In a recent project, I developed a serverless weather data pipeline on AWS to enhance solar energy forecasting in Germany. The pipeline boasts an impressive 99.999% uptime, ensuring reliable data flow. Here’s how it works:
Data Collection: A Lambda function fetches weather data from an API every 15 minutes, ensuring the data is current.
Data Storage: Another Lambda function writes this data into a DynamoDB table, allowing for quick access and updates.
Data Conversion: A third Lambda function converts the stored data into CSV format for easy analysis and visualization.
The entire system leverages AWS’s serverless architecture, which means no server management is required, reducing costs and complexity. This setup not only provides real-time data but also scales automatically with demand. The project’s success highlights the importance of real-time data in forecasting models, particularly for renewable energy sources like solar power.
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