Sports fans thrive on up-to-the-minute updates, especially during game day. As a DevOps engineer, I recently built a system that delivers real-time notifications of NBA game information via SMS or email using AWS, Python, and NBA APIs. This project demonstrates how to integrate cloud services, API interactions, and best practices to create an efficient, scalable solution.
Overview
The system combines multiple technologies and principles:
Amazon SNS: For sending notifications.
AWS Lambda: To process NBA game data.
Amazon EventBridge: To automate periodic data fetching.
Python: For API integration and data processing.
IAM Least Privilege: Ensuring secure and minimal access.
NBA API: Fetches real-time game information(sportsdata.io.
Key Features
Real-time game updates via SMS or email.
Tracks scores, team names, and game status.
Automates notifications using EventBridge and Lambda.
Ensures secure access with IAM best practices.
Step-by-Step Implementation
1. Set Up Prerequisites:
AWS Account: Ensure you have admin access.
NBA API Key: Sign up with an NBA API provider (e.g., Sportsdata.io).
IAM Role with Least Privilege: Grant Lambda minimal permissions for SNS and EventBridge.
2. Create an SNS Topic:
Navigate to Amazon SNS and create a
Standardtopic namedNBA_Game_Alerts.Allow users to subscribe with email or phone numbers.
3. Write the Lambda Function: Use Python to fetch NBA scores using the NBA API, process the data from JSON to human readable format, and publish updates to the SNS topic. The code snippet can be found in this GitHub Repo: https://github.com/Faoziyah/30_days_devops_challenge/tree/main/DevOps_Challenge_Day2/NBA_Game_Day_Notification
4. Configure Amazon EventBridge:
Create a rule to trigger the Lambda function every 2 hours from 9am to 11pm and from 12am to 2am (or as per API limits).
Link the rule to the Lambda function.
5. Test the System:
Subscribe to the SNS topic.
Trigger the Lambda function and verify notifications.
What I Learned
AWS Services: SNS for notifications, EventBridge for scheduling, and Lambda for serverless processing.
API Integration: Leveraging Python for robust and efficient data handling.
Secure Practices: Using IAM least privilege to secure resources.
Automation: Reducing manual intervention with EventBridge triggers.
Future Enhancements
User-specific preferences (e.g., favorite teams).
Advanced game stats in notifications.
Data visualization integration.
CI/CD pipeline for seamless updates.
Conclusion
This project illustrates how cloud services and Python can power real-time systems for dynamic user experiences. By leveraging AWS and NBA APIs, I’ve built a scalable and secure solution that connects fans to the game they love. Stay tuned for more enhancements!
Check this GitHub repo for the step-by-step procedure to get it done.