标签：10 示例 hpa demoapp Deployment HPA k8s demoappv10 度量
web服务
depoly-demoapp-v10.yaml
apiVersion: v1
kind: Namespace
metadata:
name: hpa-demoapp
---
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: demoappv10
name: demoappv10
namespace: hpa-demoapp
spec:
#replicas: 1
selector:
matchLabels:
app: demoappv10
strategy: {}
template:
metadata:
creationTimestamp: null
labels:
app: demoappv10
spec:
containers:
- image: registry.k8s.io/hpa-example
name: demoapp
resources:
limits:
cpu: 500m
memory: "256Mi"
requests:
cpu: 200m
memory: "256Mi"
---
apiVersion: v1
kind: Service
metadata:
labels:
app: demoappv10-svc
name: demoappv10-svc
namespace: hpa-demoapp
spec:
ports:
- name: http-8080
port: 8080
protocol: TCP
targetPort: 80
selector:
app: demoappv10
type: ClusterIP
创建资源
# kubectl apply -f depoly-demoapp-v10.yaml
namespace/hpa-demoapp created
deployment.apps/demoappv10 created
service/demoappv10-svc created
查看资源
查看pod
# kubectl get pod -n hpa-demoapp
NAME READY STATUS RESTARTS AGE
demoappv10-cdf9995cb-s54n8 1/1 Running 0 43s
查看svc
# kubectl get svc -n hpa-demoapp
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
demoappv10-svc ClusterIP 10.100.1.117 <none> 8080/TCP 10s
访问资源
# curl `kubectl get svc/demoappv10-svc -n hpa-demoapp -o jsonpath="{.spec.clusterIP}"`:8080
OK!
基于单指标自动扩缩
hpa-demoapp.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: hpa-demoapp
namespace: hpa-demoapp
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: demoappv10
minReplicas: 1
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 50
创建hpa资源
# kubectl apply -f hpa-demoapp.yaml
horizontalpodautoscaler.autoscaling/hpa-demoapp created
查看hpa资源
# kubectl get hpa -n hpa-demoapp
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa-demoapp Deployment/demoappv10 0%/50% 1 10 1 47s
请注意当前的 CPU 利用率是 0%
增加负载
访问服务
# while sleep 0.01; do curl `kubectl get svc/demoappv10-svc -n hpa-demoapp -o jsonpath="{.spec.clusterIP}"`:8080;done
OK!OK!OK!OK!OK!......
观察cpu使用情况
# kubectl get hpa/hpa-demoapp -n hpa-demoapp -w
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa-demoapp Deployment/demoappv10 2%/50% 1 10 1 3m12s
hpa-demoapp Deployment/demoappv10 84%/50% 1 10 1 3m45s
hpa-demoapp Deployment/demoappv10 198%/50% 1 10 2 4m
hpa-demoapp Deployment/demoappv10 176%/50% 1 10 4 4m16s
hpa-demoapp Deployment/demoappv10 93%/50% 1 10 4 4m31s
hpa-demoapp Deployment/demoappv10 103%/50% 1 10 4 4m46s
hpa-demoapp Deployment/demoappv10 98%/50% 1 10 4 5m1s
hpa-demoapp Deployment/demoappv10 93%/50% 1 10 4 5m16s
hpa-demoapp Deployment/demoappv10 70%/50% 1 10 4 5m31s
hpa-demoapp Deployment/demoappv10 60%/50% 1 10 4 5m46s
hpa-demoapp Deployment/demoappv10 54%/50% 1 10 4 6m1s
hpa-demoapp Deployment/demoappv10 55%/50% 1 10 4 6m16s
hpa-demoapp Deployment/demoappv10 53%/50% 1 10 5 6m31s
hpa-demoapp Deployment/demoappv10 44%/50% 1 10 5 6m46s
hpa-demoapp Deployment/demoappv10 43%/50% 1 10 5 7m1s
hpa-demoapp Deployment/demoappv10 41%/50% 1 10 5 7m16s
hpa-demoapp Deployment/demoappv10 43%/50% 1 10 5 7m31s
hpa-demoapp Deployment/demoappv10 42%/50% 1 10 5 7m46s
查看pod数量
# kubectl get pod -n hpa-demoapp
NAME READY STATUS RESTARTS AGE
demoappv10-57fc7f894c-8mzbf 1/1 Running 0 49s
demoappv10-57fc7f894c-8pmxr 1/1 Running 0 3m4s
demoappv10-57fc7f894c-drv9r 1/1 Running 0 7m5s
demoappv10-57fc7f894c-ls965 1/1 Running 0 3m5s
demoappv10-57fc7f894c-mhblr 1/1 Running 0 3m20s
查看HPA日志
# kubectl describe hpa/hpa-demoapp -n hpa-demoapp
....
Normal SuccessfulRescale 6m38s horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target
Normal SuccessfulRescale 6m23s horizontal-pod-autoscaler New size: 4; reason: cpu resource utilization (percentage of request) above target
Normal SuccessfulRescale 4m7s horizontal-pod-autoscaler New size: 5; reason: cpu resource utilization (percentage of request) above target
停止产生负载
停止访问服务
输入 <Ctrl> + C 来终止负载的产生。
观察cpu使用情况
# kubectl get hpa/hpa-demoapp -n hpa-demoapp -w
...
hpa-demoapp Deployment/demoappv10 4%/50% 1 10 5 14m
hpa-demoapp Deployment/demoappv10 2%/50% 1 10 5 15m
查看pod数量
自动扩缩完成副本数量的改变可能需要几分钟的时间。
# kubectl get pod -n hpa-demoapp
NAME READY STATUS RESTARTS AGE
demoappv10-57fc7f894c-drv9r 1/1 Running 0 20m
查看HPA日志
# kubectl describe hpa/hpa-demoapp -n hpa-demoapp
....
Normal SuccessfulRescale 6m38s horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target
Normal SuccessfulRescale 6m23s horizontal-pod-autoscaler New size: 4; reason: cpu resource utilization (percentage of request) above target
Normal SuccessfulRescale 4m7s horizontal-pod-autoscaler New size: 5; reason: cpu resource utilization (percentage of request) above target
Normal SuccessfulRescale 2m18s horizontal-pod-autoscaler New size: 4; reason: All metrics below target
Normal SuccessfulRescale 2m2s horizontal-pod-autoscaler New size: 1; reason: All metrics below target
基于多项度量指标自动扩缩
CPU 利用率这个度量指标是一个 resource metric（资源度量指标），因为它表示容器上指定资源的百分比。 除 CPU 外，你还可以指定其他资源度量指标。默认情况下，目前唯一支持的其他资源度量指标为内存。 只要 metrics.k8s.io API 存在，这些资源度量指标就是可用的，并且他们不会在不同的 Kubernetes 集群中改变名称。
hpa-v2.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: php-apache
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: php-apache
minReplicas: 1
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 50
- type: Resource
resource:
name: memory
target:
type: AverageValue
averageValue: 30Mi
HorizontalPodAutoscaler 将会尝试确保每个 Pod 的 CPU 利用率在 50% 以内，可用内存保持在30Mi以上。
基于自定义度量指标自动扩缩
你还可以指定资源度量指标使用绝对数值，而不是百分比，你需要将 target.type 从 Utilization 替换成 AverageValue，同时设置 target.averageValue 而非 target.averageUtilization 的值。
还有两种其他类型的度量指标，他们被认为是 custom metrics（自定义度量指标）： 即 Pod 度量指标和 Object 度量指标。 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。
hpa-v2.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: php-apache
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: php-apache
minReplicas: 1
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 50
- type: Pods
pods:
metric:
name: packets-per-second
target:
type: AverageValue
averageValue: 1k
- type: Object
object:
metric:
name: requests-per-second
describedObject:
apiVersion: networking.k8s.io/v1
kind: Ingress
name: main-route
target:
type: Value
value: 10k
- type: External
external:
metric:
name: queue_messages_ready
selector:
matchLabels:
queue: "worker_tasks"
target:
type: AverageValue
averageValue: 30
HorizontalPodAutoscaler 将会尝试确保每个 Pod 的 CPU 利用率在 50% 以内， 每秒能够服务 1000 个数据包请求， 并确保所有在 Ingress 后的 Pod 每秒能够服务的请求总数达到 10000 个。
基于更特别的度量值来扩缩
许多度量流水线允许你通过名称或附加的 标签 来描述度量指标。 对于所有非资源类型度量指标（Pod、Object 和后面将介绍的 External）， 可以额外指定一个标签选择算符。例如，如果你希望收集包含 verb 标签的 http_requests 度量指标，可以按如下所示设置度量指标块，使得扩缩操作仅针对 GET 请求执行：
- type: Object
object:
metric:
name: http_requests
selector: {matchLabels: {verb: GET}}
这个选择算符使用与 Kubernetes 标签选择算符相同的语法。 如果名称和标签选择算符匹配到多个系列，监测管道会决定如何将多个系列合并成单个值。 选择算符是可以累加的，它不会选择目标以外的对象（类型为 Pods 的目标 Pod 或者类型为 Object 的目标对象）。
运行在 Kubernetes 上的应用程序可能需要基于与 Kubernetes 集群中的任何对象没有明显关系的度量指标进行自动扩缩， 例如那些描述与任何 Kubernetes 名字空间中的服务都无直接关联的度量指标。
使用外部度量指标时，需要了解你所使用的监控系统，相关的设置与使用自定义指标时类似。 外部度量指标使得你可以使用你的监控系统的任何指标来自动扩缩你的集群。 你需要在 metric 块中提供 name 和 selector，同时将类型由 Object 改为 External。 如果 metricSelector 匹配到多个度量指标，HorizontalPodAutoscaler 将会把它们加和。 外部度量指标同时支持 Value 和 AverageValue 类型，这与 Object 类型的度量指标相同。
例如，如果你的应用程序处理来自主机上消息队列的任务， 为了让每 30 个任务有 1 个工作者实例，你可以将下面的内容添加到 HorizontalPodAutoscaler 的配置中。
- type: External
external:
metric:
name: queue_messages_ready
selector:
matchLabels:
queue: "worker_tasks"
target:
type: AverageValue
averageValue: 30
如果可能，还是推荐定制度量指标而不是外部度量指标，因为这便于让系统管理员加固定制度量指标 API。 而外部度量指标 API 可以允许访问所有的度量指标。 当暴露这些服务时，系统管理员需要仔细考虑这个问题。
标签：10,
示例,
hpa,
demoapp,
Deployment,
HPA,
k8s,
demoappv10,
度量
From： https://www.cnblogs.com/wangguishe/p/17480541.html