Introduction to CI/CD on AWS

1. Introduction to CI/CD on AWS

Hello and welcome to this course on Automating Deployments on AWS.

2. Continuous cycle

Imagine this: every time your team deploys manually, something breaks. In this course, you'll learn to automate that entire process using AWS.

3. Meet the Instructor

I'm Dunieski Otano, an AWS Solutions Architect with 16 AWS certifications and nearly a decade of cloud experience. I've helped organizations build CI/CD pipelines and automate their deployment workflows, and I'm excited to help you do the same. Everything we cover maps to the deployment portion of the AWS Certified Developer Associate exam, the DVA-C02, so this course doubles as exam prep. Let's dive in.

4. Why CI/CD matters

Picture this: a developer finishes a feature, zips the code, and emails it to the ops team. Ops manually copies files to a server and hopes nothing breaks. This is slow, error-prone, and impossible to scale. CI/CD automates the entire path from code commit to production. Every change flows through a pipeline that builds and tests it, then deploys it on its own, giving you faster releases with far fewer mistakes.

5. The CI/CD lifecycle

A CI/CD pipeline has four stages. It starts at Source, where a commit triggers the pipeline. From there, Build compiles your code and installs dependencies, Test runs your automated checks, and Deploy pushes the release to staging or production. Each stage hands its output to the next as an artifact. The Build stage, for example, produces a ZIP file that Deploy then uses, like handing a package from one station to the next on an assembly line.

6. AWS Code services overview

AWS gives you one service per stage of the pipeline, so the four map cleanly onto Source, Build, Deploy, and orchestration. Your source lives in CodeCommit, a managed Git repository. The build and test work runs in CodeBuild, which compiles code, runs tests, and produces a deployable artifact. Deployment to EC2, Lambda, or ECS is handled by CodeDeploy. Tying it all together is CodePipeline, which moves artifacts from one stage to the next automatically.

7. CI vs continuous delivery vs continuous deployment

Three terms often get confused: Continuous Integration (CI) means every push triggers an automatic build and test. Continuous Delivery extends CI by deploying to staging automatically, but production still requires manual approval. This is the most common enterprise model. Continuous Deployment goes further: every passing build deploys to production with no human intervention. The right choice depends on your risk tolerance and regulatory requirements.

8. How CodePipeline orchestrates everything

CodePipeline connects stages in sequence. Each stage contains actions, which are specific tasks like pulling source code or running a build. The pipeline triggers automatically when code is pushed to your repository, then moves through each stage, passing artifacts along the way. If any stage fails, the pipeline stops and reports the error. You never have to manually kick off the next step; CodePipeline handles the entire flow.

9. A real-world pipeline example

Here is a real pipeline. When a developer pushes to CodeCommit, CodeBuild picks up the change, compiles the application, runs tests, and packages a ZIP artifact. That artifact then flows to staging, where CodeDeploy releases it for integration testing. Before production, a manual approval stage lets a team lead review the release, and once they approve, the same artifact deploys to production. Everything is automated except that single approval step.

10. Let's practice!

Now let's map these services to a real pipeline. Let's practice!

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