End-to-End Automation with AWS, Kubernetes, etc
End-to-End Automation with AWS,
Kubernetes, and Integrated Security
Scans
Project Overview:
Our client needed to streamline and automate the CI/CD pipeline for their Java
application, ensuring both code quality and security compliance across the
development and deployment lifecycle. Challenges included:
● Manual Code Reviews and Security Scans: Code quality and
security vulnerabilities were inconsistently addressed, resulting
in delays and risks.
● Continuous Integration and Delivery: Building and deploying the
Java application manually was inefficient, increasing the risk of
human error.
● Security Compliance: The client required robust, automated
security checks for their Docker images and Kubernetes
deployment files to maintain compliance.
Proposed Solution & Architecture
Unified Techs designed and implemented a fully automated CI/CD pipeline using AWS
native services, focusing on both code quality and security.
CI/CD Pipeline Flow Overview
Architecture:
The pipeline included the following key stages:
● Code Review Automation with SonarQube: When a developer
submits a pull request (PR) in the CodeCommit repository,
SonarQube automatically analyzes the Java code for best
practices and provides feedback to the developer.
● Event-Driven Pipeline Triggering: After a PR is merged, an
Amazon EventBridge event is triggered to initiate the CI/CD
pipeline.
● Continuous Security Scanning:
● In the security scan stage, CodeBuild pipeline scans
the Dockerfile, Kubernetes Helm deployment files
using Checkov, and application source code based on
incremental changes.
● Aqua Security Trivy scans the resulting Docker image
for vulnerabilities before storing it in Amazon Elastic
Container Registry (ECR).
● Continuous Integration and Build: CodeBuild packages the
artifact into a Docker image and ensures the image meets
security standards before deployment.
● Continuous Delivery: The Docker image is automatically
deployed to Amazon Elastic Kubernetes Service (EKS) as a
container workload using Helm charts, ensuring a consistent
and secure deployment process.
Metrics for Success:
● Improved Code Quality: Automated code analysis reduced manual code
review time and increased adherence to best practices.
● Enhanced Security: Integrated security scanning identified vulnerabilities
early in the development process, minimizing risks before deployment.
● Faster Time to Production: By automating the entire build, security, and
deployment pipeline, deployment times were reduced by 50%.
● Increased Developer Efficiency: Developers could focus on coding while
the automated pipeline handled code quality checks, security scans, and
deployments.
Lessons Learned:
● Automation Enhances Security: Integrating continuous security scans into
the pipeline reduced vulnerabilities and maintained compliance.
● Efficiency Through Integration: Automating the entire CI/CD process from
code commits to deployment improved both speed and reliability.