Building a Scalable CI/CD Pipeline with GitHub Actions and AWS Deployment

In today’s fast-paced development environment, seamless software delivery is no longer optional — it’s a necessity. At DETL, we empower startups and enterprises to embrace modern DevOps workflows that prioritize speed, reliability, and scalability. Our success stories — from Cap AI and Psyvatar to Hutsy and EMAS Toronto — demonstrate our deep technical expertise in building scalable infrastructure and cloud-based solutions.

In this article, we’ll deep dive into building a scalable CI/CD pipeline using GitHub Actions and AWS deployment. You’ll learn how to implement continuous integration, continuous delivery, automated testing, and pipeline automation strategies that accelerate your development cycles, improve code quality, and deliver consistent value to your users.

Why CI/CD is Central to Modern Software Development

Continuous Integration and Continuous Delivery (CI/CD) are at the heart of modern DevOps workflows.

• Continuous Integration (CI) ensures every code change is automatically built, tested, and validated before merging into the main branch.
• Continuous Delivery (CD) automates the release process so new features and fixes can be deployed seamlessly and safely.

With a well-structured CI/CD pipeline, teams can deliver reliable updates multiple times per day, minimize bugs, and drastically reduce manual intervention.

At DETL, we’ve integrated custom CI/CD pipelines for clients like Absolute Football Training and Hutsy, enabling them to push frequent, zero-downtime updates while meeting rigorous quality and security standards.

Choosing GitHub Actions for Pipeline Automation

GitHub Actions is a powerful and flexible automation tool for building CI/CD pipelines. It allows developers to define custom workflows directly within their repositories using simple YAML configuration files.

Why we love GitHub Actions for DevOps:

• Tight integration with GitHub repositories
• Built-in support for secrets and environment variables
• Scalable runners (hosted or self-hosted)
• Easy integration with AWS, Docker, and other DevOps tools

Here’s a basic example of a CI pipeline that runs tests on each pull request:

1name: Run Tests
2
3on:
4  pull_request:
5    branches: [main]
6
7jobs:
8  test:
9    runs-on: ubuntu-latest
10
11    steps:
12    - name: Checkout repo
13      uses: actions/checkout@v3
14
15    - name: Set up Node.js
16      uses: actions/setup-node@v4
17      with:
18        node-version: '18'
19
20    - name: Install dependencies
21      run: npm install
22
23    - name: Run tests
24      run: npm test

This basic automation validates each PR, ensuring code quality is maintained at every stage of development.

Integrating AWS Deployment into Your Pipeline

Cloud deployment is a critical phase in a robust CI/CD journey. At DETL, we commonly work with AWS because of its mature ecosystem, scalability, and flexible service offerings.

For example, in the Cap AI project, we used Amazon ECS (Elastic Container Service) and AWS Fargate to handle scalable, containerized backend deployments. Meanwhile, Psyvatar makes heavy use of AWS Lambda for rapid function deployments via CI/CD pipelines.

Let’s explore how you can integrate AWS into your GitHub Actions workflow.

Example: Deploying to AWS S3 via GitHub Actions

For static websites and frontend applications, Amazon S3 is an excellent choice. Here's a sample deployment pipeline that builds a React app and uploads the compiled assets to an S3 bucket:

1name: Deploy to S3
2
3on:
4  push:
5    branches: [main]
6
7jobs:
8  deploy:
9    runs-on: ubuntu-latest
10
11    steps:
12    - name: Checkout code
13      uses: actions/checkout@v3
14
15    - name: Install dependencies
16      run: npm install
17
18    - name: Build frontend
19      run: npm run build
20
21    - name: Deploy to S3
22      uses: jakejarvis/s3-sync-action@v0.5.1
23      with:
24        args: --acl public-read --delete
25      env:
26        AWS_S3_BUCKET: ${{ secrets.AWS_S3_BUCKET }}
27        AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
28        AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
29        AWS_REGION: 'us-east-1'
30        SOURCE_DIR: 'build'

This is pipeline automation in action — the application deploys automatically to the cloud whenever code is pushed to the main branch.

Implementing Infrastructure as Code (IaC)

Infrastructure as Code (IaC) is foundational to scalable and repeatable deployments. With IaC tools such as AWS CloudFormation or Terraform, teams can version control their infrastructure just like application code.

For EMAS Toronto, DETL leveraged CloudFormation templates to provision and maintain cloud resources — including EC2 instances, VPCs, and RDS databases — securely and consistently across environments.

Here’s a simplified CloudFormation snippet that provisions an S3 bucket:

1Resources:
2  StaticAssetsBucket:
3    Type: AWS::S3::Bucket
4    Properties:
5      BucketName: my-app-assets-bucket
6      AccessControl: PublicRead
7      VersioningConfiguration:
8        Status: Enabled

By committing this configuration to your Git repo, you can automate deployment using your GitHub Actions CI/CD pipeline.

Testing Automation in CI/CD Workflows

Automated testing is essential in CI/CD to catch issues early. Unit tests, integration tests, and end-to-end tests should all be part of your pipeline.

In the Hutsy fintech project, we ensured financial data integrity through robust test coverage and test-driven development (TDD). GitHub Actions ran automated test suites on every pull request, dramatically reducing production bugs.

A common setup might include Jest for unit testing and Cypress for end-to-end browser testing:

1- name: Run Jest tests
2  run: npm run test:unit
3
4- name: Run Cypress tests
5  run: npm run test:e2e

Test failures prevent broken code from progressing down the pipeline, ensuring only vetted code reaches production.

Real-World CI/CD Architecture in Practice

Let’s examine a real-world CI/CD architecture implemented by DETL for a recent AI web application.

Use Case: Deploying Cap AI with GitHub Actions + AWS ECS

The Cap AI platform — a social media caption generator using artificial intelligence — required scalable backend processing with real-time API responses.

We implemented CI/CD pipelines as follows:

• Developers push code to GitHub triggering the CI pipeline
• GitHub Actions runs unit tests, builds Docker image
• Image is pushed to Amazon ECR (container registry)
• A CD workflow automatically deploys the newest image to ECS via AWS CLI

Key pipeline components:

1- name: Configure AWS credentials
2  uses: aws-actions/configure-aws-credentials@v2
3  with:
4    role-to-assume: ${{ secrets.AWS_DEPLOY_ROLE }}
5    aws-region: us-east-1
6
7- name: Build and push Docker image
8  run: |
9    docker build -t capai-backend .
10    docker tag capai-backend:latest $AWS_ACCOUNT_ID.dkr.ecr.us-east-1.amazonaws.com/capai-backend:latest
11    docker push $AWS_ACCOUNT_ID.dkr.ecr.us-east-1.amazonaws.com/capai-backend:latest
12
13- name: Deploy to ECS
14  run: |
15    aws ecs update-service \
16      --cluster capai-cluster \
17      --service capai-backend \
18      --force-new-deployment

This automated workflow ensures production deployments are consistent, secure, and fully traceable.

Benefits of an Optimized CI/CD Pipeline

Adopting a streamlined CI/CD solution like the one we build at DETL offers several benefits:

• Faster release cycles
• Lower risk deployments
• Improved developer productivity
• Better collaboration via automated QA checks
• Scalable infrastructure with cloud-native tools

Whether it's launching a fintech platform like Hutsy or scaling AI mental health services with Psyvatar, we apply CI/CD best practices at every level of infrastructure and application lifecycle.

Conclusion: Power Your Software Delivery with DETL

Building a scalable CI/CD pipeline isn't just about automation — it’s about building a culture of high-velocity, low-risk delivery.

With expertise in GitHub Actions, AWS cloud deployment, automated testing, and infrastructure as code, DETL helps development teams ship faster with confidence. Our strategic CI/CD implementations for projects like Cap AI, Psyvatar, and EMAS Toronto are proof of how infrastructure and workflow automation can directly enhance business outcomes.

Ready to modernize your DevOps workflow? Contact DETL today to start building a future-proof CI/CD pipeline that’s tailored to your business goals. Let’s turn great ideas into production-ready products — efficiently, securely, and at scale.