Hands-On Lab: Implementing Multi-Stage CI/CD Pipelines with AWS CodePipeline

In this lab, you will architect and deploy a fully automated Continuous Integration and Continuous Delivery (CI/CD) pipeline. Following the AWS Certified DevOps Engineer - Professional curriculum, you will integrate source control, automated builds, and a manual approval gate before a simulated deployment.

[!WARNING] Remember to run the teardown commands at the end of this lab to avoid ongoing charges. AWS CodePipeline charges $1.00 per active pipeline per month after the first 30 days.

Prerequisites

• AWS Account: An active AWS account with Administrator access.
• AWS CLI: Installed and configured with aws configure using your credentials.
• Region: This lab uses <YOUR_REGION> (e.g., us-east-1).
• IAM Knowledge: Basic understanding of IAM roles and service-linked roles.

Learning Objectives

• Configure an Amazon S3 source provider for versioned artifacts.
• Orchestrate a build process using AWS CodeBuild.
• Implement a Manual Approval stage to enforce governance.
• Manage and inspect pipeline Artifacts stored in S3.

Architecture Overview

The following diagram illustrates the flow of code from source to manual approval.

Step-by-Step Instructions

Step 1: Create the Source and Artifact Buckets

CodePipeline requires versioned S3 buckets to detect changes and store intermediate artifacts.

▶Console alternative

1. Navigate to S3 > Create bucket.
2. Name: brainybee-lab-source-<YOUR_ACCOUNT_ID>.
3. Under Bucket Versioning, select Enable.
4. Click Create bucket.

Step 2: Prepare the Source Artifact

You need a buildspec.yml file to tell CodeBuild how to handle your code.

1. Create a file named index.html with simple text: <h1>Hello DevOps Pro!</h1>.
2. Create a file named buildspec.yml with the following content:

1. Zip these files and upload them to your source bucket:

Step 3: Create the CodeBuild Project

CodeBuild will take your source.zip, read the buildspec.yml, and generate an output artifact.

[!TIP] If you don't have an IAM role ready, use the Console alternative below as it creates the service role automatically.

▶Console alternative

1. Go to CodeBuild > Create build project.
2. Project name: BrainyBee-Build.
3. Source provider: Amazon S3.
4. Bucket: brainybee-lab-source-<YOUR_ACCOUNT_ID>, S3 object: source.zip.
5. Environment: Managed image, Ubuntu, Standard runtime, Image: aws/codebuild/standard:5.0.
6. Service role: New service role.
7. Click Create build project.

Step 4: Create the Pipeline

Now, connect the Source and Build stages using CodePipeline.

▶Console Instructions (Recommended for Pipeline Creation)

1. Navigate to CodePipeline > Create pipeline.
2. Name: BrainyBee-Pipeline.
3. Source Stage: Provider: Amazon S3. Bucket: your source bucket. S3 object key: source.zip. Change detection: AWS CloudWatch Events.
4. Build Stage: Provider: AWS CodeBuild. Project name: BrainyBee-Build.
5. Deploy Stage: Click Skip deploy stage (we will add a manual approval instead).
6. Review and Create pipeline.

Step 5: Add a Manual Approval Stage

1. In the CodePipeline console, select your pipeline and click Edit.
2. Click + Add stage at the end of the pipeline. Name it Approval.
3. Click + Add action group.
4. Action name: Manager-Approval. Action provider: Manual approval.
5. Click Done and then Save.

Checkpoints

Troubleshooting

Challenge

Add a Unit Test Stage: Modify your pipeline to include a second CodeBuild project called BrainyBee-Test. This project should run a simple shell script to verify the content of output.html (e.g., grep "Hello" output.html). Insert this stage between Build and Approval.

Teardown

To avoid costs, delete all resources created:

Cost Estimate

Concept Review

Pipeline Concepts vs. DevOps Professional Exam