Deploy Kubeflow and MLFlow using juju on MicroK8s Cluster
We will deploy Kubeflow and MLFlow on our MicroK8S Cluster using juju application modeling tool.
Ubuntu 22.04 
https://releases.ubuntu.com/jammy
Juju
MicroK8s 
Kubeflow 
MLflow
Prepare your Ubuntu 22.04
sudo apt update && sudo apt upgrade -y
I prefer using htop, atop, nload, iftop, nvtop and btop for various system level indepth analysis, so we will install these tools using below mentioned commands.
sudo apt install htop atop nload iftop nvtop btop -y
Now we will install and configure microk8s a lightweight kubernetes distribution, we will install k8s 1.32 stable version for better performance and security.
sudo snap install microk8s --channel=1.32/stable --classic
sudo usermod -a -G microk8s $USER
newgrp microk8s
Now we will reboot our system to get microk8s working with our system.
sudo microk8s enable dns hostpath-storage metallb:192.168.100.240-192.168.100.254 rbac
microk8s status
microk8s.enable gpu
Now install juju
sudo snap install juju --channel=3.4/stable
mkdir -p ~/.local/share
Configure microk8s with juju
microk8s config | juju add-k8s my-k8s --client
Now bootstrap juju controller inside microk8s cluster
juju bootstrap my-k8s kubeflow
Now add model for juju
juju add-model kubeflow
Fix kernel parameters with below mentioned commands
sudo sysctl fs.inotify.max_user_instances=1280
sudo sysctl fs.inotify.max_user_watches=655360
Now save it for permanent configuration in Sysctl file
sudo nano /etc/sysctl.conf
fs.inotify.max_user_instances=1280
fs.inotify.max_user_watches=655360
Now we will deploy kubeflow 1.9 stable version using juju command
juju deploy kubeflow --trust --channel=1.9/stable
To check the deployment status
juju status
watch juju status
Configure dex auth to access the application using juju config command
juju config dex-auth static-username=kubeflow
juju config dex-auth static-password=Pakistani
Now check ip from metallb load balancer has been assigned to kubeflow dashboard
microk8s kubectl -n kubeflow get svc istio-ingressgateway-workload -o jsonpath='{.status.loadBalancer.ingress[0].ip}'
Deploy MLFlow
Now we will deploy MLflow and integrate it with kubeflow
juju deploy mlflow --channel=2.15/stable --trust
juju integrate mlflow-server:ingress istio-pilot:ingress
juju integrate mlflow-server:dashboard-links kubeflow-dashboard:links
microk8s kubectl -n kubeflow get svc istio-ingressgateway-workload -o jsonpath='{.status.loadBalancer.ingress[0].ip}'
Refences:
https://microk8s.io/docs/getting-started
https://charmhub.io/kubeflow/docs/get-started
https://documentation.ubuntu.com/charmed-mlflow/en/latest/tutorial/mlflow-kubeflow