Access Microsoft Azure > Kubernetes services > Overview

Under Kubernetes cluster, click [Create].

1. Select Resource group.
2. Enter Kubernetes cluster name.
3. Once the basic configuration is finished, click [Next].

Keep default networking unless you have requirements for private cluster, custom CNI, or restricted egress. Proceed to [Next].

Review integrations (e.g., Azure Monitor, policy) based on your org standards, then proceed to [Review + create].

After the cluster is created, configure kubectl to connect to the cluster via API:

1. Log in to the Azure CLI, or skip this step and log in to the Cloud Shell:

az login

2. Set the correct subscription (if needed):

az account set --subscription <subscription-id-or-name>

3. Fetch kubeconfig credentials:

az aks get-credentials --resource-group <rg-name> --name <aks-name> --overwrite-existing

4. Verify access:

kubectl get nodes

# Change these four parameters as needed for your own environment AKS_PERS_STORAGE_ACCOUNT_NAME=mystorageaccount$RANDOM 
AKS_PERS_RESOURCE_GROUP=myAKSShare 
AKS_PERS_LOCATION=eastus 
AKS_PERS_SHARE_NAME=aksshare 

# Create a resource group
az group create --name $AKS_PERS_RESOURCE_GROUP --location $AKS_PERS_LOCATION 

# Create a storage account 
az storage account create -n $AKS_PERS_STORAGE_ACCOUNT_NAME -g $AKS_PERS_RESOURCE_GROUP -l $AKS_PERS_LOCATION --sku Standard_LRS 

# Export the connection string as an environment variable, this is used when creating the Azure file share 
export AZURE_STORAGE_CONNECTION_STRING=$(az storage account show-connection-string -n $AKS_PERS_STORAGE_ACCOUNT_NAME -g $AKS_PERS_RESOURCE_GROUP -o tsv) 

# Create the file share 
az storage share create -n $AKS_PERS_SHARE_NAME --connection-string $AZURE_STORAGE_CONNECTION_STRING 

# Get storage account key 
STORAGE_KEY=$(az storage account keys list --resource-group $AKS_PERS_RESOURCE_GROUP --account-name $AKS_PERS_STORAGE_ACCOUNT_NAME --query "[0].value" -o tsv)

# Echo storage account name and key 
echo Storage account name: $AKS_PERS_STORAGE_ACCOUNT_NAME 
echo Storage account key: $STORAGE_KEY

kubectl create secret generic azure-secret --from-literal=azurestorageaccountname=$AKS_PERS_STORAGE_ACCOUNT_NAME --from-literal=azurestorageaccountkey=$STORAGE_KEY

Create a PersistentVolume (PV) and PersistentVolumeClaim (PVC) backed by Azure Files (CSI). The mount options set UID/GID to 33, which matches the service user used by Metric Insights containers. Update the placeholders below:

• resourceGroup: <AKS_PERS_RESOURCE_GROUP>
• shareName: <AKS_PERS_SHARE_NAME>
• volumeHandle: <unique-id> (must be unique in the cluster)

Save as volume.yml and apply:

kubectl apply -f volume.yml

---
apiVersion: v1
kind: PersistentVolume
metadata:
  name: azurefile
spec:
  capacity:
    storage: 200Gi
  accessModes:
    - ReadWriteMany
  persistentVolumeReclaimPolicy: Retain
  storageClassName: azurefile-csi
  csi:
    driver: file.csi.azure.com
    readOnly: false
    volumeHandle: unique-volumeid  # make sure this volumeid is unique in the cluster
    volumeAttributes:
      resourceGroup: myAKSShare  # optional, only set this when storage account is not in the same resource group as agent node
      shareName: aksshare
    nodeStageSecretRef:
      name: azure-secret
      namespace: default
  mountOptions:
    - dir_mode=0755
    - file_mode=0644
    - uid=33
    - gid=33
    - mfsymlinks
    - cache=strict
    - nosharesock
    - nobrl
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: azurefile
spec:
  accessModes:
    - ReadWriteMany
  storageClassName: azurefile-csi
  volumeName: azurefile
  resources:
    requests:
      storage: 200Gi

See Access Software Downloads and License Keys via Get MI for details.

tar xvf MetricInsights-Installer-v7.X.X-Lite.tar.gz

Run the installer to generate Kubernetes manifests and secret files locally. Then create Kubernetes secrets from the generated files and apply the deployment manifest: kubectl --namespace default apply -f deployment.yml

./installer.py kubernetes --persistent-volume-claim azurefile --db-hostname testkubernetes.mysql.database.azure.com --db-user dashboard_admin --db-password 'enter_your_password_here' -o deployment.yml --images-pull-secret-name metricinsights-docker-registry
CONGRATULATIONS! Configuration and credential files are ready to deploy into Kubernetes.

        Use the following commands to deploy Metric Insights application:
        ...
        $kubectl create namespace default
        $kubectl create secret generic --namespace default metricinsights-mysql-root-password --from-file mysql.secret
        $kubectl create secret generic --namespace default metricinsights-data-analyzer --from-file data-analyzer.env
        $kubectl create secret generic --namespace default metricinsights-dataprocessor --from-file dataprocessor.env
        $kubectl create secret generic --namespace default metricinsights-console --from-file console.env
        $kubectl create secret generic --namespace default metricinsights-image-generator --from-file image-generator.env
        $kubectl create secret generic --namespace default metricinsights-web --from-file web.env
        $kubectl create secret generic --namespace default metricinsights-redis --from-file redis.env
        $kubectl create secret docker-registry --namespace default metricinsights-docker-registry --docker-server docker.metricinsights.com --docker-username <registry login> --docker-password <registry password> --docker-email <[email protected]>
        $kubectl --namespace default apply -f deployment.yml
        $kubectl get deployments --namespace default