🚀 SpaceX Launch Tracker (Technical Challenge - efrouting)

Serverless backend for ingesting and exposing SpaceX launch data.
Built with AWS Lambda, DynamoDB, API Gateway, and automated using SAM and GitHub Actions.

📁 Project Structure

SpacexBackend/               # Backend (Lambda functions + API Gateway + DynamoDB)
.
├── api-docs/
│   ├── swagger_template.yaml       # Template file (with placeholder for API URL)
│   ├── swagger_ui/
│   │   └── index.html              # Swagger UI HTML
│   └── upload_swagger.sh           # Upload script (replaces API URL + syncs to S3)
├── aws_lambda/
│   ├── fetch_launches/         # Lambda to fetch SpaceX launches and store in DynamoDB
│   └── get_launches/           # Lambda to expose latest launches via GET
├── tests/                      # Unit tests per lambda
├── .github/workflows/          # GitHub Actions CI/CD workflows
│   ├── deploy-backend.yml
│   └── test-backend.yml
├── template.yaml               # SAM infrastructure template
├── samconfig.toml              # SAM deployment config
├── requirements.txt            # Shared dependencies (if needed)
└── README.md

📘 API Documentation (Swagger / OpenAPI)

This project includes an OpenAPI specification for the SpaceX Launches API.
The Swagger UI is automatically deployed to S3 every time swagger_template.yaml or upload_swagger.sh is modified on the main branch.

🧪 Preview Interactive API Docs

Once deployed, Swagger UI will be available at: swagger

👉 Open Swagger Editor

🛠️ How to Deploy Infrastructure from Scratch

📌 Requirements

• AWS CLI configured (with credentials)
• AWS SAM CLI installed
• Python 3.10+

🚀 Initial setup

sam build
sam deploy --guided

You’ll be prompted to set:

• Stack name: spacex-backend
• Region: e.g., us-east-1
• IAM capabilities: CAPABILITY_IAM
• Save configuration: yes → will create samconfig.toml

Next time:

sam deploy

🚀 Manual Deployment From Scratch

This project uses AWS SAM to provision the full backend infrastructure automatically.

📦 Requirements

• AWS CLI configured (aws configure)
• AWS SAM CLI installed (sam --version)
• Python 3.10 or higher

🛠️ Steps to deploy manually

1. Clone the repository:

git clone https://github.com/your-username/SpacexBackend.git
cd SpacexBackend

2. Build the SAM application:

sam build

3. Deploy the stack for the first time:

sam deploy --guided

You’ll be prompted to configure: Stack name → spacex-backend AWS region → us-east-1 Capabilities → CAPABILITY_IAM Save config to samconfig.toml → Yes

4. On future deployments:

sam deploy

📄 Deploy Swagger UI Manually

The Swagger UI is hosted on an S3 bucket configured as a static website.

📁 Folder structure

Make sure your folder api-docs/swagger_ui/ contains:

• index.html → Swagger UI frontend
• swagger.yaml → Generated API definition (automatically injected from template)

🛠️ Generate and upload Swagger files manually:

1. Make the upload script executable:

chmod +x api-docs/upload_swagger.sh

2. Run the script:

bash ./api-docs/upload_swagger.sh

This will:

• Inject the deployed API Gateway URL into your swagger_template.yaml.
• Generate swagger_ui/swagger.yaml.
• Upload the entire swagger_ui/ folder to the S3 bucket created by SAM.

⚠️ The bucket name is automatically derived as: spacex-swagger-ui-<your-account-id>

🧪 Running Tests Locally

Tests are isolated per lambda.

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
pytest --cov=aws_lambda tests/

⚙️ CI/CD Pipeline with GitHub Actions

🔁 Automated Triggers

• On push to main
• On pull request to main

🧪 test-backend.yml

• Installs dependencies
• Runs all unit tests
• Shows coverage report

🚀 deploy-backend.yml

• Runs tests
• Builds SAM application
• Deploys stack to AWS
• Exports API Gateway URL (SpaceXLaunchesApiEndpoint)

📘 upload-swagger.yml

• Watches for changes to swagger_template.yaml or upload_swagger.sh.
• Automatically rebuilds Swagger and syncs it to the S3 bucket.
• Uses outputs from the backend stack to inject the correct API URL.

AWS credentials and region are managed via GitHub Secrets and Environment Variables.

🔗 How Components Interact

graph TD
    SpaceXAPI[SpaceX API] -->|fetch_launches.py| FetchLambda
    FetchLambda -->|PutItem| DynamoDBTable(SpaceXLaunchesDB)
    User -->|GET /launches| ApiGateway
    ApiGateway --> GetLambda
    GetLambda -->|Scan| DynamoDBTable

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• fetch_launches Lambda runs every 6 hours (cron schedule).
• get_launches Lambda exposes the last 10 launches via HTTP GET.
• All infrastructure is deployed via template.yaml.

📤 Output Exports

The backend exposes this output:

Outputs:
  SpaceXLaunchesApiEndpoint:
    Description: "Base URL for the SpaceX Launches HTTP API"
    Value: !Sub "https://${ServerlessHttpApi}.execute-api.${AWS::Region}.amazonaws.com"
    Export:
      Name: SpaceXLaunchesApiEndpoint

This URL is consumed by the frontend through CI and injected into the build.

✨ Extending

This solution is scalable and professional:

• Add new Lambdas in aws_lambda/
• Add integration tests with mocks or live resources
• Add rollback handling in CI with sam deploy versions
• Integrate monitoring via CloudWatch

🧠 Summary

✅ Infrastructure as Code (SAM)

✅ Automated testing and deployment (CI/CD)

✅ Separation of logic per lambda

✅ Cloud-native, production-ready stack