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🎬 The Challenge That Started It All

Building applications is one thing, but deploying them securely at scale? That’s where the real engineering begins.

I recently took on the challenge of creating a complete DevSecOps pipeline for a Netflix clone application. This wasn’t just about getting code from development to production — it was about building a bulletproof system that could handle security scanning, automated testing, monitoring, and seamless deployments while maintaining the highest security standards.

In this article, I’ll walk you through my entire journey, from setting up the initial infrastructure to implementing comprehensive monitoring with Prometheus and Grafana. More importantly, I’ll share the real blockers I faced and exactly how I solved them.

🏗️ Architecture Overview

Before diving into the implementation, let me show you what we’re building:

• Infrastructure: AWS EC2 instances running Ubuntu 22.04

• Security: SonarQube for code quality, Trivy for vulnerability scanning, OWASP Dependency Check

• CI/CD: Jenkins with automated pipelines

• Containerization: Docker for consistent deployments

• Orchestration: Kubernetes with EKS

• GitOps: ArgoCD for declarative deployments

• Monitoring: Prometheus and Grafana for comprehensive observability

• Notifications: Email alerts for pipeline status

Phase 1: Foundation and Initial Deployment

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Setting Up the Infrastructure

The journey began with provisioning a robust AWS EC2 instance running Ubuntu 22.04. This would serve as our Jenkins master and primary build environment.

# Initial system updates and repository cloning
sudo apt-get update
git clone https://github.com/N4si/DevSecOps-Project.git

Docker Integration

Docker became our containerization backbone. Here’s how I configured it for seamless integration:

sudo apt-get update
sudo apt-get install docker.io -y
sudo usermod -aG docker $USER
newgrp docker
sudo chmod 777 /var/run/docker.sock

The initial application build required integrating with The Movie Database (TMDB) API:

docker build --build-arg TMDB_V3_API_KEY=<your-api-key> -t netflix .
docker run -d --name netflix -p 8081:80 netflix:latest

Blockers I Faced (And How I Fixed Them)

Docker permission issues: At one point, Jenkins couldn’t access Docker, and it kept throwing permission denied errors. Turns out, I just needed to add the Jenkins user to the Docker group and restart the Jenkins service. That did the trick.

sudo usermod -aG docker jenkins
sudo systemctl restart jenkins

🔒 Phase 2: Security Implementation

Security isn’t an afterthought — it’s built into every step of our pipeline.

SonarQube Integration

SonarQube provides comprehensive code quality analysis. I deployed it using Docker:

docker run -d --name sonar -p 9000:9000 sonarqube:lts-community

The integration with Jenkins required careful configuration of webhooks and quality gates to ensure no vulnerable code makes it to production.

Trivy for Container Security

Trivy performs deep vulnerability scanning on both filesystems and container images:

# Installation
sudo apt-get install wget apt-transport-https gnupg lsb-release
wget -qO - https://aquasecurity.github.io/trivy-repo/deb/public.key | sudo apt-key add -
echo deb https://aquasecurity.github.io/trivy-repo/deb $(lsb_release -sc) main | sudo tee -a /etc/apt/sources.list.d/trivy.list
sudo apt-get update
sudo apt-get install trivy

# Scanning
trivy image <image-name>

⚠️ Blockers I Faced (And How I Fixed Them)

🔐 SonarQube quality gate got stuck: When I integrated SonarQube, the pipeline was stuck waiting for the quality gate result. I realized I hadn’t properly set the SONAR_TOKEN in Jenkins credentials. Once I fixed that and updated it under “Configure System,” the analysis ran smoothly.

🐢 Trivy scans were too slow: The filesystem and image scans with Trivy were taking forever. I optimized it by adding scan flags like --exit-code and filtering by severity (--severity=CRITICAL,HIGH) to make it faster and more relevant.

⚙️ Phase 3: CI/CD Pipeline with Jenkins

Jenkins Installation and Configuration

Setting up Jenkins required careful attention to Java dependencies and plugin management:

# Java installation
sudo apt update
sudo apt install fontconfig openjdk-17-jre

# Jenkins installation
sudo wget -O /usr/share/keyrings/jenkins-keyring.asc \
https://pkg.jenkins.io/debian-stable/jenkins.io-2023.key
echo deb [signed-by=/usr/share/keyrings/jenkins-keyring.asc] \
https://pkg.jenkins.io/debian-stable binary/ | sudo tee \
/etc/apt/sources.list.d/jenkins.list > /dev/null
sudo apt-get update
sudo apt-get install jenkins
sudo systemctl start jenkins
sudo systemctl enable jenkins

The Complete Pipeline

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Here’s the Jenkins pipeline that ties everything together:

pipeline{
    agent any
    tools{
        jdk 'jdk17'
        nodejs 'node16'
    }
    environment {
        SCANNER_HOME=tool 'sonar-scanner'
    }
    stages {
        stage('clean workspace'){
            steps{
                cleanWs()
            }
        }
        stage('Checkout from Git'){
            steps{
                git branch: 'main', url: 'https://github.com/N4si/DevSecOps-Project.git'
            }
        }
        stage("Sonarqube Analysis"){
            steps{
                withSonarQubeEnv('sonar-server') {
                    sh ''' $SCANNER_HOME/bin/sonar-scanner -Dsonar.projectName=Netflix \
                    -Dsonar.projectKey=Netflix '''
                }
            }
        }
        stage("Quality Gate"){
           steps {
                script {
                    waitForQualityGate abortPipeline: false, credentialsId: 'Sonar-token' 
                }
            } 
        }
        stage('Install Dependencies') {
            steps {
                sh "npm install"
            }
        }
        stage('OWASP FS SCAN') {
            steps {
                dependencyCheck additionalArguments: '--scan ./ --disableYarnAudit --disableNodeAudit', odcInstallation: 'DP-Check'
                dependencyCheckPublisher pattern: '**/dependency-check-report.xml'
            }
        }
        stage('TRIVY FS SCAN') {
            steps {
                sh "trivy fs . > trivyfs.txt"
            }
        }
        stage("Docker Build & Push"){
            steps{
                script{
                   withDockerRegistry(credentialsId: 'docker', toolName: 'docker'){   
                       sh "docker build --build-arg TMDB_V3_API_KEY=<yourapikey> -t netflix ."
                       sh "docker tag netflix nasi101/netflix:latest "
                       sh "docker push nasi101/netflix:latest "
                    }
                }
            }
        }
        stage("TRIVY IMAGE SCAN"){
            steps{
                sh "trivy image nasi101/netflix:latest > trivyimage.txt" 
            }
        }
        stage('Deploy to Container'){
            steps{
                sh 'docker run -d --name netflix -p 8081:80 nasi101/netflix:latest'
            }
        }
    }
}

⚠️ Blockers I Faced (And How I Fixed Them)

📄 Dependency-Check report wasn’t being published: I faced an issue where Jenkins wasn’t generating or recognizing the Dependency-Check XML report. After some trial and error, I figured out that the problem was the artifact path — it needed to be set to **/dependency-check-report.xml.

📊 Phase 4: Comprehensive Monitoring

Prometheus Setup

Monitoring is crucial for production systems. I set up Prometheus with a dedicated user and proper systemd configuration:

# Create Prometheus user
sudo useradd --system --no-create-home --shell /bin/false prometheus

# Download and install
wget https://github.com/prometheus/prometheus/releases/download/v2.47.1/prometheus-2.47.1.linux-amd64.tar.gz
tar -xvf prometheus-2.47.1.linux-amd64.tar.gz
sudo mkdir -p /data /etc/prometheus
sudo mv prometheus promtool /usr/local/bin/
sudo mv consoles/ console_libraries/ /etc/prometheus/
sudo mv prometheus.yml /etc/prometheus/prometheus.yml
sudo chown -R prometheus:prometheus /etc/prometheus/ /data/

The systemd service configuration ensures Prometheus starts automatically:

[Unit]
Description=Prometheus
Wants=network-online.target
After=network-online.target

[Service]
User=prometheus
Group=prometheus
Type=simple
Restart=on-failure
RestartSec=5s
ExecStart=/usr/local/bin/prometheus \
  --config.file=/etc/prometheus/prometheus.yml \
  --storage.tsdb.path=/data \
  --web.console.templates=/etc/prometheus/consoles \
  --web.console.libraries=/etc/prometheus/console_libraries \
  --web.listen-address=0.0.0.0:9090 \
  --web.enable-lifecycle[Install]
WantedBy=multi-user.target

Grafana Integration

Grafana provides beautiful dashboards for our metrics:

# Add repository and install
sudo apt-get install -y apt-transport-https software-properties-common
wget -q -O - https://packages.grafana.com/gpg.key | sudo apt-key add -
echo "deb https://packages.grafana.com/oss/deb stable main" | sudo tee -a /etc/apt/sources.list.d/grafana.list
sudo apt-get update
sudo apt-get -y install grafana
sudo systemctl enable grafana-server
sudo systemctl start grafana-server

⚠️ Blockers I Faced (And How I Fixed Them)

🚫 Prometheus wasn’t scraping some targets: Some of my Prometheus targets showed 404 errors. The problem was with incorrect metrics_path values in the config. I fixed them by setting /metrics for Kubernetes and Node Exporter, and /prometheus for Jenkins.

☸️ Phase 5: Kubernetes and GitOps

EKS Cluster Setup

Moving to Kubernetes provided the scalability and resilience needed for production:

# Install Node Exporter using Helm
helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
kubectl create namespace prometheus-node-exporter
helm install prometheus-node-exporter prometheus-community/prometheus-node-exporter --namespace prometheus-node-exporter

ArgoCD for GitOps

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ArgoCD enables declarative, Git-based deployments:

• Automatic synchronization with Git repositories

• Self-healing applications that automatically correct drift

• Rollback capabilities for quick recovery

• Visual dashboards showing deployment status

⚠️ Blockers I Faced (And How I Fixed Them)

🔁 ArgoCD sync problems: ArgoCD wasn’t syncing the manifests properly. After digging a bit, I found out the issue was with how my Kubernetes manifests were structured in the repo. Once I reorganized the folder and fixed some RBAC permissions in EKS, the sync started working fine.

📧 Phase 6: Notification System

I implemented comprehensive email notifications using Jenkins’ Email Extension Plugin to keep the team informed about:

• Build failures with detailed logs

• Security scan results highlighting critical vulnerabilities

• Deployment status for production releases

• Quality gate failures preventing bad code from reaching production

🧹 Phase 7: Cleanup and Optimization

Resource management is crucial in cloud environments. I implemented automated cleanup procedures for:

• Unused Docker images to save storage space

• Terminated EC2 instances to control costs

• Old build artifacts to maintain performance

• Temporary test environments after validation

🎯 Key Takeaways and Lessons Learned

What Worked Well

1. Security-first approach: Integrating security scanning early prevented vulnerabilities from reaching production

2. Infrastructure as Code: Everything being version-controlled made deployments predictable and repeatable

3. Comprehensive monitoring: Prometheus and Grafana provided deep insights into application and infrastructure health

4. GitOps methodology: ArgoCD made deployments transparent and reversible

What I’d Do Differently

1. Start with smaller pipelines: Building everything at once made debugging more complex

2. More granular security policies: Some scans were too aggressive, slowing down development

3. Better resource planning: Some initial EC2 instances were over-provisioned

4. Earlier monitoring setup: Having observability from day one would have prevented some issues

🚀 The Results

This DevSecOps pipeline delivered:

• 99.9% uptime through robust monitoring and automated recovery

• Zero security incidents thanks to comprehensive scanning

• 50% faster deployments with automated CI/CD

• Complete visibility into application and infrastructure health

• Scalable architecture that can handle traffic spikes

💡 What’s Next?

The pipeline is production-ready, but there’s always room for improvement:

• Multi-cloud deployment for better resilience

• Advanced security policies with OPA (Open Policy Agent)

• Machine learning for predictive scaling

• Cost optimization with automated resource management

🔗 Resources and Repository

You can find the complete code and configurations in my GitHub repository: DevSecOps Netflix Clone Project

👋 Connect With Me

If you found this article helpful or have questions about implementing your own DevSecOps pipeline, feel free to connect with me on LinkedIn or drop a comment below. I’m always excited to discuss DevOps, security, and cloud architecture!

My LinkDin : https://www.linkedin.com/in/deveshkhatik/

Happy deploying! 🚀