From Code to Cloud: Building Your First CI/CD Pipeline on AWS
Learn how to build a CI/CD pipeline on AWS that automatically builds, containerizes, and deploys an application whenever new code is pushed to GitHub.
Series: From Code to Cloud: My DevOps Journey on AWS (5 articles)
- 1From Code to Cloud: Building Your First CI/CD Pipeline on AWS This article
From Code to Cloud: Building Your First CI/CD Pipeline on AWS
Introduction
When I started learning DevOps, CI/CD was one of the first concepts that caught my attention.
The idea is simple: instead of manually building and deploying an application every time a change is made, we can automate the process.
In this article, I'll explain how I approached building a simple CI/CD workflow using AWS and how the different services work together.
What Is CI/CD?
CI/CD stands for Continuous Integration and Continuous Delivery/Deployment.
A typical workflow looks like this:
Code → Build → Test → Package → Deploy
Whenever a developer pushes a change, the pipeline can automatically take that change through the required stages.
This helps reduce repetitive manual work and provides faster feedback when something goes wrong.
What Are We Building?
For this project, the goal is to create a simple workflow that takes application code from a GitHub repository and deploys it to an application running on AWS.
The overall flow looks like this:
GitHub → AWS CodePipeline → AWS CodeBuild → Amazon ECR → Amazon ECS
Each service has a different responsibility.
GitHub
GitHub stores the application's source code.
When a change is pushed to the repository, it can trigger the pipeline.
AWS CodePipeline
CodePipeline coordinates the different stages of the delivery process.
It connects the source, build, and deployment stages into a single workflow.
AWS CodeBuild
CodeBuild provides the environment needed to build and test the application.
It can also create the container image that will be deployed.
Amazon ECR
Amazon Elastic Container Registry (ECR) stores the application's container images.
The image produced during the build process can be pushed to ECR and later retrieved by the deployment environment.
Amazon ECS
Amazon Elastic Container Service (ECS) runs the containerized application.
This is where the application eventually becomes available as a running service.
Understanding the Complete Flow
Once these services are connected, the workflow looks like this:
Developer
↓
Pushes code to GitHub
↓
CodePipeline detects the change
↓
CodeBuild builds the application
↓
Container image is stored in ECR
↓
ECS deploys the updated application
↓
Application is running
This is the part that made CI/CD much easier for me to understand.
Instead of thinking about CI/CD as a single tool, I started seeing it as a collection of automated stages working together.
Why Automation Matters
Imagine making several changes to an application every day.
If every change requires manually building the application, creating a container, uploading it, and deploying it, the process can quickly become repetitive and error-prone.
With CI/CD, many of these steps can happen automatically.
The goal isn't simply to deploy faster. Automation also creates a repeatable process that can be tested, monitored, and improved over time.
What I Learned
Building and exploring this workflow helped me understand several important DevOps concepts:
- Automation reduces repetitive manual tasks.
- CI/CD is a process, not just a single tool.
- Containers provide a consistent way to package applications.
- AWS services can be combined to create an automated delivery workflow.
- IAM permissions are an important part of connecting AWS services securely.
- Monitoring and logs are essential when troubleshooting failures.
Most importantly, I learned that understanding how the pieces connect is just as important as learning each AWS service individually.
What's Next?
This is only the beginning of my DevOps journey.
The next step I want to explore is Infrastructure as Code (IaC).
Instead of manually creating AWS resources, Infrastructure as Code allows infrastructure to be defined and managed using configuration files.
Terraform is one of the tools I plan to explore next.
My goal is to gradually move from:
Manual → Automated → Reproducible → Scalable
and continue building my understanding of DevOps and AWS through practical projects.
Conclusion
Building a first CI/CD workflow is a great way to understand how DevOps concepts come together.
The complete journey can be summarized simply:
Code → Build → Package → Deploy → Monitor
AWS provides many services that can help automate this journey.
For me, this project was less about creating a complex production system and more about turning a concept I had only read about into something I could understand through practice.
This is just the first step in my journey from code to cloud.
Series: From Code to Cloud: My DevOps Journey on AWS (5 articles)
- 1From Code to Cloud: Building Your First CI/CD Pipeline on AWS This article
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