INTEGRATE PROMETHEUS AND GRAFANA ON THE TOP OF KUBERNETES

Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.

Prometheus is a free software application used for event monitoring and alerting. It records real-time metrics in a time series database built using a HTTP pull model, with flexible queries and real-time alerting.

Grafana is a multi-platform open source analytics and interactive visualization web application. It provides charts, graphs, and alerts for the web when connected to supported data sources. It is expandable through a plug-in system. End users can create complex monitoring dashboards using interactive query builders.

Task :

Integrate Prometheus and Grafana and perform in following way:

1. Deploy them as pods on top of Kubernetes by creating resources Deployment, ReplicaSet, Pods or Services
2. And make their data to be remain persistent
3. And both of them should be exposed to outside world

Steps wise explaination of task:-

1. Deploy Prometheus and Grafana as pods on top of Kubernetes by creating resources Deployment, ReplicaSet, Pods or Services.

Now let us create the required PVC,service and deployment to make Prometheus data persistent and expose it as well.

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: prompvc
spec:
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
   
     storage: 2Gi

The above code will create persistent volume claim(PVC) for prometheus pod.

apiVersion: v1
kind: Service
metadata:
  name: prometheus
  labels:
    app: prm
spec:
  ports:
    - port: 9090
  selector:
    app: prm
  
  type: NodePort

The above code will create service for Prometheus pod.

apiVersion: apps/v1 
kind: Deployment
metadata:
  name: deployprom
  labels:
    app: prm
spec:
  replicas: 1
  selector:
    matchLabels:
      app: prm
  strategy:
    type: Recreate
  template:
    metadata:
      labels:
        app: prm
    spec:
      containers:
      - image: vimal13/prometheus
        name: prm
        ports:
        - containerPort: 9090
          name: prm
        volumeMounts:
        - name: configpr
          mountPath: /prometheus-2.19.2.linux-amd64/prometheus.yml
          subPath: prometheus.yml
        - name: prompvc
          mountPath: /prometheus-2.19.2.linux-amd64/data
      volumes:
        - name: configpr
          configMap:
            name: configpr
        - name: prompvc
          persistentVolumeClaim:

         
            claimName: prompvc

The above code creates deployment for Prometheus.

This is the code for creating one service, PVC, and deployment resource for launch, expose and make Grafana persistent...

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: grafpvc
spec:
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
    
  storage: 2Gi

The above code creates persistent volume claim for Grafana.

apiVersion: v1
kind: Service
metadata:
  name: svcgrafana
  labels:
    app: grf
spec:
  ports:
    - port: 3000
  selector:
    app: graf

  type: NodePort

The above code will create service for Prometheus pod.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: deploygraf
  labels:
    app: grf
spec:
  replicas: 1
  selector:
    matchLabels:
      app: grf
  strategy:
    type: Recreate
  template:
    metadata:
      labels:
        app: grf
    spec:
      containers:
      - image: vimal13/grafana
        name: grf
        ports:
        - containerPort: 3000
          name: grf
        volumeMounts:
        - name: grafpvc
          mountPath: "/usr/share/grafana/data"
      volumes:
        - name: grafpvc
          persistentVolumeClaim:

          
            claimName: grafpvc

The above code creates Deployment for Grafana .

Prometheus is configured via command-line flags and a configuration file. While the command-line flags configure immutable system parameters (such as storage locations, amount of data to keep on disk and in memory, etc.), the configuration file defines everything related to scraping jobs and their instances, as well as which rule files to load.

so we need to create a ConfigMap for attaching config file with prometheus server...

apiVersion: v1
kind: ConfigMap
metadata:
  name: config
  labels:
    app: prm
data:
  prometheus.yml: |
    global:
      scrape_interval:     15s 
      evaluation_interval: 15s 
    scrape_configs:
     - job_name: 'prometheus'
       static_configs:

       - targets: ['localhost:9090']

Now we can use kustomization file to launch the whole setup in a click

apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
resources:
  - configmap.yml
  - pvcprom.yml
  - svcprom.yml
  - promdeploy.yml
  - svcgraf.yml
  - pvcgraf.yml
  - graphdeploy.yml

Now execute the kustomization file run the following command:

kubectl apply -k .

We can check all the resources using the following command:

kubectl get all

This gives the port for Prometheus and Grafana as well in our case it is 31373,31872 respectively for Grafana and Prometheus.

The following are respective Pometheus and Grafana consoles after launching the resources.

To open Prometheus we need to use the IP along with the port allotted and same for the Grafana.

The above image shows Prometheus (port no:-31872) integrated with Grafana (port no:- 31373).

The end.