Introduction to CI/CD on AWS

Automating Deployments on AWS

Dunieski Otano

Amazon Web Services Solutions Architect

Continuous cycle

Meet the Instructor

Why CI/CD matters

• Manual deployments are slow and error-prone
• Developers push code, then wait for someone to deploy it
• CI/CD automates the path from code to production
• Faster releases, fewer errors

 

The CI/CD lifecycle

• Source: Code is committed to a repository
• Build: Code is compiled, dependencies installed
• Test: Automated tests validate the build
• Deploy: Application is released; artifacts pass between stages

AWS Code services overview

• CodeCommit: Source control (Git repository)
• CodeBuild: Compile, test, and package
• CodeDeploy: Release to EC2, Lambda, or ECS
• CodePipeline: Orchestrates all stages together

   

 

CI vs continuous delivery vs continuous deployment

• Continuous Integration (CI): Merge, build, and test on every push
• Continuous Delivery: Auto-deploy to staging; manual approval for prod (most common)
• Continuous Deployment: Every passing build goes live automatically

 

How CodePipeline orchestrates everything

• CodePipeline connects stages in sequence
• Each stage contains one or more actions
• Pipeline triggers automatically on source changes
• If any stage fails, the pipeline stops

A real-world pipeline example

• Source: Developer pushes to CodeCommit
• Build: CodeBuild runs tests, packages a ZIP
• Staging: CodeDeploy releases to staging
• Approval => Production: Team lead approves, then deploys to prod

 

Let's practice!

Automating Deployments on AWS