devops 1

DevOps me “pipeline” ka matlab hota hai automation steps jo code ko developer se production tak le jaate hain.
Docker, Jenkins aur Kubernetes sab ke alag roles hote hain — isliye unke pipelines bhi alag stages me kaam karte hain.

Main simple 3 pipelines (Jenkins, Docker, Kubernetes) production flow me samjha raha hoon.

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1️⃣ Jenkins Pipeline (CI Pipeline)

Purpose: Code ko build aur test karna (CI – Continuous Integration).

Typical Jenkins pipeline stages:

Code → Build → Test → Package → Docker Build → Push → Deploy

Example Jenkinsfile pipeline:

pipeline {
  agent any

  stages {
    stage('Code Checkout') {
      steps {
        git 'https://github.com/app/project.git'
      }
    }

    stage('Build') {
      steps {
        sh 'npm install'
      }
    }

    stage('Test') {
      steps {
        sh 'npm test'
      }
    }

    stage('Docker Build') {
      steps {
        sh 'docker build -t myapp:v1 .'
      }
    }

    stage('Push Image') {
      steps {
        sh 'docker push myrepo/myapp:v1'
      }
    }

    stage('Deploy') {
      steps {
        sh 'kubectl apply -f deployment.yaml'
      }
    }
  }
}

👉 Jenkins automation engine hai jo pipeline run karta hai.

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2️⃣ Docker Pipeline

Purpose: Application ko container image me convert karna.

Typical Docker pipeline:

Source Code
↓
Dockerfile
↓
Docker Build
↓
Docker Image
↓
Push to Registry

Example steps:

1️⃣ Dockerfile

FROM node:18
WORKDIR /app
COPY . .
RUN npm install
CMD ["node","app.js"]

2️⃣ Image build

docker build -t myapp:v1 .

3️⃣ Push to registry

docker push myrepo/myapp:v1

Registry examples:

• Docker Hub
• AWS ECR

👉 Docker pipeline ka output hota hai container image.

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3️⃣ Kubernetes Pipeline (Deployment Pipeline)

Purpose: Docker containers ko production me run aur manage karna.

Typical Kubernetes pipeline:

Docker Image
↓
Deployment YAML
↓
Kubernetes Cluster
↓
Pods
↓
Service
↓
Load Balancer
↓
Users

Example deployment:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  replicas: 3
  template:
    spec:
      containers:
      - name: myapp
        image: myrepo/myapp:v1

Deploy command:

kubectl apply -f deployment.yaml

Kubernetes automatically:

• containers run karega
• scaling karega
• crash hone par restart karega
• rolling update karega

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4️⃣ Full Production Pipeline (Real DevOps Flow)

Developer
↓
GitHub
↓
Jenkins Pipeline
↓
Build + Test
↓
Docker Pipeline
↓
Docker Image
↓
Registry
↓
Kubernetes Pipeline
↓
Pods
↓
Load Balancer
↓
Users

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5️⃣ Role Comparison

Tool	Role
Jenkins	CI/CD automation
Docker	Application containerization
Kubernetes	Container orchestration

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✅ Simple analogy

• Jenkins → manager
• Docker → packaging machine
• Kubernetes → factory workers

Manager pipeline run karta hai, packaging machine product banata hai, workers product run karte hain.

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