前言
在kubernetes中，我们使用pod对外提供服务。这时候，我们需要以下两种情形需要关注：
pod因为不明原因挂掉，导致服务不可用
Pod在高负荷的情况下，不能支撑我们的服务
如果我们人工监控pods，人工进行调整副本那么这个工作量无疑是巨大的，但kubernetes已经有了相应的机制来应对了。
那么今天就来介绍一下在k8s 1.6中的弹性伸缩的实施
k8s是kubernetes的官方简称
HPA全称Horizontal Pod Autoscaler
HPA的原理
Kubernetes有一个HPA(Horizontal Pod Autoscaler)的资源，可以实现基于CPU使用率的Pod自动伸缩的功能。HPA基于Master Node上的kube-controller-manager服务启动参数–horizontal-pod-autoscaler-sync-period定义的时长(默认为30秒)，周期性的检测Pod的CPU使用率(需要事先安装heapster)。如果需要设置–horizontal-pod-autoscaler-sync-period可以在Master Node上的/etc/default/kube-controller-manager中修改。
graph TD
A[ms-a] --> B(RC/Deployment)
A1[ms-b] --> B(RC/Deployment)
A3[ms-c] --> B(RC/Deployment)
A4[其他服务] --> B(RC/Deployment)
B --- C(Horizontal Pod Autoscaler)
安装Heapster
K8S从1.8版本开始，CPU、内存等资源的metrics信息可以通过 Metrics API来获取，用户可以直接获取这些metrics信息（例如通过执行kubect top命令），HPA使用这些metics信息来实现动态伸缩，但是在之前我们使用Heapster来收集节点的相关数据
导入相关镜像
我们在实施的时候一般会创建/data目录，把所有的deployment放在此目录下，因此在k8s master创建kube-system目录
[root@master data]# mkdir kube-system
上传相镜像，并导入
# 导入heasper
[root@master kube-system]# docker load < heapster_3.tar
38ac8d0f5bb3: Loading layer [==================================================>] 1.312MB/1.312MB
388f58c4d5b0: Loading layer [==================================================>] 99.87MB/99.87MB
c6772246bc46: Loading layer [==================================================>] 281.1kB/281.1kB
Loaded image: registry.cn-hangzhou.aliyuncs.com/lczean/heapster-amd64-v1.3.0-beta.1:v1.3.0-beta.1
# 导入influxdb数据库
[root@master kube-system]# docker load < influxdb13.tar
7da815924651: Loading layer [==================================================>] 10.48MB/10.48MB
2d447b9e914f: Loading layer [==================================================>] 5.12kB/5.12kB
Loaded image: registry.cn-hangzhou.aliyuncs.com/golden/heapster-influxdb-amd64:latest
查看导入images
[root@master kube-system]# docker images |grep heapster
registry.cn-hangzhou.aliyuncs.com/lczean/heapster-amd64-v1.3.0-beta.1 v1.3.0-beta.1 6393b81e2220 17 months ago 101MB
registry.cn-hangzhou.aliyuncs.com/golden/heapster-influxdb-amd64 latest d3fccbedd180 22 months ago 11.6MB
修改images tag以便我们可以导入到私有registry中
[root@master kube-system]# docker tag registry.cn-hangzhou.aliyuncs.com/lczean/heapster-amd64-v1.3.0-beta.1:v1.3.0-beta.1 registry.k8s.osc:5000/heapster:v1.3.0
[root@master kube-system]# docker tag registry.cn-hangzhou.aliyuncs.com/golden/heapster-influxdb-amd64 registry.k8s.osc:5000/heapster-influxdb
# 查看修改后的images
[root@master kube-system]# docker images |grep heapster
registry.cn-hangzhou.aliyuncs.com/lczean/heapster-amd64-v1.3.0-beta.1 v1.3.0-beta.1 6393b81e2220 17 months ago 101MB
registry.k8s.osc:5000/heapster v1.3.0 6393b81e2220 17 months ago 101MB
registry.cn-hangzhou.aliyuncs.com/golden/heapster-influxdb-amd64 latest d3fccbedd180 22 months ago 11.6MB
registry.k8s.osc:5000/heapster-influxdb latest d3fccbedd180 22 months ago 11.6MB
推送到私有仓库
[root@master kube-system]# docker push registry.k8s.osc:5000/heapster:v1.3.0
The push refers to repository [registry.k8s.osc:5000/heapster]
c6772246bc46: Pushed
388f58c4d5b0: Pushed
38ac8d0f5bb3: Pushed
v1.3.0: digest: sha256:e23b30d2e131e042eec9b5fdc30af905b63e454d140dc335246e74a4e8b4c857 size: 949
[root@master kube-system]# docker push registry.k8s.osc:5000/heapster-influxdb
The push refers to repository [registry.k8s.osc:5000/heapster-influxdb]
2d447b9e914f: Pushed
7da815924651: Pushed
38ac8d0f5bb3: Mounted from heapster
latest: digest: sha256:d2ecd285eb6585d56e8853da7b9fd8f4a57de4a3006f6720173a3f3942c0e7c9 size: 945
influxdb时间序列库介绍
创建deployment
[root@master kube-system]# vim influxdb-deployment.yaml
[root@master kube-system]# vim influxdb-service.yaml
[root@master kube-system]# vim heapster-deployment.yaml
[root@master kube-system]# vim heapster-service.yaml
分别看一下yaml：
influxdb-deployment.yaml
修改image
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: monitoring-influxdb
namespace: kube-system
spec:
replicas: 1
template:
metadata:
labels:
task: monitoring
k8s-app: influxdb
spec:
volumes:
- name: influxdb-storage
emptyDir: {}
containers:
- name: influxdb
image: registry.k8s.osc:5000/heapster-influxdb
volumeMounts:
- mountPath: /data
name: influxdb-storage
influxdb-service.yaml
apiVersion: v1
kind: Service
metadata:
labels:
task: monitoring
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: monitoring-influxdb
name: monitoring-influxdb
namespace: kube-system
spec:
ports:
- name: http
port: 8083
targetPort: 8083
- name: api
port: 8086
targetPort: 8086
selector:
k8s-app: influxdb
创建deployment、service
[root@master kube-system]# kubectl create -f influxdb-deployment.yaml
[root@master kube-system]# kubectl create -f influxdb-service.yaml
安装这两个后查看influxdb坐在的pod ip
[root@master kube-system]# kubectl get pods -n kube-system -o wide
NAME READY STATUS RESTARTS AGE IP NODE
monitoring-influxdb-3696415694-q9tds 1/1 Running 0 16m 172.99.39.6 172.16.187.158
测试安装正常，再安装flanneld的node访问以下链接，如果无报错说明安装成功
[root@node0 ~]# curl http://172.99.39.6:8086/ping
创建heapster-deployment.yaml
修改image、--source、--sink
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: heapster
namespace: kube-system
spec:
replicas: 1
template:
metadata:
labels:
task: monitoring
k8s-app: heapster
version: v6
spec:
containers:
- name: heapster
image: registry.k8s.osc:5000/heapster:v1.3.0
imagePullPolicy: Always
command:
- /heapster
- --source=kubernetes:http://172.16.187.162:8080
- --sink=influxdb:http://172.99.39.6:8086
创建heapster-service.yaml
apiVersion: v1
kind: Service
metadata:
labels:
task: monitoring
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: Heapster
name: heapster
namespace: kube-system
spec:
ports:
- port: 80
targetPort: 8082
selector:
k8s-app: heapster
创建heapster的deployment、service
[root@master kube-system]# kubectl create -f heapster-deployment.yaml
deployment "heapster" created
[root@master kube-system]# kubectl create -f heapster-service.yaml
service "heapster" created
全部安装后可以查看日志是否是正常启动的
[root@master kube-system]# kubectl get pods -n kube-system -o wide
NAME READY STATUS RESTARTS AGE IP NODE
heapster-1258036176-sjg7s 1/1 Running 0 1m 172.99.93.13 172.16.187.160
monitoring-influxdb-3696415694-q9tds 1/1 Running 0 26m 172.99.39.6 172.16.187.158
[root@master kube-system]# kubectl logs -f monitoring-influxdb-3696415694-q9tds -n kube-system
8888888 .d888 888 8888888b. 888888b.
888 d88P" 888 888 "Y88b 888 "88b
888 888 888 888 888 888 .88P
888 88888b. 888888 888 888 888 888 888 888 888 8888888K.
888 888 "88b 888 888 888 888 Y8bd8P' 888 888 888 "Y88b
888 888 888 888 888 888 888 X88K 888 888 888 888
888 888 888 888 888 Y88b 888 .d8""8b. 888 .d88P 888 d88P
8888888 888 888 888 888 "Y88888 888 888 8888888P" 8888888P"
[run] 2018/12/07 05:27:33 InfluxDB starting, version unknown, branch unknown, commit unknown
[run] 2018/12/07 05:27:33 Go version go1.7.4, GOMAXPROCS set to 16
[run] 2018/12/07 05:27:33 Using configuration at: /etc/config.toml
[store] 2018/12/07 05:27:33 Using data dir: /data/data
[subscriber] 2018/12/07 05:27:33 opened service
[monitor] 2018/12/07 05:27:33 Starting monitor system
[monitor] 2018/12/07 05:27:33 'build' registered for diagnostics monitoring
[monitor] 2018/12/07 05:27:33 'runtime' registered for diagnostics monitoring
[monitor] 2018/12/07 05:27:33 'network' registered for diagnostics monitoring
[monitor] 2018/12/07 05:27:33 'system' registered for diagnostics monitoring
[shard-precreation] 2018/12/07 05:27:33 Starting precreation service with check interval of 10m0s, advance period of 30m0s
[snapshot] 2018/12/07 05:27:33 Starting snapshot service
[continuous_querier] 2018/12/07 05:27:33 Starting continuous query service
[httpd] 2018/12/07 05:27:33 Starting HTTP service
[httpd] 2018/12/07 05:27:33 Authentication enabled: false
## heapster
[root@master kube-system]# kubectl logs -f heapster-1258036176-sjg7s -n kube-system
I1207 05:53:00.275512 1 heapster.go:71] /heapster --source=kubernetes:http://172.16.187.162:8080 --sink=influxdb:http://172.99.39.6:8086
I1207 05:53:00.275568 1 heapster.go:72] Heapster version v1.3.0-beta.1
I1207 05:53:00.275794 1 configs.go:61] Using Kubernetes client with master "http://172.16.187.162:8080" and version v1
I1207 05:53:00.275816 1 configs.go:62] Using kubelet port 10255
I1207 05:53:00.283647 1 influxdb.go:252] created influxdb sink with options: host:172.99.39.6:8086 user:root db:k8s
I1207 05:53:00.283680 1 heapster.go:193] Starting with InfluxDB Sink
I1207 05:53:00.283687 1 heapster.go:193] Starting with Metric Sink
I1207 05:53:00.294214 1 heapster.go:105] Starting heapster on port 8082
I1207 05:54:05.082812 1 influxdb.go:215] Created database "k8s" on influxDB server at "172.99.39.6:8086"
最后查看heapster，由于收集数据需要时间，过一段时间后，查看节点的node的监控数据
[root@master ~]# kubectl top node
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
172.16.187.158 121m 0% 19721Mi 30%
172.16.187.159 112m 0% 15805Mi 24%
172.16.187.160 172m 1% 28090Mi 43%
创建HPA
以上步骤都成功的时候，我们可以创建HorizontalPodAutoscaler来管理，下面就用ms-wechat来进行测试
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: ms-wechat # 名称
namespace: default #k8s命名空间
spec:
maxReplicas: 10 # 最大副本数
minReplicas: 3 # 最小副本数
scaleTargetRef:
apiVersion: apps/v1beta1
kind: Deployment
name: ms-wechat # 监控名为ms-wechat的Deployment
targetCPUUtilizationPercentage: 80 # cpu 阈值
查看hpa
[root@master ~]# kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
ms-wechat Deployment/ms-wechat / 80% 3 10 3 10m
大家看到 targets为unknown有两种原因
- 查看原始deployment的resource有没有设置cpu的限制如果没有：
kubectl set resources deployment/ms-wechat --limits=cpu=2000m动态设置 - 等一段时间再查看
查看结果
[root@master ~]# kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
ms-wechat Deployment/ms-wechat 47% / 80% 3 10 3 11m
可以进行压力测试，观察REPLICAS变化