AWS Logo
Menu
Building a Weather Alert System with AWS services and OpenWeather API

Building a Weather Alert System with AWS services and OpenWeather API

A serverless weather monitoring system built on AWS that fetches real-time weather data from OpenWeather API for specified locations and automatically stores it in S3 for historical tracking.

openweatherlambdas3python
Aditya Putta
Amazon Employee
Published Jun 5, 2025

Introduction

Weather affects every aspect of our daily lives, from planning outdoor activities to ensuring public safety. In this comprehensive guide, we'll build a sophisticated weather alert system that leverages AWS services and the OpenWeather API. This system will automatically monitor weather conditions, store historical data, and send alerts when specific weather thresholds are exceeded. Whether you're a developer looking to build a similar system or just interested in weather monitoring, this guide provides valuable insights into modern cloud architecture.

Project Setup Guide

Before diving into the implementation, let's understand what we're building:
  • A serverless application that periodically checks weather conditions
  • Automated storage of weather data for historical analysis
  • Real-time alert system for extreme weather conditions
  • Scalable architecture that can monitor multiple locations

Prerequisites

  1. AWS Account with appropriate permissions
  2. Python 3.8 or higher installed
  3. OpenWeather API key
  4. AWS CLI configured
  5. Required Python packages:
pip install boto3 requests python-dotenv pandas

Project Structure

weather-alert-system/
├── src/
│ ├── init.py
│ ├── config.py
│ ├── weather_client.py
│ ├── data_store.py
│ ├── alert_processor.py
│ └── notification_service.py
├── tests/
├── .env
├── requirements.txt
└── README.md

1. Environment Setup

This crucial first step establishes our project's configuration management. We're using environment variables to keep sensitive information secure and make our application configurable.

Create .env file

OPENWEATHER_API_KEY=your_api_key_here
AWS_BUCKET_NAME=weather-alerts-archive
AWS_REGION=us-east-1
SNS_TOPIC_ARN=arn:aws:sns:region:account:weather-alertsSign up for Open Weather API key here: https://openweathermap.org/appid

config.py

2. Weather Data Collection

Our WeatherClient class serves as the bridge between our application and the OpenWeather API. It handles API communication and data transformation, ensuring we receive standardized weather information regardless of location.

weather_client.py

3. Data Storage Implementation

The DataStore class implements a sophisticated storage strategy using AWS S3. It creates a partitioned structure based on timestamps, making it efficient to query historical weather data and perform analytics.

data_store.py

4. Alert Processing

This component contains the business logic for determining when weather conditions warrant an alert. It's designed to be easily extensible - you can add new types of alerts by updating the alert_thresholds dictionary.

alert_processor.py

5. Notification Service

The notification service leverages AWS SNS to deliver alerts through multiple channels. It formats messages for clarity and ensures important weather information reaches stakeholders quickly.

notification_service.py

6. Main Application

The main application orchestrates all components, implementing the core business logic in a Lambda function that can be triggered on a schedule.

main.py

Deployment

The deployment process involves several AWS services. Here's a step-by-step guide to getting your system into production:
  1. S3 Bucket Creation: Setting up secure storage for weather data
  2. SNS Topic Setup: Establishing the notification infrastructure
  3. Lambda Function Deployment: Deploying the core application
  4. EventBridge Configuration: Setting up automated scheduling

Create S3 bucket:
aws s3api create-bucket \
--bucket weather-alerts-archive \
--region us-east-1

Create SNS topic:
aws sns create-topic --name weather-alerts

Subscribe to this topic with Email to receive email notification.

Set up Lambda function:

Create EventBridge rule for scheduling:

Validation:

Every hour, Lambda will get triggered and the weather data files will be stored in S3 as below.

Conclusion

This implementation provides a complete, production-ready weather alert system using multiple aws services. The modular design allows for easy maintenance and scaling. The system can be enhanced by adding more alert types, implementing machine learning for pattern recognition, or integrating with additional notification channels.
 

Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.

Comments