AutoDeployX is a small end-to-end deployment pipeline I built while practicing real-world DevOps workflows. It takes a simple application, builds it with Jenkins, packages it into a Dockerimage, and deploys it using Terraform-managed infrastructure.

This project helped me understand how different DevOps tools fit together in an actual delivery pipeline rather than learning them individually.

• Pulls application code from GitHub

• Builds the app using Jenkins

• Creates a production-ready Docker image

• Pushes the image to Docker Hub

• Deploys infrastructure using Terraform

• Automatically deploys the latest build onto the provisioned server

The idea was to make a minimal but realistic CI/CD flow that I can reuse for my future projects

• Developer pushes code → GitHub

• Jenkins triggers a new pipeline run

• Code is built + tested

• A new Docker image is created and pushed to Docker Hub

• Terraform provisions the infrastructure if needed

• Application is deployed automatically on the target VM or container platform

• Logs and status are visible directly in Jenkins

This resembles a production workflow but stays lightweight and easy to understand

Tool Why I Used It

• Jenkins * Automates the build → test → deploy stages
• Docker * Packages the application consistently for any environment
• Terraform * Manages cloud infrastructure cleanly and repeatably
• GitHub* Version control + webhook trigger for Jenkins

CSS

AutoDeployX/ ├── Jenkinsfile ├── Dockerfile ├── terraform/ │ ├── main.tf │ ├── variables.tf │ └── outputs.tf └── src/ └── (application files)

bash

git clone https://github.com/suhano5/AutoDeployX.git cd AutoDeployX

-Add your GitHub credentials

-Set the Docker Hub credentials

-Point the pipeline to your Jenkinsfile

bash

-cd terraform -terraform init -terraform apply

Each commit pushes an updated image and redeploys the app.

• Writing and debugging Jenkins pipelines

• Connecting GitHub → Jenkins → Docker → Terraform

• Handling environment variables and credentials

• Deploying a simple app in an automated way

• Making the whole flow repeatable and Infrastructure-as-Code driven

• Add automated rollback strategy

• Implement Prometheus + Grafana monitoring

• Add a staging → production promotion step

• Convert deployment to Kubernetes (K8s)

• This project is mainly for my own learning, but improvements are welcome.