriggerauth keda.sh/v1alpha1 false ClusterTriggerAuthentication
scaledjobs sj keda.sh/v1alpha1 true ScaledJob
scaledobjects so keda.sh/v1alpha1 true ScaledObject
triggerauthentications ta,triggerauth keda.sh/v1alpha1 true TriggerAuthentication
1.1.3 KEDA卸载
如果要从集群中删除 KEDA，首先需要删除您创建的所有 ScaledObject 和 ScaledJobs。完成后，可以卸载 Helm ：
#删除相关资源
kubectl delete $(kubectl get scaledobjects.keda.sh,scaledjobs.keda.sh -A \
-o jsonpath='{"-n "}{.items[*].metadata.namespace}{" "}{.items[*].kind}{"/"}{.items[*].metadata.name}{"\n"}')
#卸载keda
helm uninstall keda -n keda
注意：如果在未先删除已创建的任何 ScaledObject 或 ScaledJob 资源的情况下卸载 Helm chart，则它们将成为孤立资源。在这种情况下，您需要修补资源以删除其终结器。完成此作后，它们应自动删除：
for i in $(kubectl get scaledobjects -A \
-o jsonpath='{"-n "}{.items[*].metadata.namespace}{" "}{.items[*].kind}{"/"}{.items[*].metadata.name}{"\n"}');
do kubectl patch $i -p '{"metadata":{"finalizers":null}}' --type=merge
done
for i in $(kubectl get scaledjobs -A \
-o jsonpath='{"-n "}{.items[*].metadata.namespace}{" "}{.items[*].kind}{"/"}{.items[*].metadata.name}{"\n"}');
do kubectl patch $i -p '{"metadata":{"finalizers":null}}' --type=merge
done
1.2 KEDA弹性伸缩实战
二、KEDA弹性伸缩实战
2.1 周期性定时扩缩容
官方链接：https://keda.sh/docs/2.16/scalers/cron/
KEDA支持周期性弹性收缩服务,且支持缩容至0。假设有个服务只有每天早上7-9点属于业务高峰,就可以利用KEDA实现在7-9点扩展服务,除此之外的时间在缩减副本,以节省资源。
2.1.1 创建测试资源
1.定义一个yaml文件
## 生成模板文件
[root@k8s-master01 ~]# kubectl create deploy nginx-server --image=registry.cn-hangzhou.aliyuncs.com/zq-demo/nginx:1.14.2 --dry-run=client -oyaml > nginx-server.yaml
## 重新编辑模板文件
[root@k8s-master01 ~]# vim nginx-server.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: nginx-server
name: nginx-server
spec:
replicas: 1
selector:
matchLabels:
app: nginx-server
strategy: {}
template:
metadata:
labels:
app: nginx-server
spec:
containers:
- image: registry.cn-hangzhou.aliyuncs.com/zq-demo/nginx:1.14.2
name: nginx
resources:
requests:
cpu: 10m
memory: 128Mi
2.创建Deployment
[root@k8s-master01 ~]# k create -f nginx-server.yaml
3.查看pod
[root@k8s-master01 ~]# k get po
NAME READY STATUS RESTARTS AGE
nginx-server-5f44c4b986-4rvjd 1/1 Running 0 14s
2.1.2 开始实战
1、创建Cron类型的ScaledObject
#编写yaml文件
[root@k8s-master01 ~]# vim cron.yaml
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
name: cron-scaledobject
namespace: default
spec:
scaleTargetRef:
name: nginx-server
minReplicaCount: 0
cooldownPeriod: 300
triggers:
- type: cron
metadata:
timezone: Asia/Shanghai
start: 35 12 * * *
end: 40 12 * * *
desiredReplicas: "10"
#应用yaml文件
[root@k8s-master01 ~]# kaf cron.yaml
2、查看资源
#查看之前创建的deploy副本数自动设置为0
[root@k8s-master01 ~]# kg deploy
NAME READY UP-TO-DATE AVAILABLE AGE
nginx-server 0/0 0 0 9m43s
#查看ScaledObject资源
[root@k8s-master01 ~]# kg so
NAME SCALETARGETKIND SCALETARGETNAME MIN MAX READY ACTIVE FALLBACK PAUSED TRIGGERS AUTHENTICATIONS AGE
cron-scaledobject apps/v1.Deployment nginx-server 0 True True False Unknown 4m43s
#查看hpa
[root@k8s-master01 ~]# kg hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
keda-hpa-cron-scaledobject Deployment/nginx-server 1/1 (avg) 1 100 10 5m24s
#等待12点35后进行扩容，观察到副本已经被扩成10个
[root@k8s-master01 ~]# kgp
NAME READY STATUS RESTARTS AGE
nginx-server-5f44c4b986-4pnmv 1/1 Running 0 77s
nginx-server-5f44c4b986-5rlc5 1/1 Running 0 77s
nginx-server-5f44c4b986-729fm 1/1 Running 0 93s
nginx-server-5f44c4b986-76ls4 1/1 Running 0 77s
nginx-server-5f44c4b986-87j9m 1/1 Running 0 92s
nginx-server-5f44c4b986-9bww2 1/1 Running 0 92s
nginx-server-5f44c4b986-gz7pj 1/1 Running 0 62s
nginx-server-5f44c4b986-hg76z 1/1 Running 0 77s
nginx-server-5f44c4b986-jlwjz 1/1 Running 0 92s
nginx-server-5f44c4b986-nkmw6 1/1 Running 0 62s
2.1.3 环境清理
k delete -f nginx-server.yaml -f cron.yaml
2.2 基于RabbitMQ消息队列的弹性伸缩配置
官方链接：https://keda.sh/docs/2.16/scalers/rabbitmq-queue/
KEDA支持基于消息队列的弹性伸缩,比如基于RabbitMO、Kafka、Redis队列进行扩缩容,以便更快的处理。
2.2.1 创建测试资源
1.定义一个yaml文件创建一个RabbitMQ
#创建deployment模板文件
[root@k8s-master01 ~]# kubectl create deploy rabbitmq --image=registry.cn-beijing.aliyuncs.com/dotbalo/rabbitmq:4.0.5-management-alpine --dry-run=client -oyaml > rabbitmq-deploy.yaml
#重新定义deployment模板文件
[root@k8s-master01 ~]# vim rabbitmq-deploy.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
annotations: {}
labels:
app: rabbitmq
name: rabbitmq
spec:
replicas: 1
selector:
matchLabels:
app: rabbitmq
strategy:
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
type: RollingUpdate
template:
metadata:
labels:
app: rabbitmq
spec:
containers:
- env:
- name: TZ
value: Asia/Shanghai
- name: LANG
value: C.UTF-8
- name: RABBITMQ_DEFAULT_USER
value: user
- name: RABBITMQ_DEFAULT_PASS
value: password
image: registry.cn-beijing.aliyuncs.com/dotbalo/rabbitmq:4.0.5-management-alpine
name: rabbitmq
imagePullPolicy: IfNotPresent
livenessProbe:
failureThreshold: 2
initialDelaySeconds: 30
periodSeconds: 10
successThreshold: 1
tcpSocket:
port: 5672
timeoutSeconds: 2
name: rabbitmq
ports:
- containerPort: 5672
name: web
protocol: TCP
readinessProbe:
failureThreshold: 2
initialDelaySeconds: 30
periodSeconds: 10
successThreshold: 1
tcpSocket:
port: 5672
timeoutSeconds: 2
#定义一个Service文件
[root@k8s-master01 ~]# vim rabbitmq-svc.yaml
apiVersion: v1
kind: Service
metadata:
name: rabbitmq
spec:
selector:
app: rabbitmq
sessionAffinity: None
type: NodePort
ports:
- name: web
port: 5672
targetPort: 5672
protocol: TCP
nodePort: 30672
- name: http
port: 15672
targetPort: 15672
protocol: TCP
nodePort: 31672
2.创建Deployment
[root@k8s-master01 ~]# kaf rabbitmq-deploy.yaml
[root@k8s-master01 ~]# kaf rabbitmq-svc.yaml
3.查看资源
#查看pod
[root@k8s-master01 ~]# kgp | grep rabbitmq
rabbitmq-5c445844c-5qpff 1/1 Running 0 5m25s
#查看svc
[root@k8s-master01 ~]# kg svc | grep rabbitmq
rabbitmq NodePort 10.109.228.249 <none> 5672:30672/TCP,15672:31672/TCP 2m15
4.打开浏览器中输入http://10.0.0.20:31672进行登录测试，账号为user,密码为password
5.使用一个Job模拟生产者生产消息
创建一个job
#定义yaml文件
[root@k8s-master01 ~]# vim rabbitmq-publish-job.yaml
apiVersion: batch/v1
kind: Job
metadata:
name: rabbitmq-publish
spec:
backoffLimit: 4
template:
spec:
containers:
- name: rabbitmq-client
command:
- "send"
- "amqp://user:password@rabbitmq.default.svc.cluster.local:5672"
- "10"
image: registry.cn-hangzhou.aliyuncs.com/github_images1024/rabbitmq-publish:v1.0
imagePullPolicy: IfNotPresent
restartPolicy: Never
#应用
[root@k8s-master01 ~]# kaf rabbitmq-publish-job.yaml
#查看资源
[root@k8s-master01 ~]# kgp
NAME READY STATUS RESTARTS AGE
rabbitmq-5c445844c-5qpff 1/1 Running 0 38m
rabbitmq-publish-g2bmx 0/1 Completed 0 3m55s
打开浏览器中输入http://10.0.0.20:31672进行登录，查看到生产消息数量为10
6.使用一个Job模拟消费者来消费消息
创建一个job
#创建模板文件
[root@k8s-master01 ~]# k create deploy rabbitmq-consumer --image=registry.cn-hangzhou.aliyuncs.com/github_images1024/rabbitmq-consumer:v1.0 --dry-run=client -oyaml > rabbitmq-consumer-deploy.yaml
#定义yaml文件
[root@k8s-master01 ~]# vim rabbitmq-consumer-deploy.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: rabbitmq-consumer
name: rabbitmq-consumer
spec:
replicas: 1
selector:
matchLabels:
app: rabbitmq-consumer
strategy: {}
template:
metadata:
labels:
app: rabbitmq-consumer
spec:
containers:
- image: registry.cn-hangzhou.aliyuncs.com/github_images1024/rabbitmq-consumer:v1.0
name: rabbitmq-consumer
command:
- receive
args:
- "amqp://user:password@rabbitmq.default.svc.cluster.local:5672"
#应用
[root@k8s-master01 ~]# kaf rabbitmq-consumer-deploy.yaml
#查看资源
[root@k8s-master01 ~]# kgp | grep rabbitmq-consumer
rabbitmq-consumer-df797d958-28lpw 1/1 Running 0 96s
打开浏览器中输入http://10.0.0.20:31672进行登录，查看到生产消息数量逐渐减少，最后变为0
2.2.2 开始实战
1、创建TriggerAuthentication和Secret
#定义资源文件
[root@k8s-master01 ~]# vim rabbitmq-ta.yaml
apiVersion: v1
kind: Secret
metadata:
name: keda-rabbitmq-secret
stringData:
host: amqp://user:password@rabbitmq:5672
---
apiVersion: keda.sh/v1alpha1
kind: TriggerAuthentication
metadata:
name: keda-trigger-auth-rabbitmq-conn
namespace: default
spec:
secretTargetRef:
- parameter: host
name: keda-rabbitmq-secret
key: host
#创建资源
[root@k8s-master01 ~]# kaf rabbitmq-ta.yaml
#查看资源
[root@k8s-master01 ~]# kg ta
NAME PODIDENTITY SECRET ENV VAULTADDRESS
keda-trigger-auth-rabbitmq-conn keda-rabbitmq-secret
2、创建ScaledObject
#定义资源文件
[root@k8s-master01 ~]# vim rabbitmq-so.yaml
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
name: rabbitmq-scaledobject
namespace: default
spec:
scaleTargetRef:
name: rabbitmq-consumer
pollingInterval: 5
cooldownPeriod: 30
minReplicaCount: 1
maxReplicaCount: 30
triggers:
- type: rabbitmq
metadata:
protocol: amqp
queueName: hello
mode: QueueLength
value: "50"
authenticationRef:
name: keda-trigger-auth-rabbitmq-conn
#创建资源
[root@k8s-master01 ~]# kaf rabbitmq-so.yaml
#查看so
[root@k8s-master01 ~]# kg so | grep rabbitmq
rabbitmq-scaledobject apps/v1.Deployment rabbitmq-consumer 1 30 False Unknown False Unknown 27m
说明：上面queueName需要根据自己环境来决定
3、重新定义Job中消息数量为300
#重新定义消息数量，由原来的10个变为300个
[root@k8s-master01 ~]# vim rabbitmq-publish-job.yaml
apiVersion: batch/v1
kind: Job
metadata:
name: rabbitmq-publish
spec:
backoffLimit: 4
template:
spec:
containers:
- name: rabbitmq-client
command:
- "send"
- "amqp://user:password@rabbitmq.default.svc.cluster.local:5672"
- "300"
image: registry.cn-hangzhou.aliyuncs.com/github_images1024/rabbitmq-publish:v1.0
imagePullPolicy: IfNotPresent
restartPolicy: Never
#重新创建job
[root@k8s-master01 ~]# k delete -f rabbitmq-publish-job.yaml ; kaf rabbitmq-publish-job.yaml
4、重新查看资源，观察到因为消息队列设置是300个，同时设置扩容消息队列是50个，导致pod会正常扩容到6个，
[root@k8s-master01 ~]# kgp
2.2.3 环境清理
k delete -f rabbitmq-deploy.yaml -f rabbitmq-svc.yaml -f rabbitmq-publish-job.yaml -f rabbitmq-consumer-deploy.yaml -f rabbitmq-ta.yaml -f rabbitmq-so.yaml
2.3 基于MySQL数据变化的弹性伸缩
2.3.1 创建测试资源
1、创建一个MySQL实例
#创建mysql资源
[root@k8s-master01 ~]# k create deploy mysql --image=registry.cn-hangzhou.aliyuncs.com/abroad_images/mysql:8.0.20
#设置Mysql环境变量
[root@k8s-master01 ~]# k set env deploy mysql MYSQL_ROOT_PASSWORD=password
#暴露服务
[root@k8s-master01 ~]# k expose deploy mysql --port 3306
#查看创建的资源信息
[root@k8s-master01 ~]# kgp | grep mysql
mysql-669d986df7-vvncb 1/1 Running 0 3m53s
[root@k8s-master01 ~]# kg svc | grep mysql
mysql ClusterIP 10.109.131.136 <none> 3306/TCP 3m20s
2、创建用于测试的库和表
[root@k8s-master01 ~]# k exec -it mysql-669d986df7-vvncb -- bash
root@mysql-669d986df7-vvncb:/# mysql -uroot -hmysql -p
Enter password: password
mysql> create database dukuan;
mysql> use dukuan;
mysql>
CREATE TABLE orders (
id INT AUTO_INCREMENT PRIMARY KEY,
customer_name VARCHAR(100),
order_amount DECIMAL(10,2),
status ENUM('pending', 'processed') DEFAULT 'pending',
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
3、模拟写入数据的程序
#创建资源
[root@k8s-master01 ~]# k create job insert-orders-job --image=registry.cn-hangzhou.aliyuncs.com/abroad_images/mysql:insert
#查看资源
[root@k8s-master01 ~]# kgp | grep insert-orders-job
insert-orders-job-t9fps 0/1 Completed 0 29s
#重新登录数据库中查看插入的数据，，观察到status这一列除了processed还有pending
[root@k8s-master01 ~]# k exec -it mysql-669d986df7-vvncb -- bash
root@mysql-669d986df7-vvncb:/# mysql -uroot -hmysql -p
Enter password: password
mysql> select * from dukuan.orders;
+-----+---------------+--------------+-----------+---------------------+
| id | customer_name | order_amount | status | created_at |
+-----+---------------+--------------+-----------+---------------------+
| 1 | Frank | 444.00 | processed | 2025-04-03 08:17:41 |
| 2 | Eve | 444.00 | pending | 2025-04-03 08:17:41 |
| 3 | Bob | 444.01 | processed | 2025-04-03 08:17:41 |
| 4 | Frank | 444.00 | pending | 2025-04-03 08:17:41 |
| 5 | Eve | 444.01 | processed | 2025-04-03 08:17:41 |
| 6 | Frank | 444.01 | processed | 2025-04-03 08:17:41 |
| 7 | Bob | 444.00 | pending | 2025-04-03 08:17:41 |
| 8 | Bob | 444.01 | pending | 2025-04-03 08:17:42 |
| 9 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 10 | Grace | 575.01 | pending | 2025-04-03 08:17:42 |
| 11 | David | 575.01 | processed | 2025-04-03 08:17:42 |
| 12 | Frank | 575.01 | pending | 2025-04-03 08:17:42 |
| 13 | Judy | 575.01 | processed | 2025-04-03 08:17:42 |
| 14 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 15 | Alice | 575.00 | pending | 2025-04-03 08:17:42 |
| 16 | Bob | 575.00 | pending | 2025-04-03 08:17:42 |
| 17 | Eve | 575.01 | pending | 2025-04-03 08:17:42 |
| 18 | Alice | 575.01 | processed | 2025-04-03 08:17:42 |
| 19 | Grace | 575.01 | pending | 2025-04-03 08:17:42 |
| 20 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 21 | Alice | 575.00 | pending | 2025-04-03 08:17:42 |
| 22 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 23 | Grace | 575.00 | pending | 2025-04-03 08:17:42 |
| 24 | Alice | 575.00 | pending | 2025-04-03 08:17:42 |
| 25 | Bob | 575.01 | pending | 2025-04-03 08:17:42 |
| 26 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 27 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 28 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 29 | Judy | 575.01 | pending | 2025-04-03 08:17:42 |
| 30 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 31 | Grace | 575.00 | processed | 2025-04-03 08:17:42 |
| 32 | David | 575.01 | pending | 2025-04-03 08:17:42 |
| 33 | Judy | 575.00 | pending | 2025-04-03 08:17:42 |
| 34 | Judy | 575.00 | processed | 2025-04-03 08:17:42 |
| 35 | David | 575.01 | processed | 2025-04-03 08:17:42 |
| 36 | Bob | 575.01 | pending | 2025-04-03 08:17:42 |
| 37 | Charlie | 575.00 | pending | 2025-04-03 08:17:42 |
| 38 | Frank | 575.00 | pending | 2025-04-03 08:17:42 |
| 39 | Grace | 575.00 | pending | 2025-04-03 08:17:42 |
| 40 | Eve | 575.01 | pending | 2025-04-03 08:17:42 |
| 41 | David | 575.00 | pending | 2025-04-03 08:17:42 |
| 42 | Charlie | 575.01 | processed | 2025-04-03 08:17:42 |
| 43 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 44 | Grace | 575.00 | pending | 2025-04-03 08:17:42 |
| 45 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 46 | Frank | 575.01 | pending | 2025-04-03 08:17:42 |
| 47 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 48 | Eve | 575.00 | pending | 2025-04-03 08:17:42 |
| 49 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 50 | Frank | 575.01 | processed | 2025-04-03 08:17:42 |
| 51 | Bob | 575.01 | pending | 2025-04-03 08:17:42 |
| 52 | Heidi | 575.01 | processed | 2025-04-03 08:17:42 |
| 53 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 54 | David | 575.01 | processed | 2025-04-03 08:17:42 |
| 55 | Grace | 575.01 | pending | 2025-04-03 08:17:42 |
| 56 | Judy | 575.01 | processed | 2025-04-03 08:17:42 |
| 57 | Eve | 575.00 | pending | 2025-04-03 08:17:42 |
| 58 | David | 575.00 | pending | 2025-04-03 08:17:42 |
| 59 | Bob | 575.01 | processed | 2025-04-03 08:17:42 |
| 60 | Judy | 575.01 | pending | 2025-04-03 08:17:42 |
| 61 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 62 | Eve | 575.00 | pending | 2025-04-03 08:17:42 |
| 63 | David | 575.01 | pending | 2025-04-03 08:17:42 |
| 64 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 65 | Charlie | 575.01 | processed | 2025-04-03 08:17:42 |
| 66 | Judy | 575.00 | processed | 2025-04-03 08:17:42 |
| 67 | Charlie | 575.00 | pending | 2025-04-03 08:17:42 |
| 68 | Judy | 575.01 | pending | 2025-04-03 08:17:42 |
| 69 | Bob | 575.00 | pending | 2025-04-03 08:17:42 |
| 70 | Bob | 575.00 | pending | 2025-04-03 08:17:42 |
| 71 | Charlie | 575.00 | processed | 2025-04-03 08:17:42 |
| 72 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 73 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 74 | Charlie | 575.00 | processed | 2025-04-03 08:17:42 |
| 75 | Bob | 575.00 | pending | 2025-04-03 08:17:42 |
| 76 | Charlie | 575.00 | pending | 2025-04-03 08:17:42 |
| 77 | Heidi | 575.01 | processed | 2025-04-03 08:17:42 |
| 78 | Eve | 575.01 | pending | 2025-04-03 08:17:42 |
| 79 | Charlie | 575.00 | pending | 2025-04-03 08:17:42 |
| 80 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 81 | Frank | 575.01 | processed | 2025-04-03 08:17:42 |
| 82 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 83 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 84 | David | 575.00 | pending | 2025-04-03 08:17:42 |
| 85 | David | 575.00 | pending | 2025-04-03 08:17:42 |
| 86 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 87 | Alice | 575.00 | pending | 2025-04-03 08:17:42 |
| 88 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 89 | Judy | 575.00 | pending | 2025-04-03 08:17:42 |
| 90 | Eve | 575.01 | pending | 2025-04-03 08:17:42 |
| 91 | Heidi | 575.01 | pending | 2025-04-03 08:17:42 |
| 92 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 93 | Ivan | 575.01 | processed | 2025-04-03 08:17:42 |
| 94 | Alice | 575.01 | processed | 2025-04-03 08:17:42 |
| 95 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 96 | Bob | 575.00 | processed | 2025-04-03 08:17:42 |
| 97 | Ivan | 575.00 | pending | 2025-04-03 08:17:42 |
| 98 | Bob | 575.00 | pending | 2025-04-03 08:17:42 |
| 99 | Grace | 575.00 | pending | 2025-04-03 08:17:42 |
| 100 | Ivan | 575.01 | pending | 2025-04-03 08:17:42 |
+-----+---------------+--------------+-----------+---------------------+
100 rows in set (0.00 sec)
4、创建处理程序
#创建资源
[root@k8s-master01 ~]# k create deploy update-orders --image=registry.cn-hangzhou.aliyuncs.com/abroad_images/mysql:process
#查看资源
[root@k8s-master01 ~]# kgp | grep update-orders
update-orders-bf567b97c-66d27 1/1 Running 0 48s
#进入数据库再次查看数据，观察到status这一列都变为processed
[root@k8s-master01 ~]# k exec -it mysql-669d986df7-vvncb -- bash
root@mysql-669d986df7-vvncb:/# mysql -uroot -hmysql -p
Enter password: password
mysql> select * from dukuan.orders;
+-----+---------------+--------------+-----------+---------------------+
| id | customer_name | order_amount | status | created_at |
+-----+---------------+--------------+-----------+---------------------+
| 1 | Frank | 444.00 | processed | 2025-04-03 08:17:41 |
| 2 | Eve | 444.00 | processed | 2025-04-03 08:17:41 |
| 3 | Bob | 444.01 | processed | 2025-04-03 08:17:41 |
| 4 | Frank | 444.00 | processed | 2025-04-03 08:17:41 |
| 5 | Eve | 444.01 | processed | 2025-04-03 08:17:41 |
| 6 | Frank | 444.01 | processed | 2025-04-03 08:17:41 |
| 7 | Bob | 444.00 | processed | 2025-04-03 08:17:41 |
| 8 | Bob | 444.01 | processed | 2025-04-03 08:17:42 |
| 9 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 10 | Grace | 575.01 | processed | 2025-04-03 08:17:42 |
| 11 | David | 575.01 | processed | 2025-04-03 08:17:42 |
| 12 | Frank | 575.01 | processed | 2025-04-03 08:17:42 |
| 13 | Judy | 575.01 | processed | 2025-04-03 08:17:42 |
| 14 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 15 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 16 | Bob | 575.00 | processed | 2025-04-03 08:17:42 |
| 17 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 18 | Alice | 575.01 | processed | 2025-04-03 08:17:42 |
| 19 | Grace | 575.01 | processed | 2025-04-03 08:17:42 |
| 20 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 21 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 22 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 23 | Grace | 575.00 | processed | 2025-04-03 08:17:42 |
| 24 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 25 | Bob | 575.01 | processed | 2025-04-03 08:17:42 |
| 26 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 27 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 28 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 29 | Judy | 575.01 | processed | 2025-04-03 08:17:42 |
| 30 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 31 | Grace | 575.00 | processed | 2025-04-03 08:17:42 |
| 32 | David | 575.01 | processed | 2025-04-03 08:17:42 |
| 33 | Judy | 575.00 | processed | 2025-04-03 08:17:42 |
| 34 | Judy | 575.00 | processed | 2025-04-03 08:17:42 |
| 35 | David | 575.01 | processed | 2025-04-03 08:17:42 |
| 36 | Bob | 575.01 | processed | 2025-04-03 08:17:42 |
| 37 | Charlie | 575.00 | processed | 2025-04-03 08:17:42 |
| 38 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 39 | Grace | 575.00 | processed | 2025-04-03 08:17:42 |
| 40 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 41 | David | 575.00 | processed | 2025-04-03 08:17:42 |
| 42 | Charlie | 575.01 | processed | 2025-04-03 08:17:42 |
| 43 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 44 | Grace | 575.00 | processed | 2025-04-03 08:17:42 |
| 45 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 46 | Frank | 575.01 | processed | 2025-04-03 08:17:42 |
| 47 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 48 | Eve | 575.00 | processed | 2025-04-03 08:17:42 |
| 49 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 50 | Frank | 575.01 | processed | 2025-04-03 08:17:42 |
| 51 | Bob | 575.01 | processed | 2025-04-03 08:17:42 |
| 52 | Heidi | 575.01 | processed | 2025-04-03 08:17:42 |
| 53 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 54 | David | 575.01 | processed | 2025-04-03 08:17:42 |
| 55 | Grace | 575.01 | processed | 2025-04-03 08:17:42 |
| 56 | Judy | 575.01 | processed | 2025-04-03 08:17:42 |
| 57 | Eve | 575.00 | processed | 2025-04-03 08:17:42 |
| 58 | David | 575.00 | processed | 2025-04-03 08:17:42 |
| 59 | Bob | 575.01 | processed | 2025-04-03 08:17:42 |
| 60 | Judy | 575.01 | processed | 2025-04-03 08:17:42 |
| 61 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 62 | Eve | 575.00 | processed | 2025-04-03 08:17:42 |
| 63 | David | 575.01 | processed | 2025-04-03 08:17:42 |
| 64 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 65 | Charlie | 575.01 | processed | 2025-04-03 08:17:42 |
| 66 | Judy | 575.00 | processed | 2025-04-03 08:17:42 |
| 67 | Charlie | 575.00 | processed | 2025-04-03 08:17:42 |
| 68 | Judy | 575.01 | processed | 2025-04-03 08:17:42 |
| 69 | Bob | 575.00 | processed | 2025-04-03 08:17:42 |
| 70 | Bob | 575.00 | processed | 2025-04-03 08:17:42 |
| 71 | Charlie | 575.00 | processed | 2025-04-03 08:17:42 |
| 72 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 73 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 74 | Charlie | 575.00 | processed | 2025-04-03 08:17:42 |
| 75 | Bob | 575.00 | processed | 2025-04-03 08:17:42 |
| 76 | Charlie | 575.00 | processed | 2025-04-03 08:17:42 |
| 77 | Heidi | 575.01 | processed | 2025-04-03 08:17:42 |
| 78 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 79 | Charlie | 575.00 | processed | 2025-04-03 08:17:42 |
| 80 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 81 | Frank | 575.01 | processed | 2025-04-03 08:17:42 |
| 82 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 83 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 84 | David | 575.00 | processed | 2025-04-03 08:17:42 |
| 85 | David | 575.00 | processed | 2025-04-03 08:17:42 |
| 86 | Heidi | 575.00 | processed | 2025-04-03 08:17:42 |
| 87 | Alice | 575.00 | processed | 2025-04-03 08:17:42 |
| 88 | Frank | 575.00 | processed | 2025-04-03 08:17:42 |
| 89 | Judy | 575.00 | processed | 2025-04-03 08:17:42 |
| 90 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 91 | Heidi | 575.01 | processed | 2025-04-03 08:17:42 |
| 92 | Eve | 575.01 | processed | 2025-04-03 08:17:42 |
| 93 | Ivan | 575.01 | processed | 2025-04-03 08:17:42 |
| 94 | Alice | 575.01 | processed | 2025-04-03 08:17:42 |
| 95 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 96 | Bob | 575.00 | processed | 2025-04-03 08:17:42 |
| 97 | Ivan | 575.00 | processed | 2025-04-03 08:17:42 |
| 98 | Bob | 575.00 | processed | 2025-04-03 08:17:42 |
| 99 | Grace | 575.00 | processed | 2025-04-03 08:17:42 |
| 100 | Ivan | 575.01 | processed | 2025-04-03 08:17:42 |
+-----+---------------+--------------+-----------+---------------------+
100 rows in set (0.00 sec)
#调整处理程序的副本数为0
[root@k8s-master01 ~]# k scale deploy update-orders --replicas=0
#验证查看
[root@k8s-master01 ~]# kg deploy update-orders
NAME READY UP-TO-DATE AVAILABLE AGE
update-orders 0/0 0 0 6m2s
2.3.2 开始实战
1、创建TriggerAuthentication和Secret
#定义资源文件
[root@k8s-master01 ~]# vim mysql-ta.yaml
apiVersion: v1
kind: Secret
metadata:
name: keda-mysql-secret
stringData:
mysql_conn_str: root:password@tcp(mysql:3306)/dukuan
---
apiVersion: keda.sh/v1alpha1
kind: TriggerAuthentication
metadata:
name: keda-trigger-auth-mysql-conn
spec:
secretTargetRef:
- parameter: connectionString
name: keda-mysql-secret
key: mysql_conn_str
#创建资源
[root@k8s-master01 ~]# kaf mysql-ta.yaml
#查看资源
[root@k8s-master01 ~]# kg -f mysql-ta.yaml
NAME TYPE DATA AGE
secret/keda-mysql-secret Opaque 1 11s
NAME PODIDENTITY SECRET ENV VAULTADDRESS
triggerauthentication.keda.sh/keda-trigger-auth-mysql-conn keda-mysql-secret
2、创建ScaledObject
#定义资源文件
[root@k8s-master01 ~]# vim mysql-so.yaml
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
name: mysql-scaledobject
spec:
scaleTargetRef:
name: update-orders
pollingInterval: 5
cooldownPeriod: 30
minReplicaCount: 0
maxReplicaCount: 5
triggers:
- type: mysql
metadata:
queryValue: "4.4"
query: "SELECT COUNT(*) FROM orders WHERE status='pending'"
authenticationRef:
name: keda-trigger-auth-mysql-conn
#创建资源
[root@k8s-master01 ~]# kaf mysql-so.yaml
#查看so
[root@k8s-master01 ~]# kg so | grep mysql
mysql-scaledobject apps/v1.Deployment update-orders 0 5 False Unknown False Unknown 4m46s
3、重新插入数据
[root@k8s-master01 ~]# k create job insert-orders-job2 --image=registry.cn-hangzhou.aliyuncs.com/abroad_images/mysql:insert
4、等待30s后查看pod,观察到pod已经被扩容
[root@k8s-master01 ~]# kgp
2.3.3 环境清理
k delete deploy mysql update-orders
k delete svc mysql
k delete job insert-orders-job insert-orders-job2
k delete -f mysql-ta.yaml -f mysql-so.yaml
2.4 使用ScaledJob处理任务与环境清理
KEDA可以使用ScaledJob实现单次或者临时的任务处理,用来处理一些数据,比如图片、视频等。
假设有一个需求,需要从Redis队列获取数据,然后进行处理,就可以使用ScaledJob实现。
2.4.1 创建测试资源
创建一个Redis实例
#添加helm的repo源
[root@k8s-master01 ~]# helm repo add bitnami https://charts.bitnami.com/bitnami
#验证是否添加成功
[root@k8s-master01 ~]# helm repo list | grep bitnami
bitnami https://charts.bitnami.com/bitnami
#下载redis实例
[root@k8s-master01 ~]# helm upgrade --install redis bitnami/redis --version 20.1.6 --set global.imageRegistry=docker.kubeasy.com --set architecture=standalone --set persistence.enabled=false --set master.persistence.enabled=false --set auth.password=dukuan
#验证redis实例
[root@k8s-master01 ~]# kgp | grep redis
redis-master-0 1/1 Running 0 3m8s
2.4.2 开始实战
1、创建TriggerAuthentication和Secret
#定义资源文件
[root@k8s-master01 ~]# vim redis-ta.yaml
apiVersion: v1
kind: Secret
metadata:
name: keda-redis-secret
stringData:
redis_username: ""
redis_password: "dukuan"
---
apiVersion: keda.sh/v1alpha1
kind: TriggerAuthentication
metadata:
name: keda-trigger-auth-redis-conn
spec:
secretTargetRef:
- parameter: username
name: keda-redis-secret
key: redis_username
- parameter: password
name: keda-redis-secret
key: redis_password
#创建资源
[root@k8s-master01 ~]# kaf redis-ta.yaml
#查看资源
[root@k8s-master01 ~]# kg -f redis-ta.yaml
NAME TYPE DATA AGE
secret/keda-redis-secret Opaque 2 43s
NAME PODIDENTITY SECRET ENV VAULTADDRESS
triggerauthentication.keda.sh/keda-trigger-auth-redis-conn keda-redis-secret
2、写入测试数据
#写入测试数据
[root@k8s-master01 ~]# k exec -it redis-master-0 -- bash
I have no name!@redis-master-0:/$ redis-cli -h redis-master -a dukuan
redis-master:6379> LPUSH test_list "t1" "t2" "t3"
(integer) 3
#查看全部数据
redis-master:6379> LRANGE test_list 0 -1
1) "t3"
2) "t2"
3) "t1"
#读取数据
redis-master:6379> RPOP test_list
"t1"
redis-master:6379> LPOP test_list
"t3"
2、创建ScaledJob监听数据
#定义资源文件
[root@k8s-master01 ~]# vim redis-sj.yaml
apiVersion: keda.sh/v1alpha1
kind: ScaledJob
metadata:
name: redis-queue-scaledjob
spec:
jobTargetRef:
parallelism: 1
completions: 1
backoffLimit: 4
template:
spec:
containers:
- name: redis-queue-consumer
image: registry.cn-hangzhou.aliyuncs.com/abroad_images/redis:process
pollingInterval: 30
successfulJobsHistoryLimit: 3
failedJobsHistoryLimit: 3
maxReplicaCount: 5
successfulJobsHistoryLimit: 3
failedJobsHistoryLimit: 3
triggers:
- type: redis
metadata:
address: redis-master.default.svc.cluster.local:6379
listName: test_list
listLength: '5'
authenticationRef:
name: keda-trigger-auth-redis-conn
#创建资源
[root@k8s-master01 ~]# kaf redis-sj.yaml
#查看sj
[root@k8s-master01 ~]# kg sj | grep redis
redis-queue-scaledjob 5 True False Unknown 4m59s
3、写入测试数据
[root@k8s-master01 ~]# k exec -it redis-master-0 -- bash
I have no name!@redis-master-0:/$ redis-cli -h redis-master -a dukuan
redis-master:6379> LPUSH test_list "t1" "t2" "t3"
redis-master:6379> LPUSH test_list "t1" "t2" "t3"
redis-master:6379> LPUSH test_list "t1" "t2" "t3"
redis-master:6379> LPUSH test_list "t1" "t2" "t3"
redis-master:6379> LPUSH test_list "t1" "t2" "t3"
redis-master:6379> LPUSH test_list "t1" "t2" "t3"
redis-master:6379> LPUSH test_list "t1" "t2" "t3"
4、查看ScaledJob任务，观察到已经开始扩容
[root@k8s-master01 ~]# kgp | grep redis-queue-scaledjob
redis-queue-scaledjob-ltmds-5st29 0/1 Completed 0 102s
redis-queue-scaledjob-lz5jn-mfpbq 0/1 Completed 0 102s
redis-queue-scaledjob-mj57n-lffsj 0/1 Completed 0 102s
2.4.3 环境清理
#卸载redis
[root@k8s-master01 ~]# helm uninstall redis
#删除
[root@k8s-master01 ~]# kubectl delete -f redis-ta.yaml -f redis-sj.yaml
添加helm源
[root@k8s-master01 ~]# helm repo add kedacore https://kedacore.github.io/charts
更新helm源
[root@k8s-master01 ~]# helm repo update
Hang tight while we grab the latest from your chart repositories…
…Successfully got an update from the “ot-helm” chart repository
…Successfully got an update from the “kedacore” chart repository
Update Complete. ⎈Happy Helming!⎈
2、安装KEDA
```shell
[root@k8s-master01 ~]# helm install keda kedacore/keda --namespace keda --create-namespace
...
...
Learn more about KEDA:
- Documentation: https://keda.sh/
- Support: https://keda.sh/support/
- File an issue: https://github.com/kedacore/keda/issues/new/choose
3、查看服务状态
[root@k8s-master01 ~]# kgp -n keda
2.5.1.2 Helm离线安装
1、添加KEDA的Helm源
#添加helm源
[root@k8s-master01 ~]# helm repo add kedacore https://kedacore.github.io/charts
#更新helm源
[root@k8s-master01 ~]# helm repo update
Hang tight while we grab the latest from your chart repositories...
...Successfully got an update from the "ot-helm" chart repository
...Successfully got an update from the "kedacore" chart repository
Update Complete. ⎈Happy Helming!⎈
2、下载并解压keda包
#下载keda包
[root@k8s-master01 ~]# helm pull kedacore/keda --version 2.16.1
#解压keda包
[root@k8s-master01 ~]# tar xf keda-2.16.1.tgz
3、创建ns
[root@k8s-master01 ~]# kubectl create ns keda
4、修改values.yaml文件
[root@k8s-master01 ~]# vim /root/keda/values.yaml
...
...
#修改第13行内容
13 registry: registry.cn-hangzhou.aliyuncs.com
#修改第15行内容
15 repository: github_images1024/keda
#修改第17行内容
17 tag: "2.16.1"
#修改第20行内容
20 registry: registry.cn-hangzhou.aliyuncs.com
#修改第22行内容
22 repository: github_images1024/keda-metrics-apiserver
#修改第24行内容
24 tag: "2.16.1"
#修改第27行内容
27 registry: registry.cn-hangzhou.aliyuncs.com
#修改第29行内容
29 repository: github_images1024/keda-admission-webhooks
#修改第31行内容
31 tag: "2.16.1"
完整values.yaml文件
[root@k8s-master01 ~]# egrep -v "^#|^$|#" /root/keda/values.yaml
global:
image:
registry: null
image:
keda:
registry: registry.cn-hangzhou.aliyuncs.com
repository: github_images1024/keda
tag: "2.16.1"
metricsApiServer:
registry: registry.cn-hangzhou.aliyuncs.com
repository: github_images1024/keda-metrics-apiserver
tag: "2.16.1"
webhooks:
registry: registry.cn-hangzhou.aliyuncs.com
repository: github_images1024/keda-admission-webhooks
tag: "2.16.1"
pullPolicy: Always
clusterName: kubernetes-default
clusterDomain: cluster.local
crds:
install: true
additionalAnnotations:
{}
watchNamespace: ""
imagePullSecrets: []
networkPolicy:
enabled: false
flavor: "cilium"
cilium:
operator:
extraEgressRules: []
operator:
name: keda-operator
revisionHistoryLimit: 10
replicaCount: 1
disableCompression: true
affinity: {}
extraContainers: []
extraInitContainers: []
livenessProbe:
initialDelaySeconds: 25
periodSeconds: 10
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
readinessProbe:
initialDelaySeconds: 20
periodSeconds: 3
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
metricsServer:
revisionHistoryLimit: 10
replicaCount: 1
disableCompression: true
dnsPolicy: ClusterFirst
useHostNetwork: false
affinity: {}
livenessProbe:
initialDelaySeconds: 5
periodSeconds: 10
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
readinessProbe:
initialDelaySeconds: 5
periodSeconds: 3
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
webhooks:
enabled: true
port: ""
healthProbePort: 8081
livenessProbe:
initialDelaySeconds: 25
periodSeconds: 10
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
readinessProbe:
initialDelaySeconds: 20
periodSeconds: 3
timeoutSeconds: 1
failureThreshold: 3
successThreshold: 1
useHostNetwork: false
name: keda-admission-webhooks
revisionHistoryLimit: 10
replicaCount: 1
affinity: {}
failurePolicy: Ignore
upgradeStrategy:
operator: {}
metricsApiServer: {}
webhooks: {}
podDisruptionBudget:
operator: {}
metricServer: {}
webhooks: {}
additionalLabels:
{}
additionalAnnotations:
{}
podAnnotations:
keda: {}
metricsAdapter: {}
webhooks: {}
podLabels:
keda: {}
metricsAdapter: {}
webhooks: {}
rbac:
create: true
aggregateToDefaultRoles: false
enabledCustomScaledRefKinds: true
controlPlaneServiceAccountsNamespace: kube-system
scaledRefKinds:
- apiGroup: "*"
kind: "*"
serviceAccount:
operator:
create: true
name: keda-operator
automountServiceAccountToken: true
annotations: {}
metricServer:
create: true
name: keda-metrics-server
automountServiceAccountToken: true
annotations: {}
webhooks:
create: true
name: keda-webhook
automountServiceAccountToken: true
annotations: {}
podIdentity:
azureWorkload:
enabled: false
clientId: ""
tenantId: ""
tokenExpiration: 3600
aws:
irsa:
enabled: false
audience: "sts.amazonaws.com"
roleArn: ""
stsRegionalEndpoints: "true"
tokenExpiration: 86400
gcp:
enabled: false
gcpIAMServiceAccount: ""
grpcTLSCertsSecret: ""
hashiCorpVaultTLS: ""
logging:
operator:
level: info
format: console
timeEncoding: rfc3339
stackTracesEnabled: false
metricServer:
level: 0
stderrthreshold: ERROR
webhooks:
level: info
format: console
timeEncoding: rfc3339
securityContext:
operator:
capabilities:
drop:
- ALL
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
seccompProfile:
type: RuntimeDefault
metricServer:
capabilities:
drop:
- ALL
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
seccompProfile:
type: RuntimeDefault
webhooks:
capabilities:
drop:
- ALL
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
seccompProfile:
type: RuntimeDefault
podSecurityContext:
operator:
runAsNonRoot: true
metricServer:
runAsNonRoot: true
webhooks:
runAsNonRoot: true
service:
type: ClusterIP
portHttps: 443
portHttpsTarget: 6443
annotations: {}
resources:
operator:
limits:
cpu: 1
memory: 1000Mi
requests:
cpu: 100m
memory: 100Mi
metricServer:
limits:
cpu: 1
memory: 1000Mi
requests:
cpu: 100m
memory: 100Mi
webhooks:
limits:
cpu: 1
memory: 1000Mi
requests:
cpu: 100m
memory: 100Mi
nodeSelector: {}
tolerations: []
topologySpreadConstraints:
operator: []
metricsServer: []
webhooks: []
affinity: {}
priorityClassName: ""
http:
timeout: 3000
keepAlive:
enabled: true
minTlsVersion: TLS12
profiling:
operator:
enabled: false
port: 8082
metricsServer:
enabled: false
port: 8083
webhooks:
enabled: false
port: 8084
extraArgs:
keda: {}
metricsAdapter: {}
env: []
volumes:
keda:
extraVolumes: []
extraVolumeMounts: []
metricsApiServer:
extraVolumes: []
extraVolumeMounts: []
webhooks:
extraVolumes: []
extraVolumeMounts: []
prometheus:
metricServer:
enabled: false
port: 8080
portName: metrics
serviceMonitor:
enabled: false
jobLabel: ""
targetLabels: []
podTargetLabels: []
port: metrics
targetPort: ""
interval: ""
scrapeTimeout: ""
relabellings: []
relabelings: []
metricRelabelings: []
additionalLabels: {}
scheme: http
tlsConfig: {}
podMonitor:
enabled: false
interval: ""
scrapeTimeout: ""
namespace: ""
additionalLabels: {}
relabelings: []
metricRelabelings: []
operator:
enabled: false
port: 8080
serviceMonitor:
enabled: false
jobLabel: ""
targetLabels: []
podTargetLabels: []
port: metrics
targetPort: ""
interval: ""
scrapeTimeout: ""
relabellings: []
relabelings: []
metricRelabelings: []
additionalLabels: {}
scheme: http
tlsConfig: {}
podMonitor:
enabled: false
interval: ""
scrapeTimeout: ""
namespace: ""
additionalLabels: {}
relabelings: []
metricRelabelings: []
prometheusRules:
enabled: false
namespace: ""
additionalLabels: {}
alerts:
[]
webhooks:
enabled: false
port: 8080
serviceMonitor:
enabled: false
jobLabel: ""
targetLabels: []
podTargetLabels: []
port: metrics
targetPort: ""
interval: ""
scrapeTimeout: ""
relabellings: []
relabelings: []
metricRelabelings: []
additionalLabels: {}
scheme: http
tlsConfig: {}
prometheusRules:
enabled: false
namespace: ""
additionalLabels: {}
alerts: []
opentelemetry:
collector:
uri: ""
operator:
enabled: false
certificates:
autoGenerated: true
secretName: kedaorg-certs
mountPath: /certs
certManager:
enabled: false
generateCA: true
caSecretName: "kedaorg-ca"
secretTemplate: {}
issuer:
generate: true
name: foo-org-ca
kind: ClusterIssuer
group: cert-manager.io
operator:
permissions:
metricServer:
restrict:
secret: false
operator:
restrict:
secret: false
namesAllowList: []
extraObjects: []
asciiArt: true
customManagedBy: ""
5、安装keda
[root@k8s-master01 keda]# helm install keda . -n keda
查看资源
#查看pod
[root@k8s-master01 keda]# kgp -n keda
NAME READY STATUS RESTARTS AGE
keda-admission-webhooks-9664c747b-rxk88 1/1 Running 0 46s
keda-operator-848cf7589c-swfzd 1/1 Running 1 (42s ago) 46s
keda-operator-metrics-apiserver-7bc7d5755b-zdkbm 1/1 Running 0 46s
#查看crd
[root@k8s-master01 ~]# kg crd | grep keda
cloudeventsources.eventing.keda.sh 2025-04-03T03:49:23Z
clustercloudeventsources.eventing.keda.sh 2025-04-03T03:49:23Z
clustertriggerauthentications.keda.sh 2025-04-03T03:49:23Z
scaledjobs.keda.sh 2025-04-03T03:49:23Z
scaledobjects.keda.sh 2025-04-03T03:49:23Z
triggerauthentications.keda.sh 2025-04-03T03:49:23Z
#查看api-resources
[root@k8s-master01 ~]# kubectl api-resources | grep keda
cloudeventsources eventing.keda.sh/v1alpha1 true CloudEventSource
clustercloudeventsources eventing.keda.sh/v1alpha1 false ClusterCloudEventSource
clustertriggerauthentications cta,clustertriggerauth keda.sh/v1alpha1 false ClusterTriggerAuthentication
scaledjobs sj keda.sh/v1alpha1 true ScaledJob
scaledobjects so keda.sh/v1alpha1 true ScaledObject
triggerauthentications ta,triggerauth keda.sh/v1alpha1 true TriggerAuthentication
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