Deploying Grafana and Prometheus on AKS using Terraform

Monitoring is a critical component of any Kubernetes deployment. In this guide, we will deploy Prometheus for monitoring and Grafana for visualization on an existing Azure Kubernetes Service (AKS) cluster using Terraform.

Prerequisites

Before we begin, ensure you have the following:

• An existing AKS cluster
• Terraform installed (version 1.0.0+)
• Azure CLI configured with appropriate permissions
• Helm installed (for manual verification if needed)

Project Structure

Organize your Terraform project as follows:

aks-monitoring/
├── main.tf
├── variables.tf
├── outputs.tf
└── terraform.tfvars

Provider Configuration

In main.tf, configure the Terraform provider for Azure:

terraform {
  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 3.0"
    }
  }
}

provider "azurerm" {
  features {}
}

Deploying Prometheus and Grafana via Helm

Add the Helm provider and configure the deployments.

provider "helm" {
  kubernetes {
    host                   = azurerm_kubernetes_cluster.aks.kube_config.0.host
    client_certificate     = base64decode(azurerm_kubernetes_cluster.aks.kube_config.0.client_certificate)
    client_key             = base64decode(azurerm_kubernetes_cluster.aks.kube_config.0.client_key)
    cluster_ca_certificate = base64decode(azurerm_kubernetes_cluster.aks.kube_config.0.cluster_ca_certificate)
  }
}

resource "helm_release" "prometheus" {
  name       = "prometheus"
  repository = "https://prometheus-community.github.io/helm-charts"
  chart      = "prometheus"
  namespace  = "monitoring"
  create_namespace = true

  values = [<<EOF
    alertmanager:
      enabled: true
    server:
      persistentVolume:
        enabled: true
  EOF
  ]
}

resource "helm_release" "grafana" {
  name       = "grafana"
  repository = "https://grafana.github.io/helm-charts"
  chart      = "grafana"
  namespace  = "monitoring"
  depends_on = [helm_release.prometheus]
  
  values = [<<EOF
    persistence:
      enabled: true
    adminPassword: "SuperSecurePassword"
    service:
      type: LoadBalancer
  EOF
  ]
}

Variables Configuration

Define variables for customization in variables.tf:

variable "aks_cluster_name" {
  type        = string
  description = "Name of the existing AKS cluster"
}

variable "resource_group_name" {
  type        = string
  description = "Resource group where the AKS cluster is deployed"
}

Output Configuration

Expose the Grafana service URL and credentials in outputs.tf:

output "grafana_dashboard_url" {
  value = "http://${helm_release.grafana.name}.monitoring.svc.cluster.local"
}

output "grafana_admin_password" {
  value = "SuperSecurePassword"
  sensitive = true
}

Deploying the Monitoring Stack

1. Initialize Terraform:

terraform init

2. Configure terraform.tfvars:

aks_cluster_name       = "my-aks-cluster"
resource_group_name    = "my-resource-group"

3. Plan and apply the configuration:

terraform plan
terraform apply

4. Verify the installation:

kubectl get pods -n monitoring

Conclusion

This guide demonstrates how to deploy Grafana and Prometheus on an AKS cluster using Terraform and Helm. By automating the deployment, you ensure consistency and scalability in your monitoring setup.

For further customization, consider integrating Azure Monitor and setting up persistent storage for metrics retention.