Kube-proxy with built-in power minimization policy

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Kubernetes is a portable, extensible, open source platform for facilitating declarative configuration management and automation, and managing containerized workloads and services. Kubernetes has a huge and fast-growing ecosystem with a wide range of services, support and tools available.

This document shows the steps to build and deploy kube-proxy with power minimization policy.

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Prerequisites

• Go-lang v1.15.1
• Kubernetes v1.19.7
• ipmi_exporter
  Running on each node
• local docker repository
• docker image of tensorflow serving containing power consumption model of each node.

Build kube-proxy with power minimization policy

1. Download the Kubernetes source code

   *Since the directory structure is different in the latest version, use Kubernetes v1.19.7

   curl -L -o kubernetes.tar.gz https://github.com/kubernetes/kubernetes/archive/v1.19.7.tar.gz
   tar xvzf kubernetes.tar.gz
   

2. Add Kube-proxy source code with power minimization policy

   git clone https://github.com/kaz260/wao-ploxy
   

   After cloning, copy to kubernetes/pkg/proxy/ipvs
   *Overwrite the file with the same name

3. Add the required packages

   Add the prom2json package

   go get github.com/prometheus/prom2json
   

4. Build a proxy

   Build results are output to kubernetes/cmd/proxy/

   cd ./kubernetes/cmd/proxy/
   CGO_ENABLED=0 go build -mod=mod proxy.go
   

Deploy to Kubernetes

Since there are multiple files required for deployment, it is recommended to create a suitable directory and work in it.

1. Create a Docker image for kube-proxy

   Create Dockerfile with the following contents. The original image has been confirmed and may be up to date.

   FROM k8s.gcr.io/kube-proxy:v1.18.8
   COPY ./proxy /usr/local/bin/kube-proxy

   Copy the proxy built in the above steps to the same directory as the Dockerfile.
   Create an image and push it to your local repository.

   docker build -t [repository-address]/[image-name] .
   docker image push [repository-address]/[image-name]
   

2. Preparing to start kube-proxy

   The following preparations are required for the first statup.

   • Change to a setting that users ipvs

     kubectl edit configmap kube-proxy -n kube-system
     Change two lines like below.
     mode: "ipvs"
     scheduler: "wrr"
     

   • Add role so that kube-proxy can get pods informations.

     kubectl create clusterrolebinding default-view --clusterrole=view --serviceaccount=kube-system:kube-proxy
     

   • Launch metrics-server (Kubernetes Metrics Server)

     kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml
     

   • Launch tensorflow

     kubectl create -f tensorflow-server-dep.yaml
     

   • Labeling Give each node the following label;

     • ambient/max : Maximum ambinet temperature in celsius
     • ambient/min : Mimimum ambinet temperature in celsius
     • cpu1/max : Maximum CPU1 temperature in celsius
     • cpu1/min : Minimum CPU1 temperature in celsius
     • cpu2/max : Maximum CPU2 temperature in celsius
     • cpu2/min : Minimum CPU2 temperature in celsius
     • tensorflow/host: IP address of tensorflow serving
     • tensorflow/port: Port number of tensorflow serving
     • tensorflow/name: model name of tensorflow serving

3. Launch kube-proxy

   Stop the currently running kube-proxy
   

   kubectl delete daemonset -n kube-system kube-proxy

   Lauch a new kube-proxy
   

   kubectl create -f kube-proxy.yaml

   Success if you can confirm the startup on each node with the following command
   (Successful if the pod status is [Running])
   

   kubectl get pod -n kube-system -o wide | grep kube-proxy

   If you want to see the result of ipvs, you need to install ipvsadm
   

   Installation

   sudo apt install ipset ipvsadm -y
   

   Verification

   sudo ipvsadm -Ln