Initial experience of edge computing k8s cluster superedge

Li Guobao 2021-01-21 23:49:28
initial experience edge computing k8s


Preface
There's always a bunch of student hosts on hand , Machines from all kinds of channels .

It's a pain in the management all the time , I don't even remember where they are and what they are IP, Management is a headache .

When I was idle for a while, I wanted to toss about the edge computing cluster solution .

Hope to manage them , Make a general calculation scheme .

Yes dalao, Recommend to me k3s.

K3s | Lightweight Kubernetes | Internet of things and edge computing K8S Solution | Rancher

www.rancher.cn
The truth is very good , however ....

notice Rancher It's both amazing and joyful .

17 In http://ruff.io When it comes to things , The cluster solution uses rancher, Easy to use is easy to use , Many things are true, many things are true .

Experience it , When nodes are assembled into clusters, there are a lot of things to do , And it has its own management master, Used it for a while and gave up .

Later in a fish
@ Small white fish
In one of my conversations , We also see that kubeEdge This set of plans .

https://kubeedge.io/zh/

kubeedge.io
In line with the theme that playing dead machine is not worth life , It must be hugging it .

then ....

I wasted another weekend .

evaluation : Something that can't run well according to the official website documents , It's not worth my time .jpg

Not allowed to gang, I'll ask you again .

PS: Later I saw that it was donated by Huawei , I don't want to make trouble .

later , See a cloud that has been used for a long time out of the public beta of the edge computing cluster .

good heavens ,master I don't have to give it to you , Add your own machine directly to it as node node .

complete k8s Cluster solution , There is no difference between ordinary clusters used in peacetime .

perfect , That's what I want .

Cluster configuration is basically done by clicking on the page .

kubectl See the official or a cloud tutorial OK.

https://kubernetes.io/docs/tasks/tools/install-kubectl/

The cluster access credentials can also be set after downloading to the local .

The way to add nodes is brainless .

edgectl After downloading to local , Execute it. ./edgectl --help have a look

root@nucubuntu:~# ./edgectl --help

Usage:
edgectl command [flags]

Available Commands:
check Check the edge node if to be add to clusters
install Install components to edge node
clear Clear edge node and recovery as usual

Flags:
-h, --help Help for edgectl

OK.

Direct installation .

pc-name Take a name you like , A lowercase letter + Horizontal line + The combination of numbers is Ok, You can't underline

./edgectl install -n pc-name
When it's done , Success sees Successfull And so on .

After installation , This machine can be seen in the node management of a cloud cluster .

It can also be directly passed through kubectl Check the machine information .

* ~ kc get node
NAME STATUS ROLES AGE VERSION
aliyun-changan Ready 23d v1.18.2
aliyun-huang Ready 23d v1.18.2
nuc-vm-ubuntu Ready 23d v1.18.2
* ~ kc describe node nuc-vm-ubuntu
Name: nuc-vm-ubuntu
Roles:
Labels: beta.kubernetes.io/arch=amd64
beta.kubernetes.io/os=linux
kubernetes.io/arch=amd64
kubernetes.io/hostname=nuc-vm-ubuntu
kubernetes.io/os=linux
region=cn
Annotations: flannel.alpha.coreos.com/backend-data: {"VtepMAC":"72:83:61:5b:7c:b7"}
flannel.alpha.coreos.com/backend-type: vxlan
flannel.alpha.coreos.com/kube-subnet-manager: true
flannel.alpha.coreos.com/public-ip: 10.0.2.15
node.alpha.kubernetes.io/ttl: 0
nodeunhealth: yes
volumes.kubernetes.io/controller-managed-attach-detach: true
CreationTimestamp: Tue, 29 Dec 2020 11:00:29 +0800
Taints:
Unschedulable: false
Lease:
HolderIdentity: nuc-vm-ubuntu
AcquireTime:
RenewTime: Thu, 21 Jan 2021 22:45:23 +0800
Conditions:
Type Status LastHeartbeatTime LastTransitionTime Reason Message


NetworkUnavailable False Mon, 18 Jan 2021 10:05:43 +0800 Mon, 18 Jan 2021 10:05:43 +0800 FlannelIsUp Flannel is running on this node
MemoryPressure False Thu, 21 Jan 2021 22:42:47 +0800 Wed, 20 Jan 2021 17:07:46 +0800 KubeletHasSufficientMemory kubelet has sufficient memory available
DiskPressure False Thu, 21 Jan 2021 22:42:47 +0800 Wed, 20 Jan 2021 17:07:46 +0800 KubeletHasNoDiskPressure kubelet has no disk pressure
PIDPressure False Thu, 21 Jan 2021 22:42:47 +0800 Wed, 20 Jan 2021 17:07:46 +0800 KubeletHasSufficientPID kubelet has sufficient PID available
Ready True Thu, 21 Jan 2021 22:42:47 +0800 Wed, 20 Jan 2021 17:07:46 +0800 KubeletReady kubelet is posting ready status. AppArmor enabled
Addresses:
InternalIP: 10.0.2.15
Hostname: nuc-vm-ubuntu
Capacity:
cpu: 2
ephemeral-storage: 19475088Ki
hugepages-2Mi: 0
memory: 8054976Ki
pods: 127
Allocatable:
cpu: 1940m
ephemeral-storage: 17948241072
hugepages-2Mi: 0
memory: 7788736Ki
pods: 127
System Info:
Machine ID: 8056248ceff544a3972666b79b1f3fb6
System UUID: 0d728d29-d62c-e948-a3b9-01ee8625bfe3
Boot ID: 7bddb25d-d02c-4341-9db4-ef3840795e3d
Kernel Version: 5.4.0-62-generic
OS Image: Ubuntu 20.04.1 LTS
Operating System: linux
Architecture: amd64
Container Runtime Version: docker://18.6.3
Kubelet Version: v1.18.2
Kube-Proxy Version: v1.18.2
PodCIDR: 172.16.1.0/24
PodCIDRs: 172.16.1.0/24
Non-terminated Pods: (18 in total)
Namespace Name CPU Requests CPU Limits Memory Requests Memory Limits AGE


default crawl-douban-edge-1611231000-mmbmk 10m (0%) 200m (10%) 64Mi (0%) 256Mi (3%) 155m
kube-system application-grid-wrapper-dqrgd 10m (0%) 50m (2%) 20Mi (0%) 100Mi (1%) 23d
kube-system coredns-lf2fr 50m (2%) 50m (2%) 70Mi (0%) 170Mi (2%) 6d22h
kube-system edge-health-cvzg4 10m (0%) 50m (2%) 20Mi (0%) 100Mi (1%) 23d
kube-system flannel-7zw8b 50m (2%) 100m (5%) 50Mi (0%) 200Mi (2%) 23d
kube-system kube-proxy-gnmpv 10m (0%) 50m (2%) 50Mi (0%) 100Mi (1%) 23d
kube-system proxy-edge-4lkrk 0 (0%) 0 (0%) 0 (0%) 0 (0%) 23d
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.)
Resource Requests Limits


cpu 240m (12%) 2500m (128%)
memory 1490Mi (19%) 5790Mi (76%)
ephemeral-storage 0 (0%) 0 (0%)
hugepages-2Mi 0 (0%) 0 (0%)
Events:

* ~ kc top node
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
aliyun-changan 29m 3% 679Mi 43%
aliyun-huang 48m 5% 1137Mi 65%
nuc-vm-ubuntu 509m 26% 1869Mi 24%
Finally, it's basically like using one normally k8s The cluster is done .

版权声明
本文为[Li Guobao]所创,转载请带上原文链接,感谢
https://javamana.com/2021/01/20210121225912631S.html

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