Lab: Preparing Application Artifacts for AWS Deployment

In this lab, you will learn how to organize application code, manage dependencies, and prepare environment-specific configurations as required for the AWS Certified Developer - Associate (DVA-C02) exam. We will focus on creating a deployment-ready package for an AWS Lambda function, utilizing a standard directory structure and AWS Systems Manager Parameter Store for externalized configuration.

[!WARNING] This lab involves creating resources in your AWS account. Ensure you follow the Clean-Up / Teardown section at the end to avoid unnecessary charges.

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Prerequisites

• AWS Account: An active AWS account with Administrator access or equivalent permissions for IAM, SSM, and S3.
• AWS CLI: Installed and configured with your credentials (aws configure).
• Python 3.9+: Installed on your local machine to manage dependencies.
• Text Editor: VS Code, Sublime, or similar.

Learning Objectives

• Organize a project directory structure compliant with AWS deployment best practices.
• Manage code dependencies within a package (e.g., requirements.txt and vendor folders).
• Externalize application configuration using AWS Systems Manager Parameter Store.
• Create a valid buildspec.yml file for AWS CodeBuild to automate artifact creation.

Architecture Overview

This lab simulates the "Preparation" phase of a CI/CD pipeline. We focus on the local environment and the cloud configuration store.

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Step-by-Step Instructions

Step 1: Initialize the Project Structure

AWS recommends a clean separation between source code, tests, and configuration files.

▶Console alternative

Navigate to your local file explorer and create the folder brainybee-todo-app. Inside, create a folder named src and three empty files named app.py, requirements.txt, and buildspec.yml.

Step 2: Define Dependencies

For AWS Lambda, dependencies must be packaged along with the function code. We will use the requests library as an example.

1. Open requirements.txt and add:

1. Install dependencies locally into a temporary directory to simulate a deployment package:

[!TIP] Installing with -t src/ (target) places the libraries directly in your source folder so they are included when the folder is zipped for Lambda.

Step 3: Configure Environment-Specific Settings

Instead of hardcoding the "Database Table Name" or "API Endpoint," we use AWS Systems Manager Parameter Store.

▶Console alternative

1. Open the AWS Systems Manager console.
2. In the left navigation, choose Parameter Store.
3. Click Create parameter.
4. Name: /todo-app/dev/api-url | Type: String | Value: https://dev.api.brainybee.com.
5. Click Create parameter.

Step 4: Create the Build Specification

AWS CodeBuild requires a buildspec.yml file in the root directory to know how to handle your artifacts.

Paste the following into your buildspec.yml file:

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Checkpoints

1. Directory Check: Run ls -R. You should see src/ containing app.py and several library folders (like requests).
2. Parameter Store Check: Verify your parameter exists in AWS.
   bashCopy

   aws ssm get-parameter --name "/todo-app/dev/api-url" --query "Parameter.Value"
3. Artifact Readiness: Run zip -v. If you can generate a .zip file from the src folder, your artifact is ready for deployment to S3 or Lambda.

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Troubleshooting

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Clean-Up / Teardown

[!IMPORTANT] Always delete cloud resources to prevent unexpected bills.

1. Delete the SSM Parameter:

1. Remove local files:

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Challenge

Scenario: Your security team requires that the API URL for production be encrypted. Task: Create a new parameter named /todo-app/prod/api-url using the --type "SecureString" flag in the CLI. Then, attempt to retrieve its value using aws ssm get-parameter --name ... --with-decryption.

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Cost Estimate

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Concept Review