Secure CI/CD Pipeline with Trivy, SonarQube, and Azure DevOps
Integrating DevSecOps in Azure DevOps: Automating Code Quality, Dependency Scanning, and Secure Deployments to Kubernetes
1. Problem Statement
In modern software development, ensuring code quality and application security throughout the CI/CD lifecycle is essential to avoid vulnerabilities reaching production. However, integrating tools for dependency scanning, container security, and code quality checks into a seamless DevSecOps pipeline can be complex and error-prone.
The objective of this lab is to build a complete CI/CD pipeline using Azure DevOps that emphasizes security at every stage of the software delivery process. This includes:
Provisioning a self-hosted build agent with tools like Maven, Docker, Trivy, and SonarQube.
Running unit tests, code quality scans with SonarQube, and vulnerability scans using Trivy for both dependencies and Docker images.
Enforcing quality gates and fail conditions to prevent insecure or low-quality code from progressing in the pipeline.
Automatically building and pushing a secure Docker image to a registry.
Deploying the application to a Kubernetes cluster via a release pipeline.
Demonstrating secure SDLC principles with continuous integration and delivery triggers.
This lab helps teams adopt DevSecOps practices by integrating security scanning and code validation early into the CI/CD pipeline, ensuring reliable and secure application delivery.
2. Why We Need This Use Case
To catch vulnerabilities and code quality issues early in the software delivery lifecycle.
To automate secure software delivery with consistent standards using Azure DevOps.
To eliminate manual scanning processes, ensuring repeatable and reliable CI/CD practices.
To empower developers with security insights through SonarQube and Trivy before code is merged or deployed.
To integrate DevSecOps culture into the development cycle with minimal resistance.
This use case represents a real-world, production-ready solution to enforce “shift-left” security in CI/CD pipelines.
3. When We Need This Use Case
When building microservices or containerized applications for production.
When you need compliance with security or audit standards (e.g., OWASP, ISO).
When teams are deploying to Kubernetes clusters via automated release pipelines.
When traditional manual QA and security steps become bottlenecks.
When vulnerabilities in dependencies or images could risk your delivery speed or reputation.