内存
要使用基于内存或者自定义指标进行扩缩容(现在的版本都必须依赖 metrics-server 这个项目)。现在我们再用 Deployment 来创建一个 Nginx Pod,然后利用 HPA 来进行自动扩缩容。资源清单如下所示:(hpa-mem-demo.yaml)
apiVersion: apps/v1
kind: Deployment
metadata:
name: hpa-mem-demo
spec:
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
volumes:
- name: increase-mem-script
configMap:
name: increase-mem-config
containers:
- name: nginx
image: nginx
ports:
- containerPort: 80
volumeMounts:
- name: increase-mem-script
mountPath: /etc/script
resources:
requests:
memory: 50Mi
cpu: 50m
securityContext:
privileged: true
这里和前面普通的应用有一些区别,我们将一个名为 increase-mem-config
的 ConfigMap 资源对象挂载到了容器中,该配置文件是用于后面增加容器内存占用的脚本,配置文件如下所示:(increase-mem-cm.yaml)
apiVersion: v1
kind: ConfigMap
metadata:
name: increase-mem-config
data:
increase-mem.sh: |
#!/bin/bash
mkdir /tmp/memory
mount -t tmpfs -o size=40M tmpfs /tmp/memory
dd if=/dev/zero of=/tmp/memory/block
sleep 60
rm /tmp/memory/block
umount /tmp/memory
rmdir /tmp/memory
由于这里增加内存的脚本需要使用到 mount
命令,这需要声明为特权模式,所以我们添加了 securityContext.privileged=true
这个配置。现在我们直接创建上面的资源对象即可:
$ kubectl apply -f increase-mem-cm.yaml
$ kubectl apply -f hpa-mem-demo.yaml
$ kubectl get pods -l app=nginx
NAME READY STATUS RESTARTS AGE
hpa-mem-demo-66944b79bf-tqrn9 1/1 Running 0 35s
然后需要创建一个基于内存的 HPA 资源对象:(hpa-mem.yaml)
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
name: nginx-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: hpa-mem-demo
minReplicas: 1
maxReplicas: 5
metrics:
- type: Resource
resource:
name: memory
targetAverageUtilization: 60
要注意这里使用的 apiVersion
是 autoscaling/v2beta1
,然后 metrics
属性里面指定的是内存的配置,直接创建上面的资源对象即可:
$ kubectl apply -f hpa-mem.yaml
horizontalpodautoscaler.autoscaling/nginx-hpa created
$ kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
nginx-hpa Deployment/hpa-mem-demo 2%/60% 1 5 1 12s
到这里证明 HPA 资源对象已经部署成功了,接下来我们对应用进行压测,将内存压上去,直接执行上面我们挂载到容器中的 increase-mem.sh
脚本即可:
$ kubectl exec -it hpa-mem-demo-66944b79bf-tqrn9 /bin/bash
root@hpa-mem-demo-66944b79bf-tqrn9:/# ls /etc/script/
increase-mem.sh
root@hpa-mem-demo-66944b79bf-tqrn9:/# source /etc/script/increase-mem.sh
dd: writing to '/tmp/memory/block': No space left on device
81921+0 records in
81920+0 records out
41943040 bytes (42 MB, 40 MiB) copied, 0.584029 s, 71.8 MB/s
然后打开另外一个终端观察 HPA 资源对象的变化情况:
$ kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
nginx-hpa Deployment/hpa-mem-demo 83%/60% 1 5 1 5m3s
$ kubectl describe hpa nginx-hpa
Name: nginx-hpa
Namespace: default
Labels: <none>
Annotations: kubectl.kubernetes.io/last-applied-configuration:
{"apiVersion":"autoscaling/v2beta1","kind":"HorizontalPodAutoscaler","metadata":{"annotations":{},"name":"nginx-hpa","namespace":"default"...
CreationTimestamp: Tue, 07 Apr 2020 13:13:59 +0800
Reference: Deployment/hpa-mem-demo
Metrics: ( current / target )
resource memory on pods (as a percentage of request): 3% (1740800) / 60%
Min replicas: 1
Max replicas: 5
Deployment pods: 2 current / 2 desired
Conditions:
Type Status Reason Message
---- ------ ------ -------
AbleToScale True ScaleDownStabilized recent recommendations were higher than current one, applying the highest recent recommendation
ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from memory resource utilization (percentage of request)
ScalingLimited False DesiredWithinRange the desired count is within the acceptable range
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Warning FailedGetResourceMetric 5m26s (x3 over 5m58s) horizontal-pod-autoscaler unable to get metrics for resource memory: no metrics returned from resource metrics API
Warning FailedComputeMetricsReplicas 5m26s (x3 over 5m58s) horizontal-pod-autoscaler invalid metrics (1 invalid out of 1), first error is: failed to get memory utilization: unable to get metrics for resource memory: no metrics returned from resource metrics API
Normal SuccessfulRescale 77s horizontal-pod-autoscaler New size: 2; reason: memory resource utilization (percentage of request) above target
$ kubectl top pod hpa-mem-demo-66944b79bf-tqrn9
NAME CPU(cores) MEMORY(bytes)
hpa-mem-demo-66944b79bf-tqrn9 0m 41Mi
可以看到内存使用已经超过了我们设定的 60% 这个阈值了,HPA 资源对象也已经触发了自动扩容,变成了两个副本了:
$ kubectl get pods -l app=nginx
NAME READY STATUS RESTARTS AGE
hpa-mem-demo-66944b79bf-8m4d9 1/1 Running 0 2m51s
hpa-mem-demo-66944b79bf-tqrn9 1/1 Running 0 8m11s
当内存释放掉后,controller-manager 默认5分钟过后会进行缩放,到这里就完成了基于内存的 HPA 操作。