Cloud-Native Image Processing API

Role

End-to-end API design, cloud deployment, and integrations

Context

Teams needed reliable large-scale image handling with efficient storage and smoother bulk uploads from enterprise file sources.

Approach

Built a Flask API on Cloud Run with automated compression via Firebase Extensions, OneDrive Picker integration for batch uploads, and solid error handling and monitoring.

Outcomes

• Automated compression pipeline tied to Firebase Extensions
• Integrated Microsoft OneDrive Picker for large batch uploads
• Streamlined CI/CD and operational monitoring for the service

Details

Designed and implemented a Python Flask API deployed on Google Cloud Run for large-scale image processing operations. The system includes automated image compression using Firebase Extensions, resulting in 96% reduction in storage costs. Integrated with Microsoft OneDrive Picker API to accelerate client upload workflows by 60% for large image batches. The API handles long-running tasks efficiently and includes comprehensive error handling and monitoring. Successfully streamlined CI/CD processes and improved overall system performance.