Tag: prometheus

Monitoring is the backbone of any reliable Kubernetes cluster. It ensures visibility into resource usage, application health, and potential failures. Instead of manually deploying and managing Prometheus, the Prometheus Operator simplifies and automates monitoring with custom resource definitions (CRDs).

In this guide, we will:
Deploy the Prometheus Operator in Kubernetes
Configure Prometheus, Alertmanager, and Grafana
Set up automated service discovery using ServiceMonitor
Enable alerts and notifications

Let’s get started!

Installing the Prometheus Operator Using Helm

The fastest and most efficient way to deploy the Prometheus stack is through Helm.

Step 1: Add the Prometheus Helm Repository

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm repo update

Step 2: Install the Prometheus Operator

helm install prometheus prometheus-community/kube-prometheus-stack -n monitoring --create-namespace

This command installs:
Prometheus
Alertmanager
Grafana
Node Exporters

Verify the installation:

kubectl get pods -n monitoring

Deploying a Prometheus Instance

Now, we will define a Prometheus Custom Resource to manage our Prometheus deployment.

prometheus.yaml

apiVersion: monitoring.coreos.com/v1
kind: Prometheus
metadata:
  name: prometheus-instance
  namespace: monitoring
spec:
  replicas: 2
  serviceMonitorSelector: {}
  resources:
    requests:
      memory: 400Mi
      cpu: 200m

Apply the Prometheus Instance

kubectl apply -f prometheus.yaml

This will automatically create a Prometheus instance that follows Kubernetes best practices.

Configuring Service Discovery with ServiceMonitor

Prometheus requires service discovery to scrape metrics from your applications. The ServiceMonitor CRD makes this process seamless.

servicemonitor.yaml

apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: myapp-monitor
  namespace: monitoring
spec:
  selector:
    matchLabels:
      app: myapp
  endpoints:
    - port: metrics
      interval: 30s

Apply the ServiceMonitor Configuration

kubectl apply -f servicemonitor.yaml

This ensures that Prometheus automatically discovers and scrapes metrics from services with the label app: myapp.

Setting Up Alerting with Alertmanager

Alertmanager handles alerts generated by Prometheus and routes them to email, Slack, PagerDuty, etc.

alertmanager.yaml

apiVersion: monitoring.coreos.com/v1
kind: Alertmanager
metadata:
  name: alertmanager-instance
  namespace: monitoring
spec:
  replicas: 2

Apply the Alertmanager Configuration

kubectl apply -f alertmanager.yaml

Now, we have a fully functional alerting system in place.

Accessing Grafana Dashboards

Grafana provides real-time visualization for Prometheus metrics. It is already included in the Prometheus Operator stack.

Access Grafana using port-forwarding

kubectl port-forward svc/prometheus-grafana -n monitoring 3000:80

Open http://localhost:3000 in your browser.
Username: admin
Password: Retrieve using:

kubectl get secret -n monitoring prometheus-grafana -o jsonpath="{.data.admin-password}" | base64 --decode

Now, you can import dashboards and start visualizing Kubernetes metrics!

Verifying the Monitoring Stack

To ensure everything is running smoothly, check the pods:

kubectl get pods -n monitoring

If you see Prometheus, Alertmanager, and Grafana running, congratulations! You now have a fully automated Kubernetes monitoring stack.

Conclusion: Why Use the Prometheus Operator?

By using the Prometheus Operator, we achieved:
Simplified monitoring stack deployment
Automated service discovery for metrics collection
Centralized alerting with Alertmanager
Interactive dashboards with Grafana 

With this setup, you can scale, extend, and customize monitoring based on your infrastructure needs.

Let me know if you have any questions in the comments!