Ito ay isang hakbang-hakbang na gabay sa pag-set up ng Kubernetes sa Scaleway bare-metal ARM at x86-64. Ang pangunahing dahilan kung bakit ako gumagawa sa proyektong ito ay dahil gusto kong i-automate ang paglikha ng mga kapaligiran sa pagsubok para sa OpenFaaS at Weave Net sa ARM. Naghahanap ako ng murang solusyon para magpatakbo ng mga integration test at pagkatapos kong subukan ang ilang cloud provider ay nanirahan na ako sa Scaleway. Ang Scaleway ay isang french cloud provider na nag-aalok ng bare-metal ARM at x86-64 server sa abot-kayang presyo. Gamit ang provider ng Terraform Scaleway kasama ng kubeadm maaari kang magkaroon ng fully functional na cluster ng Kubernetes sa loob ng sampung minuto

 Paunang setup
I-clone ang repositoryo at i-install ang mga dependencies:
$ git clone httpsgithub.com/stefanprodan/k8s-scw-baremetal.git $ cd k8s-scw-baremetal $ terraform init
Tandaan na kakailanganin mo ang Terraform v0.10 o mas bago para patakbuhin ang proyektong ito

Bago patakbuhin ang proyekto kailangan mong lumikha ng token ng pag-access para kumonekta ang Terraform sa Scaleway API. Gamit ang token at ang iyong access key, gumawa ng dalawang environment variable:
$ export SCALEWAY_ORGANIZATIONACCESS-KEY>"$ export SCALEWAY_TOKENACCESS-TOKEN>"Paggamit
Gumawa ng ARMv7 bare-metal Kubernetes cluster na may isang master at dalawang node:
$ terraform workspace bagong braso $ terraform apply \ -var region=par1 \ -var arch=arm \ -var server_type=C1 \ -var nodes=2 \ -var weave_passwd=ChangeMe \ -var k8s_version=stable-1.9 \ -var docker_version =17.03.0~ce-0~ubuntu-xenial
Gagawin nito ang sumusunod:
- Inilalaan ang mga pampublikong IP para sa bawat server
- nagbibigay ng tatlong bare-metal server na may Ubuntu 16.04.1 LTS
- kumokonekta sa master server sa pamamagitan ng SSH at nag-i-install ng Docker CE at kubeadm armhf apt packages
- nagpapatakbo ng kubeadm init sa master server at kino-configure ang kubectl
- dina-download ang kubectl admin config file sa iyong lokal na makina at pinapalitan ang pribadong IP ng pampubliko
- lumilikha ng lihim ng Kubernetes gamit ang password ng Weave Net
- nag-i-install ng Weave Net na may naka-encrypt na overlay
- nag-i-install ng mga cluster add-on (Kubernetes dashboard, metrics server at Heapster)
- sinisimulan ang mga node ng manggagawa nang magkatulad at ini-install ang Docker CE at kubeadm
- sumasali sa mga node ng manggagawa sa cluster gamit ang kubeadm token na nakuha mula sa master
Palakihin sa pamamagitan ng pagtaas ng bilang ng mga node:
$ terraform apply -var nodes=3
Gibain ang buong imprastraktura gamit ang:
terraform-force
Gumawa ng AMD64 bare-metal Kubernetes cluster na may isang master at isang node:
$ terraform workspace bagong amd64 $ terraform apply \ -var region=par1 \ -var arch=x86_64 \ -var server_type=C2S \ -var nodes=1 \ -var weave_passwd=ChangeMe \ -var k8s_version=stable-1.9 \ -var docker_version =17.03.0~ce-0~ubuntu-xenial
 Remote control
Pagkatapos ilapat ang Terraform plan makakakita ka ng ilang output variable tulad ng master public IP, ang kubeadmn join command at ang kasalukuyang workspace admin config.

Para tumakbo
kubectl command laban sa Scaleway cluster na maaari mong gamitin ang
kubectl_config output variable:
Suriin kung gumagana ang Heapster:
$ kubectl --kubeconfig terraform output kubectl_config) top node NAME CPU(cores) CPU% MEMORY(bytes) MEMORY% arm-master-1 655m 16% 873Mi 45% arm-node-1 147m 3% 618Mi 32% arm-node- 2 101m 2% 584Mi 30%
Ang
kubectl config file format ay
.conf as in
arm.conf or
amd64.conf

In order to access the dashboard you’ll need to find its cluster IP:
$ kubectl --kubeconfig terraform output kubectl_config) \ -n kube-system get svc --selector=k8s-app=kubernetes-dashboard NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes-dashboard ClusterIP 10.107.37.220  80/TCP 6m
Open a SSH tunnel:
ssh -L 8888::80 [email protected]
Now you can access the dashboard on your computer at
httplocalhost:8888

 Expose services outside the cluster
Since we’re running on bare-metal and Scaleway doesn’t offer a load balancer, the easiest way to expose applications outside of Kubernetes is using a NodePort service

Let’s deploy the podinfo app in the default namespace. Podinfo has a multi-arch Docker image and it will work on arm, arm64 or amd64

Create the podinfo nodeport service:
$ kubectl --kubeconfig terraform output kubectl_config) \ apply -f httpsraw.githubusercontent.com/stefanprodan/k8s-podinfo/master/deploy/auto-scaling/podinfo-svc-nodeport.yaml service "podinfo-nodeport" created
Create the podinfo deployment:
$ kubectl --kubeconfig terraform output kubectl_config) \ apply -f httpsraw.githubusercontent.com/stefanprodan/k8s-podinfo/master/deploy/auto-scaling/podinfo-dep.yaml deployment "podinfo" created
Inspect the podinfo service to obtain the port number:
$ kubectl --kubeconfig terraform output kubectl_config) \ get svc --selector=app=podinfo NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE podinfo-nodeport NodePort 10.104.132.14  9898:31190/TCP 3m
You can access podinfo at
httpMASTER_PUBLIC_IP>:31190 or using curl:

$ curl httpterraform output k8s_master_public_ip):31190 runtime: arch: arm max_procs: "4" num_cpu: "4" num_goroutine: "12" os: linux version: go1.9.2 labels: app: podinfo pod-template-hash: "1847780700" annotations: kubernetes.io/config.seen: 2018-01-08T00:39:45.580597397Z kubernetes.io/config.source: api environment: HOME: /root HOSTNAME: podinfo-5d8ccd4c44-zrczc KUBERNETES_PORT: tcp10.96.0.1:443 KUBERNETES_PORT_443_TCP: tcp10.96.0.1:443 KUBERNETES_PORT_443_TCP_ADDR: 10.96.0.1 KUBERNETES_PORT_443_TCP_PORT: "443" KUBERNETES_PORT_443_TCP_PROTO: tcp KUBERNETES_SERVICE_HOST: 10.96.0.1 KUBERNETES_SERVICE_PORT: "443" KUBERNETES_SERVICE_PORT_HTTPS: "443" PATH: /usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin externalIP: IPv4: 163.172.139.112
 OpenFaaS
You can deploy OpenFaaS on Kubernetes with Helm or by using the YAML files form the faas-netes repository

Clone the faas-netes repo:
git clone httpsgithub.com/openfaas/faas-netes cd faas-netes
Deploy OpenFaaS for ARM:
$ kubectl --kubeconfig terraform output kubectl_config) \ apply -f ./namespaces.ymlyaml_armhf
Deploy OpenFaaS for AMD64:
$ kubectl --kubeconfig terraform output kubectl_config) \ apply -f ./namespaces.ymlyaml
You can access the OpenFaaS gateway at
httpMASTER_PUBLIC_IP>:31112

 Horizontal Pod Autoscaling
Starting from Kubernetes 1.9
kube-controller-manager is configured by default with
horizontal-pod-autoscaler-use-rest-clients

In order to use HPA we need to install the metrics server to enable the new metrics API used by HPA v2

Both Heapster and the metrics server have been deployed from Terraform
when the master node was provisioned

The metric server collects resource usage data from each node using Kubelet Summary API. Check if the metrics server is running:
$ kubectl --kubeconfig terraform output kubectl_config) \ get --raw "/apis/metrics.k8s.io/v1beta1/nodes" | jq
{ "kind": "NodeMetricsList", "apiVersion": "metrics.k8s.io/v1beta1", "metadata": { "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes" }, "items": [ { "metadata": { "name": "arm-master-1", "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/arm-master-1", "creationTimestamp": "2018-01-08T15:17:09Z" }, "timestamp": "2018-01-08T15:17:00Z", "window": "1m0s", "usage": { "cpu": "384m", "memory": "935792Ki" } }, { "metadata": { "name": "arm-node-1", "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/arm-node-1", "creationTimestamp": "2018-01-08T15:17:09Z" }, "timestamp": "2018-01-08T15:17:00Z", "window": "1m0s", "usage": { "cpu": "130m", "memory": "649020Ki" } }, { "metadata": { "name": "arm-node-2", "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/arm-node-2", "creationTimestamp": "2018-01-08T15:17:09Z" }, "timestamp": "2018-01-08T15:17:00Z", "window": "1m0s", "usage": { "cpu": "120m", "memory": "614180Ki" } } ] }
Let’s define a HPA that will maintain a minimum of two replicas and will scale up to ten if the CPU average is over 80% or if the memory goes over 200Mi

apiVersion: autoscaling/v2beta1 kind: HorizontalPodAutoscaler metadata: name: podinfo spec: scaleTargetRef: apiVersion: apps/v1beta1 kind: Deployment name: podinfo minReplicas: 2 maxReplicas: 10 metrics: - type: Resource resource: name: cpu targetAverageUtilization: 80 - type: Resource resource: name: memory targetAverageValue: 200Mi

Apply the podinfo HPA:
$ kubectl --kubeconfig terraform output kubectl_config) \ apply -f httpsraw.githubusercontent.com/stefanprodan/k8s-podinfo/master/deploy/auto-scaling/podinfo-hpa.yaml horizontalpodautoscaler "podinfo" created
After a couple of seconds the HPA controller will contact the metrics server and will fetch the CPU and memory usage:
$ kubectl --kubeconfig terraform output kubectl_config) get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE podinfo Deployment/podinfo 2826240 / 200Mi, 15% / 80% 2 10 2 5m
In order to increase the CPU usage we could run a load test with hey:
#install hey go get -u github.com/rakyll/hey #do 10K requests rate limited at 20 QPS hey -n 10000 -q 10 -c 5 httpterraform output k8s_master_public_ip):31190
You can monitor the autoscaler events with:
$ kubectl --kubeconfig terraform output kubectl_config) describe hpa Events: Type Reason Age From MessageNormal SuccessfulRescale 7m horizontal-pod-autoscaler New size: 4; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 3m horizontal-pod-autoscaler New size: 8; reason: cpu resource utilization (percentage of request) above target
After the load tests finishes the autoscaler will remove replicas until the deployment reaches the initial replica count:
Events: Type Reason Age From MessageNormal SuccessfulRescale 20m horizontal-pod-autoscaler New size: 4; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 16m horizontal-pod-autoscaler New size: 8; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 12m horizontal-pod-autoscaler New size: 10; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 6m horizontal-pod-autoscaler New size: 2; reason: All metrics below target
 Conclusions
Thanks to kubeadm and Terraform, bootstrapping a Kubernetes cluster on bare-metal can be done with a single command and it takes just ten minutes to have a fully functional setup. If you have any suggestion on improving this guide please submit an issue or PR on GitHub at stefanprodan/k8s-scw-baremetal. Contributions are more than welcome!